Rate–Distortion Function via Minimum Mean Square Error Estimation

We derive a simple general parametric representation of the rate-distortion function of a memoryless source, where both the rate and the distortion are given by integrals whose integrands include the minimum mean square error (MMSE) of the distortion Δ = d(X, Y) based on the source symbol X, with respect to a certain joint distribution of these two random variables. At first glance, these relations may seem somewhat similar to the I-MMSE relations due to Guo, Shamai and Verdú, but they are, in fact, quite different. The new relations among rate, distortion, and MMSE are discussed from several aspects, and more importantly, it is demonstrated that they can sometimes be rather useful for obtaining non-trivial upper and lower bounds on the rate-distortion function, as well as for determining the exact asymptotic behavior for very low and for very large distortion. Analogous MMSE relations hold for channel capacity as well.

[1]  M. Fogiel,et al.  Handbook of mathematical, scientific, and engineering formulas, tables, functions, graphs, transforms , 1984 .

[2]  Neri Merhav Another Look at the Physics of Large Deviations With Application to Rate-Distortion Theory , 2009, ArXiv.

[3]  Neri Merhav An identity of Chernoff bounds with an interpretation in statistical physics and applications in information theory , 2008, 2008 IEEE International Symposium on Information Theory.

[4]  Shlomo Shamai,et al.  Mutual information and minimum mean-square error in Gaussian channels , 2004, IEEE Transactions on Information Theory.

[5]  E. Weinstein,et al.  Lower bounds on the mean square estimation error , 1985, Proceedings of the IEEE.

[6]  Aaron D. Wyner,et al.  Bounds on the rate-distortion function for stationary sources with memory , 1971, IEEE Trans. Inf. Theory.

[7]  Amir Dembo,et al.  Large Deviations Techniques and Applications , 1998 .

[8]  Toby Berger,et al.  Rate distortion theory : a mathematical basis for data compression , 1971 .

[9]  Neri Merhav On the physics of rate-distortion theory , 2010, 2010 IEEE International Symposium on Information Theory.

[10]  Kenneth Rose,et al.  A mapping approach to rate-distortion computation and analysis , 1994, IEEE Trans. Inf. Theory.

[11]  Irene A. Stegun,et al.  Handbook of Mathematical Functions. , 1966 .

[12]  Thomas M. Cover,et al.  Elements of Information Theory: Cover/Elements of Information Theory, Second Edition , 2005 .

[13]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[14]  G. Longo Source Coding Theory , 1970 .

[15]  Imre Csiszár,et al.  Information Theory - Coding Theorems for Discrete Memoryless Systems, Second Edition , 2011 .