Distributed Sensor Networks

Most practical applications of artificial neural networks are based on acomputational model involving the propagation of continuous variables from one processing unit tothe next. In recent years, data

This is the first comprehensive treatment of feed-forward neural networks from the perspective of statistical pattern recognition. After introducing the basic concepts, the book examines techniques fo

Wireless provides a means for effective, efficient and rapid deployment of new access networks in areas previously without telecommunications service or short of capacity. Fixed wireless access networ

This first-rate introduction to the study of social networks combines a hands-on manual with an up-to-date review of the latest research and techniques.The authors provide a thorough grounding in the

Beginning with Jackson networks and ending with spatial queuing systems, this book describes several basic stochastic network processes, with the focus on network processes that have tractable express

Wiley-Interscience Series in Systems and Optimization Queueing Networks Customers, Signals and Product Form Solutions Xiuli Chao, New Jersey Institute of Technology, USA Masakiyo Miyazawa, Science Uni

The use of neural networks in signal processing is becoming increasingly widespread, with applications in many areas. Applied Neural Networks for Signal Processing is the first book to provide a comprehensive introduction to this broad field. It begins by covering the basic principles and models of neural networks in signal processing. The authors then discuss a number of powerful algorithms and architectures for a range of important problems, and describe practical implementation procedures. A key feature of the book is that many carefully designed simulation examples are included to help guide the reader in the development of systems for new applications. The book will be an invaluable reference for scientists and engineers working in communications, control or any other field related to signal processing. It can also be used as a textbook for graduate courses in electrical engineering and computer science.

Introduction to Queueing Networks Second Edition Erol Gelenbe, Duke University, North Carolina, USA and Guy Pujolle, University of Versailles, France With new concepts emerging in recent literature, t

The ever-growing number of new telecommunications technologies, along with the rapid growth of data networks and cable television systems has created a demand for sound network planning. In one concis

This excellent reference for all those involved in neural networks research and application presents, in a single text, the necessary aspects of parallel implementation for all major artificial neural

Most practical applications of artificial neural networks are based on acomputational model involving the propagation of continuous variables from one processing unit tothe next. In recent years, data

Recent advances in the development of low-loss optical fibers have revolutionized the field of telecommunications, and fiber-based networks form a key part of international communications systems. This book introduces the physical principles of optical fibers, and details their use in sensor technology and modern optical communication systems. The authors begin by setting out the basic propagation characteristics of single mode and multimode optical fibers. In later chapters they cover optical sources, optical detectors, and fiber-optic communication system design. They also treat a wide variety of related topics such as doped fiber amplifiers, dispersion compensation, fiber sensors, and measurement techniques for the characterization of optical fibers. Throughout the book, physical and engineering aspects of the subject are interwoven, and many worked examples and exercises are included. It will be an ideal textbook for undergraduate or graduate students taking courses in optical fibe

An authoritative review of modern sensor technology-essential information for analytical chemists, biochemists, biotechnologists, spectroscopists, and chemical engineersAs sensors begin to realize the

In Activists beyond Borders, Margaret E. Keck and Kathryn Sikkink examine a type of pressure group that has been largely ignored by political analysts: networks of activists that coalesce and operate

For telecommunications engineers and researchers looking to learn about broadband networks based on the ATM standard, no other book combines the analysis of ATM theory, architecture, and performance i

Understanding Digital Signatures: Establishing Trust over the Internet and Other Networks details the business, legal, social, and technological issues surrounding Digital Signatures and public key in

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 artificia

Despite the growing literature on many aspects of communications technology, relatively little has been published on the functioning and planning of complete networks. The long-awaited 2nd edition

Traditionally, human cognition has been seen and studied as existing solely 'inside' a person's head, with relative disregard for the social, physical, and artifactual surroundings in which cognition takes place. This book is a bold attempt to re-examine the nature of cognitions and to propose that a clearer understanding of human cognition would be achieved if it were conceptualized and studied as distributed among individuals, that knowledge is socially constructed through collaborative efforts toward shared objectives within cultural surroundings and that information is processed between individuals and the tools and artifacts provided by culture. The authors use illustrations from daily life and educational activities and suggest implications for education.

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 to

Neural networks are one of the fast-growing paradigms for learning systems with a wide variety of potential applications in industry. In particular there are general results which prove the universal

This book is devoted to some mathematical methods that arise in two domains of artificial intelligence: neural networks and qualitative physics. Professor Aubin makes use of control and viability theory in neural networks and cognitive systems, regarded as dynamical systems controlled by synaptic matrices, and set-valued analysis that plays a natural and crucial role in qualitative analysis and simulation. This allows many examples of neural networks to be presented in a unified way. In addition, several results on the control of linear and nonlinear systems are used to obtain a 'learning algorithm' of pattern classification problems, such as the back-propagation formula, as well as learning algorithms of feedback regulation laws of solutions to control systems subject to state constraints. This book will be of value to anyone with an interest in neural networks and cognitive systems.

Systematically explores the relationship between principal component analysis (PCA) and neural networks. Provides a synergistic examination of the mathematical, algorithmic, application and architectu

Artificial Neural Networks (ANNs) offer an efficient method for finding optimal cleanup strategies for hazardous plumes contaminating groundwater by allowing hydrologists to rapidly search through mil

An introductory quantitative approach to the study of broadband integrated networks for graduate courses in electronic and electrical engineering programs, covering fundamentals of modeling and perfor

This book presents the newly developed theory of non-harmonic Fourier series and its applications to the control of distributed parameter systems. The authors extend the theory to include vector exponential series. The first part of the book presents the modern theory of exponentials, using an operator theory approach. The second part of the book extends and upgrades the method of moments - one of the most powerful tools in the flourishing theory of the control of distributed parameter systems. The book then goes on to discuss the controllability of systems described by parabolic and hyperbolic PDEs for internal, boundary, initial, and pointwise control. Typical applications to optimal control problems are also considered. Researchers in control theory, operator theory, functional analysis and partial differential equations will find much to interest them in this treatise.

Choice Outstanding Academic Title, 1996.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

This book covers the planning, design and implementation of hybrid fiber-optic coaxial (HFC) broadband networks in schools, universities, hospitals, factories and offices, whether they are in a single

An interdisciplinary work offering an introduction to the basic principles and operational characteristics of semiconductor sensors. Describes sensor technology, stressing bulk and surface micromachin

Comprehensive, authoritative, practical—an essential guide to the design and operation of telecommunication networks The past decade has seen what can only be described as an evolutionary leap i

This book presents a unified approach to developing accurate discrete-time models of communication and computer networks, using discrete-time queuing theory and approximation techniques to obtain solu

In a simple and accessible way it extends embedding field theory into areas of machine intelligence that have not been clearly dealt with before. Neural Networks for Pattern Recognition takes the pion

Global Networks takes up the host of issues raised by the new networking technology that now links individuals, groups, and organizations in different countries and on different continents. The twenty

This timely overview and synthesis of recent work in both artificial neural networks and neurobiology seeks to examine neurobiological data from a network perspective and to encourage neuroscientists

A topical introduction on the ability of artificial neural networks to not only solve on-line a wide range of optimization problems but also to create new techniques and architectures. Provides in-dep

How do personal networks evolve and what roles do they play for parents, and for the development of children? Can these ties with relatives, neighbours, and friends provide stability for family members during periods of disruption caused by divorce, unemployment, geographic dislocation or serious illness? How do networks change over time? To what extent are network members interchangeable; can unrelated friends take the place of close relatives? These are among the questions addressed in Extending Families, a ground-breaking study about how personal networks evolve, and what roles they play for parents and for the development of children. The volume is an outgrowth of a ten-year cooperative research effort carried out by the authors as part of the Comparative Ecology of Human Development Project at Cornell University. In this comprehensive and integrated volume, Moncrieff Cochran and his colleagues document and compare the roles network members play in the lives of African-American and

This book presents the salient features of the general theory of infinite electrical networks in a coherent exposition. Using the basic tools of functional analysis and graph theory, the author examines the fundamental developments in the field and discusses applications to other areas of mathematics. The first half of the book presents existence and uniqueness theorems for both infinite-power and finite-power voltage-current regimes, and the second half discusses methods for solving problems in infinite cascades and grids. A notable feature is the invention of transfinite networks, roughly analogous to Cantor's extension of the natural numbers to the transfinite ordinals. The last chapter is a survey of application to exterior problems of partial differential equations, random walks on infinite graphs, and networks of operators on Hilbert spaces.

Pattern Recognition by Self-Organizing Neural Networks presents the most recent advances in an area of research that is becoming vitally important in the fields of cognitive science, neuroscience, art

Pattern Recognition by Self-Organizing Neural Networks presents the most recent advances in an area of research that is becoming vitally important in the fields of cognitive science, neuroscience, art

How do personal networks evolve and what roles do they play for parents, and for the development of children? Can these ties with relatives, neighbours, and friends provide stability for family members during periods of disruption caused by divorce, unemployment, geographic dislocation or serious illness? How do networks change over time? To what extent are network members interchangeable; can unrelated friends take the place of close relatives? These are among the questions addressed in Extending Families, a ground-breaking study about how personal networks evolve, and what roles they play for parents and for the development of children. The volume is an outgrowth of a ten-year cooperative research effort carried out by the authors as part of the Comparative Ecology of Human Development Project at Cornell University. In this comprehensive and integrated volume, Moncrieff Cochran and his colleagues document and compare the roles network members play in the lives of African-American and