To find a mean and variance of a discrete random variable
Aim: To find a mean and variance of a discrete random variable
Equipment:
PC with windows (95/98/XP/NT/2000).
MATLAB Software
MATLAB PROGRAM:
clear all;
close all;
x=[1 2 3 4 5 6];
n=length(x)
m = (1/n)*sum(x)
v = (1/n)*(xm)*(xm)'
RESULTS:
n = 6
m =3.5000
v = 2.9167
VIVA QUESTIONS
1. What is Signal Modeling.
Ans: Smallsignal modeling is a common analysis technique in engineering which is used to approximate the behavior of nonlinear devices with linear equations and signals.
2.Define Periodic and a periodic Signal.
Ans: If x(t)=x(t+T) then x(t) is periodic signal otherwise it is a periodic signal.

CreatedFeb 02, 2020

UpdatedFeb 02, 2020

Views164
Introduction
Basic operations on Matrices
Genaration of various signals and sequences
Operations on signals and sequences
Finding the even and odd parts of signal/sequence and real and imaginary parts of signal
Verification of Linearity and time invariance properties of a given continuous/discrete system
Linear Convolution
Auto correlation and cross correlation between signals and sequences
Computation of unit sample, unit step and sinusoidal response of the given LTI system and verifying its physical reliability and stability properties
GIBBS phenomenon
Sampling theorem verification
Finding the Fourier transform of a given signal and plotting its magnitude and phase spectrum
Laplace Transforms
Locating the zeros and poles and plotting the pole zero maps in zplane for the given transfer function
Gaussian Noise
Verification of Wiener Khinchin relation
Removal of noise by autocorrelation/crosscorrelation
Extraction of Periodic signal masked by noise using correlation.
Checking a Random process for stationarity in wide sense
To find a mean and variance of a discrete random variable
To find a moment generating function of a discrete random variable
Computation of Energy of sinusoidal signal
Computation of energy of rectangular pulse
Computation of Average Power
Waveform Synthesis
Find and plot the cumulative distribution and probability density functions of a random variable
Verification of central limit theorem