Design of discrete coefficient FIR filters by a fast entropy-directed deterministic annealing algorithm

We present an entropy-directed deterministic annealing optimization algorithm and show its applicability to the problem of designing digital filters with discrete coefficients, each implemented as a sum of signed power-of-two terms and additional general hardware constraints. The algorithm is based on analogies from statistical mechanics and is related to the well-known mean field annealing algorithm. It utilizes estimates of conditional entropy to prune the problem during the optimization, thereby reducing the computational time by 30 to 50%. In conjunction with a scheme to compute the value of the objective function as a sequence of updates, this approach leads to a very fast algorithm. As an application example demonstrating the potential of the new method, we consider the design of digital filters with discrete coefficients consisting of a minimum number of signed power-of-two terms.