Detection of burst noise using the chi-squared goodness of fit test

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Title: Detection of burst noise using the chi-squared goodness of fit test
Author: Marwaha, Shubra
Abstract: Statistically more test samples obtained from a single chip would give a better picture of the various noise processes present . Increasing the number of samples while testing one chip would however lead to an increase in the testing time , decreasing the overall throughput . The aim of this report is to investigate the detection of non -Gaussian noise (burst noise ) in a random set of data with a small number of samples . In order to determine whether a given set of noise samples has non -Gaussian noise processes present , a Chi -Squared ‘Goodness of Fit’ test on a modeled set of random data is presented . A discussion of test methodologies using a single test measurement pass as well as two passes is presented from the obtained simulation results .
URI: http : / /hdl .handle .net /2152 /ETD -UT -2009 -08 -180
Date: 2010-06-04

Citation

Detection of burst noise using the chi-squared goodness of fit test. Master's thesis, The University of Texas at Austin. Available electronically from http : / /hdl .handle .net /2152 /ETD -UT -2009 -08 -180 .

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