REAL-TIME SIMULTANEOUS ESTIMATION AND DECOMPOSITION OF RANDOM SIGNALS

In this paper, an efficient algorithm is derived for multiresolutional estimation and decomposition of noisy random signals. This algorithm performs in real-time the estimation and decomposition simultaneously, using the discrete wavelet transform implemented by a filter bank. Al though the algorithm is developed based on the standard Kalman filteri ng scheme, the nature of blockwise Filtering results in a smoothing-eq uivalent effect. However, the interpolated filtering produces decompos ed estimate output in real-time.