Discrete optimization by combining local search and design centering techniques

The authors propose a method for the discrete optimization of arbitrary objective functions subject to any constraints. Universality of the method is achieved by combining statistical design centering and deterministic local search techniques. An important application is the design of digital filters with prescribed accuracy or wordlength for the coefficients. Due to its general applicability, the method can be used for any type of digital filter (FIR, IIR, one-dimensional, multidimensional, etc.) with various number representations for the coefficients. Some examples demonstrate how the performance of digital filters can be enhanced while still maintaining a given wordlength of the coefficients.<>