Tian, Peida and Kostina, Victoria
(2018)
*The Dispersion of the Gauss-Markov Source.*
In:
2018 IEEE International Symposium on Information Theory (ISIT).
IEEE
, Piscataway, NJ, pp. 1490-1494.
ISBN 978-1-5386-4780-6.
https://resolver.caltech.edu/CaltechAUTHORS:20181126-141849980

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## Abstract

The Gauss-Markov source produces U_i=aU_(i-1)+ Z_i for i ≥ 1, where U_0 = 0, |a| < 1 and Z_i ~ N(0, σ^2) are i.i.d. Gaussian random variables. We consider lossy compression of a block of n samples of the Gauss-Markov source under squared error distortion. We obtain the Gaussian approximation for the Gauss-Markov source with excess-distortion criterion for any distortion d > 0, and we show that the dispersion has a reverse waterfilling representation. This is the first finite blocklength result for lossy compression of sources with memory. We prove that the finite blocklength rate-distortion function R(n, d, ε) approaches the rate-distortion function R(d) as R(n, d, ε) = R(d)+√{[V(d)/n]}Q^(-1)(ε)+o([1/(√n)]), where V(d) is the dispersion, ε ∈ (0,1) is the excess-distortion probability, and Q^(-1) is the inverse of the Q-function. We give a reverse waterfilling integral representation for the dispersion V (d), which parallels that of the rate-distortion functions for Gaussian processes. Remarkably, for all 0 <; d ≤ σ2/(1+|a|)^2 ,R(n, d, c) of the Gauss-Markov source coincides with that of Zi, the i.i.d. Gaussian noise driving the process, up to the second-order term. Among novel technical tools developed in this paper is a sharp approximation of the eigenvalues of the covariance matrix of n samples of the Gauss-Markov source, and a construction of a typical set using the maximum likelihood estimate of the parameter a based on n observations.

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Additional Information: | © 2018 IEEE. This research was supported in part by the National Science Foundation (NSF) under Grant CCF-1566567. | ||||||||||||

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DOI: | 10.1109/ISIT.2018.8437463 | ||||||||||||

Record Number: | CaltechAUTHORS:20181126-141849980 | ||||||||||||

Persistent URL: | https://resolver.caltech.edu/CaltechAUTHORS:20181126-141849980 | ||||||||||||

Official Citation: | P. Tian and V. Kostina, "The Dispersion of the Gauss-Markov Source," 2018 IEEE International Symposium on Information Theory (ISIT), Vail, CO, 2018, pp. 1490-1494. doi: 10.1109/ISIT.2018.8437463 | ||||||||||||

Usage Policy: | No commercial reproduction, distribution, display or performance rights in this work are provided. | ||||||||||||

ID Code: | 91185 | ||||||||||||

Collection: | CaltechAUTHORS | ||||||||||||

Deposited By: | Tony Diaz | ||||||||||||

Deposited On: | 26 Nov 2018 22:32 | ||||||||||||

Last Modified: | 16 Nov 2021 03:39 |

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