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Ji-Gou Liu, Jin Song Chen
Frequency-selective Adaptive Filtering for Noise Suppression of Discrete Signals
Noise suppression plays an important role in sensors, measurement technology, and telecommunications. In this paper a frequency-selective filtering is introduced for the noise reduction of discrete signals. This filtering is based on a selection of frequency components of signal by using Fourier-analysis and the autocorrelation function. The output signal results from a signal reconstruction with the help of Fourier-series using the frequency components. In order to improve the filtering accuracy, a suitable adaptive algorithm is used in this filtering process. In this way a complete suppression of uncorrelated noise parts of discrete signals can be realized. The adaptive filtering is suitable for noise reduction of periodic and periodically extended signals, the spectrum of whom is super-imposed by the noise spectrum. Theoretical fundamentals, algorithms, simulation results and application examples are shown in this paper.
tm – Technisches Messen, Oldenbourg Wissenschaftsverlag
Print ISSN: 0171-8096
Volume: 70, 11/2003
Pages: 522