Abstract
We propose a novel and efficient way to design maximally decimated FIR cosine modulated filter banks, in which each analysis and synthesis filter has linear phase. We consider a class of near-perfect reconstruction CMFBs with the linear phase prototype filter, which structurally eliminates the amplitude overall distortion. The prototype filter design problem is then formulated into a multi-objective optimization problem (MOP), which aims at maximizing stop-band attenuation and minimizing reconstruction error simultaneously. We have modeled the design problem as a constrained multi-objective optimization problem which is efficiently solved by using a recently proposed algorithm MOEA/DFD. Experiment shows that the performance of MOEA/DFD exceeds that of MOEA/D and NSGA-II.
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Nasir, M., Sengupta, S., Das, S. (2012). Efficient Design of Cosine-Modulated Filter Banks Using Evolutionary Multi-objective Optimization. In: Panigrahi, B.K., Das, S., Suganthan, P.N., Nanda, P.K. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2012. Lecture Notes in Computer Science, vol 7677. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35380-2_92
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DOI: https://doi.org/10.1007/978-3-642-35380-2_92
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