Paper Info
Title
Local and Networked Mean-square Estimation with High Dimensional Log-concave Noise.
Abstract
We consider the problem of mean-square estimation of the state of a discrete time dynamical system having additive non-Gaussian noise. We assume that the noise has the structure that at each time instant, it is a projection of a fixed high-dimensional noise vector with a log-concave density. We derive conditions which guarantee that, as the dimension of this noise vector grows large, the optimal e...
Year
DOI
Venue
2018
10.1109/TIT.2017.2774818
IEEE Transactions on Information Theory
Keywords
Field
DocType
Estimation,Gaussian noise,Standards,Random variables,Sensors,Linear systems,Mean square error methods
Applied mathematics,Discrete mathematics,Central limit theorem,Linear system,Computer science,Upper and lower bounds,Kalman filter,Gaussian,Gaussian noise,Orthogonality principle,Estimator
Journal
Volume
Issue
ISSN
64
4
0018-9448
Citations 
PageRank 
References 
0
0.34
0
Authors
1
Name
Order
Citations
PageRank
Ankur A. Kulkarni110620.95