Name
Abstract | ||
|---|---|---|
This paper introduces a novel and highly efficient realization of a spherical vector quantizer (SVQ), the "Gosset Low Complexity Vector Quantizer" (GLCVQ). The GLCVQ codebook is composed of vectors that are located on spherical shells of the Gosset lattice E8. A high encoding efficiency is achieved by representing the spherical vector codebook as aggregated permutation codes. Compared to previous algorithms, the computational complexity and memory consumption is further reduced by exploiting the properties of so called classleader root vectors and by a novel approach for the codevector-to-index-mapping. The GLCVQ concept can be generalized to vector dimensions that are multiples of eight. In particular, GLCVQ for 16-dimensional vectors is used in Amd. 6 to ITU-T Rec. G.729.1. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/ICASSP.2011.5946446 | Acoustics, Speech and Signal Processing |
Keywords | Field | DocType |
audio coding,computational complexity,vector quantisation,Amd. 6,GLCVQ codebook,Gosset lattice spherical vector quantization,Gosset low-complexity vector quantizer,ITU-T Rec. G.729.1,SVQ,classleader root vectors,codevector-to-index-mapping,computational complexity,high encoding efficiency,permutation codes,spherical vector codebook,Spherical vector quantization,audio coding | Lattice (order),Computer science,Artificial intelligence,Discrete mathematics,Pattern recognition,Permutation,Algorithm,Vector quantisation,Bit rate,Quantization (signal processing),Computational complexity theory,Encoding (memory),Codebook | Conference |
ISSN | ISBN | Citations |
1520-6149 E-ISBN : 978-1-4577-0537-3 | 978-1-4577-0537-3 | 2 |
PageRank | References | Authors |
0.51 | 4 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hauke Krüger | 1 | 5 | 4.20 |
| B. Geiser | 2 | 122 | 15.25 |
| Peter Vary | 3 | 68 | 13.14 |
| Hai Ting Li | 4 | 2 | 0.51 |
| De-ming Zhang | 5 | 19 | 4.81 |