Signal-Processing

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Title of script: Signal processing Using Scilab

Author: Manas

Keywords::Signal


Visual Cue
Narration
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 spoken-tutorial.org
Slide 4 Prerequisite:Listen to basic Level tutorials in

Scilab



Slide 5 What is a Signal?

A signal is any time-varying or spatial-varying 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
  • Plotting continuous and discrete sine wave.
  • Plotting step function.
  • Plotting ramp function.


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=


10.

- 2. + 2.i

- 2. - 9.797D-16i

- 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,-2-2*%i]

The output is given by x = dft(y,1)

x =


1.

2. + 5.551D-17i

3. - 1.225D-16i

4. - 5.551D-16i



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 =


10. - 2. + 2.i - 2. - 2. - 2.i

Demonstrate I will be calculating idft using fft:

y=[10,-2+2*%i,-2,-2-2*%i];

x = fft(y,1)

x =


1. 2. 3. 4.

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 =


1.25 0.3125 0.25 - 0.9375

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://spoken-tutorial.org/NMEICT-Intro



Slide 21,22 & 23 About the Spoken Tutorial Project


  • If you do not have good bandwidth, you can download

and watch it.



Slide 24,25 & 26 Acknowledgement


  • We conduct workshops using spoken tutorials.
  • We also give certificates to those who pass an online test.
  • Please contact us for more details. We conduct workshops using spoken tutorials.
  • We also give certificates to those who pass an online test.
  • Please contact us for more details.


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

Contributors and Content Editors

Minal