SUMMARYIn many areas, it is extremely important to accurately estimate the amplitude and phase of a signal even if the frequency contained in the signal to be analyzed is known. For cases in which the signal frequencies to be analyzed are in a nonharmonic relation and white noise and interference are superposed on the signal, a method (BPLMS method) combining the IIR type BPF and the LMS algorithm has been proposed to derive the Fourier coefficients of the signal components accurately. In the present paper, in order to investigate a method of improving the BPLMS method, an approximate equation for the estimated accuracy is derived. Also, the validity of the approximate equation is confirmed by computer simulations under various conditions. As a result of the approximate analysis, it is shown that the normalized frequency difference between the signal and the interference can be increased by combining a downsampling process so that the estimation accuracy can be improved. Finally, by simulation, the proposed method and the BPLMS method are compared in terms of estimation accuracy. An example of application to the pitch estimation of musical sounds is given.

SUMMARYEstimating the amplitude and phase of a signal accurately even when the frequencies contained in the signal are already known is very important in many areas. The estimation accuracy and the estimation time are important issues in such areas and a method of improving both of these issues by combining the notch characteristics and the band passing characteristics of serially connected notch filters and an adaptive algorithm is presented in this paper. Computer simulations reveal that the performance of the proposed method is superior to previously proposed methods. © 2001 Scripta Technica, Electron Comm Jpn Pt 3, 85(2): 6573, 2002

In many fields of active noise control (ANC), the filtered-x least mean squares ( LMS ) algorithm and its relatives are popular ones[1],[2], because of their simplicity. In these algorithms, the input signal to the algorithms is the signal filtered by the plant model, which must be identified in advance. As well known, the usage of the filtered signal causes two major problems [2]: the delay between adaptive FIR filter and the error signal; the well known eigenvalue spread in the autocorrelation matrix. In this article, the active noise control is proposed for specific applications such as ventilation equipment with a duct. The reference signal is decomposed into plural narrow-band signals by estimating each resonant frequency. As this approximation leads to that frequency characteristics of the plant model around vicinity of resonant frequencies are only taken account, there is no need to identify the overall characteristics of the plant model in advance. In the proposed method, lower order adaptive filters are only needed to adjust to the plant model with on-line manner. Finally, it is shown that the proposed method has almost the same performance as the filtered-x LMS algorithm with much less computational load.

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