Codebook prediction: A nonlinear signal modeling paradigm

Andrew C. Singer, Gregory W. Wornell, Alan V. Oppenheim

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

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 (US)
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
Externally publishedYes
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

Other

Other1992 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 1992
Country/TerritoryUnited States
CitySan Francisco
Period3/23/923/26/92

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Codebook prediction: A nonlinear signal modeling paradigm'. Together they form a unique fingerprint.

Cite this