Performance analysis of FIR Low Pass FIR Filter using Artificial Neural Network
Meenakshi Kumari, Mukesh kumar, Rohini saxena, Prof. A. K. Jaiswal "Performance analysis of FIR Low Pass FIR Filter using Artificial Neural Network", International Journal of Engineering Trends and Technology (IJETT), V50(1),58-62 August 2017. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group
The aim of this paper is to design and analysis of low pass FIR filter is used for comparison of different types of learning algorithm artificial neural network. A low pass FIR filter is design by using hamming window method with the help of FDA Toolbox in MATLAB. Hamming window is used in this proposed work for achieving minimize the maximum side lobe of signal. It is an optimized Windows method. The five different algorithm of artificial neural network namely generalized regression method, radial basis function, radial basis exact, linear layer and feed forward back propagation are used for comparison. Simulation result of a different artificial neural network has achieved general regression method with the best performance has compare to radial basis function, radial basis exact, linear layer and feed forward back propagation method.
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Liner Layer, FIR Filter, ANN, GRNN, RBF, RBE, BPNN.