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Design A Kaiser Window Based Digital Filter by Using GRNN

Anil Mourya

Abstract


In this paper, we have designed the digital filter based on Kaiser Window function using ANN. Firstly we have designed the 10th order digital filter based on Kaiser Window function then calculate the coefficient of designed filter. Similarly this process is repeated for the 15th and 20th order. We have normalized the frequency and designed filter at frequency ranges 0.05 to 0.95 Hz. Then we calculated the coefficients of filter at these different frequencies. Some data group of coefficients is used to train the neural network, designed using generalized regression algorithm and rest data are used to test the input to neural network. The output corresponding to test input is approximate equal to frequency corresponding to calculated coefficients using FDA tool. The optimization of the neural model has been done using generalized regression algorithm.

Keywords: ANN, GRNN, LR, MLPFFBP, FDA TOOL

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DOI: https://doi.org/10.37628/ijmet.v2i1.285

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