Abstract:
Hardware implementation for real time RBF- based proximity effects neurocorrector 8.1 Neural network hardware survey Today one can choose from a wide range of neural network hardware. The most important benefit of such hardware is the great increase in speed over conventional sequential processors. The review here surveys a sample of neural network VLSI chips, accelerator boards, and multi- board neurocomputers. We look at the hardware from the potential users viewpoint and discuss some systems developed for high energy physics applications. While many neural network applications, such as optical character recognition programs, run well enough on conventional von Neumann processors, some applications, such as in high energy physics,
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