Series:

Adaptive and Cognitive Dynamic Systems: Signal Processing, Learning, Communications and Control

9 primary works • 12 total works

Book 20

Cover of Regularized Radial Basis Function Networks
Simon Haykin is a well-known author of books on neural networks. An authoritative book dealing with cutting edge technology. This book has no competition.

Book 21

Cover of Nonlinear Dynamical Systems
The first truly up-to-date look at the theory and capabilities of nonlinear dynamical systems that take the form of feedforward neural network structures Considered one of the most important types of structures in the study of neural networks and neural-like networks, feedforward networks incorporating dynamical elements have important properties and are of use in many applications. Specializing in experiential knowledge, a neural network stores and expands its knowledge base via strikingly human routes-through a learning process and information storage involving interconnection strengths known as synaptic weights. In Nonlinear Dynamical Systems: Feedforward Neural Network Perspectives, six leading authorities describe recent contributions to the development of an analytical basis for the understanding and use of nonlinear dynamical systems of the feedforward type, especially in the areas of control, signal processing, and time series analysis.
Moving from an introductory discussion of the different aspects of feedforward neural networks, the book then addresses: Classification problems and the related problem of approximating dynamic nonlinear input-output maps The development of robust controllers and filters The capability of neural networks to approximate functions and dynamic systems with respect to risk-sensitive error Segmenting a time series It then sheds light on the application of feedforward neural networks to speech processing, summarizing speech-related techniques, and reviewing feedforward neural networks from the viewpoint of fundamental design issues. An up-to-date and authoritative look at the ever-widening technical boundaries and influence of neural networks in dynamical systems, this volume is an indispensable resource for researchers in neural networks and a reference staple for libraries.

Book 23

Cover of Kalman Filtering and Neural Networks
State-of-the-art coverage of Kalman filter methods for the design of neural networks This self-contained book consists of seven chapters by expert contributors that discuss Kalman filtering as applied to the training and use of neural networks. Although the traditional approach to the subject is almost always linear, this book recognizes and deals with the fact that real problems are most often nonlinear. The first chapter offers an introductory treatment of Kalman filters with an emphasis on basic Kalman filter theory, Rauch-Tung-Striebel smoother, and the extended Kalman filter.
Other chapters cover:* An algorithm for the training of feedforward and recurrent multilayered perceptrons, based on the decoupled extended Kalman filter (DEKF)* Applications of the DEKF learning algorithm to the study of image sequences and the dynamic reconstruction of chaotic processes* The dual estimation problem* Stochastic nonlinear dynamics: the expectation-maximization (EM) algorithm and the extended Kalman smoothing (EKS) algorithm* The unscented Kalman filter Each chapter, with the exception of the introduction, includes illustrative applications of the learning algorithms described here, some of which involve the use of simulated and real-life data. Kalman Filtering and Neural Networks serves as an expert resource for researchers in neural networks and nonlinear dynamical systems. An Instructor's Manual presenting detailed solutions to all the problems in the book is available upon request from the Wiley Makerting Department.

Book 30

Cover of Space-Time Layered Information Processing for Wireless Communications
Discover cutting-edge research in wireless communications This book presents cutting-edge research in wireless communications, particularly in the fast-growing subject of multiple-input multiple-output (MIMO) wireless communication systems. It begins with an introduction, which includes historical notes and a review of turbo-information processing and MIMO wireless communications, and goes on to cover:* MIMO channel capacity* BLAST architectures* Space-time turbo codes and turbo decoding principles* Turbo-BLAST* Turbo-MIMO systems The material is complemented with abundant illustrations and computer experiments that are designed to help readers reinforce their understanding of the underlying subject matter. Space-Time Layered Information Processing for Wireless Communications is an ideal resource for researchers in academia and industry and an excellent textbook for related courses at the graduate level.

Book 49

Cover of Correlative Learning – A Basis for Brain and Adpaptive Systems
Correlative Learning: A Basis for Brain and Adaptive Systems provides a bridge between three disciplines: computational neuroscience, neural networks, and signal processing. First, the authors lay down the preliminary neuroscience background for engineers. The book also presents an overview of the role of correlation in the human brain as well as in the adaptive signal processing world; unifies many well-established synaptic adaptations (learning) rules within the correlation-based learning framework, focusing on a particular correlative learning paradigm, ALOPEX; and presents case studies that illustrate how to use different computational tools and ALOPEX to help readers understand certain brain functions or fit specific engineering applications.

Book 55

Cover of Adaptive Signal Processing – Next Generation ons
This book presents the latest research results in adaptive signal processing with an emphasis on important applications and theoretical advancements. Each chapter is self-contained, comprehensive in its coverage, and written by a leader in his or her field of specialty. A uniform style is maintained throughout the book and each chapter concludes with problems for readers to reinforce their understanding of the material presented. The book can be used as a reliable reference for researchers and practitioners or as a textbook for graduate students.

Book 57

Cover of Kernel Adaptive Filtering
Reproducing kernel Hilbert spaces is a topic of great current interest for applications in signal processing, communications, and controls The first book to explain real-time learning algorithms in reproducing kernel Hilbert spaces, On-Line Kernel Learning includes simulations that illustrate the ideas discussed and demonstrate their applicability as well as MATLAB codes for simulations. This book is ideal for professionals and graduate students interested in nonlinear adaptive systems for on-line applications.

Book 63

Cover of Handbook on Array Processing and Sensor Networks
A handbook on recent advancements and the state of the art in array processing and sensor Networks

Handbook on Array Processing and Sensor Networks provides readers with a collection of tutorial articles contributed by world-renowned experts on recent advancements and the state of the art in array processing and sensor networks.

Focusing on fundamental principles as well as applications, the handbook provides exhaustive coverage of: wavelets; spatial spectrum estimation; MIMO radio propagation; robustness issues in sensor array processing; wireless communications and sensing in multi-path environments using multi-antenna transceivers; implicit training and array processing for digital communications systems; unitary design of radar waveform diversity sets; acoustic array processing for speech enhancement; acoustic beamforming for hearing aid applications; undetermined blind source separation using acoustic arrays; array processing in astronomy; digital 3D/4D ultrasound imaging technology; self-localization of sensor networks; multi-target tracking and classification in collaborative sensor networks via sequential Monte Carlo; energy-efficient decentralized estimation; sensor data fusion with application to multi-target tracking; distributed algorithms in sensor networks; cooperative communications; distributed source coding; network coding for sensor networks; information-theoretic studies of wireless networks; distributed adaptive learning mechanisms; routing for statistical inference in sensor networks; spectrum estimation in cognitive radios; nonparametric techniques for pedestrian tracking in wireless local area networks; signal processing and networking via the theory of global games; biochemical transport modeling, estimation, and detection in realistic environments; and security and privacy for sensor networks.

Handbook on Array Processing and Sensor Networks is the first book of its kind and will appeal to researchers, professors, and graduate students in array processing, sensor networks, advanced signal processing, and networking.

Book 65

Cover of Multiple-Input Multiple-Output Channel Models
Because Wideband Multiple Input and Multiple Output (MIMO) technology is just now being implemented in hardware, there is currently a great desire for knowledge of both the theory and practicality of its channels. Bringing together theoretical and practical aspects of MIMO communications, Wideband MIMO Channel Models is the first book to apply tensor calculus to the problem of wideband MIMO channel modeling. The text contains important novel material for how to model a MIMO channel, making it suitable for graduate students, researchers, and engineers.

Cover of Fundamentals of Cognitive Radio
A comprehensive treatment of cognitive radio networks and the specialized techniques used to improve wireless communications The human brain, as exemplified by cognitive radar, cognitive radio, and cognitive computing, inspires the field of Cognitive Dynamic Systems. In particular, cognitive radio is growing at an exponential rate. Fundamentals of Cognitive Radio details different aspects of the human brain and provides examples of how it can be mimicked by cognitive dynamic systems. The text offers a communication-theoretic background, including information on resource allocation in wireless networks and the concept of robustness. The authors provide a thorough mathematical background with data on game theory, variational inequalities, and projected dynamic systems. They then delve more deeply into resource allocation in cognitive radio networks. The text investigates the dynamics of cognitive radio networks from the perspectives of information theory, optimization, and control theory. It also provides a vision for the new world of wireless communications by integration of cellular and cognitive radio networks.
This groundbreaking book: * Shows how wireless communication systems increasingly use cognition to enhance their networks * Explores how cognitive radio networks can be viewed as spectrum supply chain networks * Derives analytic models for two complementary regimes for spectrum sharing (open-access and market-driven) to study both equilibrium and disequilibrium behaviors of networks * Studies cognitive heterogeneous networks with emphasis on economic provisioning for resource sharing * Introduces a framework that addresses the issue of spectrum sharing across licensed and unlicensed bands aimed for Pareto optimality Written for students of cognition, communication engineers, telecommunications professionals, and others, Fundamentals of Cognitive Radio offers a new generation of ideas and provides a fresh way of thinking about cognitive techniques in order to improve radio networks.

Cover of Impact of Attention on Perception in Cognitive Dynamic Systems

This book provides insights into developing better algorithms for machine learning, artificial intelligence and signal processing. The authors build mainly on two topics: Cognitive Dynamic Systems (CDS), which is a well-established paradigm originated in the Cognitive Systems Lab of McMaster University, and attention, an essential cognitive function the neurobiological root of which is assumed to be the reentry of neuronal firings through feedback connections. This book focuses completely on the perceptual part of a CDS, or in short, the "perceptor", which is the part responsible for visualizing the environment. In this regard, inspired by the mammalian brain, an important step has been taken to redesign the perceptor and therefore improve its functionality in light of "attention", a function that is essential to cognition. The authors demonstrate how the end result is an improved performance for the perceptor in the face of uncertainties and better separation of relevant information from irrelevant information.

Cover of Cognitive Networks

Cognitive Networks

by Simon Haykin

Published 24 April 2015
Cognitive systems are modeled after the highly complex, integrated network that is the human brain. Haykin describes the fundamental issues pertaining to performance characterizations of complex dynamic systems, including perceptual attention, controlled attention, working memory, and decisionmaking based on big data.
The book presents the cognitive network as a system of systems. The primary examples of cognitive networks presented are cognitive radar networks and cognitive radio networks (both open-access and market-driven). The book is supported by seven appendices covering, among others, probability theory, Bayesian inference, the method of stochastic gradients, and Fisher information, all of which are applicable to multiple sections in the book.