Algoritmo conjunto Kalman-Haar aplicado al procesamiento de se？ales

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