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We study sequential coding of Markov sources under an error propagation constraint. An encoder sequentially compresses a sequence of vector-sources that are spatially i.i.d. but temporally correlated according to a first-order Markov…

Information Theory · Computer Science 2012-02-24 Farrokh Etezadi , Ashish Khisti , Mitchell Trott

Efficient high-performance decoding of topological stabilizer codes has the potential to crucially improve the balance between logical failure rates and the number and individual error rates of the constituent qubits. High-threshold…

This paper characterizes the second-order coding rates for lossy source coding with side information available at both the encoder and the decoder. We first provide non-asymptotic bounds for this problem and then specialize the…

Information Theory · Computer Science 2014-10-13 Sy-Quoc Le , Vincent Y. F. Tan , Mehul Motani

The error performance of the ensemble of typical LDPC codes transmitted over the binary erasure channel (BEC) is analyzed. In the past, lower bounds on the error exponents were derived. In this paper a probabilistic upper bound on this…

Information Theory · Computer Science 2008-03-18 Idan Goldenberg , David Burshtein

As conventional communication systems based on classic information theory have closely approached the limits of Shannon channel capacity, semantic communication has been recognized as a key enabling technology for the further improvement of…

Information Theory · Computer Science 2023-06-06 Jiancheng Tang , Qianqian Yang , Zhaoyang Zhang

The error exponent of the typical random code is defined as the asymptotic normalized expectation of the logarithm of the probability of error, as opposed to the traditional definition of the random coding exponent as the normalized…

Information Theory · Computer Science 2018-12-18 Neri Merhav

A general method of source coding over expansion is proposed in this paper, which enables one to reduce the problem of compressing an analog (continuous-valued source) to a set of much simpler problems, compressing discrete sources.…

Information Theory · Computer Science 2013-08-13 Hongbo Si , O. Ozan Koyluoglu , Sriram Vishwanath

Error correction code is a major part of the communication physical layer, ensuring the reliable transfer of data over noisy channels. Recently, neural decoders were shown to outperform classical decoding techniques. However, the existing…

Machine Learning · Computer Science 2022-03-30 Yoni Choukroun , Lior Wolf

It is known that modeling an information source via a symbolic dynamical system evolving over the unit interval, leads to a natural lossless compression scheme attaining the entropy rate of the source, under general conditions. We extend…

Information Theory · Computer Science 2010-01-21 Ofer Shayevitz

Polar codes are a family of capacity-achieving codes that have explicit and low-complexity construction, encoding, and decoding algorithms. Decoding of polar codes is based on the successive-cancellation decoder, which decodes in a bit-…

Information Theory · Computer Science 2018-03-06 Boaz Shuval , Ido Tal

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

We investigate the computation of Csiszar's bounds for the joint source-channel coding (JSCC) error exponent, E_J, of a communication system consisting of a discrete memoryless source and a discrete memoryless channel. We provide equivalent…

Information Theory · Computer Science 2007-07-13 Y. Zhong , F. Alajaji , L. L. Campbell

Efficient low-delay video encoders are of fundamental importance to provide timely feedback in remotely controlled platforms such as drones. In order to fully understand the theoretical limits of low-delay video encoders, we consider an…

Information Theory · Computer Science 2018-11-16 Giuseppe Cocco , Laura Toni

The problem of mismatched decoding with an additive metric $q$ for a discrete memoryless channel $W$ is addressed. The "product-space" improvement of the random coding lower bound on the mismatch capacity, $C_q^{(\infty)}(W)$, was…

Information Theory · Computer Science 2018-05-29 Anelia Somekh-Baruch

This paper considers the joint compression of a pair of correlated sources, where the encoder is allowed to access only one of the sources. The objective is to recover both sources under separate distortion constraints for each source while…

Information Theory · Computer Science 2024-11-07 Huiyuan Yang , Yuxuan Shi , Shuo Shao , Xiaojun Yuan

We show how real-number codes can be used to compress correlated sources, and establish a new framework for lossy distributed source coding, in which we quantize compressed sources instead of compressing quantized sources. This change in…

Information Theory · Computer Science 2012-06-20 Mojtaba Vaezi , Fabrice Labeau

Using a mild variant of polar codes we design linear compression schemes compressing Hidden Markov sources (where the source is a Markov chain, but whose state is not necessarily observable from its output), and to decode from Hidden Markov…

Information Theory · Computer Science 2018-10-05 Venkatesan Guruswami , Preetum Nakkiran , Madhu Sudan

We consider the problem of encoding a deterministic source sequence (a.k.a.\ individual sequence) for the degraded wiretap channel by means of an encoder and decoder that can both be implemented as finite--state machines. Our first main…

Information Theory · Computer Science 2022-01-05 Neri Merhav

This work studies distributed compression for the uplink of a cloud radio access network where multiple multi-antenna base stations (BSs) are connected to a central unit, also referred to as cloud decoder, via capacity-constrained backhaul…

Information Theory · Computer Science 2012-06-19 Seok-Hwan Park , Osvaldo Simeone , Onur Sahin , Shlomo Shamai

We present a constraint-coding scheme to correct asymmetric magnitude-$1$ errors in multi-level non-volatile memories. For large numbers of such errors, the scheme is shown to deliver better correction capability compared to known…

Information Theory · Computer Science 2017-09-12 Evyatar Hemo , Yuval Cassuto