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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 paper, we present an application of the Ant Colony Optimization technique (ACO) in order to selected optimal values of resistors and capacitors from different manufactured series to satisfy the filter design criteria. 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 State Variable Filter. SPICE simulations are used to validate the obtained results/performances which are compared with already published works.

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In this paper, two Meta-heuristic techniques; namely Ant Colony Optimization (ACO) and Genetic Algorithm (GA) have been applied for the optimal design of digital and analog filters. Those techniques have been used to solve multimodal optimization problem in Infinite Impulse Response (IIR) filter design and to select the optimal component values from industrial series as well as to minimize the total design error of a 2nd order Sallen-Key active band-pass filter, also a comparison between the performances reached by those two Meta-heuristics was made in this article.

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