Abstract
In this paper, a recently proposed global heuristic search optimization technique, namely, Modified Firefly Algorithm (MFFA) is considered for the design of the 8th order infinite impulse response (IIR) low pass (LP) digital filter. This modified version of FFA is considered to achieve quality output response by means of properly tuned control parameters over conventional Firefly Algorithm (FFA). Newly defined randomization parameter and modification in updating formula in MFFA makes it a perfect search tool in multidimensional search space. With this approach better exploration and exploitation are achieved, which have resulted in faster convergence to near global optimal solution. The performance of the proposed MFFA based approach is compared to the performances of some well accepted evolutionary algorithms such as particle swarm optimization (PSO) and real coded genetic algorithm (RGA). From the simulation study it is established that the proposed optimization technique MFFA outperforms RGA and PSO, not only in the accuracy of the designed filter but also in the convergence speed and the solution quality, i.e., the stop band attenuation, transition width, pass band and stop band ripples.
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Saha, S.K., Kar, R., Mandal, D., Ghoshal, S. (2013). Optimal Stable IIR Low Pass Filter Design Using Modified Firefly Algorithm. In: Panigrahi, B.K., Suganthan, P.N., Das, S., Dash, S.S. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2013. Lecture Notes in Computer Science, vol 8297. Springer, Cham. https://doi.org/10.1007/978-3-319-03753-0_10
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DOI: https://doi.org/10.1007/978-3-319-03753-0_10
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