Source Coding with Side Information at the Decoder and Uncertain Knowledge of the Correlation

International audienceThis paper considers the problem of lossless source coding with side information at the decoder, when the correlation model between the source and the side information is uncertain. Four parametrized models representing the correlation between the source and the side information are introduced. The uncertainty on the correlation appears through the lack of knowledge on the value of the parameters. For each model, we propose a practical coding scheme based on non-binary Low Density Parity Check Codes and able to deal with the parameter uncertainty. At the encoder, the choice of the coding rate results from an information theoretical analysis. Then we propose decoding algorithms that jointly estimate the source vector and the parameters. As the proposed decoder is based on the Expectation-Maximization algorithm, which is very sensitive to initialization, we also propose a method to produce first a coarse estimate of the parameters

Codage Distribué dans des Réseaux de Capteurs avec Connaissance Incertaine des Corrélations

National audienceCet article aborde le problème du codage d'une source X avec information adjacente Y disponible uniquement au décodeur dans le cas où P(Y|X) est mal connue au décodeur

Neuropeptide FF/neuropeptide AF receptors (version 2019.4) in the IUPHAR/BPS Guide to Pharmacology Database

The Neuropeptide FF receptor family contains two subtypes, NPFF1 and NPFF2 (provisional nomenclature [10]), which exhibit high affinities for neuropeptide FF (NPFF, O15130) and RFamide related peptides (RFRP: precursor gene symbol NPVF, Q9HCQ7). NPFF1 is broadly distributed in the central nervous system with the highest levels found in the limbic system and the hypothalamus. NPFF2 is present in high density in the superficial layers of the mammalian spinal cord where it is involved in nociception and modulation of opioid functions

Neuropeptide FF/neuropeptide AF receptors in GtoPdb v.2023.1

The Neuropeptide FF receptor family contains two subtypes, NPFF1 and NPFF2 (provisional nomenclature [12]), which exhibit high affinities for neuropeptide FF (NPFF, O15130) and RFamide related peptides (RFRP: precursor gene symbol NPVF, Q9HCQ7). NPFF1 is broadly distributed in the central nervous system with the highest levels found in the limbic system and the hypothalamus. NPFF2 is present in high density in the superficial layers of the mammalian spinal cord where it is involved in nociception and modulation of opioid functions

Transmission and Storage Rates for Sequential Massive Random Access

This paper introduces a new source coding paradigm called Sequential Massive Random Access (SMRA). In SMRA, a set of correlated sources is encoded once for all and stored on a server, and clients want to successively access to only a subset of the sources. Since the number of simultaneous clients can be huge, the server is only allowed to extract a bitstream from the stored data: no re-encoding can be performed before the transmission of the specific client's request. In this paper, we formally define the SMRA framework and introduce both storage and transmission rates to characterize the performance of SMRA. We derive achievable transmission and storage rates for lossless source coding of i.i.d. and non i.i.d. sources, and transmission and storage rates-distortion regions for Gaussian sources. We also show two practical implementations of SMRA systems based on rate-compatible LDPC codes. Both theoretical and experimental results demonstrate that SMRA systems can reach the same transmission rates as in traditional point to point source coding schemes, while having a reasonable overhead in terms of storage rate. These results constitute a breakthrough for many recent data transmission applications in which different parts of the data are requested by the clients

Codage de Sources avec Information Adjacente et Connaissance Imparfaite de la Corr élation : le problème des cadrans

National audienceCet article aborde le problème du codage d'une source X avec information adjacente Y disponible uniquement au décodeur dans le cas où P(Y|X) est mal connue au décodeur

Modulation de conductances calciques par les peptides opioïdes et anti-opioïdes

Dans le système nerveux central, l’activation des canaux Ca2+ dépendant du potentiel déclenche la libération des neurotransmetteurs chimiques. L’activité de ces canaux est modulée par un grand nombre de récepteurs membranaires, en particulier ceux couplés aux protéines G. Dans cette revue, nous décrivons la modulation des canaux Ca2+ par les peptides opioïdes et antiopioïdes. Après une brève présentation des systèmes opioïdes, nous décrivons les caractéristiques de l’inhibition des canaux Ca2+ par l’activation de ces systèmes. Le neuropeptide FF à été pris comme exemple de système anti-opioïde. Après avoir résumé les avancées récentes dans la connaissance de ce système, nous exposons les résultats, obtenus dans notre laboratoire, qui démontrent une activité anti-opioïde du NPFF, dans la modulation des canaux Ca2+ de neurones isolés

Source Coding with Side Information at the Decoder: Models with Uncertainty, Performance Bounds, and Practical Coding Schemes

We consider the problem of source coding with side information (SI) at the decoder only, when the joint distribution between the source and the SI is not perfectly known. Four parametric models for this joint distribution are considered, where uncertainty about the distribution is turned into uncertainty about the value of the parameters. More precisely, a prior distribution for the parameters may or may not be available. Moreover, the value of the parameters may either change at every symbol or remain constant for a while. This paper overviews the results on the performance of lossless source coding with SI at the decoder for the four models. The way LDPC-based encoding and decoding schemes should be designed to cope with model uncertainty is provided. Most of the proposed practical schemes perform close to the theoretical limits

UNIVERSAL WYNER-ZIV CODING FOR GAUSSIAN SOURCES

This paper considers the problem of lossy source coding with side information at the decoder only, for Gaussian sources, when the joint statistics of the sources are partly unknown. We propose a practical universal coding scheme based on scalar quantization and nonbinary LDPC codes, which avoids the binarization of the quantized coefficients. We first explain how to choose the rate and to construct the LDPC coding matrix. Then, a decoding algorithm that jointly estimates the source sequence and the joint statistics of the sources is proposed. The proposed coding scheme suffers no loss compared to the practical coding scheme with same rate but known variance. Index Terms — Source coding with side information, Ratedistortion