Learning in neuro/fuzzy analog chips
Angel Rodriguez-Vazquez, Fernando Vidal‐Verdú · 2002
This paper focus on the design of adaptive mixed-signal fuzzy chips. These chips have parallel architecture and feature electrically-controllable surface maps. The design methodology is based on the use of composite transistors-modular and well suited for design automation. This methodology is supported by dedicated, hardware-compatible learning algorithms that combine weight-perturbation and outstar.