Abstract
This paper presents a novel hybrid algorithm based on Multi-swarm Cooperative Particle Swarm Optimization (MCPSO) and Simulated Annealing (SA) for the design of higher order Quadrature Mirror Filter (QMF) bank. The optimization of lower order filters can be carried out easily by traditional optimization methods, but these approaches failed to find higher order filter coefficients due to nonlinear and multimodality problem space. Most of the optimization algorithms are easily trapped into local optimum which yields few unwanted characteristics in filter magnitude responses like ripples in transition region, lower stop-band attenuation. The proposed algorithm, named Simulated Annealing-based Multi-swarm Cooperative PSO (SAMCPSO), is presented here to obtain prototype filter that leads to near-perfect reconstruction for both lower and higher dimensional filter banks. Comparison with other existing methods in the literature demonstrates that the proposed algorithm exhibits an average increase of 17.39% in stop-band attenuation and 47.35% reduction in Perfect Reconstruction Error (PRE) of 82-tap filter bank.
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Dhabal, S., Chakrabarti, R., Venkateswaran, P. (2019). Design of Higher Order Quadrature Mirror Filter Bank Using Simulated Annealing-Based Multi-swarm Cooperative Particle Swarm Optimization. In: Bhattacharyya, S., Mukherjee, A., Bhaumik, H., Das, S., Yoshida, K. (eds) Recent Trends in Signal and Image Processing. Advances in Intelligent Systems and Computing, vol 727. Springer, Singapore. https://doi.org/10.1007/978-981-10-8863-6_1
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DOI: https://doi.org/10.1007/978-981-10-8863-6_1
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