Adaptive Resonance Theory Microchips
This chapter addresses implementation of learning models inspired by Adaptive Resonance Theory. A real-time clustering microchip based on the ART1 algorithm is presented, capable of classification and fast learning of 100-bit input patterns into up to 18 categories. A second chip is also presented which implements the ARTMAP algorithm for pattern association. We include experimental learning results from both prototypes, fabricated in standard single-poly double-metal 1.6μm and 1.0μm CMOS digital processes. MOS Transistors mismatch characterization issues are also addressed.
KeywordsCurrent Source Input Pattern Very Large Scale Integration Current Mirror NMOS Transistor
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