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*[[Signals and systems|Signals and Systems]]
==An Introduction to the Fourier Transform==
 
A Fourier Transform is a representation of a function using a large number of sinusoids added together to create it.
 
For example, a square wave could be represented by:
<math>x_{\mathrm{square}}(t) = \frac{4}{\pi} \sum_{k=1}^\infty {\sin{\left ((2k-1)2\pi ft \right )}\over(2k-1)} </math>
 
X(f)=\int_{-\infty}^{\infty} x(t) e^{-j2\pi ft}\, dt
 
</math>
<br>
<br>
Suppose that we have some function, say <math> \beta (t) </math>, that is nonperiodic and finite in duration.<br>
This means that <math> \beta(t)=0 </math> for some <math> T_\alpha < \left | t \right | </math>
<br><br>
Now let's make a periodic function
<math>
\gamma(t)
</math>
by repeating
<math>
\beta(t)
</math>
with a fundamental period
<math>
T_\zeta
</math>.
Note that
<math>
\lim_{T_\zeta \to \infty}\gamma(t)=\beta(t)
</math>
<br>
The Fourier Series representation of <math> \gamma(t) </math> is
<br>
<math>
\gamma(t)=\sum_{k=-\infty}^\infty \alpha_k e^{j2\pi fkt}
</math>
where
<math>
f={1\over T_\zeta}
</math>
<br>and
<math>
\alpha_k={1\over T_\zeta}\int_{-{T_\zeta\over 2}}^{{T_\zeta\over 2}} \gamma(t) e^{-j2\pi kt}\,dt
</math>
<br>
<math> \alpha_k </math> can now be rewritten as
<math>
\alpha_k={1\over T_\zeta}\int_{-\infty}^{\infty} \beta(t) e^{-j2\pi kt}\,dt
</math>
<br>From our initial identity then, we can write <math> \alpha_k </math> as
<math>
\alpha_k={1\over T_\zeta}\Beta(kf)
</math>
<br> and
<math>
\gamma(t)
</math>
becomes
<math>
\gamma(t)=\sum_{k=-\infty}^\infty {1\over T_\zeta}\Beta(kf) e^{j2\pi fkt}
</math>
<br>
Now remember that
<math>
\beta(t)=\lim_{T_\zeta \to \infty}\gamma(t)
</math>
and
<math>
{1\over {T_\zeta}} = f.
</math>
<br>
Which means that
<math>
\beta(t)=\lim_{f \to 0}\gamma(t)=\lim_{f \to 0}\sum_{k=-\infty}^\infty f \Beta(kf) e^{j2\pi fkt}
</math>
<br>
Which is just to say that
<math>
\beta(t)=\int_{-\infty}^\infty \Beta(f) e^{j2\pi fkt}\,df
</math>
<br>
<br>
So we have that
<math>
\mathcal{F}[\beta(t)]=\Beta(f)=\int_{-\infty}^{\infty} \beta(t) e^{-j2\pi ft}\, dt
</math>
<br>
Further
<math>
\mathcal{F}^{-1}[\Beta(f)]=\beta(t)=\int_{-\infty}^\infty \Beta(f) e^{j2\pi fkt}\,df
</math>
==Some Useful Fourier Transform Pairs==
<math>
\mathcal{F}[\alpha(t)]=\frac{1}{\mid \alpha \mid}f(\frac{\omega}{\alpha})
</math>
<br>
{|
|-
|<math>\mathcal{F}[c_1\alpha(t)+c_2\beta(t)]</math>
|<math>=\int_{-\infty}^{\infty} (c_1\alpha(t)+c_2\beta(t)) e^{-j2\pi ft}\, dt</math>
|-
|
|<math>=\int_{-\infty}^{\infty}c_1\alpha(t)e^{-j2\pi ft}\, dt+\int_{-\infty}^{\infty}c_2\beta(t)e^{-j2\pi ft}\, dt</math>
|-
|
|<math>=c_1\int_{-\infty}^{\infty}\alpha(t)e^{-j2\pi ft}\, dt+c_2\int_{-\infty}^{\infty}\beta(t)e^{-j2\pi ft}\, dt=c_1\Alpha(f)+c_2\Beta(f)</math>
|-
|}
<br>
<math>
\mathcal{F}[\alpha(t-\gamma)]=e^{-j2\pi f\gamma}\Alpha(f)
</math>
<br>
<math>
\mathcal{F}[\alpha(t)*\beta(t)]=\Alpha(f)\Beta(f)
</math>
<br>
<math>
\mathcal{F}[\alpha(t)\beta(t)]=\Alpha(f)*\Beta(f)
</math>
<br>
Some other usefull pairs can be found here: [[Fourier Transforms]]
 
==A Second Approach to Fourier Transforms==
*[[Fourier Transforms]]

Revision as of 18:48, 8 October 2007

An Introduction to the Fourier Transform

A Fourier Transform is a representation of a function using a large number of sinusoids added together to create it.

For example, a square wave could be represented by: xsquare(t)=4πk=1sin((2k1)2πft)(2k1)

X(f)=\int_{-\infty}^{\infty} x(t) e^{-j2\pi ft}\, dt

</math>

Suppose that we have some function, say β(t), that is nonperiodic and finite in duration.
This means that β(t)=0 for some Tα<|t|

Now let's make a periodic function γ(t) by repeating β(t) with a fundamental period Tζ. Note that limTζγ(t)=β(t)
The Fourier Series representation of γ(t) is
γ(t)=k=αkej2πfkt where f=1Tζ
and αk=1TζTζ2Tζ2γ(t)ej2πktdt
αk can now be rewritten as αk=1Tζβ(t)ej2πktdt
From our initial identity then, we can write αk as αk=1TζB(kf)
and γ(t) becomes γ(t)=k=1TζB(kf)ej2πfkt
Now remember that β(t)=limTζγ(t) and 1Tζ=f.
Which means that β(t)=limf0γ(t)=limf0k=fB(kf)ej2πfkt
Which is just to say that β(t)=B(f)ej2πfktdf

So we have that [β(t)]=B(f)=β(t)ej2πftdt
Further 1[B(f)]=β(t)=B(f)ej2πfktdf

Some Useful Fourier Transform Pairs

[α(t)]=1αf(ωα)

[c1α(t)+c2β(t)] =(c1α(t)+c2β(t))ej2πftdt
=c1α(t)ej2πftdt+c2β(t)ej2πftdt
=c1α(t)ej2πftdt+c2β(t)ej2πftdt=c1A(f)+c2B(f)


[α(tγ)]=ej2πfγA(f)
[α(t)*β(t)]=A(f)B(f)
[α(t)β(t)]=A(f)*B(f)
Some other usefull pairs can be found here: Fourier Transforms

A Second Approach to Fourier Transforms