Matera 2k13 Ppts

7/30/2019 Matera 2k13 Ppts

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BY

DR.M.NARSING YADAV

B.TECH,MS,PH.DASSOCIATE PROFESSOR,

DEPT OF ECE,

BITS, KNL

MATLAB AND ITS

APPLICATIONS


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Basics of MATLAB

Matlab Desktop

Command windowWorkspace

Current directory

Figure window

Editor window


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Matlab Desktop Window


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Figure window


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Editor Window


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File Types

.m files

.mat files

.fig files

.p files

.mex files


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Some of the Desktop Command Windows

Who lists variables currently in the workspace

Whos lists variables currently in the workspace withtheir size

What lists .m, .mat and .mex files on the disk

Clear clears the workspace, all the variables areremoved

Clear all clears all the variables and functions from theworkspace

Clc clears the command window, command history isalso lost

Clf clears the figure window

Control c aborts and kills the current commandexecution


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2. Various Mathematical

Operations

arithematic operations

Trignometric operations

Exponential operations

Complex operations

Logarithmic Operations


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3. Formation of a Matrix

By explicit entering of elements

By Importing the data using real time signals

By using Generating Matrices


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A = [ 1 2 3; 4 5 6; 7 8 9]

Y=wavread(C:\Documents andSettings\user\Desktop\sig1.wav)

Y=imread(C:\Documents and

Settings\user\Desktop\yoga.jpg)


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4. Matrix Indexing

Declaring the input elements to a matrix

The matrix is always declared in the upper caseletter

A=[ 1 2 3; 4 5 6; 7 8 9]

Null Matrix A=[ ]

The powerful colon operator ; it can be used in

many ways for performing various matrixoperations


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For example:

Producing a row of integers

A=1:5

A=[1 2 3 4 5]

hence can be used to generate a row vector of size N

A=1:N

Can also be used as A=colon(1,N)

Can also be used for producing an array of non uniform spacing

x=100:-10:50

X=[100 90 80 70 60 50]X=50:10:100

Can be used to select a part of a matrix

A=[ 1 2 3; 4 5 6; 7 8 9]

C3=A(:,3)

C3= 3

6

9

R2=A(2,:)

T=A(1:2,1:3)

Can be used to convert a two dimensional matrix into a single column vector

=


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Generating Matrices zeros(M,N)

Ones(M,N)

Rand(M,N)

Randn(M,N)

Randint(M,N)

Eye(M,N)

Diag(A)

Rot90(A)

Fliplr(A)

Flipud(A)

Tril(A)

Triu(A)

Reshape(A,[m n])


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Some other operations

reshaping matrices

Let A be a 4x4 matrix , then reshape(A,2,8)

Appending a row or a column

A=[A;u] , A=[A v], A=[ A u]

Deleting a row or a column

A(2,: )=[ ]

A(:, 3:5) = [ ]

A([1 3], : ) = [ ]

Transpose of a Matrix


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Creating vectors

The general expression for creating avector is

v=Initial value: increment: Final value

Linspace(a,b,n) Logspace(a,b,n)

Importance of .operator


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Creating plots and graphs Basic 2D plots

plot(x values, y values, style-option);style option=color_linestyle_markerstyle

Labels, titles

xlabel( );ylabel( );

title( );

Use of legend

legend(string1,string2, ..) Generating overlay plots

line(xdata, ydata, parameter name, parametervalue)


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t=linspace(0,2*pi,100)y1=sin(t);y2=t;y3=t-(t.^3)/6+(t.^5)/120;plot(t,y1)line(t,y2,'linestyle','--')

line(t,y3,'marker','o')xlabel('t')ylabel('approximations of sin(t)')title('fun with sin(t)')legend('sint(t)','linear approx','fifthorder approx')

0 1 2 3 4 5 6 7-10

0

10

20

30

40

50

t

approxim

ationsofsin(t)

fun with sin(t)

sint(t)

linear approx

fifth order approx


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Subplot of a figure window

0 50 1000

0.2

0.4

0.6

0.8

1

0 50 1000

0.2

0.4

0.6

0.8

1

0 2 4 6 8

x 104

0

2

4

6

0 2 4 6 8

x 104

0

10

20

30

40

t=0:0.0001:6

%unit impulse

y1= [1 zeros(1,99)];

%figure,plot(y1)

%%%% unit step

y2=ones(1,100);

%figure,stem(y2)

%%%% unit ramp %%%%%

y3=t;%figure,stem(y3)

%%%%%%%% quadratic signal %%%%%%%

y4=t.^2;

figure,subplot(2,2,1),stem(y1)subplot(2,2,2),stem(y2)

subplot(2,2,3),stem(y3)subplot(2,2,4),stem(y4)


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Examples of periodic signals

Square wave Sine and cosine wave

Saw tooth wave; triangular wave

some common signals

Unit impulse

Unit step

Ramp Parabolic

cubic


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Examples of aperiodic signals

Gaussian Pulse

Pulse train functionThe chirp signal

The sinc signalThe dirac function


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The Guassian pulse

Syntax

yi = gauspuls(t,fc,bw)yi = gauspuls(t,fc,bw,bwr)

tc = gauspuls('cutoff',fc,bw,bwr,tpe)

yi = gauspuls(t,fc,bw) returns a unity-amplitude Gaussian RF pulse at

the times indicated in array t, with a center frequency fc in hertz anda fractional bandwidth bw, which must be greater than 0. Thedefault value for fc is 1000 Hz and for bw is 0.5.

tc = gauspuls('cutoff',fc,bw,bwr,tpe) returns the cutoff time tc(greater than or equal to 0) at which the trailing pulse envelope falls

below tpe dB with respect to the peak envelope amplitude. Thetrailing pulse envelope level tpe must be less than 0, because itindicates a reference level less than the peak (unity) envelopeamplitude. The default value for tpe is -60 dB.


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The Pulstran function

y = pulstran(t,d,'func')pulstran(t,d,'func',p1,p2,...)pulstran(t,d,p,fs)

pulstran(t,d,p)pulstran(...,'func')

y = pulstran(t,d,'func') generates a pulse train based on samples of acontinuous function, 'func', where 'func'is

'gauspuls', for generating a Gaussian-modulated sinusoidal pulse

'rectpuls', for generating a sampled aperiodic rectangle

'tripuls', for generating a sampled aperiodic triangle

t = 0 : 1/1e3 : 1; % 1 kHz sample freq for 1 secd = 0 : 1/3 : 1; % 3 Hz repetition freq

y = pulstran(t,d,'tripuls',0.1,-1); plot(t,y)


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The Sinc Function

Syntax

y = sinc(x)


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The Chirp Signal

y = chirp(t,f0,t1,f1)

y = chirp(t,f0,t1,f1,'method') y = chirp(t,f0,t1,f1) generates samples of a linear

swept-frequency cosine signal at the time instancesdefined in array t, where f0 is the instantaneousfrequency at time 0, and f1 is the instantaneous

frequency at time t1. f0 and f1 are both in hertz. Ifunspecified, f0 is e-6 for logarithmic chirp and 0 for allother methods, t1 is 1, and f1 is 100.

y = chirp(t,f0,t1,f1,'method') specifies alternativesweep method options, where methodcan be:

Linear

Quadratic

logarithmic


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The Diric Function

y = diric(x,n)

x = linspace(0,4*pi,300);

figure,plot(x,diric(x,7));

figure,plot(x,diric(x,8));

Matera 2k13 Ppts

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