(New page: 4.1 ==Continuous Time Fourier Transform Pair for Aperiodic and Periodic Signals== ::<math> x(t) = \frac{1}{2\pi}\int_{-\infty}^{\infty} X(j \omega) e^{j\omega t} \, d\omega </math> (4.8...)
 
(Properties of CT Fourier Transforms)
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===Duality===
 
===Duality===
 
===Parseval's Relation===
 
===Parseval's Relation===
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===Convolution===
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===Multiplication===
  
 
Lecture 15: Sections 4.2-4.7.
 
Lecture 15: Sections 4.2-4.7.

Revision as of 14:02, 24 October 2008

4.1

Continuous Time Fourier Transform Pair for Aperiodic and Periodic Signals

$ x(t) = \frac{1}{2\pi}\int_{-\infty}^{\infty} X(j \omega) e^{j\omega t} \, d\omega $ (4.8)
$ X(j\omega) = \int_{-\infty}^{\infty} x(t) e^{-j\omega t} \, dt $ (4.9)

The Fourier transform exists if the signal is absolutely integrable or if the signal has a finite number of discontinuities within any finite interval. (See Page 290)

Fourier Transform from the Fourier Series

This is useful for signals that fail to satisfy the previous properties of a signal that is guaranteed a Fourier Transform.

A signal represented as the sum of complex exponentials:

$ x(t) = \sum_{k = -\infty}^{+\infty} a_ke^{jk\omega_0t} $

with ak's:

$ a_k = \frac{1}{T}\int_{T} x(t)e^{-jk\omega_0 t} \, dt $

$ \xrightarrow{\mathcal{F}} $

$ X(j\omega) = \sum_{k = -\infty}^{+\infty} 2\pi a_k \delta(\omega - k\omega_0) $


Properties of CT Fourier Transforms

Linearity

Time Shifting

Conjugation and Conjugate Symmetry

Differentiation and Integration

Time and Frequency Scaling

Quiz?

Duality

Parseval's Relation

Convolution

Multiplication

Lecture 15: Sections 4.2-4.7. Lecture 16: Lecture 17: Lecture 18: October break-no classes Lecture 11: Sections 4.0-4.1 Lecture 12: Sections 4.2-4.4. 4.7 Lecture 13: Sections 4.5-4.7. Lecture 14: Sections 5.0-5.3. Lecture 15: Sections 5.4-5.5, 5.8

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