This book brings together in one place important contributions and state-of-the-art research in the rapidly advancing area of analog VLSI neural networks.
The book serves as an excellent reference, providing insights into some of the most important issues in analog VLSI neural networks research efforts.

Neural Network Parallel Computing is the first book available to the professional market on neural network computing for optimization problems. This introductory book is not only for the novice reader, but for experts in a variety of areas including parallel computing, neural network computing, computer science, communications, graph theory, computer aided design for VLSI circuits, molecular biology, management science, and operations research. The goal of the book is to facilitate an understanding as to the uses of neural network models in real-world applications.
Neural...

This book brings together in one place important contributions and state-of-the-art research in the rapidly advancing area of analog VLSI neural networks.
The book serves as an excellent reference, providing insights into some of the most important issues in analog VLSI neural networks research efforts.

This work presents a variety of optimization problems and combinatorics problems. It features applications in graph theory, mathematics, stochastic computing including the multiple relaxation, associative memory and control, resource allocation problems, and system identification.