Abstract
In analog filter design, discrete components values such as resistors (R) and capacitors (C) are selected from the series following constant values chosen. Exhaustive search on all possible combinations for an optimized design is not feasible. In this chapter, we present an application of the Ant Colony Optimization (ACO) technique for optimal filter design considering different manufacturing series for both the resistors and capacitors. Three variants of the Ant Colony Optimization are applied, namely, the AS (Ant System), the MMAS (Min-Max AS) and the ACS (Ant Colony System), for the optimal sizing of the Low-Pass Butterworth filter. Different optimal designs of the filter are provided depending on the preference between two conflicting factors, namely the cutoff frequency and selectivity factor. SPICE simulations are used to validate the obtained results/performances. A comparison with published works is also highlighted.
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Kritele, L., Benhala, B., Zorkani, I. (2019). Ant Colony Optimization for Optimal Low-Pass Filter Sizing. In: Talbi, EG., Nakib, A. (eds) Bioinspired Heuristics for Optimization. Studies in Computational Intelligence, vol 774. Springer, Cham. https://doi.org/10.1007/978-3-319-95104-1_18
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DOI: https://doi.org/10.1007/978-3-319-95104-1_18
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