Simultaneous random signal estimation and decomposition

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. Although the algorithm is developed based on the standard Kalman filtering scheme, the nature of blockwise filtering results in a smoothing-equivalent effect. However, the interpolated filtering produces a decomposed estimate output in real-time