B.TECH | ELECTRONICS & TELECOMMUNICATION | ESE WRITTEN QUALIFIED | 4 YEARS OF TEACHING Experience.. 

Shankar Kumar

In this course, Shankar Kumar will make you understand all the basics and fundamental Concepts along with the exercises on each topic for GATE-2019(EC)

GATE (Graduate Aptitude Test in Engineering) 2020 & 2021 complete preparation with best educators. Know about the detailed syllabus, best books, exam pattern and dates, previous year question papers a

GATE - Iconic Pro

English

Random Variables Part:1

Random Variables & Noise

Communications

GATE & ESE - EE, EC

GATE, ESE and IIT-JAM

Ace the toughest competitive and government exams in India 

Test Preparation

Overview

In this lessons student will get introduction about RANDOM VARIABLES & the basic understanding of the probability mass Function along with the numerical

Probability Mass Function (PMF)

In this lesson student will get the basic understanding of the CUMMULATIVE DISTRIBUTION FUNCTION(CDF) along with the numericals

Cumulative Distribution Function (CDF)

In this lesson student will get the basic understanding of the  PROBABILITY DENSITY FUNCTION(PDF) along with the numericals

Probability Density Function (PDF)

In this lesson student will get the NUMERICALS based on PDF, CDF & PMF

Exercise : 1 (PDF)

Exercise : 2 (CDF)

In this lesson student will get the NUMERICALS based on PDF & CDF

EXERCISE :3(PDF)

This lesson will cover Mean,MSQ,Variance and standard deviation formulae with full explanation..

STATISTICAL PARAMETERS OF RANDOM VARIABLES

EXERCISE :4(STATISTICAL PARAMETERS OF RANDOM VARIABLES)

EXERCISE:4(STATISTICAL PARAMETERS OF RANDOM VARIABLES)

GAUSSIAN DENSITY FUNCTION/NORMAL DENSITY FUNCTION

EXERCISE :5(STATISTICAL PARAMETERS OF RANDOM VARIABLES)

ANALYSIS :GAUSSIAN DENSITY FUNCTION/NORMAL DENSITY FUNCTION

ANLYSYS:GAUSSIAN DENSITY FUNCTION/NORMAL DENSITY FUNCTION

Here as a Teacher and Learner on Unacademy Family

Bharath S

This course covers the topics and numerical related to Information Theory. The course will be beneficial for GATE aspirants.

Information Theory - GATE (ECE)

ISRO , SCIENTIST/ENGINEER
(AIR-8)  ISRO,  E & T Engineer,
 Always remember you are different from others( If u Think u Can )

Rahul Pathak

This course will  explain probability of error in digital communication with concept of random variable and random process.
which will help Electronics and electrical student in competitive exam and engineering curriculum.

(Hindi) Probability of Errors and Random Variables: GATE

I am an Electronics engineer.Passionate to share my knowledge to students who actually need it.In my subject u definitely go well.

Vaibhav Goel

We will discuss all the theory plus questions important for GATE 2020 and ESE 2020. 
This will cover random process first followed by random variable.
Now I assure that this after watching this you have much confidence in this topic as before

(Hindi) Communication Random Variable and Random Processes Course : GATE (ECE)

Unless you dive into the depth of the most difficult problem, you can't turn impossible into possible. 

Himanshu Sen

This course deals with basic concepts related to probability and also it discusses about the random variable and random process and some important numericals.

Probability or Stochaistic Process

B.Tech. graduate from ECE with First Division Honours. Engineer by profession Educator by passion. My Motive is to 'Grow & Learn' always.

Indu Yadav

This course contains proper explanation of probability, random process and Random variable for the analysis of signal in communication which are unpredictable in nature.

Probability and Random Processes

In this course is about complete digital communication and the topics which covered are 

 Sampling theorem,
Modulation,
PCM and it's noises,
 DPCM and DM,
Bandwidth ,
digital carrier schemes,
constellation diagrams,
summary.This Course is beneficial for  GATE (ECE) aspirants.

Lessons

11 lessons • 1h 51m

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Overview

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Probability Mass Function (PMF)

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Cumulative Distribution Function (CDF)

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Probability Density Function (PDF)

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Exercise : 1 (PDF)

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Exercise : 2 (CDF)

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EXERCISE :3(PDF)

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STATISTICAL PARAMETERS OF RANDOM VARIABLES

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EXERCISE:4(STATISTICAL PARAMETERS OF RANDOM VARIABLES)

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EXERCISE :5(STATISTICAL PARAMETERS OF RANDOM VARIABLES)

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