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Introduction to Stochastic Signals & Systems
Fall 2024

Lecture
Topic
Lecture 01
Axioms, discrete probability models
Lecture 02
Cconditional probability, total probability, Baye's rule
Lecture 03
Continuous probability models, moments, PMF
Lecture 04
CDF, PDF
Lecture 05
Functions of random variables, pairs of random variables, correlation
Lecture 06
Definition of stochastic process, auto-correlation, auto-covariance
Lecture 07
Cross-correlation, arrival process, renewal process, sum process, Poisson processes
Lecture 08
Properties of Poisson processes, stationary processes
Lecture 09
Poisson Process Derivation, Poisson Randomness,
Lecture 10
Systems with Stoch. Inputs: Memoryless Systems, LTI systems
Lecture 11
LTI systems mean and autocorrelation
Lecture 12
Fourier Transform review, power spectral density
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