Title :
On greedy adaptive measurements
Author :
Liu, Entao ; Chong, Edwin K P
Author_Institution :
Dept. of ECE, Colorado State Univ., Fort Collins, CO, USA
Abstract :
The purpose of this article is to examine the greedy adaptive measurement policy in the context of a linear Guassian measurement model with an optimization criterion based on information gain. In the special case of sequential scalar measurements, we provide sufficient conditions under which the greedy policy actually is optimal in the sense of maximizing the net information gain. In the general setting, we also discuss cases where the greedy policy is not optimal.
Keywords :
Gaussian processes; greedy algorithms; optimisation; greedy adaptive measurement policy; information gain; linear Guassian measurement model; optimization criterion; sequential scalar measurements; Compressed sensing; Covariance matrix; Eigenvalues and eigenfunctions; Gain measurement; Linear programming; Mercury (metals); Optimization; compressed sensing; compressive sensing; entropy; greedy policy; information gain; optimal policy;
Conference_Titel :
Information Sciences and Systems (CISS), 2012 46th Annual Conference on
Conference_Location :
Princeton, NJ
Print_ISBN :
978-1-4673-3139-5
Electronic_ISBN :
978-1-4673-3138-8
DOI :
10.1109/CISS.2012.6310781
