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An impulse response, often denoted by h(t), is also called a transfer function or frequency response in frequency domain. It’s the output of In a LTI system when presented with a impulse signal input δ(t). In a LTI systems, impulse response is also equivalent to green’s function used in physics.
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[[Category:ECE301Spring2013JVK]] [[Category:ECE]] [[Category:ECE301]] [[Category:signalandsystems]] [[Category:problem solving]]
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[[Category:Impulse Response]]
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1.An impulse response, often denoted by h(t), is also called a transfer function or frequency response in frequency domain. It’s the output of In a LTI system when presented with a impulse signal input δ(t). In a LTI systems, impulse response is also equivalent to green’s function used in physics.
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General theory of nth order ODE:
 
General theory of nth order ODE:
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An nth order linear differential equation is an equation of the form
 
An nth order linear differential equation is an equation of the form
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[[Image:Equation1.png]]
 
[[Image:Equation1.png]]
 
   
 
   
 
Divide by Po(t) to get the following form
 
Divide by Po(t) to get the following form
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[[Image:Equation2.png]]
 
[[Image:Equation2.png]]
 
   
 
   
 
Has n initial conditions   
 
Has n initial conditions   
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[[Image:Equation3.png]]
 
[[Image:Equation3.png]]
  
 
A theorem states, if the functions p1, p2 …..,pn, and G are continuous on the open interval I, then there exists exactly one solution y = φ(t) of the differential equation (2) that also satisfies the initial conditions (3).
 
A theorem states, if the functions p1, p2 …..,pn, and G are continuous on the open interval I, then there exists exactly one solution y = φ(t) of the differential equation (2) that also satisfies the initial conditions (3).
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Source: Elementary differential eqution with boundary value problems  by William E boyce. Ricahrd DeDrima
 
Source: Elementary differential eqution with boundary value problems  by William E boyce. Ricahrd DeDrima
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[[Category:Fourier series]]
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2. Illustration of Gibbs phenomenon:
  
 
[[Image:bonus2matlab.png]]
 
[[Image:bonus2matlab.png]]
  
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The overshoot increases as the number of terms increases, but approachs a finite limit.
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Code:
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t=linspace(-2,2,2000);
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y=[sawtooth(-((t+1)*pi))];
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N=[25,50,150,500];
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for i=1:4;
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an=[];
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for m=1:N(i)
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an=[an,4*cos(m*pi/2)/(m*pi)];
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end;
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fn=0;
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for m=1:N(i)
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fn=fn+an(m)*sin(m*pi/2*t);
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end;
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subplot(2,2,i)
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plot(t,y,'LineWidth',2);
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hold on;
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plot(t,fn,'m','LineWidth',2);
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hold off;
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axis([-2 2 -1.5 1.5]);
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grid;
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xlabel('t'), ylabel('y(t)');title(['N = ',int2str(N(i))]);
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end;
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[[Category:FFT]]
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3. Spatial image filtering operations:
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[[Image:bonus2image.png]]
 
[[Image:bonus2image.png]]
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Code:
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clc
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clear all
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img = imread('Lena.jpg')
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f = fspecial('gaussian',[5 5],100);
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imgGaussian = imfilter(img,f);
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figure; imshow(img); title('Original');
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figure; imshow(imgGaussian); title('Blurred image')
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figure; surfc(f)
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s = fspecial('unsharp');
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imgSharp = imfilter(img, s);
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figure; imshow(imgSharp); title('Sharpened image')
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figure; surfc(s)
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[[ECE301bonus2|Back to the 2nd bonus point opportunity, ECE301 Spring 2013]]

Latest revision as of 23:38, 10 March 2013

1.An impulse response, often denoted by h(t), is also called a transfer function or frequency response in frequency domain. It’s the output of In a LTI system when presented with a impulse signal input δ(t). In a LTI systems, impulse response is also equivalent to green’s function used in physics.


General theory of nth order ODE:

An nth order linear differential equation is an equation of the form

Equation1.png

Divide by Po(t) to get the following form

Equation2.png

Has n initial conditions

Equation3.png

A theorem states, if the functions p1, p2 …..,pn, and G are continuous on the open interval I, then there exists exactly one solution y = φ(t) of the differential equation (2) that also satisfies the initial conditions (3).


Source: Elementary differential eqution with boundary value problems by William E boyce. Ricahrd DeDrima


2. Illustration of Gibbs phenomenon:

Bonus2matlab.png

The overshoot increases as the number of terms increases, but approachs a finite limit.

Code: t=linspace(-2,2,2000); y=[sawtooth(-((t+1)*pi))]; N=[25,50,150,500]; for i=1:4; an=[]; for m=1:N(i) an=[an,4*cos(m*pi/2)/(m*pi)]; end; fn=0; for m=1:N(i) fn=fn+an(m)*sin(m*pi/2*t); end; subplot(2,2,i) plot(t,y,'LineWidth',2); hold on; plot(t,fn,'m','LineWidth',2); hold off; axis([-2 2 -1.5 1.5]); grid; xlabel('t'), ylabel('y(t)');title(['N = ',int2str(N(i))]); end;


3. Spatial image filtering operations:

Bonus2image.png

Code: clc clear all img = imread('Lena.jpg') f = fspecial('gaussian',[5 5],100); imgGaussian = imfilter(img,f); figure; imshow(img); title('Original'); figure; imshow(imgGaussian); title('Blurred image') figure; surfc(f) s = fspecial('unsharp'); imgSharp = imfilter(img, s); figure; imshow(imgSharp); title('Sharpened image') figure; surfc(s)

Back to the 2nd bonus point opportunity, ECE301 Spring 2013

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Ph.D. 2007, working on developing cool imaging technologies for digital cameras, camera phones, and video surveillance cameras.

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