Optimal stochastic parameter design for estimation problems
Author
Soganci, H.
Gezici, Sinan
Arıkan, Orhan
Date
2012Source Title
IEEE Transactions on Signal Processing
Print ISSN
1053-587X
Publisher
Institute of Electrical and Electronics Engineers
Volume
60
Issue
9
Pages
4950 - 4956
Language
English
Type
ArticleItem Usage Stats
133
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views
89
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Abstract
In this study, the aim is to perform optimal stochastic parameter design in order to minimize the cost of a given estimator. Optimal probability distributions of signals corresponding to different parameters are obtained in the presence and absence of an average power constraint. It is shown that the optimal parameter design results in either a deterministic signal or a randomization between two different signal levels. In addition, sufficient conditions are obtained to specify the cases in which improvements over the deterministic parameter design can or cannot be achieved via the stochastic parameter design. Numerical examples are presented in order to provide illustrations of theoretical results.
Keywords
Bayes riskRandomization
Stochastic parameter design
Average power
Bayes risk
Deterministic signals
Estimation problem
Numerical example
Optimal parameter design
Parameter designs
Randomization
Signal level
Stochastic parameters
Sufficient conditions
Theoretical result
Optimization
Probability distributions
Design
Permalink
http://hdl.handle.net/11693/21357Published Version (Please cite this version)
http://dx.doi.org/10.1109/TSP.2012.2200892Collections
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