Winner-take-all networks of O(N) complexity
Advances in neural information processing systems 1
Vector quantization and signal compression
Vector quantization and signal compression
Adaptive resonance theory microchips: circuit design techniques
Adaptive resonance theory microchips: circuit design techniques
A Micropower Adaptive Linear Transform Vector Quantiser
Analog Integrated Circuits and Signal Processing - Special issue on Learning on Silicon
Analog VLSI Stochastic Perturbative Learning Architectures
Analog Integrated Circuits and Signal Processing
Differential Hot Electron Injection in an Adaptive Floating Gate Comparator
Analog Integrated Circuits and Signal Processing
Differential Hot Electron Injection in an Adaptive Floating Gate Comparator
Analog Integrated Circuits and Signal Processing
A high-performance VLSI architecture for the histogram peak-climbing data clustering algorithm
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
A network intrusion-tolerant system based on adaptive algorithm
WiCOM'09 Proceedings of the 5th International Conference on Wireless communications, networking and mobile computing
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We present a mixed-mode VLSI chip performing unsupervised clustering and classification, implementing models of Fuzzy Adaptive Resonance Theory (ART) and Learning Vector Quantization (LVQ), and extending to variants such as Kohonen Self-Organizing Maps (SOM). The parallel processor classifies analog vectorial data into a digital code in a single clock, and implements on-line learning of the analog templates, stored locally and dynamically using the same adaptive circuits for on-chip quantization and refresh. The unit cell performing fuzzy choice and vigilance functions, adaptive resonance learning and long-term analog storage, measures 43 μm×43 μm in 1.2 μm CMOS technology. Experimental learning results from a fabricated 8-input, 16-category prototype are included.