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# IEEE Transactions on Information Theory

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Displaying Results 1 - 25 of 48

Publication Year: 2013, Page(s):C1 - C4
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• ### IEEE Transactions on Information Theory publication information

Publication Year: 2013, Page(s): C2
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• ### Data-Processing Bounds for Scalar Lossy Source Codes With Side Information at the Decoder

Publication Year: 2013, Page(s):4057 - 4070
Cited by:  Papers (2)
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In this paper, we introduce new lower bounds on the distortion of scalar fixed-rate codes for lossy compression with side information available at the receiver. These bounds are derived by presenting the relevant random variables as a Markov chain and applying generalized data-processing inequalities a la Ziv and Zakai. We show that by replacing the logarithmic function with other functions, in th... View full abstract»

• ### The Infinite-Message Limit of Two-Terminal Interactive Source Coding

Publication Year: 2013, Page(s):4071 - 4094
Cited by:  Papers (8)
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A two-terminal interactive function computation problem with alternating messages is studied within the framework of distributed block source coding theory. For any finite number of messages, a single-letter characterization of the sum-rate-distortion function was established in previous works using standard information-theoretic techniques. This, however, does not provide a satisfactory character... View full abstract»

• ### An Information Inequality and Evaluation of Marton's Inner Bound for Binary Input Broadcast Channels

Publication Year: 2013, Page(s):4095 - 4105
Cited by:  Papers (3)
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We establish an information inequality concerning five random variables. This inequality is motivated by the sum-rate evaluation of Marton's inner bound for two receiver broadcast channels with a binary input alphabet. We establish that randomized time-division strategy achieves the sum rate of Marton's inner bound for all binary input broadcast channels. We also obtain an improved cardinality bou... View full abstract»

• ### On the Synergistic Benefits of Alternating CSIT for the MISO Broadcast Channel

Publication Year: 2013, Page(s):4106 - 4128
Cited by:  Papers (60)
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The degrees of freedom (DoFs) of the two-user multiple-input single-output (MISO) broadcast channel (BC) are studied under the assumption that the form, Ii, i=1, 2, of the channel state information at the transmitter (CSIT) for each user's channel can be either perfect (P), delayed (D), or not available (N), i.e., I1,I2 ∈... View full abstract»

• ### On Modulo-Sum Computation Over an Erasure Multiple-Access Channel

Publication Year: 2013, Page(s):4129 - 4138
Cited by:  Papers (2)
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We study modulo-sum computation of two binary source sequences over a two-user erasure multiple access channel. The channel is modeled as a binary-input, erasure multiple access channel, which can be in one of three states-either the channel output is a modulo-sum of the two input symbols, or the channel output equals the input symbol on the first link and an erasure on the second link, or vice ve... View full abstract»

• ### Achievable Rate Region for Gaussian MIMO MAC With Partial CSI

Publication Year: 2013, Page(s):4139 - 4170
Cited by:  Papers (3)
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In this paper, we provide an information-theoretic analysis of a Gaussian multiple-input multiple-output multiple access channel (MIMO MAC) with imperfect channel knowledge at the receiver. In particular, we derive inner and outer bounds for the MIMO MAC rate region when the inputs are Gaussian. We then apply these bounds to a Gaussian interference network with receiver cooperation, in which a cen... View full abstract»

• ### The Discrete Memoryless Interference Channel With One-Sided Generalized Feedback

Publication Year: 2013, Page(s):4171 - 4191
Cited by:  Papers (3)
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We study the interference channel with one-sided generalized feedback and secrecy requirements. In our model, Message 1 that is known just to Encoder 1 should be decoded by both receivers. Message 2 - known only to Encoder 2 - should be decoded by Decoder 2 and kept as secret as possible from Decoder 1. The uncertainty of Decoder 1 about Message 2 is measured by means of the equivocation rate. In ... View full abstract»

• ### Two Birds and One Stone: Gaussian Interference Channel With a Shared Out-of-Band Relay of Limited Rate

Publication Year: 2013, Page(s):4192 - 4212
Cited by:  Papers (7)
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The two-user Gaussian interference channel with a shared out-of-band relay is considered. The relay observes a linear combination of the source signals and broadcasts a common message to the two destinations, through a perfect link of fixed limited rate R0 bits per channel use. The out-of-band nature of the relay is reflected by the fact that the common relay message does not int... View full abstract»

• ### Capacity Pre-Log of Noncoherent SIMO Channels Via Hironaka's Theorem

Publication Year: 2013, Page(s):4213 - 4229
Cited by:  Papers (5)
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We find the capacity pre-log of a temporally correlated Rayleigh block-fading single-input multiple-output (SIMO) channel in the noncoherent setting. It is well known that for block-length L and rank of the channel covariance matrix equal to Q, the capacity pre-log in the single-input single-output (SISO) case is given by 1-Q/L. Here, Q/L can be interprete... View full abstract»

• ### Dynamic Tardos Traitor Tracing Schemes

Publication Year: 2013, Page(s):4230 - 4242
Cited by:  Papers (8)
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We construct binary dynamic traitor tracing schemes, where the number of watermark bits needed to trace and disconnect any coalition of pirates is quadratic in the number of pirates, and logarithmic in the total number of users and the error probability. Our results improve upon results of Tassa, and our schemes have several other advantages, such as being able to generate all codewords in advance... View full abstract»

• ### Support Recovery With Sparsely Sampled Free Random Matrices

Publication Year: 2013, Page(s):4243 - 4271
Cited by:  Papers (30)  |  Patents (1)
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Consider a Bernoulli-Gaussian complex n-vector whose components are Vi = XiBi, with Xi ~ C N(0, Px) and binary Bi mutually independent and iid across i. This random q-sparse vector is multiplied by a square random matrix U, and a randomly chosen subset, of ... View full abstract»

• ### Refined Support and Entropic Uncertainty Inequalities

Publication Year: 2013, Page(s):4272 - 4279
Cited by:  Papers (4)
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Generalized versions of the entropic (Hirschman- Beckner) and support (Elad-Bruckstein) uncertainty principle are presented for frames representations. Moreover, a sharpened version of the support inequality is obtained by introducing a generalization of the coherence. In the finite-dimensional case and under certain conditions, minimizers of these inequalities are given. In addition, lp no... View full abstract»

• ### Measurement Bounds for Sparse Signal Ensembles via Graphical Models

Publication Year: 2013, Page(s):4280 - 4289
Cited by:  Papers (17)
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In compressive sensing, a small collection of linear projections of a sparse signal contains enough information to permit signal recovery. Distributed compressive sensing extends this framework by defining ensemble sparsity models, allowing a correlated ensemble of sparse signals to be jointly recovered from a collection of separately acquired compressive measurements. In this paper, we introduce ... View full abstract»

• ### Asymptotic Analysis of Complex LASSO via Complex Approximate Message Passing (CAMP)

Publication Year: 2013, Page(s):4290 - 4308
Cited by:  Papers (45)
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Recovering a sparse signal from an undersampled set of random linear measurements is the main problem of interest in compressed sensing. In this paper, we consider the case where both the signal and the measurements are complex-valued. We study the popular recovery method of l1-regularized least squares or LASSO. While several studies have shown that LASSO provides desirable solu... View full abstract»

• ### Compressed Data Separation With Redundant Dictionaries

Publication Year: 2013, Page(s):4309 - 4315
Cited by:  Papers (3)
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Most of the data scientists face today might be classified as multimodal data, i.e., being composed of distinct subcomponents. One common task is to separate such data into appropriate single components for further analysis. In this paper, we consider data separation from fewer, linear, nonadaptive, and noisy measurements. We show that the distinct subcomponents, which are (approximately) sparse i... View full abstract»

• ### Restricted $p$ -Isometry Properties of Nonconvex Matrix Recovery

Publication Year: 2013, Page(s):4316 - 4323
Cited by:  Papers (12)
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Recently, a nonconvex relaxation of low-rank matrix recovery (LMR), called the Schatten- p quasi-norm minimization (0 <; p <; 1), was introduced instead of the previous nuclear norm minimization in order to approximate the problem of LMR closer. In this paper, we introduce a notion of the restricted p-isometry constants (0 <; p ≤ 1) and derive a p... View full abstract»

• ### Low-Rank Matrix Recovery From Errors and Erasures

Publication Year: 2013, Page(s):4324 - 4337
Cited by:  Papers (27)
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This paper considers the recovery of a low-rank matrix from an observed version that simultaneously contains both 1) erasures, most entries are not observed, and 2) errors, values at a constant fraction of (unknown) locations are arbitrarily corrupted. We provide a new unified performance guarantee on when minimizing nuclear norm plus l1 norm succeeds in exact recovery. Our resul... View full abstract»

• ### A Spectral Graph Uncertainty Principle

Publication Year: 2013, Page(s):4338 - 4356
Cited by:  Papers (40)
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The spectral theory of graphs provides a bridge between classical signal processing and the nascent field of graph signal processing. In this paper, a spectral graph analogy to Heisenberg's celebrated uncertainty principle is developed. Just as the classical result provides a tradeoff between signal localization in time and frequency, this result provides a fundamental tradeoff between a signal's ... View full abstract»

• ### Robust Estimation of Latent Tree Graphical Models: Inferring Hidden States With Inexact Parameters

Publication Year: 2013, Page(s):4357 - 4373
Cited by:  Papers (1)
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Latent tree graphical models are widely used in computational biology, signal and image processing, and network tomography. Here, we design a new efficient, estimation procedure for latent tree models, including Gaussian and discrete, reversible models, that significantly improves on previous sample requirement bounds. Our techniques are based on a new hidden state estimator that is robust to inac... View full abstract»

• ### Ensemble Estimators for Multivariate Entropy Estimation

Publication Year: 2013, Page(s):4374 - 4388
Cited by:  Papers (8)
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The problem of estimation of density functionals like entropy and mutual information has received much attention in the statistics and information theory communities. A large class of estimators of functionals of the probability density suffer from the curse of dimensionality, wherein the mean squared error decays increasingly slowly as a function of the sample size T as the dimension d<... View full abstract»

• ### Asymptotic Relative Efficiency and Exact Variance Stabilizing Transformation for the Generalized Gaussian Distribution

Publication Year: 2013, Page(s):4389 - 4396
Cited by:  Papers (2)
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It is demonstrated that the sampling distributions of the maximum likelihood (ML) estimator and its Studentized statistic for the generalized Gaussian distribution do not pass the most powerful normality tests even for fairly large sample sizes. This disagreement with what the standard large sample ML theory predicts and the computational burden of having to deal with its associated polygamma func... View full abstract»

• ### Probability Functionals for Self-Consistent and Invariant Inference: Entropy and Fisher Information

Publication Year: 2013, Page(s):4397 - 4407
Cited by:  Papers (2)
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Two existing methods of probabilistic inference are based on variational principles: maximum entropy and minimum Fisher information. In each case, a probability density function is inferred by setting the first variation of a functional to zero, subject to information constraints. This study considers whether other functionals could be used for this purpose, and by starting with requirements for s... View full abstract»

• ### Strongly Consistent Model Order Selection for Estimating 2-D Sinusoids in Colored Noise

Publication Year: 2013, Page(s):4408 - 4422
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The problem of jointly estimating the number as well as the parameters of 2-D sinusoidal signals, observed in the presence of an additive colored noise field, is considered. We begin by establishing the strong consistency of the nonlinear least squares estimator of the parameters of 2-D sinusoids, when the number of sinusoidal signals assumed in the field is incorrect. Based on these results, we p... View full abstract»

## Aims & Scope

IEEE Transactions on Information Theory publishes papers concerned with the transmission, processing, and utilization of information.

Full Aims & Scope

## Meet Our Editors

Editor-in-Chief
Prakash Narayan

Department of Electrical and Computer Engineering