Search for dissertations about: "optimal estimators"
Showing result 11 - 15 of 41 swedish dissertations containing the words optimal estimators.
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11. Ambiguity Domain Definitions and Covariance Function Estimation for Non-Stationary Random Processes in Discrete Time
Abstract : The ambiguity domain plays a central role in estimating the time-varying spectrum of a non-stationary random process in continuous time, since multiplication in this domain is equivalent with estimating the covariance function of the random process using an intuitively appealing estimator. For processes in discrete time there exists a corresponding covariance function estimator. READ MORE
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12. Improved sequential decision-making with structural priors: Enhanced treatment personalization with historical data
Abstract : Personalizing treatments for patients involves a period where different treatments out of a set of available treatments are tried until an optimal treatment is found, for particular patient characteristics. To minimize suffering and other costs, it is critical to minimize this search. READ MORE
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13. Low-complexity algorithms in digital receivers
Abstract : This thesis addresses low-complexity algorithms in digital receivers. This includes algorithms for estimation, detection, and source coding. READ MORE
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14. Essays on Model Assisted Survey Planning
Abstract : The quality of sample survey results is to a large degree dependent on decisions made by survey statisticians at the planning stage. The first paper studies two issues related to the planning stage: (i) the sensitivity of model assumptions concerning the relation between the size measure and a study variable in without replacement probability proportional-to-size sampling (πps sampling), and (ii) properties of practicable sample selection schemes for fixed size πps sampling. READ MORE
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15. Distributed Estimation of Network Cardinalities
Abstract : In distributed applications knowing the topological properties of the underlying communication network may lead to better performing algorithms. For instance, in distributed regression frameworks, knowing the number of active sensors allows to correctly weight prior information against evidence in the data. READ MORE