Resumen

VIEGENER, Alejandro et al. Joint Kalman-Haar algorithm applied to signal processing. Rev. Mat [online]. 2012, vol.19, n.1, pp.37-47. ISSN 1409-2433.

Under the analysis of signals disturbed by noise, in this paper we propose a working methodology aimed to seize the best estimate of combining Kalman filtering with the characterization that is achieved by applying a multiresolution analysis (MRA) using wavelets. From the standpoint of Kalman filtering this combined procedure is quasi-optimal, but the change to be made allows the simultaneous implementation of a scheme of wavelet denoising; with this decreases the computational cost of applying both procedures separately. Our proposal is to process the signal by successive non-overlapping intervals, combining the process for calculating the optimal filter with a MRA using the Haar wavelet. The method takes advantage of the combined use of both tools (Kalman-Haar) and is free from edge problems related to the signal segmentation

Palabras clave : Signal processing; Kalman filter; wavelet denoising; multiresolution analysis.

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