Abstract
A neural network which can identify a nonlinear system whose structure is very complex, is described. This neural network is constructed with four layers. In the second layer of the neural network, nonlinear relationship of input variables are generated and quantized accurately. So, high order effects of input variables can be considered in the neural network. The neural network is applied to a nonlinear system identification problem and the results are compared with those which are obtained by using another neural network and GMDH (Group Method of Data Handling) algorithm.
