Application of Quantum Particle Swarm Optimization in Adaptive Notch Filter Design

Abstract:

Abstract: adaptive notch filter is a kind of apparatus which can eliminate single frequency or narrow-band interference, normal adaptive algorithm of notch filter is LMS algorithm, but the faster convergence velocity and the smaller steady error are difficult to gain simultaneously. Aimed at the weakness of LMS, the Particle Swarm Optimization (PSO) is studied deeply in the paper, based on the PSO; the quantum mechanic theory is added to improve it. Quantum Particle Swarm Optimization (QPSO) is researched and applied for adaptive notch filter which is proved more efficient in the noise control by MATLAB simulation. The new QPSO algorithm can balance the maladjustment and the searching ability of adaptive filter with a little calculation, the speed of convergence is faster than LMS and normal PSO algorithm.

• Periodical: Advanced Materials Research (Volumes 482-484)
• Pages: 2466-2469
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.482-484.2466
• Online since: February 2012
• Authors: Jie Zhang
• Keywords: Adaptive Notch Filter, LM Algorithm, Particle Swarm Optimization Algorithm (PSO), Quantum Particle Swarm Optimization (QPSO)

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