The FIR Filter Design based on Genetic Algorithm

Year 2018, Volume: 6 , 33 - 36, 01.04.2018

Zeynep B. Garıp , Ali Fuat Boz

https://doi.org/10.17694/bajece.410234

Cited By: 1

Abstract

Especially, in the signal and image processing
fields of electronics, filters are most often used parts. Also, rapid advances
in digital systems have expanded the use of digital filters. Therefore, it is
very important to understand and learn the filters and calculation of their
coefficients. Thus, in this work, interactive graphical user interface software
which can be used for educational purposes and also accessible via the Internet
is designed in the MATLAB environment. 
In the software, genetic algorithm, which is one of the popular methods
in recent years, is used for designing the Finite Impulse Response (FIR)
filters. In this program, when the parameters of filter, which will be
designed, are entered by the user, the coefficients are obtained from genetic
algorithms, and many features of the filter are presented numerically and
graphically. Thus, the FIR filter design can easily be carried out for
practical or educational purposes using the software. Further, the superiority
of the genetic algorithm over the classical design in this field has been shown
by comparing the obtained filter coefficients for both methods.

Keywords

Digital filters, genetic algorithms, FIR filter

References

• [1] S. Winder, Analog and Digital Filter Design, Second Edition ,,-Newnes, USA, 2002.
• [2] W.-K.Chen (Ed.), The Circuits and Filters Handbook, Second Edition CRC Press, 2003.
• [3] V.K. Ingle, J.G. Proakis, Digital Signal Processing Using MATLAB ,V.4, PWS Publishing Company, Boston, 1997.
• [4] L. Thede, Practical Analog and Digital Filter Design, Artech House Publication, 2004.
• [5] D.E. Goldberg, Genetic Algorithms in Search Optimization and Machine Learning, Addison Wesley, 1989.
• [6] S. Duman, A. Öztürk, Robust Design of PID Controller for Power System Stabilization by Using Real Coded Genetic Algorithm, International Review of Electrical Engineering (IREE), vol. 5 n. 5, pp. 2159– 2170, 2010.
• [7] M. Eslami, H. Shareef, A. Mohamed, M. Khajehzadeh, Damping of Power System Oscillations Using Genetic Algorithm and Particle Swarm Optimization, International Review of Electrical Engineering (IREE), vol. 5 n. 6, pp. 2745 – 2753, 2010.
• [8] M. Rashidi, F. Rashidi, Power System Stabilizer Tuning Using Multi-Objective Genetic Algorithm, International Review of Electrical Engineering (IREE), vol. 6 n. 4, pp. 356 – 363, 2011.
• [9] A. Dey, A. Saha, S. Saha, S.A. 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, 2010.
• [10] S. Goyal, J. Raina, Design of Low Power FIR Filter Coefficients Using Genetic Algorithm, vol. 1, no. 2, pp. 1-5, 2010.
• [11] A. Ahmad, Design of Digital Filters Using Genetic Algorithms, Ph.D. dissertation, University of Victoria, Electrical and Computer Engineering, 2010.
• [12] D. Suckley, Genetic algorithm in the design of FIR filters, IEE Proceedings-G, vol. 138, no. 2, 1991.
• [13] The Matworks, MATLAB 2008.
• [14] J.H. Holland, Adaption in Natural and Artificial Systems, Cambridge, MA, MIT Press, 1975.