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Prof. Nizamettin AYDIN Digital Signal Processing 1.

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Presentation on theme: "Prof. Nizamettin AYDIN Digital Signal Processing 1."— Presentation transcript:

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

2 Lecture 20 Fourier Transform Properties Digital Signal Processing 2

3 License Info for SPFirst Slides This work released under a Creative Commons License with the following terms:Creative Commons License Attribution The licensor permits others to copy, distribute, display, and perform the work. In return, licensees must give the original authors credit. Non-Commercial The licensor permits others to copy, distribute, display, and perform the work. In return, licensees may not use the work for commercial purposes — unless they get the licensor's permission. Share Alike The licensor permits others to distribute derivative works only under a license identical to the one that governs the licensor's work. Full Text of the License This (hidden) page should be kept with the presentation

4 READING ASSIGNMENTS This Lecture: –Chapter 11, Sects. 11-5 to 11-9 –Tables in Section 11-9 Other Reading: –Recitation: Chapter 11, Sects. 11-1 to 11-9 –Next Lectures: Chapter 12 (Applications)

5 LECTURE OBJECTIVES The Fourier transform More examples of Fourier transform pairs Basic properties of Fourier transforms –Convolution property –Multiplication property

6 Fourier Transform Fourier Analysis (Forward Transform) Fourier Synthesis (Inverse Transform)

7 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)

8 Frequency Response Fourier Transform of h(t) is the Frequency Response

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12 Table of Fourier Transforms

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14 Fourier Transform of a General Periodic Signal If x(t) is periodic with period T 0,

15 Square Wave Signal

16 Square Wave Fourier Transform

17 Table of Easy FT Properties Delay Property Frequency Shifting Linearity Property Scaling

18 Scaling Property

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20 Uncertainty Principle Try to make x(t) shorter –Then X(j  ) will get wider –Narrow pulses have wide bandwidth Try to make X(j  ) narrower –Then x(t) will have longer duration Cannot simultaneously reduce time duration and bandwidthCannot simultaneously reduce time duration and bandwidth

21 Significant FT Properties Differentiation Property

22 Convolution Property Convolution in the time-domain MULTIPLICATION corresponds to MULTIPLICATION in the frequency- domain

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

24 Ideally Bandlimited Signal

25 Convolution Example

26 Cosine Input to LTI System

27 Ideal Lowpass Filter

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

30 Frequency Shifting Property

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32 Differentiation Property Multiply by j 

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34 Delay Property

35 Strategy for using the FT Develop a set of known Fourier transform pairs. Develop a set of “theorems” or properties of the Fourier transform. Develop skill in formulating the problem in either the time-domain or the frequency- domain, which ever leads to the simplest solution.

36 FT of Impulse Train The periodic impulse train is

37 Convolution Example 2


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