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Random Variable & Random Process: Problem Solving Techniques – Free Udemy Courses

Random Variable & Random Process: Problem Solving Techniques - Free Udemy Courses
Random Variable & Random Process: Problem Solving Techniques - Free Udemy Courses

Random Variable & Random Process: Problem Solving Techniques – Free Udemy Courses

Probability density function, Cumulative distribution function, Power spectral density

What you’ll learn

Random Variable & Random Process: Problem Solving Techniques – Free Udemy Courses

  • You will learn the CORRECT approach to solve the problems on Random Variables and Random Process
  • Your knowledge of Random Variables and Random Process is improved
  • You will learn about Joint Probability and Conditional Probability
  • You will learn about probability Density Function and Cumulative Probability Distribution Function

Requirements

  • Basics of Random Variables and Random Process

Description

In this course, you will learn step-by-step procedures to solve questions on Random variables and Random processes. I will discuss the problems on probability density function, cumulative probability distribution function, conditional probability, joint probability, Bayes rule, Statistical averages such as mean, mean square value, power spectral density, autocorrelation, cross-correlation, Uniform distribution, Gaussian random variable, Transmission of a Random process through a linear filter, properties of the autocorrelation function, properties of power spectral density.

Random signals are encountered in every practical communication system. Some examples of Random signals are voice signals, television signals, digital computer data, and electrical noise. A signal is random if it is not possible to predict the exact value of the signal in advance whereas a signal is deterministic if it is possible to predict the exact value of the signal in advance. The mathematical discipline that deals with the statistical characterization of random signals are probability theory.

Who this course is for:

  • Engineering students
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