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Matlab programing
M.C Saul Cantu
- Introduction to Matlab
- Variables
- Arrays
- Matrix
- Sumatory and Series
- Fourier Series
- Fourier Transformation
- Digital Signal Procesing
- Digital Image Procesing
Matlab= Matrix Laboratory
Libro:
Matlab y sus aplicaciones para la Ingenieria
David Baez.
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1 2 3 4 5 matrix 3x4
5 6 7 8 9 RAWS
10 11 12 13
COLUMNS
List Directory
>>ls
>>helpls
>>pwd
C:\users\matlab\work
>>clc
>>clear all
>>a
a is empty
>>3+2
Ans=5
>>3*2
Ans= 6
>>3/2
Ans= 1.5
>>32
Ans= 9
>>t=-2:0.001:2;
>> x=5*cos(4*pi*t)
>>plot(t,x)
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>>grid
>>t=0:0.001:5;
>>x=exp(-t);
>>plot(t,x)
>>grid
>>t=0:0.001:10
X=sawtooth
DC Component
X=0.5+0.5sawtooth(2*pi*t)
X=0.5+0.5square(2*pi*t)
X=0.5+0.2square(2*pi*t,80)
Vector X Vector = v.*v
General Formula-excos(2ft+)
Figure Another Window
>>t=0:0.001:5;
>>m=[1+0.5*sin(2*pi*t)];
>>c=cos(40*pi*t);
>>s=m*c
>>plot(t,m)
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>>grid
>>figure
>>plot(t,c)
>>grid
>>figure
>>plot(t,s)
>>grid
--------------------------------------------------------------------------------------------------------------
HOMEWORK
Amplitude modulation is defined as the multiplication of one time-domain signal byanother time-domain signal. The signals may or may not be complex in nature, i.e.,either or both signals may contain harmonics components. It is impossible tohave amplitude modulation unless at least two different signals are involved. Thesignals may be electrical in nature, or they can bevibration signals. Modulation isinherently a non-linear process, and always gives rise to frequency componentsthat did not exist in either of the two original signals
Amplitude Modulated Wave FormIf the amplitude-modulated signal shown here is passed through
a frequency analyzer, the following spectrum is the result. The highest peak isthe carrier frequency. The right-hand peakis the upper sideband, and hasa frequency of the carrier frequency plus the modulating frequency. The left-hand peak or lower sideband has a frequency of the carrier minus themodulating frequency. The sidebands are sometimes called sum and differencefrequencies because of their symmetrical spacing around the carrier.
Amplitude modulation also occurs in sound reproducing equipment, where it iscalled Intermodulation Distortion. The sum and difference frequencies are not in
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musical harmony with the tones that cause them, making intermodulation aparticularly noticeable form of sound distortion.
Spectrum of Modulated Wave Form
Rectified Wave Form
Recovered Modulating Signal
This process of demodulation is exactly what happens in an AM radio -- the carrieris a very high frequency signal generated by the radio station, and themodulating signal is the voice or music that constitutes the program. The radio
receives the modulated carrier, amplifies it, and rectifies (detects) it to recover theprogram.
AM SIGNAL
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FM SIGNAL
>>t=0:0.001:5;>>m=10*cos(2*pi*t)>>c=cos(20*pi*t)>>plot(t,m)>>grid>>figure>>plot(t,c)>>s=cos(20*pi*t*tm)>>plot(t,s)
Hold on: to unit 2 graphics
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With sawtooth
Frecuency= dfase/t
Cardinal sin
Sin(t)=sin2/t.
HOMEWORK
(100)(101)/2=5050
>>n=0;>>for k=1:100>>n=n+k;End>>n
5050
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SERIES
1+2+3+4n
FIBONACCI SERIE
0,1,1,2,3,4,5,8,13,21
FOURIER SERIE
Sinx= () ()
Cosx= () ()
Ex=
HOMEWORKFibonacci Serie
>>x(1)=0;>>x(2)=1;>>for i=3:20>>x(i)=x(i-1)+X(i-2)>>end>>x
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EULER IDENTIES
cos jsin
Cos=
Sin
FOURIER SERIES
The sumatory of all frecuencies are iqual to the total frecuency.
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Example:Make a matlab program to compute the Fourier serie of
X(t)=1v; x=0>>for k=1:2:3>>x=x+(4/(pi*k).*sin(2*pi*k*t)>>end>>plot(t,x)>>grid
EXPONENCIAL SERIE
>>x=1>>e=1>>for n=1:10E=e+(xn)/prod(1:n)>>end>>e
>>y=1
>>x=1>>for n=1:10>>y=y+[(-1)n(n-1)*[x(2n-1)]/prod(2n-1)>>End>>y
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FOURIER TRANSFORMATION
x(t)= ()
rect=1;-1/2> f=-10;0.001:10
>>xf=0j
>>for t=-.5:0.01:0.5
xF=xF+1*exp(-j*2*pi*f*t)
end
>>plot(xF,f)
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EXAMPLE
>>f=-10:.001:10
>>xF=0;
>>for t=-10:.01:10;
xF=xF+cos(4*pi*t),*exp(-j*2*pi*f*t)
>>end
>>plot(F,xF)
RECTANGULAR PULSE
>>rectpuls()
>>t=-5:0.001:5
>>x=rectpuls(1/2);
>>plot(t,x)
>>x=rectpuls(2*t)
TRIANGULAR PULSE
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>>t=-1:0.001:1>>x=tripuls(t2)>>plot(t,x)
GAUSS PULSE
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DIGITAL PROCESSING
>>sound(y)aleluya
>>sound(y,Fs/2)
low>>soun(y,Fa*2)fast>>sound(y(1:2:end),Fs/2)Normal
X=size(y)Z=zeros(2*x,1)
[x,fs,b]>>sound(x,fs,b)>>z=repeat(x,2,2)
>>z=repeat(x,2,1)>>sound(z,Fs,b)
RESULTANT
>>fs=11025;>>[x,fs]=wavread(violin.wav);>>[y,fs]=wavread(cello.wav);>>size(x)
7302123
>>size(y)436224>>x=x(1:436224,2)>>y=y(1:436224,2);>>x=x(1:436224,1);>>reslultant=[x,y]>>sound(resultant,fs);End
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IMAGE PROCESSING
0black
1..254255white
EXAMPLE
>>f=0:255>>f=repmat(f,256,1);
>>size(f)256 256>>imshow(f)>>whos fName size bytes class attributesF 256x256 52428 double>>imshow(f)>>f=uint8(f);>>who fName size bytes class attributesF 256x256 uint8
>>f=imread(rose_512.lif)>>imshowf
HOMEWORK>>f=zeros(256);>>imshow(f)>>f=(1:end,128)=1;>>(128,1:end)=1;Imshow f>>for x=1:128>>for (x,x)=1;
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UNIVERSIDAD AUTONOMA DE NUEVO LEO
FACULTAD DE INGENIERIA MECANICA Y ELECTRICA
MATLAB PROGRAMING
ING. SAUL CANTU
NOMBRE: FELIPE ANTONIO VAZQUEZ GOVEA
MATRICULA: 1299592
SALON: 7204
DIA: 6
12 DE ABRIL DEL 2013
SAN NICOLAS DE LOS GARZA NUEVO LEON
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