Chaotic neurochips for fuzzy computing
Harold H Szu, Lotfi A. Zadeh, Charles Chia-chuen Hsu, Joseph T. DeWitte, Gyu Moon, Desa Gobovic, Mona Elwakkad Zaghloul · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1994
A massive chaotic neural network (CNN) is demonstrated with a fixed-point Hebbian synaptic weight dynamic: an instantaneous input, and a piecewise negative logic output. The variable slope of the output versus the input becomes a software control of the collective chaos hardware. Two applications are given. The mean synaptic weight field plays an important role for fast pattern recognition capability in examples of both the habituation and the novelty detections. Another novel usage of CNN is to be a bridge between neural learning and learnable fuzzy logic.