Efficient design of high pass FIR filter using quantum-behaved particle swarm optimization with weighted mean best position

Author

Dhabal, Supriya ; Sengupta, Saptarshi

Author_Institution

Dept. of Electron. & Commun. Eng., Netaji Subhash Eng. Coll., Kolkata, India

fYear

2015

fDate

7-8 Feb. 2015

Firstpage

1

Lastpage

6

Abstract

Quantum-behaved particle swarm optimization (QPSO) algorithm theoretically guarantees global convergence and has been implemented on a wide suite of continuous optimization problems. In this paper, the nonlinear multimodal optimization problem of high pass FIR filter design is investigated using the weighted mean best QPSO algorithm (WQPSO). The results are compared with competitive techniques such as QPSO keeping PSO and PM as references. It is seen that WQPSO statistically outperforms QPSO in terms of convergence characteristics and ripple performance of the designed filter.

Keywords

FIR filters; high-pass filters; particle swarm optimisation; WQPSO; continuous optimization problems; designed filter; global convergence; high pass FIR filter; nonlinear multimodal optimization problem; quantum behaved particle swarm optimization; weighted mean best QPSO algorithm; weighted mean best position; Algorithm design and analysis; Band-pass filters; Convergence; Equations; Filtering algorithms; Finite impulse response filters; Particle swarm optimization; FIR Filter; Global Optimization; QPSO; Quantum Behaviour; Swarm Intelligence;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer, Communication, Control and Information Technology (C3IT), 2015 Third International Conference on

Conference_Location

Hooghly

Print_ISBN

978-1-4799-4446-0

Type

conf

DOI

10.1109/C3IT.2015.7060145

Filename

7060145