On Random Distortion Testing Based Sequential Non-Parametric Hypothesis Testing

Prashant Khanduri, Dominique Pastor, Vinod Sharma, Pramod K. Varshney

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

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, \tau, from a fixed value, \xi-{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.

Original languageEnglish (US)
Title of host publication2018 56th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages328-334
Number of pages7
ISBN (Electronic)9781538665961
DOIs
StatePublished - Feb 5 2019
Event56th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2018 - Monticello, United States
Duration: Oct 2 2018Oct 5 2018

Publication series

Name2018 56th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2018

Conference

Conference56th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2018
CountryUnited States
CityMonticello
Period10/2/1810/5/18

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Signal Processing
  • Energy Engineering and Power Technology
  • Control and Optimization

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