Digital Signal Processing Prof Nizamettin AYDIN naydinyildiz edu

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

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

Digital Signal Processing Lecture 20 Fourier Transform Properties 2

Digital Signal Processing Lecture 20 Fourier Transform Properties 2

READING ASSIGNMENTS • This Lecture: – Chapter 11, Sects. 11 -5 to 11 -9

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)

LECTURE OBJECTIVES • The Fourier transform • More examples of Fourier transform pairs •

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

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

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

WHY use the Fourier transform? • Manipulate the “Frequency Spectrum” • Analog Communication Systems

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)

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

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

Table of Fourier Transforms

Table of Fourier Transforms

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

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

Square Wave Signal

Square Wave Signal

Square Wave Fourier Transform

Square Wave Fourier Transform

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

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

Scaling Property

Scaling Property

Scaling Property

Scaling Property

Uncertainty Principle • Try to make x(t) shorter – Then X(jw) will get wider

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

Significant FT Properties Differentiation Property

Significant FT Properties Differentiation Property

Convolution Property • Convolution in the time-domain corresponds to MULTIPLICATION in the frequencydomain

Convolution Property • Convolution in the time-domain corresponds to MULTIPLICATION in the frequencydomain

Convolution Example • Bandlimited Input Signal – “sinc” function • Ideal LPF (Lowpass Filter)

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

Ideally Bandlimited Signal

Ideally Bandlimited Signal

Convolution Example

Convolution Example

Cosine Input to LTI System

Cosine Input to LTI System

Ideal Lowpass Filter

Ideal Lowpass Filter

Ideal Lowpass Filter

Ideal Lowpass Filter

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

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

Frequency Shifting Property

Frequency Shifting Property

Differentiation Property Multiply by jw

Differentiation Property Multiply by jw