Title
Efficient Code Excited Linear Predictor Using Redundant Vector Quantiser Representations
Abstract
The description of a novel linear prediction (LP) model-based coding technique was presented, where the advantages of multiple non-orthogonal domain representations of LP coefficients and the residuals were exploited in conjunction with vector quantisation. The LP model-based coding was applied to speech signals and the resulting improvement in performance was demonstrated in terms of the reconstruction quality. Sample results using speech signals exhibited improved reconstruction quality which was achieved at the cost of a moderate increase in the computation associated with the representation of the signals in multiple domains.
Publication Date
10-25-2001
Publication Title
Electronics Letters
Volume
37
Issue
22
Number of Pages
1370-1372
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1049/el:20010922
Copyright Status
Unknown
Socpus ID
0035950173 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/0035950173
STARS Citation
Krishnan, V. and Mikhael, W. B., "Efficient Code Excited Linear Predictor Using Redundant Vector Quantiser Representations" (2001). Scopus Export 2000s. 145.
https://stars.library.ucf.edu/scopus2000/145