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Advanced Digital Signal Processing

Advanced Digital Signal Processing. Prof. Nizamettin AYDIN naydin @ yildiz .edu.tr http:// www . yildiz .edu.tr/~naydin. Introduction to the Fourier Transform. Review Frequency Response Fourier Series Definition of Fourier transform Relation to Fourier Series

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Advanced Digital Signal Processing

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  1. Advanced Digital Signal Processing Prof. Nizamettin AYDIN naydin@yildiz.edu.tr http://www.yildiz.edu.tr/~naydin

  2. Introduction to the Fourier Transform

  3. Review • Frequency Response • Fourier Series • Definition of Fourier transform Relation to Fourier Series • Examples of Fourier transform pairs

  4. Everything = Sum of Sinusoids • One Square Pulse = Sum of Sinusoids • ??????????? • Finite Length • Not Periodic • Limit of Square Wave as Period  infinity • Intuitive Argument

  5. Fourier Series: Periodic x(t) Fourier Synthesis Fourier Analysis

  6. Square Wave Signal

  7. Spectrum from Fourier Series

  8. What if x(t) is not periodic? • Sum of Sinusoids? • Non-harmonically related sinusoids • Would not be periodic, but would probably be non-zero for all t. • Fourier transform • gives a “sum” (actually an integral) that involves ALL frequencies • can represent signals that are identically zero for negative t. !!!!!!!!!

  9. Limiting Behavior of FS T0=2T T0=4T T0=8T

  10. Limiting Behavior of Spectrum T0=2T T0=4T T0=8T

  11. FS in the LIMIT (long period) Fourier Synthesis Fourier Analysis

  12. Fourier Transform Defined • For non-periodic signals Fourier Synthesis Fourier Analysis

  13. Example 1:

  14. Frequency Response • Fourier Transform of h(t) is the Frequency Response

  15. Magnitude and Phase Plots

  16. Example 2:

  17. Example 3:

  18. Example 4: Shifting Property of the Impulse

  19. Example 5:

  20. Table of Fourier Transforms

  21. Fourier Transform Properties

  22. The Fourier transform • More examples of Fourier transform pairs • Basic properties of Fourier transforms • Convolution property • Multiplication property

  23. Fourier Transform Fourier Synthesis (Inverse Transform) Fourier Analysis (Forward Transform)

  24. WHY use the Fourier transform? • Manipulate the “Frequency Spectrum” • Analog Communication Systems • AM: Amplitude Modulation; FM • What are the “Building Blocks” ? • Abstract Layer, not implementation • Ideal Filters: mostly BPFs • Frequency Shifters • aka Modulators, Mixers or Multipliers: x(t)p(t)

  25. Frequency Response • Fourier Transform of h(t) is the Frequency Response

  26. Table of Fourier Transforms

  27. Fourier Transform of a General Periodic Signal • If x(t) is periodic with period T0 ,

  28. Square Wave Signal

  29. Square Wave Fourier Transform

  30. Table of Easy FT Properties Linearity Property Delay Property Frequency Shifting Scaling

  31. Scaling Property

  32. Scaling Property

  33. Uncertainty Principle • Try to make x(t) shorter • Then X(jw) will get wider • Narrow pulses have wide bandwidth • Try to make X(jw) narrower • Then x(t) will have longer duration • Cannot simultaneously reduce time duration and bandwidth

  34. Significant FT Properties Differentiation Property

  35. Convolution Property • Convolution in the time-domain corresponds to MULTIPLICATION in the frequency-domain

  36. Convolution Example • Bandlimited Input Signal • “sinc” function • Ideal LPF (Lowpass Filter) • h(t) is a “sinc” • Output is Bandlimited • Convolve “sincs”

  37. Ideally Bandlimited Signal

  38. Convolution Example

  39. Cosine Input to LTI System

  40. Ideal Lowpass Filter

  41. Ideal Lowpass Filter

  42. Signal Multiplier (Modulator) • Multiplication in the time-domain corresponds to convolution in the frequency-domain.

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