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We derive quantum counterparts of two key theorems of classical information theory, namely, the rate distortion theorem and the source-channel separation theorem. The rate-distortion theorem gives the ultimate limits on lossy data…

Quantum Physics · Physics 2012-12-21 Nilanjana Datta , Min-Hsiu Hsieh , Mark M. Wilde

We extend quantum rate distortion theory by considering auxiliary resources that might be available to a sender and receiver performing lossy quantum data compression. The first setting we consider is that of quantum rate distortion coding…

Quantum Physics · Physics 2013-12-09 Mark M. Wilde , Nilanjana Datta , Min-Hsiu Hsieh , Andreas Winter

Rate-distortion-perception theory generalizes Shannon's rate-distortion theory by introducing a constraint on the perceptual quality of the output. The perception constraint complements the conventional distortion constraint and aims to…

Information Theory · Computer Science 2022-04-14 Jun Chen , Lei Yu , Jia Wang , Wuxian Shi , Yiqun Ge , Wen Tong

Direct evaluation of the rate-distortion function has rarely been achieved when it is strictly greater than its Shannon lower bound. In this paper, we consider the rate-distortion function for the distortion measure defined by an…

Information Theory · Computer Science 2013-02-27 Kazuho Watanabe

Shannon's rate-distortion theory treats source symbols as unstructured labels. When the source is a knowledge base equipped with a logical proof system, a natural fidelity criterion is closure fidelity: a reconstruction is acceptable if it…

Information Theory · Computer Science 2026-04-14 Jianfeng Xu

Lossy data compression lies at the heart of modern communication and storage systems. Shannon's rate-distortion theory provides the fundamental limit on how much a source can be compressed at a given fidelity, but it assumes infinitely long…

Information Theory · Computer Science 2026-03-10 Bhaskar Krishnamachari

The Shannon lower bound is one of the few lower bounds on the rate-distortion function that holds for a large class of sources. In this paper, it is demonstrated that its gap to the rate-distortion function vanishes as the allowed…

Information Theory · Computer Science 2016-11-17 Tobias Koch

We introduce a new measure on secrecy, which is established based on rate-distortion theory. It is named \emph{security rate}, which is the minimum (infimum) of the additional rate needed to reconstruct the source within target distortion…

Information Theory · Computer Science 2015-04-21 Lei Yu , Houqiang Li , Weiping Li

I introduce rate-distortion theory for quantum coding, and derive a lower bound, involving the coherent information, on the rate at which qubits must be used to encode a quantum source with a given maximum level of distortion per source…

Quantum Physics · Physics 2007-05-23 Howard Barnum

Semantic communication has attracted significant interest recently due to its capability to meet the fast growing demand on user-defined and human-oriented communication services such as holographic communications, eXtended reality (XR),…

Information Theory · Computer Science 2023-12-12 Jingxuan Chai , Yong Xiao , Guangming Shi , Walid Saad

This paper deals with rate distortion or source coding with fidelity criterion, in measure spaces, for a class of source distributions. The class of source distributions is described by a relative entropy constraint set between the true and…

Information Theory · Computer Science 2013-05-07 Farzad Rezaei , Charalambos D. Charalambous , Photios A. Stavrou

Shannon's channel coding theorem describes the maximum possible rate of reliable information transfer through a classical noisy communication channel. It, together with the source coding theorem, characterizes lossless channel communication…

Quantum Physics · Physics 2021-05-17 Sristy Agrawal , Rajashik Tarafder , Graeme Smith , Arup Roy , Manik Banik

A source-channel separation theorem for a general channel has recently been shown by Aggrawal et. al. This theorem states that if there exist a coding scheme that achieves a maximum distortion level d_{max} over a general channel W, then…

Information Theory · Computer Science 2013-06-27 Nir Elkayam , Meir Feder

Channel simulation is to simulate a noisy channel using noiseless channels with unlimited shared randomness. This can be interpreted as the reverse problem to Shannon's noisy coding theorem. In contrast to previous works, our approach…

Information Theory · Computer Science 2025-06-06 Shi-Bing Li , Ke Li , Lei Yu

This paper considers lossy source coding of $n$-dimensional memoryless sources and shows an explicit approximation to the minimum source coding rate required to sustain the probability of exceeding distortion $d$ no greater than $\epsilon$,…

Information Theory · Computer Science 2017-02-28 Victoria Kostina

We introduce a new measure of information-theoretic secrecy based on rate-distortion theory and study it in the context of the Shannon cipher system. Whereas rate-distortion theory is traditionally concerned with a single reconstruction…

Information Theory · Computer Science 2014-11-25 Curt Schieler , Paul Cuff

This paper studies a variant of the rate-distortion problem motivated by task-oriented semantic communication and distributed learning problems, where $M$ correlated sources are independently encoded for a central decoder. The decoder has…

Information Theory · Computer Science 2024-05-24 Jiancheng Tang , Qianqian Yang , Deniz Gündüz

Secrecy in communication systems is measured herein by the distortion that an adversary incurs. The transmitter and receiver share secret key, which they use to encrypt communication and ensure distortion at an adversary. A model is…

Information Theory · Computer Science 2015-04-14 Curt Schieler , Paul Cuff

The indirect source-coding problem in which a Bernoulli process is compressed in a lossy manner from its noisy observations is considered. These noisy observations are obtained by passing the source sequence through a The indirect…

Information Theory · Computer Science 2015-06-05 Alon Kipnis , Stefano Rini , Andrea J. Goldsmith

Consider the problem of estimating a latent signal from a lossy compressed version of the data when the compressor is agnostic to the relation between the signal and the data. This situation arises in a host of modern applications when data…

Information Theory · Computer Science 2021-01-12 Alon Kipnis , Stefano Rini , Andrea J. Goldsmith
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