J.S. Dhillon

Work place: Sant Longowal Institute of Engineering & Technology, Longowal, India

E-mail: jsdhillon@sliet.ac.in


Research Interests: Combinatorial Optimization


J.S. Dhillon: is presently working as Professor in department of Electrical & Instrumentation Engineering, Sant Longowal Institute of Engineering & Technology, Longowal-148106, Punjab, India. He did his Bachelor's degree from Guru Nanak Dev Engineering College (GNE), Ludhiana and Master’s degree from Punjab Agriculture University (PAU), Ludhiana, both in Electrical Engineering. He did his PhD from Thapar University, Patiala. He is having over 26 years of teaching experience. His area of specialization is Economic Operations of Power System, Optimization Techniques, Microprocessors and Control Systems He is member of IEEE, IE and life member of ISTE.

Author Articles
Digital IIR Filter Design using Real Coded Genetic Algorithm

By Ranjit Kaur Manjeet Singh Patterh J.S. Dhillon

DOI: https://doi.org/10.5815/ijitcs.2013.07.03, Pub. Date: 8 Jun. 2013

The paper develops a technique for the robust and stable design of digital infinite impulse response (IIR) filters. As the error surface of IIR filters is generally multi-modal, global optimization techniques are required to design efficient digital IIR filter in order to avoid local minima. In this paper a real-coded genetic algorithm (RCGA) with arithmetic-average-bound-blend crossover and wavelet mutation is applied to design the digital IIR filter. A multicriterion optimization is employed as the design criterion to obtain the optimal stable IIR filter that satisfies the different performance requirements like minimizing the Lp-norm approximation error and minimizing the ripple magnitude. The proposed real-coded genetic algorithm is effectively applied to solve the multicriterion, multiparameter optimization problems of low-pass, high-pass, band-pass, and band-stop digital filters design. The computational experiments show that the proposed method is superior or atleast comparable to other algorithms and can be efficiently used for higher order filter design.

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