This text describes circuit strategies resulting in efficient and functional adaptive resonance theory (ART) hardware systems. ART algorithms have been developed in software by their creators, this book addresses efficient VLSI design of ART systems.

This text describes circuit strategies resulting in efficient and functional adaptive resonance theory (ART) hardware systems. ART algorithms have been developed in software by their creators, this book addresses efficient VLSI design of ART systems. All systems described in the book have been designed and fabricated (or are nearing completion) as VLSI microchips in anticipation of the impending proliferation of ART applications to autonomous intelligent systems. To accommodate these systems, the book not only provides circuit design techniques, but also validates them through experimental measurements. The book also includes a chapter tutorially describing four ART architectures (ART1, ARTMAP, Fuzzy-ART and Fuzzy-ARTMAP) while providing easily understandable MATLAB code examples to implement these four algorithms in software. In addition, an entire chapter is devoted to other potential applications for real-time data clustering and category learning.

1. Adaptive Resonance Theory Algorithms. 2. A VLSI-Friendly ART1 Algorithm. 3. ART1 and ARTMAP VLSI Circuit Implementation. 4. A Current-Mode Multi-Chip WTA-Max Circuit. 5. An ART1/ARTMAP/Fuzzy-ART/Fuzzy-ARTMAP Chip. 6. Analog Learning Fuzzy Art Chips. 7. Some Potential Applications for ART Microchips. Appendices. A: MATLAB Codes for Adaptive Resonance Theory Algorithms. B: Computational Equivalence of the Original ART1 and the Modified ART1m Models. C: Systematic Width-and-Length Dependent CMOS Transistor Mismatch Characterization.