The generalised sequentially rejective Bonferroni test applied to non-stationary, random signal classification

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The generalised sequentially rejective Bonferroni test applied to non-stationary, random signal classification

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Title: The generalised sequentially rejective Bonferroni test applied to non-stationary, random signal classification
Author: Roberts, G; Zoubir, A.M.; Boashash, B
Abstract: We present a new non-stationary signal classification algorithm based on a time-frequency distribution and multiple hypothesis testing. The time-frequency distribution is used to construct a time-dependent quadratic discriminant function. At selected points in time we evaluate the discriminant function and form a set of statistics which are used to test multiple hypotheses. We show that the statistics are a linear combinations of chi square random variables with constant coefficients and hence are not normally distributed. The multiple hypotheses are treated simultaneously using the generalised sequentially rejective Bonferroni test to control the probability of incorrect classification of one class. Finally, we show the results of classifying time-varying AR( 1) processes which have identical expected instantaneous power and power spectral densities but different time-frequency representations.
Description: This paper presents a new method for the classification of non-stationary Gaussian signals by combining time frequency analysis with multiple hypothesis testing for classes of signals that are inseparable in either the time or the frequency domain alone. (Additional relevant material and details can be found in the comprehensive book on Time-Frequency Signal Analysis and Processing (see http://www.elsevier.com/locate/isbn/0080443354). In addition, the most recent upgrade of the original software package that calculates Time-Frequency Distributions and Instantaneous Frequency estimators can be downloaded from the web site: www.time-frequency.net. This was the first software developed in the field, and it was first released publicly in 1987 at the 1st ISSPA conference held in Brisbane, Australia, and then continuously updated).
URI: http://hdl.handle.net/10576/10875
Date: 1996

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