Neural and Concurrent Real-Time Systems: The Sixth Generation
A comprehensive introduction to neural and concurrent processing. Treatment is relatively self-contained--all the fundamentals are reviewed. Exposition is straightforward, with emphasis on functions, systems, and applications. Covers neural networks of varying granularity, systems realizing 40,000 mips, and a wide range of real-life applications. Describes intelligent real-time systems applications in intelligent instruments, data acquisition, signal and speech processing, computer vision and graphics, process control and manufacturing inspection, robots, decision-making systems, on-line simulators, and flexible manufacturing cells.
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Sampling Quantizing Servicing and Queueing
Mapping Adaptation and Learning in Neural Networks
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adaptive algorithm amplitude analog application architecture artificial neural networks basic binary bits buffer cell cellular automata channel clock cluster communication components computing cluster concurrent configuration connected correlation function Courtesy and copyright cycle delay developed direct memory access display distributed engineering example execution expert systems filter frequency graphics hardware HP-IB hypercluster IEEE implemented INMOS input instruction Intelligent memory interface interrupt interval knowledge layer learning lines logic machine matrix memory chip modules multiple neural network neuron node noise nonlinearity OCCAM operating system output parallel Parallel Computers parameters Parsytec pattern performance peripheral device problem process control processor pulse quantization random real-time systems recognition robot rules Rumelhart sampling scheduling shown in Figure simulation sine wave Soucek structure subsystem supercluster switch timer tion transfer transformation transputer units vector VMEbus waveform Z-buffer