The Springer International Series in Engineering and Computer Science Neural Information Processing VLSI

Neural Information Processing and VLSI provides a unified treatment of this important subject for use in classrooms, industry, and research laboratories, in order to develop advanced artificial and biologically-inspired neural networks using compact analog and digital VLSI parallel processing techniques. This text provides a unified treatment of this subject for use in classrooms, industry and research laboratories, in order to develop advanced artificial and biologically-inspired neural networks using compact analogue and digital VLSI parallel processing techniques. The book presents various neural network paradigms, computing architectures and the associated electronic/optical implementations using efficient VLSI design methodologies. Conventional digital machines cannot perform computationally-intensive tasks with satisfactory performance in such areas as intelligent perception, including visual and auditory signal processing, recognition, understanding and logical reasoning (where the human being and even a small living animal can do a superb job). Recent research advances in artificial and biological neural networks have established an important foundation for high-performance information processing with more efficient use of computing resources.