Extraction of Coupling Coefficients for Quasi-Elliptic Function Cross-Coupled Filters

This text describes a MATLAB program that extracts coupling coefficients for quasi-elliptic function cross-coupled filters using Genetic Algorithm and Solvopt optimization toolkit. The program is designed to enhance filter design efficiency by optimizing parameters through evolutionary computation (Genetic Algorithm) and gradient-based local search (Solvopt). Key functions involve initial population generation, fitness evaluation based on filter response criteria, and constraint handling for physical realizability. If users encounter implementation challenges, detailed guidance is available via QQ: 13319810.

Alternative approaches for coupling coefficient extraction include MATLAB's built-in Optimization Toolbox with functions like fmincon for constrained nonlinear optimization, or custom algorithms employing analytical gradient calculations. Each method has distinct trade-offs: stochastic algorithms (e.g., Genetic Algorithm) avoid local minima but require higher computational cost, while deterministic methods (e.g., sequential quadratic programming) converge faster but depend on initial guesses. Comparative studies of these algorithms can advance filter synthesis techniques by balancing precision, robustness, and computational efficiency.