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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Skinnemoen, H. |
| Copyright Year | 1996 |
| Description | Author affiliation: NERA Telecommunications, Billingstad, Norway (Skinnemoen, H.) |
| Abstract | Vector quantization (VQ) is a multidimensional block quantizer methodology that can be very efficient with respect to approaching the rate-distortion bounds. Best performance is obtained for longer blocks. However, as the vectors become longer, the number of codebook vectors will generally increase, and the complexity of searching the codebook for the best codebook vector may soon become prohibitive. For best quantizer performance, the VQ must be trained for the source, but this usually prohibits the use of structured (or algebraic) codebooks that are fast to search. This paper presents a novel methodology for codebook design that combines the traditional training of codebooks by the well proven generalized Lloyd algorithm (GLA) with a structured codebook that can be searched efficiently. The concept is termed gradient search algorithm (GSA) since it is based upon a gradient in the error surface of the codebook pointing towards the optimum codebook vector choice. |
| Starting Page | 283 |
| Ending Page | 286 |
| File Size | 518331 |
| Page Count | 4 |
| File Format | |
| ISBN | 0780336291 |
| DOI | 10.1109/DSPWS.1996.555516 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1996-09-01 |
| Publisher Place | Norway |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Design methodology Vector quantization Training data Signal processing algorithms Robustness Multidimensional systems Rate-distortion Algorithm design and analysis Speech Shape |
| Content Type | Text |
| Resource Type | Article |
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