Includes bibliographical references (p. 251-262) and index.
|Statement||edited by Antony Browne.|
|LC Classifications||QA76.87 .N4748 1997|
|The Physical Object|
|Pagination||xiv, 263 p. :|
|Number of Pages||263|
|LC Control Number||97031332|
Neural Network Analysis, Architectures and Applications discusses the main areas of neural networks, with each authoritative chapter covering the latest information from different perspectives. Divided into three parts, the book first lays the groundwork for understanding and simplifying networks. Neural Network Analysis, Architectures and Applications by Browne, A. Hardcover. Part 2 Novel architectures and algorithms: Pulse-stream techniques and circuits for implementing neural networks. Cellular neural networks. Efficient training of feed-forward neural networks. Exploiting local optima in multiversion neural computing. Part 3 Applications: Neural and neuro-fuzzy control systems. Image compression using neural. The book consists of two parts: the architecture part covers architectures, design, optimization, and analysis of artificial neural networks; the applications part covers applications of artificial.
Providing detailed examples of simple applications, this new book introduces the use of neural networks. It covers simple neural nets for pattern classification; pattern association; neural networks based on competition; adaptive-resonance theory; and more. For professionals working with neural networks.4/5(3). A complex algorithm used for predictive analysis, the neural network, is biologically inspired by the structure of the human brain. A neural network provides a very simple model in comparison to the human brain, but it works well enough for our purposes. Widely used for data classification, neural networks process past and current data to [ ]. Neural Computing & Applications is an international journal which publishes original research and other information in the field of practical applications of neural computing and related techniques such as genetic algorithms, fuzzy logic and neuro-fuzzy systems. This book provides comprehensive coverage of neural networks, their evolution, their structure, the problems they can solve, and their applications. The first half of the book looks at theoretical investigations on artificial neural networks and addresses the key architectures that are capable of implementation in various application scenarios.
About the authors This book proposes a novel neural architecture, tree-based convolutional neural networks (TBCNNs),for processing tree-structured data. Artificial neural networks may probably be the single most successful technology in the last two decades which has been widely used in a large variety of applications. The purpose of this book is to provide recent advances of architectures, methodologies, and applications of artificial neural networks. Neural Network Design (2nd Edition) Martin T. Hagan, Howard B. Demuth, Mark H. Beale, Orlando De Jesús. ISBN ISBN NEURAL NETWORK DESIGN (2nd Edition) provides a clear and detailed survey of fundamental neural network architectures . This is the book I used in my AI class. I have found it very well written and interesting to read and go through the very first neural networks models such as the Hebb net, the perceptron and the Adaline. Then the book continues by presenting simple neural network applications like Reviews: