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A new approach to data compression is developed and applied to multimedia content. This method separates messages into components suitable for both lossless coding and 'lossy' or statistical coding techniques, compressing complex objects by…

Information Theory · Computer Science 2011-12-26 John Scoville

We study the degrees of freedom (DoF) of a $K$-user parallel MISO broadcast channel with arbitrary levels of partial CSIT over each subchannel. We derive a sum-DoF upperbound which depends on the average CSIT quality of each user. This…

Information Theory · Computer Science 2017-07-11 Hamdi Joudeh , Bruno Clerckx

In this paper, the duality of erasures and defects will be investigated by comparing the binary erasure channel (BEC) and the binary defect channel (BDC). The duality holds for channel capacities, capacity achieving schemes, minimum…

Information Theory · Computer Science 2019-12-25 Yongjune Kim , B V K Vijaya Kumar

We derive an upper bound on the capacity of non-binary deletion channels. Although binary deletion channels have received significant attention over the years, and many upper and lower bounds on their capacity have been derived, such…

Information Theory · Computer Science 2013-10-10 Mojtaba Rahmati , Tolga M. Duman

We compare the performance of short-length linear binary codes on the binary erasure channel and the binary-input Gaussian channel. We use a universal decoder that can decode any linear binary block code: Gaussian-elimination based…

Information Theory · Computer Science 2016-11-09 J. Van Wonterghem , A. Alloum , J. J. Boutros , M. Moeneclaey

We consider a channel with discrete binary input X that is corrupted by a given continuous noise to produce a continuous-valued output Y. A quantizer is then used to quantize the continuous-valued output Y to the final binary output Z. The…

Signal Processing · Electrical Eng. & Systems 2020-01-08 Thuan Nguyen , Thinh Nguyen

We study the problem of compressing a source sequence in the presence of side-information that is related to the source via insertions, deletions and substitutions. We propose a simple algorithm to compress the source sequence when the…

Information Theory · Computer Science 2016-11-15 Nan Ma , Kannan Ramchandran , David Tse

Divergence is not only an important mathematical concept in information theory, but also applied to machine learning problems such as low-dimensional embedding, manifold learning, clustering, classification, and anomaly detection. We…

Computation · Statistics 2016-11-22 Kun Yang , Hao Su , Wing Hung Wong

This paper studies the basic question of whether a given channel $V$ can be dominated (in the precise sense of being more noisy) by a $q$-ary symmetric channel. The concept of "less noisy" relation between channels originated in network…

Information Theory · Computer Science 2018-12-04 Anuran Makur , Yury Polyanskiy

Consider communication over the binary erasure channel BEC using random low-density parity-check codes with finite-blocklength n from `standard' ensembles. We show that large error events is conveniently described within a scaling theory,…

Information Theory · Computer Science 2007-07-13 Abdelaziz Amraoui , Andrea Montanari , Tom Richardson , Rudiger Urbanke

A new stochastic order between two fading distributions is introduced. A fading channel dominates another in the ergodic capacity ordering sense, if the Shannon transform of the first is greater than that of the second at all values of…

Information Theory · Computer Science 2016-11-15 Adithya Rajan , Cihan Tepedelenlioglu

We investigate the fundamental limits of reliable communication over multi-view channels, in which the channel output is comprised of a large number of independent noisy views of a transmitted symbol. We consider first the setting of…

Information Theory · Computer Science 2024-05-14 V. Arvind Rameshwar , Nir Weinberger

A complete degradability analysis of one-mode Gaussian Bosonic channels is presented. We show that apart from the class of channels which are unitarily equivalent to the channels with additive classical noise, these maps can be…

Quantum Physics · Physics 2009-11-13 F. Caruso , V. Giovannetti , A. S. Holevo

The data-processing inequality ensures quantum channels reduce state distinguishability, with contraction coefficients quantifying optimal bounds. However, these can be overly optimistic and not representative of the usual behavior. We…

Quantum Physics · Physics 2025-08-12 Ruben Ibarrondo , Daniel Stilck França

We consider a denoiser that reconstructs a stationary ergodic source by lossily compressing samples of the source observed through a memoryless noisy channel. Prior work on compression-based denoising has been limited to additive noise…

Information Theory · Computer Science 2025-12-17 Dan Song , Ayfer Özgür , Tsachy Weissman

The first terms of the low-signal-energy asymptotics for the mutual information in the discrete-time Poisson channel are derived and compared to an asymptotic expression of the capacity. In the presence of non-zero additive noise (either…

Information Theory · Computer Science 2008-08-21 Alfonso Martinez

This paper determines the range of feasible values of standard error exponents for binary-input memoryless symmetric channels of fixed capacity $C$ and shows that extremes are attained by the binary symmetric and the binary erasure channel.…

Information Theory · Computer Science 2012-12-06 Albert Guillen i Fabregas , Ingmar Land , Alfonso Martinez

The channel polarization behavior of polar codes under noise with memory is investigated. By introducing a genie-aided channel model, we first show that the polarized subchannels still converge to extremal channels under the standard polar…

Information Theory · Computer Science 2025-09-12 Tianfu Qi , Jun Wang

In this paper, a new and general version of Gaussian channel in presence of two-sided state information correlated to the channel input and noise is considered. Determining a general achievable rate for the channel and obtaining the…

Information Theory · Computer Science 2015-07-20 Nima S. Anzabi-Nezhad , Ghosheh Abed Hodtani , Mohammad Molavi Kakhki

The recovery of structured signals from a few linear measurements is a central point in both compressed sensing (CS) and discrete tomography. In CS the signal structure is described by means of a low complexity model e.g. co-/sparsity. The…

Optimization and Control · Mathematics 2018-12-31 Jan Kuske , Stefania Petra
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