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On Random Distortion Testing Based Sequential Non-Parametric Hypothesis Testing

Khanduri, P and Pastor, D and Sharma, V and Varshney, PK (2019) On Random Distortion Testing Based Sequential Non-Parametric Hypothesis Testing. In: UNSPECIFIED, 2 October 2018, pp. 328-334.

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Abstract

In this work, we propose a new method for sequential binary hypothesis testing. The approach is non-parametric in the sense that it does not assume any knowledge of signal distributions under each hypothesis. The proposed framework is based on Random distortion testing (RDT) which addresses the problem of testing whether or not a random signal, deviates by more than a specified tolerance, τ, from a fixed value, ξ-0. We first state the problem setup and then discuss earlier approaches to solve the problem. We then propose a new sequential algorithm, T-SeqRDT, which is shown to control the probabilities of error while reducing the number of samples required to make a decision compared to the fixed-sample-size version of RDT. Finally, via simulations we compare T-SeqRDT to other algorithms and show its robustness compared to standard likelihood ratio based approaches. © 2018 IEEE.

Item Type: Conference Paper
Additional Information: Copyright for this article belongs to Institute of Electrical and Electronics Engineers Inc.
Keywords: Computer programming; Computer science; Control engineering, Binary Hypothesis Testing; Hypothesis testing; Likelihood ratios; Number of samples; Probabilities of error; Random distortions; Sequential algorithm; Signal distribution, Problem solving
Department/Centre: Division of Electrical Sciences > Electrical Communication Engineering
Depositing User: Id for Latest eprints
Date Deposited: 15 Apr 2019 05:14
Last Modified: 15 Apr 2019 05:14
URI: http://eprints.iisc.ac.in/id/eprint/62083

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