Step Signal Detection Via Clustering Analysis With Gaussian Contamination

Alireza Moghaddamjoo

doi:10.1117/12.968274

1 January 1987 Step Signal Detection Via Clustering Analysis With Gaussian Contamination

Alireza Moghaddamjoo

Proceedings Volume 0858, Signal Acquisition and Processing; (1987) https://doi.org/10.1117/12.968274
Event: IECON, Cambridge, 1987, Cambridge, MA, United States

Abstract

An algorithm for filtering noisy step-like signals is proposed. This algorithm is based on the assumption of Gaussian contamination. In this procedure data within a moving window is divided into two almost equal clusters and a hypothesis tests (F-test) for differences in the means between two such clusters. Histogram analysis and/or our a priori knowledge about the number of discrete amplitudes in the ideal noise free signal provide information that is used to filter the signal further and produce a clean signal with the desired number of discrete amplitudes (levels). As an illustration the method is tested by simulation.

Citation Download Citation

Alireza Moghaddamjoo "Step Signal Detection Via Clustering Analysis With Gaussian Contamination", Proc. SPIE 0858, Signal Acquisition and Processing, (1 January 1987); https://doi.org/10.1117/12.968274

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