1. EE313 Linear Systems and Signals Fall 2010 Initial conversion of content to PowerPoint by Dr. Wade C. Schwartzkopf Prof. Brian L. Evans Dept. of Electrical and Computer Engineering The University of Texas at Austin Fourier Transform Properties

2. 13 - 2 0 1  /2-  /2 t f(t)f(t) 0   F()F()             Duality Forward/inverse transforms are similar Example: rect(t/  )   sinc(   / 2) Apply duality  sinc(t  /2)  2  rect(-  /  ) rect(·) is even  sinc(t  /2)  2  rect(  /  )

3. 13 - 3 Scaling Given and that a  0 |a| > 1: compress time axis, expand frequency axis |a| < 1: expand time axis, compress frequency axis Extent in time domain is inversely proportional to extent in frequency domain (a.k.a bandwidth) f(t) is wider  spectrum is narrower f(t) is narrower  spectrum is wider

4. 13 - 4 Shifting in Time Shift in time Does not change magnitude of the Fourier transform Shifts phase of Fourier transform by -  t 0 (so  t 0 is the slope of the linear phase) Derivation Let u = t – t 0, so du = dt and integration limits stay same

5. 13 - 5 Sinusoidal Amplitude Modulation

6. 13 - 6 Sinusoidal Amplitude Modulation Example: y(t) = f(t) cos(  0 t) f(t) is an ideal lowpass signal Assume  1 <<  0 Demodulation (i.e. recovery of f(t) from y(t)) is modulation followed by lowpass filtering Similar derivation for modulation with sin(  0 t) 0 1  --  F()F()  0 Y()Y()  -   -   -   +      F      -     +     F   

7. 13 - 7 Frequency-shifting Property

8. 13 - 8 Time Differentiation Property Conditions f(t)  0 when |t|   f(t) is differentiable Derivation of property: Given f(t)  F(  )

9. 13 - 9 Time Integration Property Example:

10. 13 - 10 Summary Definition of Fourier Transform Two ways to find Fourier Transform Use definition Use transform pairs and properties