Analog VLSI Implementation of Artificial Neural Networks with Supervised On-Chip Learning
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Scalable hybrid computation with spikes
Neural Computation
ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
Digital Least Squares Support Vector Machines
Neural Processing Letters
Conic section function neural network circuitry for offline signature recognition
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Stability analysis of autonomous ratio-memory cellular nonlinear networks for pattern recognition
IEEE Transactions on Circuits and Systems Part I: Regular Papers
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ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part III
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From the Publisher:Learning on Silicon combines models of adaptive information processing in the brain with advances in microelectronics technology and circuit design. The premise is to construct integrated systems not only loaded with sufficient computational power to handle demanding signal processing tasks in sensory perception and pattern recognition, but also capable of operating autonomously and robustly in unpredictable environments through mechanisms of adaptation and learning.. "As the first comprehensive treatment on the subject, Learning on Silicon serves as a reference for beginners and experienced researchers alike. It provides excellent material for an advanced course, and a source of inspiration for continued research towards building intelligent adaptive machines.