Abstract

The authors introduce an autocomponent selection (ACS) algorithm to remove the cross-components produced by the discrete pseudo-Wigner distribution (DPWD). The ACS treats the DPWD as an image with polarity. This image is processed with an averaging filter to eliminate negative values. The result is then compared with a preprocessed DPWD to classify each image pixel. This approach yields a subset of the DPWD free of redundancies. Unlike traditional smoothing technique, this algorithm does not reduce the time-frequency resolution. >

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