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Codebook prediction: A nonlinear signal modeling paradigm

  • Massachusetts Institute of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

30 Scopus citations

Abstract

A nonlinear generalization of the family of autoregressive signal models is introduced. This generalization can be viewed as an autoregressive model with state-varying parameters. For such signals, minimum mean-square error prediction can be reformulated as an interpolation problem. A novel interpretation of the signal as a codebook for its own prediction leads to an interpolation strategy resembling a predictive counterpart to vector quantization. The applicability of this model is then demonstrated empirically for a variety of signals.

Original languageEnglish
Title of host publicationICASSP 1992 - 1992 International Conference on Acoustics, Speech, and Signal Processing
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages325-328
Number of pages4
ISBN (Electronic)0780305329
DOIs
StatePublished - 1992
Event1992 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 1992 - San Francisco, United States
Duration: Mar 23 1992Mar 26 1992

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume5
ISSN (Print)1520-6149

Conference

Conference1992 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 1992
Country/TerritoryUnited States
CitySan Francisco
Period03/23/9203/26/92

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