This paper proposes a new adaptive comb filter which automatically designs its characteristics. The comb filter is used to eliminate a periodic noise from an observed signal. To design the comb filter, there exists three important factors which are so-called notch frequency, notch gain, and notch bandwidth. The notch frequency is the null frequency which is aligned at equally spaced frequencies. The notch gain controls an elimination quantity of the observed signal at notch frequencies. The notch bandwidth controls an elimination bandwidth of the observed signal at notch frequencies. We have previously proposed a comb filter which can adjust the notch gain adaptively to eliminate the periodic noise. In this paper, to eliminate the periodic noise when its frequencies fluctuate, we propose the comb filter which achieves the adaptive notch gain and the adaptive notch bandwidth, simultaneously. Simulation results show the effectiveness of the proposed adaptive comb filter.

This paper proposes an adaptive comb filter with flexible notch gain. It can appropriately remove a periodic noise from an observed signal. The proposed adaptive comb filter uses a simple LMS algorithm to update the notch gain coefficient for removing the noise and preserving a desired signal, simultaneously. Simulation results show the effectiveness of the proposed comb filter.

This paper proposes a comb filter design method which utilizes two linear phase FIR filters for flexibly adjusting the comb filter's frequency response. The first FIR filter is used to individually adjust the notch gains, which denote the local minimum gains of the comb filter's frequency response. The second FIR filter is used to design the elimination bandwidths for individual notch gains. We also derive an efficient comb filter by incorporating these two FIR filters with an all-pass filter which is used in a conventional comb filter to accurately align the nulls with the undesired harmonic frequencies. Several design examples of the derived comb filter show the effectiveness of the proposed comb filter design method.

An optimum filter for extracting a time-varying harmonic signal from the noise-corrupted measurement is proposed. It is derived as a solution of the least mean square estimation with consideration of the pitch estimation error even without any assumption on the filter model. We obtain a comb-like impulse response which consists of homologous and dilated distribution of weights just located periodically with a pitch interval. This remarkable structure is well suited to the proportionally expanding error of pitch repetition times. Examples of the filter design are presented, and the performance of noise suppression is examined by comparison with conventional comb filters.