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ANKUR JAIN MATLAB 0361563608

INTRODUCTION

The tutorials are independent of the rest of the document. The primarily objective is to help you learn

quicklythe rst steps. The emphasis here is \learning by doing". Therefore, the best way to learn is by

trying it yourself. Working through the examples will give you a feel for the way that MATLAB operates.

In this introduction we will describe how MATLAB handles simple numerical expressions andmathematical formulas.

The name MATLAB stands for MATrix LABoratory. MATLAB was written originally to provide easy access

to matrix software developed by the LINPACK (linear system package) and EISPACK (Eigen system

package) projects.

MATLAB [1] is a high-performance language for technical computing. It integrates computation,

visualization, andprogramming environment. Furthermore, MATLAB is a modern programming

language environment: it has sophisticated data structures, contains built-in editing and debugging

tools, and supports object-oriented programming. These factors make MATLAB an excellent tool for

teaching and research.

MATLAB has many advantages compared to conventional computer languages (e.g., C, FORTRAN) for

solving technical problems. MATLAB is an interactive system whose basic data element is an arraythatdoes not require dimensioning. The software package has been commercially available since 1984 and is

now considered as a standard tool at most universities and industries worldwide.

It has powerful built-in routines that enable a very wide variety of computations. It also has easy to use

graphics commands that make the visualization of results immediately available. Specic applications are

collected in packages referred to as toolbox. There are toolboxes for signal processing, symbolic

computation, control theory, simulation, optimization, and several other elds of applied science and

engineering.

In addition to the MATLAB documentation which is mostly available on-line, we would

1 recommend the following books: [2], [3], [4], [5], [6], [7], [8], and [9]. They are excellent in their

specic applications.

HISTORY

Version[17]

Release

nameYear Notes

MATLAB1.0

1984

MATLAB 2 1986

MATLAB 3 1987

MATLAB

3.5 1990Ran on MS-DOS but required at least a 386 processor. Version

3.5m required math coprocessor

MATLAB 4 1992

MATLAB

4.2cR7 1994 Ran on Windows 3.1. Required a math coprocessor

MATLAB

5.0R8 1996
http://en.wikipedia.org/wiki/MATLAB#cite_note-growth-16http://en.wikipedia.org/wiki/MATLAB#cite_note-growth-16http://en.wikipedia.org/wiki/MATLAB#cite_note-growth-16


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MATLAB5.1

R9

1997MATLAB

5.1.1R9.1

MATLAB

5.2 R101998

MATLAB

5.2.1R10.1

MATLAB5.3

R11

1999MATLAB

5.3.1R11.1

MATLAB

6.0R12 2000

MATLAB

6.1 R12.1 2001

MATLAB

6.5R13 2002

MATLAB

6.5.1R13SP1 2003

MATLAB

6.5.1R13SP1 2003

MATLAB

6.5.2R13SP2

MATLAB 7 R14 2004

MATLAB7.0.1

R14SP1

MATLAB

7.0.4R14SP2 2005

MATLAB7.1

R14SP3

MATLAB

7.2R2006a 2006

MATLAB

7.3R2006b

MATLAB

7.4R2007a 2007

MATLAB

7.5R2007b Last release for Windows 2000 and PowerPC Mac.

MATLAB

7.6R2008a 2008

MATLAB R2008b


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7.7

MATLAB

7.8R2009a 2009 First release for 32-bit & 64-bit Windows 7.

MATLAB

7.9R2009b First release for Intel 64-bit Mac, and last for Solaris SPARC.

MATLAB

7.10R2010a 2010 Last release for Intel 32-bit Mac.

MATLAB

7.11R2010b


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EXPERIMENT NO:-01

AIM:- TO STUDY AND GENERATE BASIC SIGNALS.

SOFTWARE USED: MATLAB

CODE:-

1. FOR COS SIGNALt=0:.01:pi;

y=cos(2*pi*t);

subplot(2,1,2);

plot(t,y);

ylabel('Amplitude');

xlabel('(b)n-->');

WAVEFORM OUTPUT

2. FOR SIN SIGNALt=0:.01:pi;

y=sin(2*pi*t);

subplot(2,1,2);

plot(t,y);

ylabel('Amplitude-->');

xlabel('(a)n-->');

0 0.5 1 1.5 2 2.5 3 3.5-1

-0.5

0

0.5

1

a

mplitude-->

(b)n-->


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WAVEFORM OUTPUT

3. FOR RAMP SIGNALn=input(enter the N values=);

enter the N values=6

t=0:n;

subplot(2,2,3);

stem(t,t);


xlabel('(c)n-->');

WAVEFORM OUTPUT

0 0.5 1 1.5 2 2.5 3 3.5-1

-0.5

0

0.5

1

Amplitude-->

(a)n-->

0 2 4 60

2

4

6

Amplitude-->

(c)n-->


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4.FOR UNIT STEP SIGNAL

n=input(enter the N values=);

enter the N values=4

t=0:1:n-1;

y1=ones(1,n);

subplot(2,2,2);

stem(t,y1);


xlabel('(d)n-->');

WAVEFORM OUTPUT

RESULT:- THE BASIC SIGNALS HAVE BEEN VERIFIED.

0 1 2 30

0.5

1

Amplitude-->

(d)n==>


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EXPERIMENT NO. 02

AIM:- TO STUDY AND GENERATE COMPLEX EXPONENTIAL SEQUENCE.

SOFTWARE USED:- MATLAB

CODE:-

a=input(Type in real complex exponential sequence=);

Type in real complex exponential sequence=4

b=input(Type in imaginary exponential sequence=);

Type in imaginary exponential sequence=10

C=a+b*I;

K=input(Type in the gain constant=);

Type in the gain constant=5

a=input(Type in the length of the sequence=);

Type in the length of the sequence=8

N=1:N;

X=K*exp(c*n);

Stem(n,real(x));

Xlabel(Time index n);

Ylabel(Amplitude);

title(Real part);

disp(press return for imginary part);

pause

stem(n,imag(x));

xlabel(Time index n);

ylabel(Amplitude);

title(imaginary part)


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WAVEFORM OUTPUT

RESULT:- COMPLEX EXPONENTIAL SEQUENCE HAS BEEN VERIFIED.

1 2 3 4 5 6 7 8-4.5

-4

-3.5

-3

-2.5

-2

-1.5

-1

-0.5

0

0.5x 10

13

Time index n

amplitude

Real Part

1 2 3 4 5 6 7 8

-4

-3.5

-3

-2.5

-2

-1.5

-1

-0.5

0

0.5x 10

14

Time index n

amplitude

imaginary part


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EXPERIMENT NO:-03

AIM:- TO STUDY AND GENERATE REAL EXPONENTIAL SEQUENCE.


CODE:-

a=input(Type in argument=);

Type in argument=3

K=input(Type in the gain constant=);

Type in the gain constant=1

N=input(Type in the lengthof sequence=);

Type in the lengthof sequence=2

n=0:N;

Stem(n,real(x));

Xlabel(Time index n);

Ylabel(Amplitude);

WAVEFORM OUTPUT

RESULT:- REAL EXPONENTIAL CODE HAS BEEN VERIFIED.

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 20

1

2

3

4

5

6

7

8

9

Type index n

Amplitude


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EXPERIMENT NO:- 04

AIM:- TO STUDY THE ILLUSTRATION OF CONVOLUTION.


CODE:-

a=input(Type in first sequence=);

Type in first sequence=2

b=input(Type in second sequence=);

Type in second sequence=4

C=conv(a,b);

M=length(c)-1;

n=0:1:M;

disp(output sequence=);

disp(c);

stem(n,c);


ylabel(Amplitude);

WAVEFORM OUTPUT :

RESULT:- CONVOLUTION HAS BEEN SUCCESSFULLY ILLUSTRATED.

-1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 10

1

2

3

4

5

6

7

8

Time index n

Amplitude


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EXPERIMENT NO:- 05

AIM:- TO STUDY AND COMPUTE THE CROSS CORRELATION SEQUENCE.


CODE:-

%computation of cross correlation

X=input(Type in the reference sequence=);

Type in the reference sequence=3

y=input(Type in the second sequence=);

Type in the second sequence=20

%computation of correlation sequence

n1=length(y)-1;

n2=length(x)-1;

r=conv(x,fliplr(y);

%fliplr:-Fliplr:-Flip matrices left-right [syntax B=fliplr(A)]

K=(-n1):n2;

Stem(k,r);

Xlabel(lag index);

Ylabel(amplitude);


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WAVEFORM OUTPUT

RESULT:- CROSS CORRELATION SEQUENCE HAS BEEN VERIFIED.

-1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 10

10

20

30

40

50

60

lag index

amplitude


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EXPERIMENT NO:- 06

AIM:- TO STUDY AND COMPUTE THE AUTO CORRELATION SEQUENCE.


CODE:-

N=96;

N=1:N;

x=cos(pi*0.25*n);

y=x+d;

r=conv(y,fliplr(y));

K=-28:28;

Stem(K,r(68:124));

Xlabel(lag index);

Ylabel(Amplitude);

WAVEFORM OUTPUT

RESULT:- THE AUTO CORRELATION SEQUENCE HAS BEEN VERIFIED.

-30 -20 -10 0 10 20 30-60

-40

-20

0

20

40

60

Lag index

Amplitude


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EXPERIMENT NO:- 07

AIM:-ILLUSTRATION OF IDFT COMPUTATION.


CODE:-

K=input(Type in the length of the DFT=);

Type in the length of the DFT=4

N=input(Type in the length of the IDFT=);

Type in the length of the IDFT=7

k=0:K-1;

V=k/K;

V=ifft(V,N);

Stem(k,V);

title(original DFT sample);


ylabel(Amplitude);

pause

subplot(2,1,1);

n=0:N-1;

stem(n,real(v));

title(real part of the time-domain samples);

xlabel(time index n);

ylabel(Amplitude);

subplot(2,1,2);

stem(n,imag(v));

title(imaginary part of the domain samples);


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ylabel(Amplitude);

WAVEFORM OUTPUT

RESULT:- IDFT HAS BEEN COMPUTED.

0 0.5 1 1.5 2 2.5 30

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8original DFT sample

Time index n

Amplitude

0 1 2 3 4 5 6-0.1

0

0.1

0.2

0.3real part of the time-domain samples

time index n

Amplitud

e

0 1 2 3 4 5 6-0.2

-0.1

0

0.1

0.2imaginary part of the time domain samples

Time index n

Am

plitude


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EXPERIMENT NO:- 08

AIM:- TO FIND THE MAGNITUDE AND PHASE ANGLE OF A SEQUENCE.


CODE:-

a=[1 -0.9 0.81];

b=[1 1];

w=(0:500)*(pi/500);

x=freqz(b,a,w);

mag=abs(x);

phase=angle(x)*180/pi;

subplot(2,1,1);

plot(mag);

gtext(magnitude);

subplot(2.1.1);

plot(phase);

gtext(phase angle);

WAVEFORM OUTPUT

RESULT:- MAGNITUDE AND PHASE ANGLE HAVE BEEN DETERMINED.

0 100 200 300 400 500 6000

5

10

15

magnitude

0 100 200 300 400 500 600-150

-100

-50

0

50

phase angle


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EXPERIMENT NO:- 09

AIM:- TO FIND THE DFT OF A GIVEN SEQUENCE.


CODE:-

N=input(Type in the length of sequence=);

Type in the length of sequence=4

M=input(Type in the length of DFT=);

Type in the length of DFT=7

u=[ones(1,N)];

U=fft(u,M);

t=0:1:N-1;

stem(t,u);

title(original time domain sequence);


ylabel(Amplitude);

pause

subplot(2,1,1);

k=0:1:M-1;

stem(k,abs(U));

title(mag of the DFT samples);

xlabel(Frequency index k);

ylabel(Magnitude);

subplot(2,1,2);

stem(k.angle(U));

title(phase of the DFT samples);


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xlabel(Frequency index k);

ylabel(phase);

WAVEFORM OUTPUT

RESULT:- THE DFT OF THE GIVEN SEQUENCE HAS BEEN DETERMINED.

0 0.5 1 1.5 2 2.5 30

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1original t ime domain sequence

Time index n

Amplitude

0 1 2 3 4 5 60

1

2

3

4mag of the DFT samples

Frequency index k

Magnitude

0 1 2 3 4 5 6-2

-1

0

1

2phase of the DFT samples

Frequency index k

phase


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INDEX

S.NO TOPIC DATE SIGNATURE

1TO STUDY AND GENERATE BASICSIGNALS.

2

TO STUDY AND GENERATE COMPLEX

EXPONENTIAL SEQUENCE.

3

TO STUDY AND GENERATE REAL

EXPONENTIAL SEQUENCE.

4

TO STUDY THE ILLUSTRATION OF

CONVOLUTION.

5

STUDY AND COMPUTE THE CROSS

CORRELATION SEQUENCE.

6

TO STUDY AND COMPUTE THE AUTO

CORRELATION SEQUENCE.

7

ILLUSTRATION OF IDFT

COMPUTATION.

8 TO FIND THE MAGNITUDE AND PHASEANGLE OF A SEQUENCE.

9 TO FIND THE DFT OF A GIVENSEQUENCE.


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MATLAB

PRACTICAL FILE

SUBMITTED BY:

NAME: ANKUR JAIN

BRANCH: MAE IIIRD YEAR

ROLL NO: 0361563608

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