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Joint Universal Lossy Coding and Identification of I.I.D. Vector Sources

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1 Author(s)
Raginsky, M. ; Beckman Inst., Illinois Univ., Urbana, IL

The problem of joint universal source coding and modeling, addressed by Rissanen in the context of lossless codes, is generalized to fixed-rate lossy coding of continuous-alphabet memoryless sources. We show that, for bounded distortion measures, any compactly parametrized family of i.i.d. real vector sources with absolutely continuous marginals (satisfying appropriate smoothness and Vapnik-Chervonenkis learnability conditions) admits a joint scheme for universal lossy block coding and parameter estimation, and give nonasymptotic estimates of convergence rates for distortion redundancies and variational distances between the active source and the estimated source. We also present explicit examples of parametric sources admitting such joint universal compression and modeling schemes

Published in:

Information Theory, 2006 IEEE International Symposium on

Date of Conference:

9-14 July 2006

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