Abstract
Noise cancellation is the primary issue of the theory and practice of signal processing. The Savitzky-Golay (SG) smoothing and differentiation filter is a well studied simple and efficient technique for noise eliminating problems. In spite of all, only few book on signal processing contain this method. The performance of the classical SG-filter depends on the appropriate setting of the windowlength and the polynomial degree. Thus, the main limitations of the performance of this filter are the most conspicious in processing of signals with high rate of change. In order to evade these deficiencies in this paper we present a new adaptive design to smooth signals based on the Savitzky-Golay algorithm. The here provided method ensures high precision noise removal by iterative multi-round smoothing. The signal approximated by linear regression lines and corrections are made in each step. Also, in each round the parameters are dynamically change due to the results of the previous smoothing. The applicability of this strategy has been validated by simulation results.
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