Pulse density neural network system using simultaneous perturbation learning rule

Learning scheme is very important in implementation of neural networks to take advantage of their learning ability. Usually, the back-propagation method is widely used as a learning rule of neural networks. Since the backpropagation needs error back propagation to update weights, realizing it in a form of hardware is relatively difficult. In this paper, we present a pulse density neural network system with learning ability. As learning rules, the simultaneous perturbation method is used. The learning rules need only one forward operation of networks. Thus, without a complicated circuit to calculate gradients of an error function, we could construct the network system with learning ability. Pulse density is used to represent basic quantities in this system. A result for the exclusive OR problem is shown