On the relation between the Gaussian information bottleneck and MSE-optimal rate-distortion quantization
SSP（2014）
摘要
We use the Gaussian information bottleneck (GIB) to investigate the optimal rate-information trade-off for signal compression in linear Gaussian models and we provide a novel interpretation of the GIB in terms of the eigendecomposition of the Wiener filter. We further study mean-square-error-optimal rate-distortion compression preceded by a linear filter. Choosing this filter as square root of the Wiener filter is shown to be rate-information optimal. Finally, we extend our results to jointly stationary Gaussian random processes.
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关键词
optimal rate-information trade-off,Wiener filtering,eigendecomposition,GIB,random processes,square root,channel output compression,Gaussian information bottleneck,Wiener filters,MSE,linear filter,rate-distortion theory,Gaussian processes,linear Gaussian models,signal compression,mean-square-error-optimal rate-distortion compression,eigenvalues and eigenfunctions,stationary Gaussian random processes,mean square error methods,Wiener filter
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