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Statistical inference
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Gaussian Random Vectors

Explores Gaussian random vectors and their statistical properties, emphasizing the importance of specifying statistical properties in complex valued random vectors.

Statistical Signal & Data Processing

Explores Statistical Signal & Data Processing fundamentals, tools, and applications in various fields.

Generalized Linear Models

Explores Generalized Linear Models, Bayesian methods, compressed sensing, and perception in high-dimensional statistics.

Signals and Systems II: Statistical Properties and Signal Representation

Explores statistical properties, signal representation, discrete signals, and binary signals.

Source Coding Theorems: Entropy and Source Models

Covers source coding theorems, entropy, and various source models in information theory.

Probabilistic Functions: Free Fields and Random Variables

Covers free fields and probabilistic functions, focusing on random variables and their properties.

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

Explores hypothesis testing, emphasizing the likelihood ratio test and its applications in statistical analysis.

Optimality in Decision Theory: Unbiased Estimation

Explores optimality in decision theory and unbiased estimation, emphasizing sufficiency, completeness, and lower bounds for risk.