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Lecture
Classification Detection
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Related lectures (32)
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Detection & Estimation
Covers binary classification, hypothesis testing, likelihood ratio tests, and decision rules.
Statistical Theory: Cramér-Rao Bound & Hypothesis Testing
Explores the Cramér-Rao bound, hypothesis testing, and optimality in statistical theory.
Likelihood Ratio Test: Detection & Estimation
Covers the likelihood ratio test for detection and estimation in statistical analysis.
Likelihood Ratio Tests: Optimality and Applications
Explores the theory and applications of likelihood ratio tests in statistical hypothesis testing.
Maximum Likelihood Estimation: Multivariate Statistics
Explores maximum likelihood estimation and multivariate hypothesis testing, including challenges and strategies for testing multiple hypotheses.
Likelihood Ratio Test: Hypothesis Testing
Covers the Likelihood Ratio Test and hypothesis testing methods using Maximum Likelihood Estimators.
Likelihood Ratio Tests: Optimality and Extensions
Covers Likelihood Ratio Tests, their optimality, and extensions in hypothesis testing, including Wilks' Theorem and the relationship with Confidence Intervals.
Likelihood Ratio Test: Hypothesis Testing
Explores hypothesis testing, emphasizing the likelihood ratio test and its applications in statistical analysis.
Hypothesis Testing: State of Nature
Explores hypothesis testing, emphasizing the state of nature and the importance of choosing the most powerful test.
Frame Synchronization: Systematic Derivation with Likelihood Test
Covers the systematic derivation of a synchronization algorithm with a generalized likelihood test in wireless receivers.
