A composition of the neural network using switched-capacitor circuit
説明
A switched-capacitor (SC) neural network is described. The motion of the SC neural network is represented with stochastic difference equations. The network consists of two-state neurons (ON-OFF neurons). The equations can lead to a convergence to global minima even with the two-state neurons by introducing the technique of simulated annealing. The two-state neurons make the circuits of the activation function and multiplication very simple. The network limitation of the SC neural network is analyzed in detail, and the circuit performance of 32.8 GCPS is confirmed. The computational capacity of the SC neural network is confirmed in connection with the solution of an optimization problem. >
収録刊行物
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- [Proceedings 1992] IEEE International Conference on Systems Engineering
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[Proceedings 1992] IEEE International Conference on Systems Engineering 40-43, 2003-01-02
IEEE