DESIGN OF DIGITAL FIR FILTER USING GREY WOLF OPTIMIZER ALGORITHM

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DESIGN OF DIGITAL FIR FILTER USING GREY WOLF OPTIMIZER ALGORITHM

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Sidhu, Navdeep Kaur / Dhillon, J.S.

In this paper, Grey Wolf Optimizer is applied to design digital FIR filters. The GWO algorithm mimics the hunting mechanism and leadership hierarchy of grey wolves. In GWO algorithm, four types of wolves such as alpha, beta, delta and omega are engaged for simulating the leadership hierarchy. The design of digital FIR filters involves the computation of best optimal filter coefficients which trying to meet ideal filter characteristics. Three key parameters which are responsible for filter performance are maximum pass-band ripple, maximum stop-band ripples and stop-band attenuation. The results of proposed GWO based approach has been compared with other optimization methods available in literature. Results reveal that the FIR filter design approach by using GWO outperforms other techniques undertaken for comparison in terms of pass-band ripples, stop-band ripples and stop-band attenuation.

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Title :

DESIGN OF DIGITAL FIR FILTER USING GREY WOLF OPTIMIZER ALGORITHM

Contributors:

Sidhu, Navdeep Kaur (author) / Dhillon, J.S. (author)

Publication date :

2017-08-28

Remarks:

doi:10.26483/ijarcs.v8i7.4545
International Journal of Advanced Research in Computer Science; Vol 8, No 7 (2017): July-August 2017; 968-973 ; 0976-5697 ; 10.26483/ijarcs.v8i7

DOI :

https://doi.org/10.26483/ijarcs.v8i7.4545

Type of media :

Article (Journal)

Type of material :

Electronic Resource

Language :

English

Keywords :

Real Coded Genetic algorithm (RCGA) , Particle Swarm Optimization (PSO) , Differential Evolution (DE) , Cat Swarm Optimization (CSO) , Gravitational Search Algorithm (GSA) , Cuckoo Search Algorithm (CSA) and Grey Wolf Optimizer (GWO) , Finite Impulse

Classification :

DDC: