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| networks an introduction: Networks Mark Newman, 2010-03-25 The scientific study of networks, including computer networks, social networks, and biological networks, has received an enormous amount of interest in the last few years. The rise of the Internet and the wide availability of inexpensive computers have made it possible to gather and analyze network data on a large scale, and the development of a variety of new theoretical tools has allowed us to extract new knowledge from many different kinds of networks. The study of networks is broadly interdisciplinary and important developments have occurred in many fields, including mathematics, physics, computer and information sciences, biology, and the social sciences. This book brings together for the first time the most important breakthroughs in each of these fields and presents them in a coherent fashion, highlighting the strong interconnections between work in different areas. Subjects covered include the measurement and structure of networks in many branches of science, methods for analyzing network data, including methods developed in physics, statistics, and sociology, the fundamentals of graph theory, computer algorithms, and spectral methods, mathematical models of networks, including random graph models and generative models, and theories of dynamical processes taking place on networks. |
| networks an introduction: Networks: An Introduction Mark Newman, 2010-03-25 The scientific study of networks, including computer networks, social networks, and biological networks, has received an enormous amount of interest in the last few years. The rise of the Internet and the wide availability of inexpensive computers have made it possible to gather and analyze network data on a large scale, and the development of a variety of new theoretical tools has allowed us to extract new knowledge from many different kinds of networks. The study of networks is broadly interdisciplinary and important developments have occurred in many fields, including mathematics, physics, computer and information sciences, biology, and the social sciences. This book brings together for the first time the most important breakthroughs in each of these fields and presents them in a coherent fashion, highlighting the strong interconnections between work in different areas. Subjects covered include the measurement and structure of networks in many branches of science, methods for analyzing network data, including methods developed in physics, statistics, and sociology, the fundamentals of graph theory, computer algorithms, and spectral methods, mathematical models of networks, including random graph models and generative models, and theories of dynamical processes taking place on networks. |
| networks an introduction: An Introduction to Neural Networks Kevin Gurney, 2018-10-08 Though mathematical ideas underpin the study of neural networks, the author presents the fundamentals without the full mathematical apparatus. All aspects of the field are tackled, including artificial neurons as models of their real counterparts; the geometry of network action in pattern space; gradient descent methods, including back-propagation; associative memory and Hopfield nets; and self-organization and feature maps. The traditionally difficult topic of adaptive resonance theory is clarified within a hierarchical description of its operation. The book also includes several real-world examples to provide a concrete focus. This should enhance its appeal to those involved in the design, construction and management of networks in commercial environments and who wish to improve their understanding of network simulator packages. As a comprehensive and highly accessible introduction to one of the most important topics in cognitive and computer science, this volume should interest a wide range of readers, both students and professionals, in cognitive science, psychology, computer science and electrical engineering. |
| networks an introduction: Artificial Neural Networks Kevin L. Priddy, Paul E. Keller, 2005 This tutorial text provides the reader with an understanding of artificial neural networks (ANNs), and their application, beginning with the biological systems which inspired them, through the learning methods that have been developed, and the data collection processes, to the many ways ANNs are being used today. The material is presented with a minimum of math (although the mathematical details are included in the appendices for interested readers), and with a maximum of hands-on experience. All specialized terms are included in a glossary. The result is a highly readable text that will teach the engineer the guiding principles necessary to use and apply artificial neural networks. |
| networks an introduction: Social Networks Jeroen Bruggeman, 2013-05-13 Social Networks: An Introduction is the first textbook that combines new with still-valuable older methods and theories. Designed to be a core text for graduate (and some undergraduate) courses in a variety of disciplines it is well-suited for everybody who makes a first encounter with the field of social networks, both academics and practitioners. This book includes reviews, study questions and text boxes as well as using innovative pedagogy to explain mathematical models and concepts. Examples ranging from anthropology to organizational sociology and business studies ensure wide applicability. An easy to use software tool, free of charge and open source, is appended on the supporting website that enables readers to depict and analyze networks of their interest. It is essential reading for students in sociology, anthropology, and business studies and can be used as secondary material for courses in economics and political science. |
| networks an introduction: Dynamical Systems on Networks Mason Porter, James Gleeson, 2016-03-31 This volume is a tutorial for the study of dynamical systems on networks. It discusses both methodology and models, including spreading models for social and biological contagions. The authors focus especially on “simple” situations that are analytically tractable, because they are insightful and provide useful springboards for the study of more complicated scenarios. This tutorial, which also includes key pointers to the literature, should be helpful for junior and senior undergraduate students, graduate students, and researchers from mathematics, physics, and engineering who seek to study dynamical systems on networks but who may not have prior experience with graph theory or networks. Mason A. Porter is Professor of Nonlinear and Complex Systems at the Oxford Centre for Industrial and Applied Mathematics, Mathematical Institute, University of Oxford, UK. He is also a member of the CABDyN Complexity Centre and a Tutorial Fellow of Somerville College. James P. Gleeson is Professor of Industrial and Applied Mathematics, and co-Director of MACSI, at the University of Limerick, Ireland. |
| networks an introduction: OSS for Telecom Networks Kundan Misra, 2012-12-06 Places OSS software in the context of telecommunications as a business Gives a concrete understanding of what OSS is, what it does and how it does it, avoiding deep technical details Frequently relates OSS software to business drivers of telecom service providers |
| networks an introduction: From Molecules to Networks Ruth Heidelberger, M. Neal Waxham, John H. Byrne, James L. Roberts, 2009-01-27 An understanding of the nervous system at virtually any level of analysis requires an understanding of its basic building block, the neuron. From Molecules to Networks provides the solid foundation of the morphologic, biochemical, and biophysical properties of nerve cells. All chapters have been thoroughly revised for this second edition to reflect the significant advances of the past 5 years. The new edition expands on the network aspects of cellular neurobiology by adding a new chapter, Information Processing in Neural Networks, and on the relation of cell biological processes to various neurological diseases. The new concluding chapter illustrates how the great strides in understanding the biochemical and biophysical properties of nerve cells have led to fundamental insights into important aspects of neurodegenerative disease. - Written and edited by leading experts in the field, the second edition completely and comprehensively updates all chapters of this unique textbook - Discusses emerging new understanding of non-classical molecules that affect neuronal signaling - Full colour, professional graphics throughout - Includes two new chapters: Information Processing in Neural Networks - describes the principles of operation of neural networks and the key circuit motifs that are common to many networks in the nervous system. Molecular and Cellular Mechanisms of Neurodegenerative Disease - introduces the progress made in the last 20 years in elucidating the cellular and molecular mechanisms underlying brain disorders, including Amyotrophic Lateral Sclerosis (ALS), Parkinson disease, and Alzheimer's disease |
| networks an introduction: Bayesian Networks Timo Koski, John Noble, 2009-11-02 Bayesian Networks: An Introduction provides a self-contained introduction to the theory and applications of Bayesian networks, a topic of interest and importance for statisticians, computer scientists and those involved in modelling complex data sets. The material has been extensively tested in classroom teaching and assumes a basic knowledge of probability, statistics and mathematics. All notions are carefully explained and feature exercises throughout. Features include: An introduction to Dirichlet Distribution, Exponential Families and their applications. A detailed description of learning algorithms and Conditional Gaussian Distributions using Junction Tree methods. A discussion of Pearl's intervention calculus, with an introduction to the notion of see and do conditioning. All concepts are clearly defined and illustrated with examples and exercises. Solutions are provided online. This book will prove a valuable resource for postgraduate students of statistics, computer engineering, mathematics, data mining, artificial intelligence, and biology. Researchers and users of comparable modelling or statistical techniques such as neural networks will also find this book of interest. |
| networks an introduction: Neural Networks Berndt Müller, Joachim Reinhardt, Michael T. Strickland, 2012-12-06 Neural Networks presents concepts of neural-network models and techniques of parallel distributed processing in a three-step approach: - A brief overview of the neural structure of the brain and the history of neural-network modeling introduces to associative memory, preceptrons, feature-sensitive networks, learning strategies, and practical applications. - The second part covers subjects like statistical physics of spin glasses, the mean-field theory of the Hopfield model, and the space of interactions approach to the storage capacity of neural networks. - The final part discusses nine programs with practical demonstrations of neural-network models. The software and source code in C are on a 3 1/2 MS-DOS diskette can be run with Microsoft, Borland, Turbo-C, or compatible compilers. |
| networks an introduction: An Introduction to ATM Networks Harry G. Perros, 2001-11-28 Asynchronous Transfer Mode (ATM) has revolutionized telecommunications, and has become an integral part of the networking infrastructure. This introductory well-structured text on ATM networks describes their development, architecture, congestion control, deployment, and signalling in an intuitive, accessible way. It covers extensive background information and includes exercises that support the explanations throughout the book. The networking expert Harry G. Perros explains ATM networks, including such hot topics as: * ATM adaptation layer 2 * Quality of Service * Congestion control * Tag switching and MPLS (Multi-Protocol Label Switching) * ADSL-based access networks * Signalling * PNNI (Private Network Node Interface) An Introduction to ATM Networks is a textbook for graduate students and undergraduates in electrical engineering and computer science as well as a reference work for networking engineers. An Online solutions Manual is now available. |
| networks an introduction: An Introduction to Neural Networks James A. Anderson, 1995 An Introduction to Neural Networks falls into a new ecological niche for texts. Based on notes that have been class-tested for more than a decade, it is aimed at cognitive science and neuroscience students who need to understand brain function in terms of computational modeling, and at engineers who want to go beyond formal algorithms to applications and computing strategies. It is the only current text to approach networks from a broad neuroscience and cognitive science perspective, with an emphasis on the biology and psychology behind the assumptions of the models, as well as on what the models might be used for. It describes the mathematical and computational tools needed and provides an account of the author's own ideas. Students learn how to teach arithmetic to a neural network and get a short course on linear associative memory and adaptive maps. They are introduced to the author's brain-state-in-a-box (BSB) model and are provided with some of the neurobiological background necessary for a firm grasp of the general subject. The field now known as neural networks has split in recent years into two major groups, mirrored in the texts that are currently available: the engineers who are primarily interested in practical applications of the new adaptive, parallel computing technology, and the cognitive scientists and neuroscientists who are interested in scientific applications. As the gap between these two groups widens, Anderson notes that the academics have tended to drift off into irrelevant, often excessively abstract research while the engineers have lost contact with the source of ideas in the field. Neuroscience, he points out, provides a rich and valuable source of ideas about data representation and setting up the data representation is the major part of neural network programming. Both cognitive science and neuroscience give insights into how this can be done effectively: cognitive science suggests what to compute and neuroscience suggests how to compute it. |
| networks an introduction: Machine Learning with Neural Networks Bernhard Mehlig, 2021-10-28 This modern and self-contained book offers a clear and accessible introduction to the important topic of machine learning with neural networks. In addition to describing the mathematical principles of the topic, and its historical evolution, strong connections are drawn with underlying methods from statistical physics and current applications within science and engineering. Closely based around a well-established undergraduate course, this pedagogical text provides a solid understanding of the key aspects of modern machine learning with artificial neural networks, for students in physics, mathematics, and engineering. Numerous exercises expand and reinforce key concepts within the book and allow students to hone their programming skills. Frequent references to current research develop a detailed perspective on the state-of-the-art in machine learning research. |
| networks an introduction: Networks , 2009 In the last 20 years interest in network phenomena has grown immensely among anthropologists, psychologists, political scientists, economists and lawyers. Empirical observation shows that network arrangements can be found in many branches of business. This is often linked to rapid changes in today's markets and technologies, but it is not the only reason. Legal institutions have been at the centre of private law since the industrial revolution but today contracts and corporations cannot cope with the risks and opportunities posed by networks. Legal practice needs solutions which go beyond the classical traditions of thinking in the dichotomy of contract and corporation. This volume is the outcome of a conference held in Fribourg, Switzerland, which focused on the legal treatment of contractual networks, in particular questions of network expectations, the fragility of network institutions, and the question of how law can minimise network specific risks towards third parties. The contributors, among them many of the world's leading scholars in this field, include Roger Brownsword, Simon Deakin, Gunther Teubner, Hugh Collins and Marc Amstutz. The book will be of interest to scholars of contract, corporate law, and legal theory. |
| networks an introduction: Networks, Crowds, and Markets David Easley, Jon Kleinberg, 2010-07-19 Are all film stars linked to Kevin Bacon? Why do the stock markets rise and fall sharply on the strength of a vague rumour? How does gossip spread so quickly? Are we all related through six degrees of separation? There is a growing awareness of the complex networks that pervade modern society. We see them in the rapid growth of the internet, the ease of global communication, the swift spread of news and information, and in the way epidemics and financial crises develop with startling speed and intensity. This introductory book on the new science of networks takes an interdisciplinary approach, using economics, sociology, computing, information science and applied mathematics to address fundamental questions about the links that connect us, and the ways that our decisions can have consequences for others. |
| networks an introduction: A First Course in Network Science Filippo Menczer, Santo Fortunato, Clayton A. Davis, 2020-01-30 Networks are everywhere: networks of friends, transportation networks and the Web. Neurons in our brains and proteins within our bodies form networks that determine our intelligence and survival. This modern, accessible textbook introduces the basics of network science for a wide range of job sectors from management to marketing, from biology to engineering, and from neuroscience to the social sciences. Students will develop important, practical skills and learn to write code for using networks in their areas of interest - even as they are just learning to program with Python. Extensive sets of tutorials and homework problems provide plenty of hands-on practice and longer programming tutorials online further enhance students' programming skills. This intuitive and direct approach makes the book ideal for a first course, aimed at a wide audience without a strong background in mathematics or computing but with a desire to learn the fundamentals and applications of network science. |
| networks an introduction: Fundamentals of Brain Network Analysis Alex Fornito, Andrew Zalesky, Edward Bullmore, 2016-03-04 Fundamentals of Brain Network Analysis is a comprehensive and accessible introduction to methods for unraveling the extraordinary complexity of neuronal connectivity. From the perspective of graph theory and network science, this book introduces, motivates and explains techniques for modeling brain networks as graphs of nodes connected by edges, and covers a diverse array of measures for quantifying their topological and spatial organization. It builds intuition for key concepts and methods by illustrating how they can be practically applied in diverse areas of neuroscience, ranging from the analysis of synaptic networks in the nematode worm to the characterization of large-scale human brain networks constructed with magnetic resonance imaging. This text is ideally suited to neuroscientists wanting to develop expertise in the rapidly developing field of neural connectomics, and to physical and computational scientists wanting to understand how these quantitative methods can be used to understand brain organization. - Winner of the 2017 PROSE Award in Biomedicine & Neuroscience and the 2017 British Medical Association (BMA) Award in Neurology - Extensively illustrated throughout by graphical representations of key mathematical concepts and their practical applications to analyses of nervous systems - Comprehensively covers graph theoretical analyses of structural and functional brain networks, from microscopic to macroscopic scales, using examples based on a wide variety of experimental methods in neuroscience - Designed to inform and empower scientists at all levels of experience, and from any specialist background, wanting to use modern methods of network science to understand the organization of the brain |
| networks an introduction: Networks Guido Caldarelli, Michele Catanzaro, 2012-10-25 From ecosystems to Facebook, from the Internet to the global financial market, some of the most important and familiar natural systems and social phenomena are based on a networked structure. It is impossible to understand the spread of an epidemic, a computer virus, large-scale blackouts, or massive extinctions without taking into account the network structure that underlies all these phenomena. In this Very Short Introduction, Guido Caldarelli and Michele Catanzaro discuss the nature and variety of networks, using everyday examples from society, technology, nature, and history to explain and understand the science of network theory. They show the ubiquitous role of networks; how networks self-organize; why the rich get richer; and how networks can spontaneously collapse. They conclude by highlighting how the findings of complex network theory have very wide and important applications in genetics, ecology, communications, economics, and sociology. ABOUT THE SERIES: The Very Short Introductions series from Oxford University Press contains hundreds of titles in almost every subject area. These pocket-sized books are the perfect way to get ahead in a new subject quickly. Our expert authors combine facts, analysis, perspective, new ideas, and enthusiasm to make interesting and challenging topics highly readable. |
| networks an introduction: An Introduction to Quantum Communication Networks Mohsen Razavi, 2018-05-25 With the fast pace of developments in quantum technologies, it is more than ever necessary to make the new generation of students in science and engineering familiar with the key ideas behind such disruptive systems. This book intends to fill such a gap between experts and non-experts in the field by providing the reader with the basic tools needed to understand the latest developments in quantum communications and its future directions. This is not only to expand the audience knowledge but also to attract new talents to this flourishing field. To that end, the book as a whole does not delve into much detail and most often suffices to provide some insight into the problem in hand. The primary users of the book will then be students in science and engineering in their final year of undergraduate studies or early years of their post-graduate programmes. |
| networks an introduction: Artificial Neural Networks P.J. Braspenning, F. Thuijsman, A.J.M.M. Weijters, 1995-06-02 This book presents carefully revised versions of tutorial lectures given during a School on Artificial Neural Networks for the industrial world held at the University of Limburg in Maastricht, Belgium. The major ANN architectures are discussed to show their powerful possibilities for empirical data analysis, particularly in situations where other methods seem to fail. Theoretical insight is offered by examining the underlying mathematical principles in a detailed, yet clear and illuminating way. Practical experience is provided by discussing several real-world applications in such areas as control, optimization, pattern recognition, software engineering, robotics, operations research, and CAM. |
| networks an introduction: Handbook of Graphs and Networks in People Analytics Keith McNulty, 2022-06-19 Handbook of Graphs and Networks in People Analytics: With Examples in R and Python covers the theory and practical implementation of graph methods in R and Python for the analysis of people and organizational networks. Starting with an overview of the origins of graph theory and its current applications in the social sciences, the book proceeds to give in-depth technical instruction on how to construct and store graphs from data, how to visualize those graphs compellingly and how to convert common data structures into graph-friendly form. The book explores critical elements of network analysis in detail, including the measurement of distance and centrality, the detection of communities and cliques, and the analysis of assortativity and similarity. An extension chapter offers an introduction to graph database technologies. Real data sets from various research contexts are used for both instruction and for end of chapter practice exercises and a final chapter contains data sets and exercises ideal for larger personal or group projects of varying difficulty level. Key features: Immediately implementable code, with extensive and varied illustrations of graph variants and layouts. Examples and exercises across a variety of real-life contexts including business, politics, education, social media and crime investigation. Dedicated chapter on graph visualization methods. Practical walkthroughs of common methodological uses: finding influential actors in groups, discovering hidden community structures, facilitating diverse interaction in organizations, detecting political alignment, determining what influences connection and attachment. Various downloadable data sets for use both in class and individual learning projects. Final chapter dedicated to individual or group project examples. |
| networks an introduction: The Structure and Dynamics of Networks: Mark Newman, Albert-László Barabási, Duncan J. Watts, 2006-05-07 From the Internet to networks of friendship, disease transmission, and even terrorism, the concept--and the reality--of networks has come to pervade modern society. But what exactly is a network? What different types of networks are there? Why are they interesting, and what can they tell us? In recent years, scientists from a range of fields--including mathematics, physics, computer science, sociology, and biology--have been pursuing these questions and building a new science of networks. This book brings together for the first time a set of seminal articles representing research from across these disciplines. It is an ideal sourcebook for the key research in this fast-growing field. The book is organized into four sections, each preceded by an editors' introduction summarizing its contents and general theme. The first section sets the stage by discussing some of the historical antecedents of contemporary research in the area. From there the book moves to the empirical side of the science of networks before turning to the foundational modeling ideas that have been the focus of much subsequent activity. The book closes by taking the reader to the cutting edge of network science--the relationship between network structure and system dynamics. From network robustness to the spread of disease, this section offers a potpourri of topics on this rapidly expanding frontier of the new science. |
| networks an introduction: The Oxford Handbook of Social Networks Ryan Light, James Moody, 2020-11-20 While some social scientists may argue that we have always been networked, the increased visibility of networks today across economic, political, and social domains can hardly be disputed. Social networks fundamentally shape our lives and social network analysis has become a vibrant, interdisciplinary field of research. In The Oxford Handbook of Social Networks, Ryan Light and James Moody have gathered forty leading scholars in sociology, archaeology, economics, statistics, and information science, among others, to provide an overview of the theory, methods, and contributions in the field of social networks. Each of the thirty-three chapters in this Handbook moves through the basics of social network analysis aimed at those seeking an introduction to advanced and novel approaches to modeling social networks statistically. They cover both a succinct background to, and future directions for, distinctive approaches to analyzing social networks. The first section of the volume consists of theoretical and methodological approaches to social networks, such as visualization and network analysis, statistical approaches to networks, and network dynamics. Chapters in the second section outline how network perspectives have contributed substantively across numerous fields, including public health, political analysis, and organizational studies. Despite the rapid spread of interest in social network analysis, few volumes capture the state-of-the-art theory, methods, and substantive contributions featured in this volume. This Handbook therefore offers a valuable resource for graduate students and faculty new to networks looking to learn new approaches, scholars interested in an overview of the field, and network analysts looking to expand their skills or substantive areas of research. |
| networks an introduction: Networks of Networks in Biology Narsis A. Kiani, David Gomez-Cabrero, Ginestra Bianconi, 2021-04-01 Biological systems are extremely complex and have emergent properties that cannot be explained or even predicted by studying their individual parts in isolation. The reductionist approach, although successful in the early days of molecular biology, underestimates this complexity. As the amount of available data grows, so it will become increasingly important to be able to analyse and integrate these large data sets. This book introduces novel approaches and solutions to the Big Data problem in biomedicine, and presents new techniques in the field of graph theory for handling and processing multi-type large data sets. By discussing cutting-edge problems and techniques, researchers from a wide range of fields will be able to gain insights for exploiting big heterogonous data in the life sciences through the concept of 'network of networks'. |
| networks an introduction: Introduction to Operating Systems and Networks Ruth A. Watson, 2004 Introducing basic networking concepts as well as providing an introduction to Windows 2000/XP Professional, this book provides a solid foundation for all beginning users. Readers will gain a fundamental knowledge of operating systems as well as understand the client/server relationship in a local area network environment--crucial to anyone working in Information Technologies.Operating Systems Conceptscovers the use of Windows 2000/XP Professional, as well as demystifies many aspects of using a personal computer. The second half of the book describes local area networks and the client/server relationship. For anyone wishing to enter the field of Information Technology, including Internet/multimedia, programming, and networking. |
| networks an introduction: DWDM and Optical Networks Ottmar Krauss, 2002-05-27 The book intends to introduce DWDM and Optical Networks to all those who need information about it without having to know special physical and mathematical details. So this should become the standard book on DWDM and Optical Networks for technicians, engineers and and most of the people working for the manufacturing industry, as well as for service and maintenance providers and for network providers. |
| networks an introduction: Networks of International Trade and Investment Sara Gorgoni, Alessia Amighini, Matthew Smith,, 2018-03-30 In recent decades, the international economy has witnessed fundamental changes in the way manufacturing is organised: products are no longer manufactured in their entirety in a single location. Instead, the production process is often split across a number of stages located in countries that are frequently far apart from each other. By spreading out their manufacturing and supply chain activities globally through international investment and intra-firm trade, Multinational enterprises (MNEs) play a focal role in this reorganisation of production. Our ability to understand the global economy, therefore, requires an understanding of the interdependencies between the entities involved in such fragmented production. Traditional methods and statistical approaches are insufficient to address this challenge. Instead, an approach is required that allows us to account for these interdependencies. The most promising approach so far is network analysis. ‘Networks of International Trade and Investment’ makes a case for the use of network analysis alongside existing techniques in order to investigate pressing issues in international business and economics. The authors put forward a range of well-informed studies that examine compelling topics such as the role of emerging economies in global trade and the evolution of world trade patterns. They look at how network analysis, as both an approach and a methodology, can explain international business and economics phenomena, in particular, in relation to international trade and investment. Providing a comprehensive but accessible explanation of the applications of network analysis and some of the most recent methodological advances in its field, this edited volume is an important contribution to research in international trade and investment. |
| networks an introduction: Introduction to Storage Area Networks Jon Tate, Pall Beck, Hector Hugo Ibarra, Shanmuganathan Kumaravel, Libor Miklas, IBM Redbooks, 2018-10-09 The superabundance of data that is created by today's businesses is making storage a strategic investment priority for companies of all sizes. As storage takes precedence, the following major initiatives emerge: Flatten and converge your network: IBM® takes an open, standards-based approach to implement the latest advances in the flat, converged data center network designs of today. IBM Storage solutions enable clients to deploy a high-speed, low-latency Unified Fabric Architecture. Optimize and automate virtualization: Advanced virtualization awareness reduces the cost and complexity of deploying physical and virtual data center infrastructure. Simplify management: IBM data center networks are easy to deploy, maintain, scale, and virtualize, delivering the foundation of consolidated operations for dynamic infrastructure management. Storage is no longer an afterthought. Too much is at stake. Companies are searching for more ways to efficiently manage expanding volumes of data, and to make that data accessible throughout the enterprise. This demand is propelling the move of storage into the network. Also, the increasing complexity of managing large numbers of storage devices and vast amounts of data is driving greater business value into software and services. With current estimates of the amount of data to be managed and made available increasing at 60% each year, this outlook is where a storage area network (SAN) enters the arena. SANs are the leading storage infrastructure for the global economy of today. SANs offer simplified storage management, scalability, flexibility, and availability; and improved data access, movement, and backup. Welcome to the cognitive era. The smarter data center with the improved economics of IT can be achieved by connecting servers and storage with a high-speed and intelligent network fabric. A smarter data center that hosts IBM Storage solutions can provide an environment that is smarter, faster, greener, open, and easy to manage. This IBM® Redbooks® publication provides an introduction to SAN and Ethernet networking, and how these networks help to achieve a smarter data center. This book is intended for people who are not very familiar with IT, or who are just starting out in the IT world. |
| networks an introduction: An Introduction to Broadband Networks Anthony S. Acampora, 2013-06-29 This is an elementary textbook on an advanced topic: broadband telecommunica tion networks. I must declare at the outset that this book is not primarily intended for an audience of telecommunication specialists who are weIl versed in the concepts, system architectures, and underlying technologies of high-speed, multi media, bandwidth-on-demand, packet-switching networks, although the techni caIly sophisticated telecommunication practitioner may wish to use it as a refer ence. Nor is this book intended to be an advanced textbook on the subject of broadband networks. Rather, this book is primarily intended for those eager to leam more about this exciting fron tier in the field of telecommunications, an audience that includes systems designers, hardware and software engineers, en gineering students, R&D managers, and market planners who seek an understand ing of local-, metropolitan-, and wide-area broadband networks for integrating voice, data, image, and video. Its primary audience also includes researchers and engineers from other disciplines or other branches of telecommunications who anticipate a future involvement in, or who would simply like to leam more about, the field of broadband networks, along with scientific researchers and corporate telecommunication and data communication managers whose increasingly sophis ticated applications would benefit from (and drive the need for) broadband net works. Advanced topics are certainly not ignored (in fact, a plausible argument could be mounted that aIl of the material is advanced, given the infancy of the topic). |
| networks an introduction: Introduction to Local Area Networks Judson Miers, 2006-06 Readers of this book will learn about Local Area Network (LAN) basics through the analysis of case studies that explore common operating systems, network services, security, and more! Each chapter of this innovative manual develops a concrete foundation in LAN concepts and applications by exposing readers to a variety of situations and networks. A back-of-book CD-ROM that contains PowerPoint presentations gives detailed examples of what a business presentation for each case study would look like. Excel spreadsheets are also included so that users can input costs and other data to fashion their own real world presentations for a hands-on learning experience. |
| networks an introduction: Neural Networks Raul Rojas, 1996-07-12 Neural networks are a computing paradigm that is finding increasing attention among computer scientists. In this book, theoretical laws and models previously scattered in the literature are brought together into a general theory of artificial neural nets. Always with a view to biology and starting with the simplest nets, it is shown how the properties of models change when more general computing elements and net topologies are introduced. Each chapter contains examples, numerous illustrations, and a bibliography. The book is aimed at readers who seek an overview of the field or who wish to deepen their knowledge. It is suitable as a basis for university courses in neurocomputing. |
| networks an introduction: Connections Sanjeev Goyal, 2009-03-01 Networks pervade social and economic life, and they play a prominent role in explaining a huge variety of social and economic phenomena. Standard economic theory did not give much credit to the role of networks until the early 1990s, but since then the study of the theory of networks has blossomed. At the heart of this research is the idea that the pattern of connections between individual rational agents shapes their actions and determines their rewards. The importance of connections has in turn motivated the study of the very processes by which networks are formed. In Connections, Sanjeev Goyal puts contemporary thinking about networks and economic activity into context. He develops a general framework within which this body of research can be located. In the first part of the book he demonstrates that location in a network has significant effects on individual rewards and that, given this, it is natural that individuals will seek to form connections to move the network in their favor. This idea motivates the second part of the book, which develops a general theory of network formation founded on individual incentives. Goyal assesses the robustness of current research findings and identifies the substantive open questions. Written in a style that combines simple examples with formal models and complete mathematical proofs, Connections is a concise and self-contained treatment of the economic theory of networks, one that should become the natural source of reference for graduate students in economics and related disciplines. |
| networks an introduction: Building Electrical Systems and Distribution Networks Radian Belu, 2020-02-13 This book covers all important, new, and conventional aspects of building electrical systems, power distribution, lighting, transformers and rotating electric machines, wiring, and building installations. Solved examples, end-of-chapter questions and problems, case studies, and design considerations are included in each chapter, highlighting the concepts, and diverse and critical features of building and industrial electrical systems, such as electric or thermal load calculations; wiring and wiring devices; conduits and raceways; lighting analysis, calculation, selection, and design; lighting equipment and luminaires; power quality; building monitoring; noise control; building energy envelope; air-conditioning and ventilation; and safety. Two chapters are dedicated to distributed energy generation, building integrated renewable energy systems, microgrids, DC nanogrids, power electronics, energy management, and energy audit methods, topics which are not often included in building energy textbooks. Support materials are included for interested instructors. Readers are encouraged to write their own solutions while solving the problems, and then refer to the solved examples for more complete understanding of the solutions, concepts, and theory. |
| networks an introduction: An Introduction to Grids, Graphs, and Networks C. Pozrikidis, 2014-02-17 An Introduction to Grids, Graphs, and Networks aims to provide a concise introduction to graphs and networks at a level that is accessible to scientists, engineers, and students. In a practical approach, the book presents only the necessary theoretical concepts from mathematics and considers a variety of physical and conceptual configurations as prototypes or examples. The subject is timely, as the performance of networks is recognized as an important topic in the study of complex systems with applications in energy, material, and information grid transport (epitomized by the internet). The book is written from the practical perspective of an engineer with some background in numerical computation and applied mathematics, and the text is accompanied by numerous schematic illustrations throughout. In the book, Constantine Pozrikidis provides an original synthesis of concepts and terms from three distinct fields-mathematics, physics, and engineering-and a formal application of powerful conceptual apparatuses, like lattice Green's function, to areas where they have rarely been used. It is novel in that its grids, graphs, and networks are connected using concepts from partial differential equations. This original material has profound implications in the study of networks, and will serve as a resource to readers ranging from undergraduates to experienced scientists. |
| networks an introduction: Networks of the Brain Olaf Sporns, 2016-02-12 An integrative overview of network approaches to neuroscience explores the origins of brain complexity and the link between brain structure and function. Over the last decade, the study of complex networks has expanded across diverse scientific fields. Increasingly, science is concerned with the structure, behavior, and evolution of complex systems ranging from cells to ecosystems. In Networks of the Brain, Olaf Sporns describes how the integrative nature of brain function can be illuminated from a complex network perspective. Highlighting the many emerging points of contact between neuroscience and network science, the book serves to introduce network theory to neuroscientists and neuroscience to those working on theoretical network models. Sporns emphasizes how networks connect levels of organization in the brain and how they link structure to function, offering an informal and nonmathematical treatment of the subject. Networks of the Brain provides a synthesis of the sciences of complex networks and the brain that will be an essential foundation for future research. |
| networks an introduction: Network Science Francesca Biagini, Göran Kauermann, Thilo Meyer-Brandis, 2019-11-19 This book provides an overview of network science from the perspective of diverse academic fields, offering insights into the various research areas within network science. The authoritative contributions on statistical network analysis, mathematical network science, genetic networks, Bayesian networks, network visualisation, and systemic risk in networks explore the main questions in the respective fields: What has been achieved to date? What are the research challenges and obstacles? What are the possible interconnections with other fields? And how can cross-fertilization between these fields be promoted? Network science comprises numerous scientific disciplines, including computer science, economics, mathematics, statistics, social sciences, bioinformatics, and medicine, among many others. These diverse research areas require and use different data-analytic and numerical methods as well as different theoretical approaches. Nevertheless, they all examine and describe interdependencies, associations, and relationships of entities in different kinds of networks. The book is intended for researchers as well as interested readers working in network science who want to learn more about the field – beyond their own research or work niche. Presenting network science from different perspectives without going into too much technical detail, it allows readers to gain an overview without having to be a specialist in any or all of these disciplines. |
| networks an introduction: Spatial Networks Marc Barthelemy, 2023-02-22 This book provides a complete introduction into spatial networks. It offers the mathematical tools needed to characterize these structures and how they evolve in time and presents the most important models of spatial networks. The book puts a special emphasis on analyzing complex systems which are organized under the form of networks where nodes and edges are embedded in space. In these networks, space is relevant, and topology alone does not contain all the information. Characterizing and understanding the structure and the evolution of spatial networks is thus crucial for many different fields, ranging from urbanism to epidemiology. This subject is therefore at the crossroad of many fields and is of potential interest to a broad audience comprising physicists, mathematicians, engineers, geographers or urbanists. In this book, the author has expanded his previous book (Morphogenesis of Spatial Networks) to serve as a textbook and reference on this topic for a wide range of students and professional researchers. |
| networks an introduction: Neural Networks Phil Picton, 2001-01-06 This updated and revised second edition assumes no prior knowledge and sets out to describe what neural nets are, what they do, and how they do it. The main networks covered include ADALINE, WISARD, the Hopfield Network, Bidirectional Associative Memory, the Boltzmann machine, counter-propogation, ART networks, and Kohonen's self-organizing maps. These networks are discussed by means of examples, giving the reader a good overall knowledge of current developments in the field. |
| networks an introduction: An Introduction to Neural Network Methods for Differential Equations Neha Yadav, Anupam Yadav, Manoj Kumar, 2015-03-23 This book introduces a variety of neural network methods for solving differential equations arising in science and engineering. The emphasis is placed on a deep understanding of the neural network techniques, which has been presented in a mostly heuristic and intuitive manner. This approach will enable the reader to understand the working, efficiency and shortcomings of each neural network technique for solving differential equations. The objective of this book is to provide the reader with a sound understanding of the foundations of neural networks and a comprehensive introduction to neural network methods for solving differential equations together with recent developments in the techniques and their applications. The book comprises four major sections. Section I consists of a brief overview of differential equations and the relevant physical problems arising in science and engineering. Section II illustrates the history of neural networks starting from their beginnings in the 1940s through to the renewed interest of the 1980s. A general introduction to neural networks and learning technologies is presented in Section III. This section also includes the description of the multilayer perceptron and its learning methods. In Section IV, the different neural network methods for solving differential equations are introduced, including discussion of the most recent developments in the field. Advanced students and researchers in mathematics, computer science and various disciplines in science and engineering will find this book a valuable reference source. |
| networks an introduction: Analysis of Biological Networks Björn H. Junker, Falk Schreiber, 2008-03-14 An introduction to biological networks and methods for their analysis Analysis of Biological Networks is the first book of its kind to provide readers with a comprehensive introduction to the structural analysis of biological networks at the interface of biology and computer science. The book begins with a brief overview of biological networks and graph theory/graph algorithms and goes on to explore: global network properties, network centralities, network motifs, network clustering, Petri nets, signal transduction and gene regulation networks, protein interaction networks, metabolic networks, phylogenetic networks, ecological networks, and correlation networks. Analysis of Biological Networks is a self-contained introduction to this important research topic, assumes no expert knowledge in computer science or biology, and is accessible to professionals and students alike. Each chapter concludes with a summary of main points and with exercises for readers to test their understanding of the material presented. Additionally, an FTP site with links to author-provided data for the book is available for deeper study. This book is suitable as a resource for researchers in computer science, biology, bioinformatics, advanced biochemistry, and the life sciences, and also serves as an ideal reference text for graduate-level courses in bioinformatics and biological research. |
List of United States radio networks - Wikipedia
Alabama Radio Network, a subsidiary of iHeartMedia.; Arizona News Radio, a subsidiary of Skyview Networks. Arkansas Radio Network, a subsidiary of Cumulus Media; California Headline News, a …
What is a Network? - Computer Hope
Jul 18, 2024 · A network is a collection of computers, servers, mainframes, peripherals, or other devices connected to facilitate communication and data sharing.Essentially, it is a system that …
Basics of Computer Networking - GeeksforGeeks
Feb 15, 2025 · Number of ports: 65,536 Range: 0 – 65535 Type “ netstat -a ” in the command prompt and press ‘Enter’, this lists all the ports being used. List of Ports. Socket: The unique …
What is a network? Definition, explanation, and examples
Oct 5, 2020 · The Wireless LAN (Wireless Local Area Network, i.e. the Wi-Fi network) in your home is a good example of a small client-server network.The various devices in your home are …
11 Types of Networks: Understanding the Differences - Auvik
Oct 24, 2024 · What are the different types of networks? Networks come in various forms, each tailored to specific needs and scales, from local area networks (LANs) that connect devices …
What Is Computer Networking? | IBM
Jul 1, 2024 · Before we delve into more complex networking topics, it’s important to understand fundamental networking components, including: IP address: An IP address is the unique number …
What Is Computer Networking? - Cisco
How does a computer network work. Specialized devices such as switches, routers, and access points form the foundation of computer networks. Switches connect and help to internally secure …
What is a Computer Network? | Definition from TechTarget
Mar 28, 2023 · Network topologies include the following types: Star network. A star network topology connects all nodes to a common central computer.; Ring network. Network devices are …
Computer network | Definition & Types | Britannica
Apr 24, 2025 · Two basic network types are local area networks (LANs) and wide area networks (WANs). LANs connect computers and peripheral devices in a limited physical area, such as a …
What is Computer Networking + Basics - Codecademy
Feb 17, 2022 · Computer networks: Who hasn’t heard of them? We connect to them all the time, whether we’re at home, school, or work. But what exactly is a computer network, and what do …
List of United States radio networks - Wikipedia
Alabama Radio Network, a subsidiary of iHeartMedia.; Arizona News Radio, a subsidiary of Skyview Networks. Arkansas Radio Network, a subsidiary of Cumulus Media; California …
What is a Network? - Computer Hope
Jul 18, 2024 · A network is a collection of computers, servers, mainframes, peripherals, or other devices connected to facilitate communication and data sharing.Essentially, it is a system that …
Basics of Computer Networking - GeeksforGeeks
Feb 15, 2025 · Number of ports: 65,536 Range: 0 – 65535 Type “ netstat -a ” in the command prompt and press ‘Enter’, this lists all the ports being used. List of Ports. Socket: The unique …
What is a network? Definition, explanation, and examples
Oct 5, 2020 · The Wireless LAN (Wireless Local Area Network, i.e. the Wi-Fi network) in your home is a good example of a small client-server network.The various devices in your home …
11 Types of Networks: Understanding the Differences - Auvik
Oct 24, 2024 · What are the different types of networks? Networks come in various forms, each tailored to specific needs and scales, from local area networks (LANs) that connect devices …
What Is Computer Networking? | IBM
Jul 1, 2024 · Before we delve into more complex networking topics, it’s important to understand fundamental networking components, including: IP address: An IP address is the unique …
What Is Computer Networking? - Cisco
How does a computer network work. Specialized devices such as switches, routers, and access points form the foundation of computer networks. Switches connect and help to internally …
What is a Computer Network? | Definition from TechTarget
Mar 28, 2023 · Network topologies include the following types: Star network. A star network topology connects all nodes to a common central computer.; Ring network. Network devices …
Computer network | Definition & Types | Britannica
Apr 24, 2025 · Two basic network types are local area networks (LANs) and wide area networks (WANs). LANs connect computers and peripheral devices in a limited physical area, such as a …
What is Computer Networking + Basics - Codecademy
Feb 17, 2022 · Computer networks: Who hasn’t heard of them? We connect to them all the time, whether we’re at home, school, or work. But what exactly is a computer network, and what do …
