Harry L. Van Trees
Abstract
This chapter's discussion considers parameters that are constant during the observation period. The discussion of the parameter estimation problem is divided into two chapters. Chapter 8 focuses on maximum likelihood (ML) and maximum a posteriori probability (MAP) estimators and on bounds on the performance of any estimator.
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This chapter's discussion considers parameters that are constant during the observation period. The discussion of the parameter estimation problem is divided into two chapters. Chapter 8 focuses on maximum likelihood (ML) and maximum a posteriori probability (MAP) estimators and on bounds on the performance of any estimator.
Key concepts: Maximum a posteriori estimation, Maximum likelihood, Estimator, Maximum likelihood sequence estimation, Estimation theory, Statistics, Mathematics, Constant (computer programming)