Performance analysis of FIR Low Pass FIR Filter using Artificial Neural Network

Performance analysis of FIR Low Pass FIR Filter using Artificial Neural Network

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
  
© 2017 by IJETT Journal
Volume-50 Number-1
Year of Publication : 2017
Authors : Meenakshi Kumari, Mukesh kumar, Rohini saxena, Prof. A. K. Jaiswal
DOI :  10.14445/22315381/IJETT-V50P210

Citation 

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

Abstract
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.

Reference
[1] Design and Analysis of Low Pass FIR & IIR Filter and Find Optimum Result Using Neural Network [Global Journal of Researches in Engineering].
[2] Sara Moein, “FIR Cutoff Frequency Calculating for ECG Signal Noise Removing Using Artificial Neural Network” Verlag Berlin Heidelberg,pp.124-131(2010).
[3] Sanjit K. Mitra, “Digital Signal Processing: AComputer-Based Approach”, Second Edition, Mc GrawHillScience/Engineering/Math,2001,pp.446-472.
[4] S. Salivahanan, “Digital Signal Processing”, McGraw-Hill, 2000, pp. 735-749.
[5] M. S. Chavan, R. A. Agarwala, and M. D. Uplane, “Use of Kaiser window FOR ECG processing,” in Proc. 5th WSEAS Int. Conf. on Signal Processing, Robotics and Automation, Madrid, Spain, Feb. 15-17, 2006, pp. 285-289.
[6] S. Thapar, “A low pass FIR filter design using genetic algorithm based artificial neural network,” International Journal of Computer Technology and Electronics Engineering (IJCTEE), vol. 2, no. 4, Aug. 2012.
[7] T. Saramaki and S. K. Mitra, Finite Impulse Response Filter Design, Handbook for Digital Signal Processing, New York: Wiley-Interscience, 1993.
[8] Amanpreet Kaur, “Design of FIR filter using particle swarm optimization algorithm for audio processing,” International Journal of Computer Science and Network (IJCSN), vol. 1, no. 4, Aug. 2012.
[9] Harpreet Kaur and Balwinder Dhaliwal, “Design of low pass FIR filter using artificial neural network,” International Journal of Information and Electronics Engineering, vol. 3, no. 2, Mar. 2013.
[10] D. Suckley, “Genetic Algorithm in the Design of FIR Filters”, IEEE Proceedings Circuits Devices and Systems, vol. 138, pp.234-238, April 1991.
[11] M. Oner, “A Genetic Algorithm for Optimization of Linear-phase FIR Filter Coefficients”, in Proc. Conference on Signals, Systems and Computers, vol. 2, pp. 1397-1400, November 1998.
[12] K. Dey, S. Saha, A. Saha and S. Ghosh, “A Method of Genetic Algorithm (GA) for FIR filter Construction: Design and Development with Newer Approaches in Neural Network Platform”, International Journal of Advanced Computer Science and Applications, vol. 1, no. 6, pp.87-90, December 2010.
[13] E. Rashedi, N. Hossien, S. Saryazdi, “Filter modelling using gravitational search algorithm,” Engineering Applications of Artificial Intelligence, vol. 24, issue. 1, pp. 117–122, 2011.
[14] Esmat Rashedi, Hossein Nezamabadi-pour, and Saeid Saryazdi, “GSA: A Gravitational Search Algorithm,” Information Sciences, vol. 179 pp. 2232–2248, 2009.
[15] Eldon Y. Li, “Artificial Neural Networks and their Business Applications”, Taiwan, 1994. FLEXChip Signal Processor (MC68175/D), Motorola, 1996.
[16] Christos Stergiou and Dimitrios Siganos, “Neural Networks”.
[17] Harpreet Kaur and Balwinder S. Dhaliwal,(2011) “Design of low pass FIR filter using Artificial Neural Network” 3 rd International Conference on Computer and Automation Engineering(ICCAE), Chongqing, China,2011,pp.463- 466.
[18] Hintz K. J. and Spofford J. J., (1990) “Evoling Neural Network” Proceedings of the IEEE Transactions on Communication and Intelligence, May 1990, pp. 333–338.
[19] P. Pomenka and Z. Raida, “Methodology of neural design: applications in microwave engineering”, Radio Engineering June 2006, Vol. 15 No. 2,pp 12-17.
[20] Donald F. Specht. “A General Regression Neural Network”, IEEE Transactions on Neural Networks, November 1991. VOL. 2 . NO. 6, pp. 568-576.
[21] K. Arun Kumar, R. Ashwath, D. Sriram Kumar, R. Malmathanraj, “Optimization of Multislotted Rectangular Microstrip Patch Antenna using ANN and Bacterial Foraging Optimization”, Asia-Pacific International Symposium on Electromagnetic Compatibility, Beijing, China,2010,pp. 449-452.

Keywords
Liner Layer, FIR Filter, ANN, GRNN, RBF, RBE, BPNN.