Publisher's Synopsis
This long-standing series reviews current research in natural and synthetic networks, as well as reviewing state-of-the-art research in modeling, analysis, design, and development of neural networks in software and hardware areas. Contributions from leading researchers and practitioners shape academic and professional programs in this area. They serve as a platform for detailed and expanded discussion of topics of interest to the neural network and cognitive information processing communities. Topics covered in this volume include: - Networks for Regression Analysis - Faulted, and Fault Tolerant Neural Networks - Learning by Generalized Entropy - Adaptive Network Systems - Hebbian Learning - Control Theory - Implementation of a Neurocomputer - Uses of Hybrid Neural Networks and Multilayer Networks This series is directly aimed at those professionally involved in networks research,including lecturers and primary investigators in neural computing, learning, and memory.
