Design of Low Pass FIR Filter Using General Regression Neural Network (GRNN)

With the technological evolution, great advances have been made on design techniques for various digital filters. In this paper, a type of Artificial Neural Network (ANN) called General Regression Neural Network (GRNN) is proposed to design a Low Pass FIR filter. Kaiser Window is used to prepare the data set for the training and testing of proposed General Regression Neural Network (GRNN). The performance evaluation of the proposed Neural Network (NN) is done in terms of the error between the actual and desired output filter coefficients and the filter response graphs.

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