Sequential prediction of individual sequences in the presence of computational errors

Mehmet A. Donmez, Andrew C. Singer

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

Abstract

We study the performance of a sequential linear prediction system built on nanoscale beyond-CMOS circuit fabric that may introduce in computation. We propose a new sequential linear prediction algorithm under a mixture-of-experts framework that performs satisfactorily in the presence of computational errors. We introduce a worst-case approach to model the computational errors, where we view erroneous circuit fabric as an adversary that perturbs the prediction algorithm to heavily deteriorate its performance. We demonstrate that our algorithm achieves uniformly good performance under the worst-case error approach in an individual sequence manner.

Original languageEnglish (US)
Title of host publicationConference Record of the 48th Asilomar Conference on Signals, Systems and Computers
EditorsMichael B. Matthews
PublisherIEEE Computer Society
Pages1773-1778
Number of pages6
ISBN (Electronic)9781479982974
DOIs
StatePublished - Apr 24 2015
Event48th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015 - Pacific Grove, United States
Duration: Nov 2 2014Nov 5 2014

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
Volume2015-April
ISSN (Print)1058-6393

Other

Other48th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015
CountryUnited States
CityPacific Grove
Period11/2/1411/5/14

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

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