Abstract
The approximation of general continuous functions by nonlinear network is very useful for system modeling and identification. Therefore, different type of networks and their combinations have developed. In present paper a wavelet neural network is used and a linear regression of inputs is used as a wavelet weight, also this model is applied in wavelet neuro-fuzzy model.