<?xml version="1.0" encoding="UTF-8"?> <article key="pdf/16975" mdate="2013-09-06 00:00:00"> <author>Ephraim Gower and Thato Tsalaile and Monageng Kgwadi and Malcolm Hawksford.</author> <title>Robust Coherent Noise Suppression by Point Estimation of the Cauchy Location Parameter</title> <pages>262 - 268</pages> <year>2013</year> <volume>7</volume> <number>2</number> <journal>International Journal of Mathematical and Computational Sciences</journal> <ee>https://publications.waset.org/16975.pdf</ee> <url>https://publications.waset.org/vol/74</url> <publisher>World Academy of Science, Engineering and Technology</publisher> <abstract>This paper introduces a new point estimation algorithm, with particular focus on coherent noise suppression, given several measurements of the device under test where it is assumed that 1) the noise is firstorder stationery and 2) the device under test is linear and timeinvariant. The algorithm exploits the robustness of the Pitman estimator of the Cauchy location parameter through the initial scaling of the test signal by a centred Gaussian variable of predetermined variance. It is illustrated through mathematical derivations and simulation results that the proposed algorithm is more accurate and consistently robust to outliers for different tailed density functions than the conventional methods of sample mean (coherent averaging technique) and sample median search. </abstract> <index>Open Science Index 74, 2013</index> </article>