Probability & Random Variables

Video Lectures

Displaying all 40 video lectures.
Lecture 1
Introduction to the Theory of Probability
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Introduction to the Theory of Probability
Lecture 2
Axioms of Probability
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Axioms of Probability
Lecture 3
Axioms of Probability (Contd.)
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Axioms of Probability (Contd.)
Lecture 4
Introduction to Random Variables
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Introduction to Random Variables
Lecture 5
Probability Distributions and Density Functions
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Probability Distributions and Density Functions
Lecture 6
Conditional Distribution and Density Functions
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Conditional Distribution and Density Functions
Lecture 7
Function of a Random Variable
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Function of a Random Variable
Lecture 8
Function of a Random Variable (Contd.)
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Function of a Random Variable (Contd.)
Lecture 9
Mean and Variance of a Random Variable
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Mean and Variance of a Random Variable
Lecture 10
Moments
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Moments
Lecture 11
Characteristic Function
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Characteristic Function
Lecture 12
Two Random Variables
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Two Random Variables
Lecture 13
Function of Two Random Variables
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Function of Two Random Variables
Lecture 14
Function of Two Random Variables (Contd.)
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Function of Two Random Variables (Contd.)
Lecture 15
Correlation Covariance and Related Innver
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Correlation Covariance and Related Innver
Lecture 16
Vector Space of Random Variables
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Vector Space of Random Variables
Lecture 17
Joint Moments
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Joint Moments
Lecture 18
Joint Characteristic Functions
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Joint Characteristic Functions
Lecture 19
Joint Conditional Densities
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Joint Conditional Densities
Lecture 20
Joint Conditional Densities (Contd.)
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Joint Conditional Densities (Contd.)
Lecture 21
Sequences of Random Variables
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Sequences of Random Variables
Lecture 22
Sequences of Random Variables (Contd.)
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Sequences of Random Variables (Contd.)
Lecture 23
Correlation Matrices and their Properties
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Correlation Matrices and their Properties
Lecture 24
Correlation Matrices and their Properties
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Correlation Matrices and their Properties
Lecture 25
Conditional Densities of Random Vectors
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Conditional Densities of Random Vectors
Lecture 26
Characteristic Functions and Normality
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Characteristic Functions and Normality
Lecture 27
Thebycheff Inquality and Estimation
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Thebycheff Inquality and Estimation
Lecture 28
Central Limit Theorem
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Central Limit Theorem
Lecture 29
Introduction to Stochastic Process
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Introduction to Stochastic Process
Lecture 30
Stationary Processes
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Stationary Processes
Lecture 31
Cyclostationary Processes
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Cyclostationary Processes
Lecture 32
System with Random Process at Input
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System with Random Process at Input
Lecture 33
Ergodic Processes
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Ergodic Processes
Lecture 34
Introduction to Spectral Analysis
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Introduction to Spectral Analysis
Lecture 35
Spectral Analysis Contd.
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Spectral Analysis Contd.
Lecture 36
Spectrum Estimation - Non Parametric Methods
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Spectrum Estimation - Non Parametric Methods
Lecture 37
Spectrum Estimation - Parametric Methods
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Spectrum Estimation - Parametric Methods
Lecture 38
Autoregressive Modeling and Linear Prediction
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Autoregressive Modeling and Linear Prediction
Lecture 39
Linear Mean Square Estimation - Wiener (FIR)
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Linear Mean Square Estimation - Wiener (FIR)
Lecture 40
Adaptive Filtering - LMS Algorithm
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Adaptive Filtering - LMS Algorithm