文章基本信息

标题：Design of Low Pass FIR Filter Using General Regression Neural Network (GRNN)
本地全文：下载
作者：Jasdeep Singh ; Charanjit Singh
期刊名称：International Journal of Advanced Research In Computer Science and Software Engineering
印刷版ISSN：2277-6451
电子版ISSN：2277-128X
出版年度：2013
卷号：3
期号：10
出版社：S.S. Mishra
摘要：With the technological evolution, great advances have been made on design techniques for various digita l filters. In this paper, a type of Artificial Neural Network (ANN) ca lled 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.
关键词：Artificial Neural Network (ANN); General Regression Neural Network (G RNN); Neural Network (NN); ;Radial Basis Function (RBF); Stop band Attenuation (SBA); Pass band Ripple (PBR).