Step Signal Detection Via Clustering Analysis With Gaussian Contamination

Alireza Moghaddamjoo

doi:10.1117/12.968274

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

Alireza Moghaddamjoo

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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.

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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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