This chapter describes mixed analog/digital circuit implementations of a chaotic neuro-computer system. The chaotic neuron model is implemented with a switched-capacitor (SC) integrated circuit technique. The analog SC circuit can handle real numbers electrically in the sense that the state variables of the analog circuits are continuous. Therefore, chaotic dynamics can be faithfully replicated with the SC chaotic neuron circuit. The synaptic connections, on the other hand, are realized with digital circuits to accommodate a vast number of synapses. We propose a memory-based digital synapse circuit architecture that draws upon the table look-up method to achieve rapid calculation of a large number of weighted summations. The first generation chaotic neuro-computer with 16 SC neurons and 256 synapses is reviewed. Finally, a large-scale system with 10000 neurons and 10000 ² synapses is described.

12.1 Introduction

Cross-disciplinary research in physiology, anatomy, cell biology, biogenetics, biophysics, and so on, is rapidly revealing the structure and the function of the brain. The brain is a nonlinear network with a vast number of mutually connected neurons. It is also a continuously changing system that is never trapped into an equilibrium state. Moreover, the brain is an adaptive and self-organizing system with plasticity. The so-called "analysis by synthesis" or "constructive research" method is important approach to...