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In this paper we derive analytical expressions for the central and side quantizers which, under high-resolutions assumptions, minimize the expected distortion of a symmetric multiple-description lattice vector quantization (MD-LVQ) system…

Information Theory · Computer Science 2016-11-17 Jan Ostergaard , Jesper Jensen , Richard Heusdens

This paper is about the design and analysis of an index-assignment (IA) based multiple-description coding scheme for the n-channel asymmetric case. We use entropy constrained lattice vector quantization and restrict attention to simple…

Information Theory · Computer Science 2010-12-02 Jan Ostergaard , Richard Heusdens , Jesper Jensen

The problem of designing a multiple description vector quantizer with lattice codebook Lambda is considered. A general solution is given to a labeling problem which plays a crucial role in the design of such quantizers. Numerical…

Combinatorics · Mathematics 2016-11-18 Vinay A. Vaishampayan , N. J. A. Sloane , Sergio D. Servetto

We consider the design of asymmetric multiple description lattice quantizers that cover the entire spectrum of the distortion profile, ranging from symmetric or balanced to successively refinable. We present a solution to a labeling…

Combinatorics · Mathematics 2007-05-23 Suhas N. Diggavi , N. J. A. Sloane , Vinay A. Vaishampayan

We address the connection between the multiple-description (MD) problem and Delta-Sigma quantization. The inherent redundancy due to oversampling in Delta-Sigma quantization, and the simple linear-additive noise model resulting from…

Information Theory · Computer Science 2009-07-15 Jan Ostergaard , Ram Zamir

For uniform scalar quantization, the error distribution is approximately a uniform distribution over an interval (which is also a 1-dimensional ball). Nevertheless, for lattice vector quantization, the error distribution is uniform not over…

Information Theory · Computer Science 2024-01-25 Chih Wei Ling , Cheuk Ting Li

A new lower bound on the average reconstruction error variance of multidimensional sampling and reconstruction is presented. It applies to sampling on arbitrary lattices in arbitrary dimensions, assuming a stochastic process with constant,…

Information Theory · Computer Science 2018-06-19 Erik Agrell , Balázs Csébfalvi

A lattice quantizer approximates an arbitrary real-valued source vector with a vector taken from a specific discrete lattice. The quantization error is the difference between the source vector and the lattice vector. In a classic 1996…

Information Theory · Computer Science 2024-01-25 Erik Agrell , Bruce Allen

Lattices with minimal normalized second moments are designed using a new numerical optimization algorithm. Starting from a random lower-triangular generator matrix and applying stochastic gradient descent, all elements are updated towards…

Information Theory · Computer Science 2025-07-24 Erik Agrell , Daniel Pook-Kolb , Bruce Allen

In this paper will be presented methodology of encoding information in valuations of discrete lattice with some translational invariant constrains in asymptotically optimal way. The method is based on finding statistical description of such…

Information Theory · Computer Science 2008-11-02 Jarek Duda

This paper studies fixed-rate randomized vector quantization under the constraint that the quantizer's output has a given fixed probability distribution. A general representation of randomized quantizers that includes the common models in…

Information Theory · Computer Science 2016-11-15 Naci Saldi , Tamás Linder , Serdar Yüksel

In this paper, we study an asymptotic approximation of the Fisher information for the estimation of a scalar parameter using quantized measurements. We show that, as the number of quantization intervals tends to infinity, the loss of Fisher…

Information Theory · Computer Science 2013-10-28 Rodrigo Cabral Farias , Jean-Marc Brossier

In this paper, we investigate the quantization of the output of a binary input discrete memoryless channel that maximizing the mutual information between the input and the quantized output under an entropy-constrained of the quantized…

Information Theory · Computer Science 2020-01-08 Thuan Nguyen , Thinh Nguyen

The quantization of the output of a binary-input discrete memoryless channel to a smaller number of levels is considered. An algorithm which finds an optimal quantizer, in the sense of maximizing mutual information between the channel input…

Information Theory · Computer Science 2014-05-16 Brian M. Kurkoski , Hideki Yagi

This paper presents a detailed study of constrained quantization for both finite and infinite discrete probability distributions supported on subsets of the real line. Under specific geometric constraints - namely, a semicircular arc and…

In many quantization problems, the distortion function is given by the Euclidean metric to measure the distance of a source sample to any given reproduction point of the quantizer. We will in this work regard distortion functions, which are…

Information Theory · Computer Science 2018-11-07 Jun Guo , Philipp Walk , Hamid Jafarkhani

A Lattice is a partially ordered set where both least upper bound and greatest lower bound of any pair of elements are unique and exist within the set. K\"{o}tter and Kschischang proved that codes in the linear lattice can be used for error…

Discrete Mathematics · Computer Science 2021-09-30 Pranab Basu

In this paper, we have studied various mixed distributions generated by two uniform distributions: first, where the supports are two connected line segments, and second, where the supports are two disconnected line segments. For these mixed…

Probability · Mathematics 2025-08-12 Asha Barua , Gustavo Fernandez , Ashley Gomez , Ogla Lopez , Mrinal Kanti Roychowdhury

A number of engineering and scientific problems require representing and manipulating probability distributions over large alphabets, which we may think of as long vectors of reals summing to $1$. In some cases it is required to represent…

Information Theory · Computer Science 2023-10-27 Aviv Adler , Jennifer Tang , Yury Polyanskiy

We consider the problem of solving a distributed optimization problem using a distributed computing platform, where the communication in the network is limited: each node can only communicate with its neighbours and the channel has a…

Systems and Control · Computer Science 2015-04-10 Ye Pu , Melanie N. Zeilinger , Colin N. Jones
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