The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Lorsque nous concevons un quantificateur vectoriel (VQ) robuste pour les canaux bruyants, une fonction d'attribution d'index appropriée doit être conçue pour minimiser l'effet d'erreur de canal. Pour des débits relativement élevés, la complexité de recherche d’une fonction d’attribution d’index optimale est trop élevée pour être mise en œuvre. Pour surmonter un tel problème, nous utilisons un VQ structurellement contraint, appelé quantificateur de produit adaptatif à l'échantillon (SAPQ) [12], pour les faibles complexités de quantification et d'attribution d'index. Le quantificateur de produit (PQ) et sa variation SAPQ [13], qui sont basés sur le quantificateur scalaire (SQ) et appartiennent donc à une classe du réseau binaire VQ [16], ont une résilience aux erreurs inhérente même si l'attribution conventionnelle d'indices affines des fonctions, telles que le code binaire naturel, sont utilisées. La résilience aux erreurs de SAPQ est observée dans un sens faible à travers les limites du pire cas. L'utilisation de SAPQ pour les canaux bruyants est particulièrement utile pour les débits élevés, par exemple > 1 bit/échantillon, et il est démontré numériquement que les performances de limite de canal de SAPQ sont comparables à celles de la meilleure permutation de livre de codes de l'algorithme de commutation binaire (BSA) [ 23]. En outre, le livre de codes PQ ou SAPQ avec une fonction d'attribution d'index affine est utilisé pour l'estimation initiale de l'algorithme de clustering conventionnel, et il est démontré que les performances du meilleur BSA peuvent être facilement obtenues.
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Dong Sik KIM, Youngcheol PARK, "Sample-Adaptive Product Quantizers with Affine Index Assignments for Noisy Channels" in IEICE TRANSACTIONS on Communications,
vol. E92-B, no. 10, pp. 3084-3093, October 2009, doi: 10.1587/transcom.E92.B.3084.
Abstract: When we design a robust vector quantizer (VQ) for noisy channels, an appropriate index assignment function should be contrived to minimize the channel-error effect. For relatively high rates, the complexity for finding an optimal index assignment function is too high to be implemented. To overcome such a problem, we use a structurally constrained VQ, which is called the sample-adaptive product quantizer (SAPQ) [12], for low complexities of quantization and index assignment. The product quantizer (PQ) and its variation SAPQ [13], which are based on the scalar quantizer (SQ) and thus belong to a class of the binary lattice VQ [16], have inherent error resilience even though the conventional affine index assignment functions, such as the natural binary code, are employed. The error resilience of SAPQ is observed in a weak sense through worst-case bounds. Using SAPQ for noisy channels is useful especially for high rates, e.g., > 1 bit/sample, and it is numerically shown that the channel-limit performance of SAPQ is comparable to that of the best codebook permutation of binary switching algorithm (BSA) [23]. Further, the PQ or SAPQ codebook with an affine index assignment function is used for the initial guess of the conventional clustering algorithm, and it is shown that the performance of the best BSA can be easily achieved.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.E92.B.3084/_p
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@ARTICLE{e92-b_10_3084,
author={Dong Sik KIM, Youngcheol PARK, },
journal={IEICE TRANSACTIONS on Communications},
title={Sample-Adaptive Product Quantizers with Affine Index Assignments for Noisy Channels},
year={2009},
volume={E92-B},
number={10},
pages={3084-3093},
abstract={When we design a robust vector quantizer (VQ) for noisy channels, an appropriate index assignment function should be contrived to minimize the channel-error effect. For relatively high rates, the complexity for finding an optimal index assignment function is too high to be implemented. To overcome such a problem, we use a structurally constrained VQ, which is called the sample-adaptive product quantizer (SAPQ) [12], for low complexities of quantization and index assignment. The product quantizer (PQ) and its variation SAPQ [13], which are based on the scalar quantizer (SQ) and thus belong to a class of the binary lattice VQ [16], have inherent error resilience even though the conventional affine index assignment functions, such as the natural binary code, are employed. The error resilience of SAPQ is observed in a weak sense through worst-case bounds. Using SAPQ for noisy channels is useful especially for high rates, e.g., > 1 bit/sample, and it is numerically shown that the channel-limit performance of SAPQ is comparable to that of the best codebook permutation of binary switching algorithm (BSA) [23]. Further, the PQ or SAPQ codebook with an affine index assignment function is used for the initial guess of the conventional clustering algorithm, and it is shown that the performance of the best BSA can be easily achieved.},
keywords={},
doi={10.1587/transcom.E92.B.3084},
ISSN={1745-1345},
month={October},}
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TY - JOUR
TI - Sample-Adaptive Product Quantizers with Affine Index Assignments for Noisy Channels
T2 - IEICE TRANSACTIONS on Communications
SP - 3084
EP - 3093
AU - Dong Sik KIM
AU - Youngcheol PARK
PY - 2009
DO - 10.1587/transcom.E92.B.3084
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E92-B
IS - 10
JA - IEICE TRANSACTIONS on Communications
Y1 - October 2009
AB - When we design a robust vector quantizer (VQ) for noisy channels, an appropriate index assignment function should be contrived to minimize the channel-error effect. For relatively high rates, the complexity for finding an optimal index assignment function is too high to be implemented. To overcome such a problem, we use a structurally constrained VQ, which is called the sample-adaptive product quantizer (SAPQ) [12], for low complexities of quantization and index assignment. The product quantizer (PQ) and its variation SAPQ [13], which are based on the scalar quantizer (SQ) and thus belong to a class of the binary lattice VQ [16], have inherent error resilience even though the conventional affine index assignment functions, such as the natural binary code, are employed. The error resilience of SAPQ is observed in a weak sense through worst-case bounds. Using SAPQ for noisy channels is useful especially for high rates, e.g., > 1 bit/sample, and it is numerically shown that the channel-limit performance of SAPQ is comparable to that of the best codebook permutation of binary switching algorithm (BSA) [23]. Further, the PQ or SAPQ codebook with an affine index assignment function is used for the initial guess of the conventional clustering algorithm, and it is shown that the performance of the best BSA can be easily achieved.
ER -