English
Related papers

Related papers: Cumulant Generating Function of Codeword Lengths i…

200 papers

This paper presents lossless prefix codes optimized with respect to a pay-off criterion consisting of a convex combination of maximum codeword length and average codeword length. The optimal codeword lengths obtained are based on a new…

Information Theory · Computer Science 2012-08-18 Themistoklis Charalambous , Charalambos D. Charalambous , Farzad Rezaei

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

In this paper we consider lossless source coding for a class of sources specified by the total variational distance ball centred at a fixed nominal probability distribution. The objective is to find a minimax average length source code,…

Information Theory · Computer Science 2013-01-25 Themistoklis Charalambous , Charalambos D. Charalambous , Sergey Loyka

We derive a general formula of the minimum achievable rate for fixed-to-variable length coding with a regular cost function by allowing the error probability up to a constant $\varepsilon$. For a fixed-to-variable length code, we call the…

Information Theory · Computer Science 2017-10-11 Hideki Yagi , Ryo Nomura

A likelihood encoder is studied in the context of lossy source compression. The analysis of the likelihood encoder is based on the soft-covering lemma. It is demonstrated that the use of a likelihood encoder together with the soft-covering…

Information Theory · Computer Science 2016-04-07 Eva C. Song , Paul Cuff , H. Vincent Poor

A distributed lossy compression network with $L$ encoders and a decoder is considered. Each encoder observes a source and sends a compressed version to the decoder. The decoder produces a joint reconstruction of target signals with the mean…

Information Theory · Computer Science 2022-06-06 Siyao Zhou , Sadaf Salehkalaibar , Jingjing Qian , Jun Chen , Wuxian Shi , Yiqun Ge , Wen Tong

Locally decodable channel codes form a special class of error-correcting codes with the property that the decoder is able to reconstruct any bit of the input message from querying only a few bits of a noisy codeword. It is well known that…

Information Theory · Computer Science 2013-08-28 Ali Makhdoumi , Shao-Lun Huang , Muriel Medard , Yury Polyanskiy

We extend Ziv and Lempel's model of finite-state encoders to the realm of lossy compression of individual sequences. In particular, the model of the encoder includes a finite-state reconstruction codebook followed by an information lossless…

Information Theory · Computer Science 2024-01-04 Neri Merhav

This paper considers the problem of soft guessing under a logarithmic loss distortion measure while allowing errors. We find an optimal guessing strategy, and derive single-shot upper and lower bounds for the minimal guessing moments as…

Information Theory · Computer Science 2025-10-13 Shota Saito , Hamdi Joudeh

This study investigates the fundamental limits of variable-length compression in which prefix-free constraints are not imposed (i.e., one-to-one codes are studied) and non-vanishing error probabilities are permitted. Due in part to a…

Information Theory · Computer Science 2021-10-05 Yuta Sakai , Recep Can Yavas , Vincent Y. F. Tan

This paper considers the problem of lossy compression for the computation of a function of two correlated sources, both of which are observed at the encoder. Due to presence of observation costs, the encoder is allowed to observe only…

Information Theory · Computer Science 2013-07-22 Xi Liu , Osvaldo Simeone , Elza Erkip

This paper studies several properties of channel codes that approach the fundamental limits of a given (discrete or Gaussian) memoryless channel with a non-vanishing probability of error. The output distribution induced by an…

Information Theory · Computer Science 2013-09-03 Yury Polyanskiy , Sergio Verdu

This paper presents a one shot analysis of the lossy compression problem under average distortion constraints. We calculate the exact expected distortion of a random code. The result is given as an integral formula using a newly defined…

Information Theory · Computer Science 2020-05-18 Nir Elkayam , Meir Feder

The problem of joint universal source coding and identification is considered in the setting of fixed-rate lossy coding of continuous-alphabet memoryless sources. For a wide class of bounded distortion measures, it is shown that any…

Information Theory · Computer Science 2007-07-13 Maxim Raginsky

The penalty incurred by imposing a finite delay constraint in lossless source coding of a memoryless source is investigated. It is well known that for the so-called block-to-variable and variable-to-variable codes, the redundancy decays at…

Information Theory · Computer Science 2016-11-17 Ofer Shayevitz , Eado Meron , Meir Feder , Ram Zamir

We consider transmission of discrete memoryless sources (DMSes) across discrete memoryless channels (DMCs) using variable-length lossy source-channel codes with feedback. The reliability function (optimum error exponent) is shown to be…

Information Theory · Computer Science 2019-04-09 Lan V. Truong , Vincent Y. F. Tan

In this paper the ensemble of codes formed by a serial concatenation of a repetition code with multiple accumulators connected through random interleavers is considered. Based on finite length weight enumerators for these codes, asymptotic…

Information Theory · Computer Science 2008-10-21 Joerg Kliewer , Kamil S. Zigangirov , Christian Koller , Daniel J. Costello

Motivated by applications of biometric identification and content identification systems, we consider the problem of random coding for channels, where each codeword undergoes lossy compression (vector quantization), and where the decoder…

Information Theory · Computer Science 2016-09-29 Neri Merhav

We propose computationally efficient encoders and decoders for lossy compression using a Sparse Regression Code. The codebook is defined by a design matrix and codewords are structured linear combinations of columns of this matrix. The…

Information Theory · Computer Science 2014-05-20 Ramji Venkataramanan , Tuhin Sarkar , Sekhar Tatikonda

We study the problem of lossy joint source-channel coding in a single-user energy harvesting communication system with causal energy arrivals and the energy storage unit may have leakage. In particular, we investigate the achievable…

Information Theory · Computer Science 2015-08-20 Meysam Shahrbaf Motlagh , Masoud Badiei Khuzani , Patrick Mitran