Soğancı, HamzaGezici, SinanArıkan, Orhan2016-02-082016-02-082014- 05http://hdl.handle.net/11693/27875Date of Conference: 4-9 May 2014Conference name: 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)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.EnglishParameter estimationStochastic parameter designAverage powerBayes riskEstimation problemMultiparametersOptimal designPerformance criterionStochastic designStochastic parametersSignal processingConference Paper10.1109/ICASSP.2014.6854685