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Representing a continuous-time signal by a set of samples is a classical problem in signal processing. We study this problem under the additional constraint that the samples are quantized or compressed in a lossy manner under a limited…

Information Theory · Computer Science 2018-04-12 Alon Kipnis , Yonina C. Eldar , Andrea J. Goldsmith

Consider a Gaussian memoryless multiple source with $m$ components with joint probability distribution known only to lie in a given class of distributions. A subset of $k \leq m$ components are sampled and compressed with the objective of…

Information Theory · Computer Science 2018-03-16 Vinay Praneeth Boda

Consider a lossy compression system with $\ell$ distributed encoders and a centralized decoder. Each encoder compresses its observed source and forwards the compressed data to the decoder for joint reconstruction of the target signals under…

Information Theory · Computer Science 2018-07-19 Yizhong Wang , Li Xie , Xuan Zhang , Jun Chen

We consider finite blocklength lossy compression of information sources whose components are independent but non-identically distributed. Crucially, Gaussian sources with memory and quadratic distortion can be cast in this form. We show…

Information Theory · Computer Science 2026-02-11 Eyyup Tasci , Victoria Kostina

The distortion-rate function of output-constrained lossy source coding with limited common randomness is analyzed for the special case of squared error distortion measure. An explicit expression is obtained when both source and…

Information Theory · Computer Science 2024-03-25 Li Xie , Liangyan Li , Jun Chen , Zhongshan Zhang

We consider the transmission of a memoryless bivariate Gaussian source over an average-power-constrained one-to-two Gaussian broadcast channel. The transmitter observes the source and describes it to the two receivers by means of an…

Information Theory · Computer Science 2009-03-20 Shraga Bross , Amos Lapidoth , Stephan Tinguely

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

We explore two fundamental questions at the intersection of sampling theory and information theory: how channel capacity is affected by sampling below the channel's Nyquist rate, and what sub-Nyquist sampling strategy should be employed to…

Information Theory · Computer Science 2015-03-19 Yuxin Chen , Yonina C. Eldar , Andrea J. Goldsmith

An encoder, subject to a rate constraint, wishes to describe a Gaussian source under squared error distortion. The decoder, besides receiving the encoder's description, also observes side information consisting of uncompressed source symbol…

Information Theory · Computer Science 2013-05-10 Chris T. K. Ng , Chao Tian , Andrea J. Goldsmith , Shlomo Shamai

This paper investigates the information rate loss in analog channels when the sampler is designed to operate independent of the instantaneous channel occupancy. Specifically, a multiband linear time-invariant Gaussian channel under…

Information Theory · Computer Science 2017-03-14 Yuxin Chen , Andrea Goldsmith , Yonina C. Eldar

Conventional sub-Nyquist sampling methods for analog signals exploit prior information about the spectral support. In this paper, we consider the challenging problem of blind sub-Nyquist sampling of multiband signals, whose unknown…

Information Theory · Computer Science 2015-05-13 Moshe Mishali , Yonina C. Eldar

A general theoretical framework is presented for analyzing information transmission over Gaussian channels with memoryless transceiver distortion, which encompasses various nonlinear distortion models including transmit-side clipping,…

Information Theory · Computer Science 2016-11-15 Wenyi Zhang

The Gauss-Markov source produces $U_i = aU_{i-1} + Z_i$ for $i\geq 1$, where $U_0 = 0$, $|a|<1$ and $Z_i\sim\mathcal{N}(0, \sigma^2)$ are i.i.d. Gaussian random variables. We consider lossy compression of a block of $n$ samples of the…

Information Theory · Computer Science 2019-09-26 Peida Tian , Victoria Kostina

We study the problem of the reconstruction of a Gaussian field defined in [0,1] using N sensors deployed at regular intervals. The goal is to quantify the total data rate required for the reconstruction of the field with a given mean square…

Information Theory · Computer Science 2007-10-23 Akshay Kashyap , Luis Alfonso Lastras-Montaño , Cathy Xia , Zhen Liu

We consider the recovery of a continuous-time Wiener process from a quantized or lossy compressed version of its uniform samples under limited bitrate and sampling rate. We derive a closed form expression for the optimal tradeoff among…

Information Theory · Computer Science 2018-07-27 Alon Kipnis , Andrea J. Goldsmith , Yonina C. Eldar

In Fourier-based medical imaging, sampling below the Nyquist rate results in an underdetermined system, in which linear reconstructions will exhibit artifacts. Another consequence of under-sampling is lower signal to noise ratio (SNR) due…

Computer Vision and Pattern Recognition · Computer Science 2016-10-04 Patrick Virtue , Michael Lustig

A new source model, which consists of an intrinsic state part and an extrinsic observation part, is proposed and its information-theoretic characterization, namely its rate-distortion function, is defined and analyzed. Such a source model…

Information Theory · Computer Science 2022-06-02 Jiakun Liu , Shuo Shao , Wenyi Zhang , H. Vincent Poor

Due to excessive need for faster propagations of signals and necessity to reduce number of measurements and rapidly increase efficiency, new sensing theories have been proposed. Conventional sampling approaches that follow Shannon-Nyquist…

Signal Processing · Electrical Eng. & Systems 2019-02-21 Milan Resetar , Gojko Ratkovic , Svetlana Zecevic

We consider the problem of distributed lossy linear function computation in a tree network. We examine two cases: (i) data aggregation (only one sink node computes) and (ii) consensus (all nodes compute the same function). By quantifying…

Information Theory · Computer Science 2017-01-16 Yaoqing Yang , Pulkit Grover , Soummya Kar

Quantum random variable, distortion operator are introduced based on canonical operators. As the lower bound of rate distortion, the entanglement information rate distortion is achieved by Gaussian map for Gaussian source. General Gaussian…

Quantum Physics · Physics 2007-05-23 Xiao-yu Chen
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