An Analog Neural Network System with Learning Capability Using Simultaneous Perturbation

摘要

In this paper, we describe an implementation of analog neural network system with on-line learning capability. A learning rule using the simultaneous perturbation is adopted. Compared with usage of the ordinary back-propagation method, we can easily implement the simultaneous perturbation learning rule. The neural system can monitor weight values and an error value. The exclusive OR problem and a simple function problem are shown.