The Springer International Series in Engineering and Computer Science Neural Network Parallel Computing

Neural Network Parallel Computing is the first book available to the professional market on neural network computing for optimization problems. This introductory book is aimed not only for the novice reader, but also 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 aim of the book is to facilitate an understanding as to the uses of neural network models in real-world applications. It demonstrates the computational power of neural network computing by solving numerous problems such as N-queen, crossbar switch scheduling, four-colouring and k-colorability, graph planarization and channel routing, RNA secondary structure prediction, knight's tour, spare allocation, sorting and searching, and tiling.