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The objective of this paper is to further investigate various applications of information Nonanticipative Rate Distortion Function (NRDF) by discussing two working examples, the Binary Symmetric Markov Source with parameter $p$ (BSMS($p$))…

Information Theory · Computer Science 2014-04-30 Photios A. Stavrou , Christos K. Kourtellaris , Charalambos D. Charalambous

We deal with zero-delay source coding of a vector-valued Gauss-Markov source subject to a mean-squared error (MSE) fidelity criterion characterized by the operational zero-delay vector-valued Gaussian rate distortion function (RDF). We…

Information Theory · Computer Science 2018-10-02 Photios A. Stavrou , Jan Ostergaard , Charalambos D. Charalambous

In this paper we invoke a nonanticipative information Rate Distortion Function (RDF) for sources with memory, and we analyze its importance in probabilistic matching of the source to the channel so that transmission of a symbol-by-symbol…

Information Theory · Computer Science 2013-04-26 Christos Kourtellaris , Charalambos D. Charalambous , Photios A. Stavrou

In this paper the relation between nonanticipative rate distortion function (RDF) and Bayesian filtering theory is further investigated on general Polish spaces. The relation is established via an optimization on the space of conditional…

Information Theory · Computer Science 2014-01-21 Photios A. Stavrou , Charalambos D. Charalambous

This paper deals with the computation of a non-asymptotic lower bound by means of the nonanticipative rate-distortion function (NRDF) on the discrete-time zero-delay variable-rate lossy compression problem for discrete Markov sources with…

Information Theory · Computer Science 2024-11-19 Zixuan He , Charalambos D. Charalambous , Photios A. Stavrou

We deal with zero-delay source coding of a vector Gaussian autoregressive (AR) source subject to an average mean squared error (MSE) fidelity criterion. Toward this end, we consider the nonanticipative rate distortion function (NRDF) which…

Information Theory · Computer Science 2017-08-22 Photios A. Stavrou , Jan Ostergaard , Charalambos D. Charalambous , Milan Derpich

The rate-distortion function (RDF) has long been an information-theoretic benchmark for data compression. As its natural extension, the indirect rate-distortion function (iRDF) corresponds to the scenario where the encoder can only access…

Information Theory · Computer Science 2025-03-11 Zichao Yu , Qiang Sun , Wenyi Zhang

In this paper we introduce a definition for nonanticipative Rate Distortion Function (RDF) on abstract alphabets, and we invoke weak convergence of probability measures to show various of its properties, such as, existence of the optimal…

Information Theory · Computer Science 2013-01-29 Photios A. Stavrou , Charalambos D. Charalambous , Christos K. Kourtellaris

We improve the existing achievable rate regions for causal and for zero-delay source coding of stationary Gaussian sources under an average mean squared error (MSE) distortion measure. To begin with, we find a closed-form expression for the…

Information Theory · Computer Science 2011-05-03 Milan S. Derpich , Jan Østergaard

The joint nonanticipative rate distortion function (NRDF) for a tuple of random processes with individual fidelity criteria is considered. Structural properties of optimal test channel distributions are derived. Further, for the application…

Information Theory · Computer Science 2021-03-31 Charalambos D. Charalambous , Evagoras Stylianou

In this paper the relation between nonanticipative rate distortion function (RDF) and Bayesian filtering theory is investigated using the topology of weak convergence of probability measures on Polish spaces. The relation is established via…

Information Theory · Computer Science 2013-04-29 Charalambos D. Charalambous , Photios A. Stavrou

We prove achievability of the recently characterized quadratic Gaussian rate-distortion function (RDF) subject to the constraint that the distortion is uncorrelated to the source. This result is based on shaped dithered lattice quantization…

Information Theory · Computer Science 2008-07-24 Milan S. Derpich , Jan Ostergaard , Daniel E. Quevedo

In this paper we analyze the joint rate distortion function (RDF), for a tuple of correlated sources taking values in abstract alphabet spaces (i.e., continuous) subject to two individual distortion criteria. First, we derive structural…

Information Theory · Computer Science 2021-05-11 Evagoras Stylianou , Charalambos D. Charalambous , Themistoklis Charalambous

In this paper, we analyze the indirect source coding problem with side information at both the encoder and decoder, as well as only at the decoder. We first derive structural properties of the two rate distortion functions (RDFs) for…

Information Theory · Computer Science 2024-10-14 Evagoras Stylianou , Michail Gkagkos , Charalambos D. Charalambous

The relation between nonanticipative Rate Distortion Function (RDF) and filtering theory is discussed on abstract spaces. The relation is established by imposing a realizability constraint on the reconstruction conditional distribution of…

Information Theory · Computer Science 2016-11-15 Charalambos D. Charalambous , Photios A. Stavrou , Nasir U. Ahmed

We study the rate-distortion function (RDF) for the lossy compression of discrete-time (DT) wide-sense almost cyclostationary (WSACS) Gaussian processes with memory, arising from sampling continuous-time (CT) wide-sense cyclostationary…

Information Theory · Computer Science 2025-07-02 Zikun Tan , Ron Dabora , H. Vincent Poor

This paper studies the rate-distortion-perception (RDP) tradeoff for a memoryless source model in the asymptotic limit of large block-lengths. The perception measure is based on a divergence between the distributions of the source and…

Information Theory · Computer Science 2025-04-29 Sadaf Salehkalaibar , Jun Chen , Ashish Khisti , Wei Yu

We consider a remote source coding problem subject to a {distortion function}. Contrary to the use of the classical separable distortion criterion, herein we consider the more general, $f$-separable distortion measure and study its…

Information Theory · Computer Science 2023-05-19 Photios A. Stavrou , Yanina Shkel , Marios Kountouris

We consider the problem of distributed lossy linear function computation in a tree network. We examine two cases: (i) data aggregation (only one sink node computes) and (ii) consensus (all nodes compute the same function). By quantifying…

Information Theory · Computer Science 2017-01-16 Yaoqing Yang , Pulkit Grover , Soummya Kar

The rate-distortion-perception function (RDPF; Blau and Michaeli, 2019) has emerged as a useful tool for thinking about realism and distortion of reconstructions in lossy compression. Unlike the rate-distortion function, however, it is…

Information Theory · Computer Science 2021-04-29 Lucas Theis , Aaron B. Wagner
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