Techniques for high-performance analog neural networks
David P. Casasent, Leonard Neiberg, Sanjay S. Natarajan · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1992
We consider analog neural network implementations (using VLSI or optical technologies) with limited accuracy and various noise and nonlinearity error sources. Algorithms and techniques to achieve high performance (good recognition P'c% and large storage capacity) on such systems are considered. The adaptive clustering neural net (ACNN) and robust Ho-Kashyap (HK-2) associative processor (AP) are the neural networks considered in detail.