Design and Analysis of FIR Filter using Artificial Neural Network

Abstract−For the designing of low pass FIR filter it require filter specification like sampling frequency(fs), cut off frequency(fc),pass band frequency, stop band frequency etc. By using these specification we can calculate filter coefficients h(n).These filter coefficients decide the structure of filter. It is easy to get these filter cofficients from filter specification by using simple calculation, but it is difficult to find filter specification from filter coeffients. In this paper we use Blackman window for FIR filter designing & then using Neural Network tool to estimate the cut off frequency of given coefficients of FIR filter. Firstly we have designed the 10th order digital filter then calculate the coefficient of designed filter. We have normalized the frequency and designed filter at frequency ranges 0 to 1 Hz. Then we have calculated the coefficients of filter at different frequencies. Some data group of coefficients is used to train the neural network designed using generalized regression algorithm and rest are used as test input to neural network. Designing and analysis of low pass FIR filter using different artificial neural network algorithm and then comparing their result to obtain most effective among the two and accurate neural network design algorithm for FIR filter.