AD/DA conversion has become a core technology in digital signal processing. Signal compression is one of the important components for AD/DA conversion systems. Delta-sigma modulator (DSM) is well known as an effective method for encoding analog signals into digital signals. Traditional data conversion systems are composed of the post-filter and the DSM. It is required to satisfy small quantization noise and small signal distortion characteristics by appropriate design of the filter and DSM. In this study, the authors propose a new design method of data conversion system that includes pre-filter in addition to the traditional data conversion system. To design easier, an evaluation framework of the data conversion system is proposed. Then, a design algorithm based on the evaluation framework is proposed by using particle swarm optimization algorithm. Post and pre-filters are designed so as to minimize the effect of the noise and the signal distortion due to quantization. In this paper, the authors verify the AD/DA systems with post and pre-filters by using the voice signal compression system. The effectiveness of the proposed design method is illustrated by the numerical simulations.
