Title :
The adaptive separation of the overlapped periodic signals, whose periods are very close
Author :
Li, Dan ; Zhu, Y.-S. ; Li, H.-Z. ; Zhu, Yi-sheng
Author_Institution :
Dept. of Radio & Electron., Univ. of Sci. & Technol., China
Abstract :
A correlated impulse adaptive filter for separating periodic signals whose periods are very close is proposed. It is shown that the method is effective even when the signals are contaminated by white noise. The method requires multiple input of impulse series with different periods as reference signals. The periods of periodic signals must be detected through a search process in order to guarantee the correlation between the reference signals and periodic signals. By adopting the least-mean-square-error criterion, the output can be proved to be the desired signals. A μ-adjuster is used to speed up the convergence process and improve the filtering quality. A rectifying algorithm is proposed to correct the distortion of the output of the adaptive filter, which gives satisfactory results
Keywords :
adaptive filters; filtering and prediction theory; least squares approximations; white noise; adaptive separation; convergence process; correlated impulse adaptive filter; filtering quality; least-mean-square-error criterion; multiple input; overlapped periodic signals; periodic signals; reference signals; search process; white noise; Adaptive filters; Digital signal processing; Equations; Frequency domain analysis; Least squares approximation; Matched filters; Signal processing; Signal processing algorithms; Speech processing; White noise;
Conference_Titel :
Circuits and Systems, 1992., Proceedings of the 35th Midwest Symposium on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-0510-8
DOI :
10.1109/MWSCAS.1992.271399