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Heat Flow Derivatives and Minimum Mean-Square Error in Gaussian Noise
- Source :
- IEEE Transactions on Information Theory. 62:3401-3409
- Publication Year :
- 2016
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2016.
-
Abstract
- We connect recent developments on Gaussian noise estimation and the Minimum Mean-Square Error to earlier results on entropy and Fisher information heat flow expansion. In particular, the derivatives of the Minimum mean-square error with respect to the noise parameter are related to the heat flow derivatives of the Fisher information and a special Lie algebra structure on iterated gradients. The results lead in particular to a partial answer to the Minimum mean-square error conjecture.
- Subjects :
- Minimum mean square error
010102 general mathematics
Orthogonality principle
020206 networking & telecommunications
02 engineering and technology
Library and Information Sciences
01 natural sciences
Computer Science Applications
Combinatorics
symbols.namesake
Additive white Gaussian noise
Gaussian noise
Iterated function
0202 electrical engineering, electronic engineering, information engineering
symbols
Applied mathematics
Entropy (information theory)
0101 mathematics
Fisher information
Random variable
Information Systems
Mathematics
Subjects
Details
- ISSN :
- 15579654 and 00189448
- Volume :
- 62
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Information Theory
- Accession number :
- edsair.doi...........902529400b0eaff05ce7397fc40ab77d
- Full Text :
- https://doi.org/10.1109/tit.2016.2555809