The design of multiple feedback topology Chebyshev low-pass active filter with average differential evolution algorithm
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This study presents the design of a tenth-order multiple feedback Chebyshev low-pass filter (MF-C-LPF). Component selection and gain calculation of filters are generally achieved over long periods of time using traditional methods. For 1-dB and 3-dB gains, the component values of the filter were optimized for both continuous and discrete values using four different metaheuristic algorithms. In the first case where continuous values were used, component values were accepted as ideal and unlimited in order to minimize gains. In the second case, industrial E196 series component values were used to transform the design problem into a discrete optimization problem. In this case where the design problem became more complex, the performance of the metaheuristic algorithms was compared. The literature review shows that this study is the first attempt to design a 10th-order MF-C-LPF for E196 series values. The average differential evolution algorithm is proposed to determine the optimal component values of the tenth-order MF-C-LPF. The performance of the proposed method was compared with three commonly used algorithms (PSO, CSS and DE). The optimal filter component values and quality factors (Q) were presented for each stage. We believe that the quality factor values will be a reference for future studies.