Gaussian Approximation of Quantization Error for Estimation from Compressed Data
Publication
, Conference
Kipnis, A; Reeves, G
Published in: IEEE International Symposium on Information Theory - Proceedings
July 1, 2019
We consider the statistical connection between the quantized representation of a high dimensional signal X using a random spherical code and the observation of X under an additive white Gaussian noise (AWGN). We show that given X, the conditional Wasserstein distance between its bitrate-R quantized version and its observation under AWGN of signal-to-noise ratio 22R - 1 is sub-linear in the problem dimension. We then utilize this fact to connect the mean squared error (MSE) attained by an estimator based on an AWGN-corrupted version of X to the MSE attained by the same estimator when fed with its bitrate-R quantized version.
Duke Scholars
Published In
IEEE International Symposium on Information Theory - Proceedings
DOI
ISSN
2157-8095
Publication Date
July 1, 2019
Volume
2019-July
Start / End Page
2029 / 2033
Citation
APA
Chicago
ICMJE
MLA
NLM
Kipnis, A., & Reeves, G. (2019). Gaussian Approximation of Quantization Error for Estimation from Compressed Data. In IEEE International Symposium on Information Theory - Proceedings (Vol. 2019-July, pp. 2029–2033). https://doi.org/10.1109/ISIT.2019.8849826
Kipnis, A., and G. Reeves. “Gaussian Approximation of Quantization Error for Estimation from Compressed Data.” In IEEE International Symposium on Information Theory - Proceedings, 2019-July:2029–33, 2019. https://doi.org/10.1109/ISIT.2019.8849826.
Kipnis A, Reeves G. Gaussian Approximation of Quantization Error for Estimation from Compressed Data. In: IEEE International Symposium on Information Theory - Proceedings. 2019. p. 2029–33.
Kipnis, A., and G. Reeves. “Gaussian Approximation of Quantization Error for Estimation from Compressed Data.” IEEE International Symposium on Information Theory - Proceedings, vol. 2019-July, 2019, pp. 2029–33. Scopus, doi:10.1109/ISIT.2019.8849826.
Kipnis A, Reeves G. Gaussian Approximation of Quantization Error for Estimation from Compressed Data. IEEE International Symposium on Information Theory - Proceedings. 2019. p. 2029–2033.
Published In
IEEE International Symposium on Information Theory - Proceedings
DOI
ISSN
2157-8095
Publication Date
July 1, 2019
Volume
2019-July
Start / End Page
2029 / 2033