Optimal stochastic design for multi-parameter estimation problems
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Institute of Electrical and Electronics Engineers Inc.
Please cite this item using this persistent URLhttp://hdl.handle.net/11693/27875
In this study, we consider performance improvement of an array of fixed estimators by using stochastic design techniques. The optimal design is investigated both in the absence and presence of an average power constraint. Two different performance criteria are considered; the average Bayes risk and the maximum Bayes risk. It is shown that the optimal stochastic parameter design results in a randomization between different numbers of parameter values depending on the type of the performance criterion. © 2014 IEEE.
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