A New Mutated Quantum-Behaved Particle Swarm Optimizer for Digital IIR Filter Design

A New Mutated Quantum-Behaved Particle Swarm Optimizer for Digital IIR Filter Design
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用于数字 IIR 滤波器设计的新型突变量子行为粒子群优化器

DOI:
10.1155/2009/367465
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发表时间:
2010-01
影响因子:
1.9
通讯作者:
Fang, Wei
Fang, Wei
中科院分区:
工程技术4区
文献类型:
--
作者:
Sun, Jun;Xu, Wenbo;Fang, Wei

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自适应无限脉冲响应(IIR)过滤器已在各种实际应用中表现出其价值。由于在大多数情况下,IIR过滤器的误差表面是多模式的,因此避免局部最小值需要全局优化技术。
Adaptive infinite impulse response (IIR) filters have shown their worth in a wide range of practical applications. Because the error surface of IIR filters is multimodal in most cases, global optimization techniques are required for avoiding local minima. In this paper, we employ a global optimization algorithm, Quantum-behaved particle swarm optimization (QPSO) that was proposed by us previously, and its mutated version in the design of digital IIR filter. The mechanism in QPSO is based on the quantum behaviour of particles in a potential well and particle swarm optimization (PSO) algorithm. QPSO is characterized by fast convergence, good search ability, and easy implementation. The mutated QPSO (MuQPSO) is proposed in this paper by using a random vector in QPSO to increase the randomness and to enhance the global search ability. Experimental results on three examples show that QPSO and MuQPSO are superior to genetic algorithm (GA), differential evolution (DE) algorithm, and PSO algorithm in quality, convergence speed, and robustness.
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