Blind extraction of short-sampled signal based on time structure

Abstract

To enhance the quality of the restored signal extracted from short-sampled paths, this paper proposed a novel blind extraction method based on time structure. By replacing negentropy with the sum of autocorrelation statistically obtained at multiple delays as the objective function, and introducing the closeness between output signal and reference signal as well as output's variance as the constraints of non-linear programming, besides incorporating the Newton-like iterative method, a novel iterative expression was successfully deduced to extract one-path signal. In addition, a novel criterion to evaluate the short samples is presented. Simulation showed that, whatever the length of observed multiple signals is, as long as the short-duration component is contained, the proposed method can extract the useful signal in high quality.