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An alternative approach to digital filter design is presented. Although it is used in this paper to fit FIR filters to frequency domain specifications, the method is suitable to application in other problems of digital filter design, where the matter under study can be stated as finding the global minimum of a numerical function of filter parameters. The adopted numerical optimization algorithm is based upon the well-known simulated annealing paradigm and its implementation known as fuzzy adaptive simulated annealing. The overall design method is as follows: starting from frequency domain constraints and a parameterized expression of the filter family under adaptation, a corresponding training set is created, an error function synthesized and a global minimization process executed. At the end, the point that minimizes globally the particular cost function at hand determines the optimal filter.
Date of Conference: 15-18 Dec. 2007