Stochastic Models for Communications

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Related lectures (28)

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Modes of Convergence of Random Variables

Covers the modes of convergence of random variables and the Central Limit Theorem, discussing implications and approximations.

Neurobiological Signal Processing

Explores neurobiological signal processing, covering spike modeling, signal classification, and data characterization using principal component analysis.

Causal Systems & Transforms: Delay Operator Interpretation

Covers z Variable as a Delay Operator, realizable systems, probability theory, stochastic processes, and Hilbert Spaces.

Conditional Density and Expectation

Explores conditional density, expectations, and independence of random variables with practical examples.

Probability and Statistics

Covers fundamental concepts in probability and statistics, including distributions, properties, and expectations of random variables.

Random Variables: Expectation and Independence

Explores random variables, expectation, and independence in probability theory.

Probabilistic Functions: Free Fields and Random Variables

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

Probability and Statistics

Covers fundamental concepts in probability and statistics, emphasizing data analysis techniques and statistical modeling.