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About The Professor
Course
Subject:
Engineering
Topic:
Electronic Engineering
Views:
95,318
Educator
Name:
National Programme on Technology Enhanced Learning (NPTEL)
Type:
University
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Instructor
Name
M. Chakraborty
Probability & Random Variables
Video Lectures
Displaying all 40 video lectures.
Lecture 1
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Introduction to the Theory of Probability
Lecture 2
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Axioms of Probability
Lecture 3
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Axioms of Probability (Contd.)
Lecture 4
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Introduction to Random Variables
Lecture 5
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Probability Distributions and Density Functions
Lecture 6
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Conditional Distribution and Density Functions
Lecture 7
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Function of a Random Variable
Lecture 8
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Function of a Random Variable (Contd.)
Lecture 9
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Mean and Variance of a Random Variable
Lecture 10
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Moments
Lecture 11
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Characteristic Function
Lecture 12
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Two Random Variables
Lecture 13
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Function of Two Random Variables
Lecture 14
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Function of Two Random Variables (Contd.)
Lecture 15
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Correlation Covariance and Related Innver
Lecture 16
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Vector Space of Random Variables
Lecture 17
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Joint Moments
Lecture 18
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Joint Characteristic Functions
Lecture 19
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Joint Conditional Densities
Lecture 20
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Joint Conditional Densities (Contd.)
Lecture 21
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Sequences of Random Variables
Lecture 22
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Sequences of Random Variables (Contd.)
Lecture 23
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Correlation Matrices and their Properties
Lecture 24
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Correlation Matrices and their Properties
Lecture 25
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Conditional Densities of Random Vectors
Lecture 26
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Characteristic Functions and Normality
Lecture 27
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Thebycheff Inquality and Estimation
Lecture 28
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Central Limit Theorem
Lecture 29
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Introduction to Stochastic Process
Lecture 30
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Stationary Processes
Lecture 31
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Cyclostationary Processes
Lecture 32
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System with Random Process at Input
Lecture 33
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Ergodic Processes
Lecture 34
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Introduction to Spectral Analysis
Lecture 35
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Spectral Analysis Contd.
Lecture 36
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Spectrum Estimation - Non Parametric Methods
Lecture 37
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Spectrum Estimation - Parametric Methods
Lecture 38
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Autoregressive Modeling and Linear Prediction
Lecture 39
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Linear Mean Square Estimation - Wiener (FIR)
Lecture 40
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Adaptive Filtering - LMS Algorithm
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Subject: Engineering
Courses
Probability & Random Variables