Optimal design of stable recursive digital filters using unconstrained optimization methods

Generally, in filter design constrained optimization techniques are preferred to unconstrained optimization techniques because unconstrained optimization methods tend to increase the nonlinearity of the design. However, this paper presents an unconstrained optimization based method for the optimal design of stable recursive digital filters, which reduces the customary nonlinearity added by unconstrained optimization methods. Also, a novel approach for generating the initial parameter vector for any set of recursive digital filter design specifications is introduced.