SignalProcessing
Title of script: Signal processing Using Scilab
Author: Manas
Keywords::Signal



Slide 1  Dear Friends,
Welcome to the spoken tutorial on “Signal Processing using Scilab” 
Slide 2  Before starting with this tutorial, first we will see the Knowledge prerequisite and software requirement to use this tutorial. 
Slide 2 & 3  Ubuntu 11.04 is the operating system used in this tutorial with Scilab 5.3.3
version installed. 
Scilab can be installed on Ubuntu OS using the Synaptic Package Manager.
 
To install Scilab, please refer to the tutorial 'How to install Scilab in Ubuntu using Synaptic Package Manager' available on spokentutorial.org  
Slide 4  Prerequisite:Listen to basic Level tutorials in
Scilab

Slide 5  What is a Signal?
A signal is any timevarying or spatialvarying quantity. 
Slide 6  Objective of this tutorial
In this tutorial i will show the operations on or analysis of signals, in either discrete or continuous time domain. 
Slide 7  In this slide i will be describing Signal Basics

Demonstrate  Let us start first plotting continuous sine wave. This can be done as follows:
t = 0:0.1:2*%pi; x = sin(t); plot2d(t,x) 
Demonstrate  A discrete sine wave can be plotted as :
plot2d3('gnn',t,x) 
Demonstrate  I have written the codes to generate step and ramp signal in the file signals.sce. I will execute it and show how the signals are being generated. 
Slide 8  In this slide let us learn Convolution
i.e. Linear convolution of two vectors by using the inbuilt command convol() 
Demonstrate  First step is to take an discrete input signal x=[1,2 ,3,4]
Second step is to take an another input signal h=[1,1,1] And the the third step is to apply the convolution using convol() 
Slide 9  In this slide we will learn Discrete fourier transform for a discrete sequence by using the inbuilt command dft(). 
Demonstrate  Calling sequence to calculate DFT is
[xf]=dft(x,flag); Where x is the input vector and flag value is 1 for DFT. Lets take the input vector is x=[1,2,3,4] The output dft will be calculated by xf=dft(x,1) xf=
 2. + 2.i  2.  9.797D16i  2.  2.i 
Slide 10  In this slide i will be showing how to calculate inverse discrete fourier transform. This can be found by using the same inbuilt command dft(). 
Demonstrate  Here the calling sequence for this function is defined.
[x]=dft(xf,flag); Here the flag value is 1 for idft. 
Demonstrate  Let the input sequence xf = [10,2+2*%i,2,22*%i]
The output is given by x = dft(y,1) x =
2. + 5.551D17i 3.  1.225D16i 4.  5.551D16i

Slide 11  In this slide lets have a look how to calculate discrete fourier transform and inverse discrete fourier transform by using the inbuilt function fft(). 
Demonstrate  I will be calculating dft using fft:
Let the input vector is x= [1,2,3,4]; The output is given by y = fft(x,1) y =

Demonstrate  I will be calculating idft using fft:
y=[10,2+2*%i,2,22*%i]; x = fft(y,1) x =

Slide 12  In this slide we will be using corr() to find the correlation between two vectors. 
Demonstrate  Lets take two input signals are
x1 = [1,2,3,4]; and x2 = [1,3,1,5]; The cross correlation can be found by Rx1x2 = corr(x1,x2,4) Rx1x2 =

Slide 13  In this slide let us show Sampling of a given signal using intdec () 
Demonstrate  The calling sequence for sampling is
[y]=intdec(x,lom) I have written the code in sampling.sce and will execute it by clicking on the file. 
I will summarize the things we learnt in this tutorial.  
Slide 14  In this tutorial we learnt 
Slide 14  Signal basics and how to plot continuous and discrete sine wave,step and ramp signal. 
Slide 15  Linear convolution of two vectors by using the inbuilt command convol() 
Slide 16  Discrete fourier transform and inverse fourier transform for a discrete sequence by using the inbuilt command dft(). 
Slide 17  FFT by fft() 
Slide 18  Correlation between two signals by using inbuilt command corr(). 
Slide 19  Sampling of a given signal using intdec(). 
Slide 20  Spoken Tutorial is a part of the
Talk to a Teacher project

It is supported by the National Mission on
Education through ICT (NMEICT), MHRD, Government of India
 
More information on this mission is
available at http://spokentutorial.org/NMEICTIntro
 
Slide 21,22 & 23  About the Spoken Tutorial Project
and watch it.

Slide 24,25 & 26  Acknowledgement

Slide 27,28 & 29  Acknowledgement

Slide 30,31 & 32  * Thanks for joining.

Hope you found this Spoken Tutorial useful.  
This script has been contributed by Manas Das.
This is Anuradha Amrutkar from IIT Bombay, signing off  
Thanks for joining us,Good Bye 