Efficient Design of High Pass FIR Filter using Quantum-behaved Particle Swarm Optimization with Weighted Mean Best Position

被引：0
|
作者：
Dhabal, Supriya [1 ]
Sengupta, Saptarshi [1 ]
机构：
[1] Netaji Subhash Engn Coll, Dept Elect & Commun Engn, Kolkata, W Bengal, India
来源：
2015 THIRD INTERNATIONAL CONFERENCE ON COMPUTER, COMMUNICATION, CONTROL AND INFORMATION TECHNOLOGY (C3IT) | 2015年
关键词：
QPSO; Quantum Behaviour; Swarm Intelligence; Global Optimization; FIR Filter;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
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.
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页数：6
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