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::<math>\bold {T\to\infty}</math>
::<math>\bold {T\to\infty}</math>
The summation becomes integration, the harmoinic frequency becomes a continuous frequency, and the incremental spacing becomes a differential separation.  
The summation becomes integration, the harmoinic frequency becomes a continuous frequency, and the incremental spacing becomes a differential separation.  
::<math> {sum_k=-\infty}^\infty\to\int_{-\infty}^\infty</math>
::<math> {\sum_{k=-\infty}^\infty\to\int_{-\infty}^\infty</math>

Revision as of 22:12, 13 October 2005

Welcome to Gabriela's Wiki page

Introduction

Do you want to know how to contact me or find out some interesting things about me? [[1]]

Signals & Systems

Example

Find the first two orthogonormal polynomials on [-1,1]

1. What is orthogonormal? [2]

2. What is orthogonal? [3]

3. What is a polynomial? [4]

        a
        bt+c

4. Now we can find the values for the unknown variables.

<a|a>=11aadt=1
a=12


<bt+c|a>=11a(bt+c)dt=0
c=0
<bt+c|bt+c>=11(bt+c)2dt=1
b=(32)


5. Now that we know what the first two orthogonormal polynomials!

Fourier Transform

As previously discussed, Fourier series is an expansion of a periodic function therefore we can not use it to transform a non-periodic funciton from time to the frequency domain. Fortunately the Fourier transform allows for the transformation to be done on a non-periodic function.


In order to understand the relationship between a non-periodic function and it's counterpart we must go back to Fourier series. Remember the complex exponential signal? [5]

x(t)=x(t+T)=k=αkej2πktT

where

αk=1/TT2T2x(t)ej2πktT,dt

If we let

T

The summation becomes integration, the harmoinic frequency becomes a continuous frequency, and the incremental spacing becomes a differential separation.

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