A filter coefficient quantization method with genetic algorithm, including simulated annealing

Miki Haseyama, Daiki Matsuura

Abstract: A method based on a genetic algorithm (GA), including a simulated annealing (SA), is proposed for filter coefficient quantization. The proposed method uses the GA to search a population of the quantized filters of a digital filter for the optimal quantized filter. It retains the most accurate frequency characteristic of the original filter, which is either finite impulse response filter or an infinite impulse response filter. The initial population in the GA is generated by binomial distributions, which are not used for the other GAs. An SA is also embedded in the GA search, which can support the GA to converge to the optimum in the early generations. The experimental results verify that our method can provide a quantized filter with a better frequency characteristic than those obtained by the traditional quantization methods, such as rounding off, rounding up, and rounding down.