ECE 8443 – Pattern Recognition EE 3512 – Signals: Continuous and Discrete Objectives: Linearity Time Shift and Time Reversal Multiplication Integration.

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Presentation transcript:

ECE 8443 – Pattern Recognition EE 3512 – Signals: Continuous and Discrete Objectives: Linearity Time Shift and Time Reversal Multiplication Integration Convolution Parseval’s Theorem Duality Resources: BEvans: Fourier Transform Properties MIT 6.003: Lecture 8 DSPGuide: Fourier Transform Properties Wiki: Audio Timescale Modification ISIP: Spectrum Analysis BEvans: Fourier Transform Properties MIT 6.003: Lecture 8 DSPGuide: Fourier Transform Properties Wiki: Audio Timescale Modification ISIP: Spectrum Analysis LECTURE 10: FOURIER TRANSFORM PROPERTIES URL:

EE 3512: Lecture 10, Slide 1 The Fourier Transform

EE 3512: Lecture 10, Slide 2 Example: Cosine Function See “The Fourier TransformSee “The Fourier Transform”

EE 3512: Lecture 10, Slide 3 Example: Periodic Pulse Train Note: Since this is a periodic signal, we use a Fourier series to compose the signal as a sum of complex exponentials. Then we take the Fourier transform of each complex exponential.

EE 3512: Lecture 10, Slide 4 Recall our expressions for the Fourier Transform and its inverse: The property of linearity: Proof: Linearity (synthesis) (analysis)

EE 3512: Lecture 10, Slide 5 Time Shift: Proof: Note that this means time delay is equivalent to a linear phase shift in the frequency domain (the phase shift is proportional to frequency). We refer to a system as an all-pass filter if: Phase shift is an important concept in the development of surround sound. Time Shift

EE 3512: Lecture 10, Slide 6 Time Scaling: Proof: Generalization for a < 0, the negative value is offset by the change in the limits of integration. What is the implication of a 1? Any real-world applications of this property? Hint: sampled signals.78 Time Scaling

EE 3512: Lecture 10, Slide 7 Time Reversal: Proof: We can also note that for real-valued signals: Time reversal is equivalent to conjugation in the frequency domain. Can we time reverse a signal? If not, why is this property useful? Time Reversal

EE 3512: Lecture 10, Slide 8 Multiplication by a power of t: Proof: We can repeat the process for higher powers of t. Multiplication by a Power of t

EE 3512: Lecture 10, Slide 9 Multiplication by a complex exponential: Proof: Why is this property useful? First, another property: This produces a translation in the frequency domain. How might this be useful in a communication system? Multiplication by a Complex Exponential (Modulation)

EE 3512: Lecture 10, Slide 10 Differentiation in the Time Domain: Integration in the Time Domain: What are the implications of time-domain differentiation in the frequency domain? Why might this be a problem? Hint: additive noise. How can we apply these properties? Hint: unit impulse, unit step, … Differentiation / Integration

EE 3512: Lecture 10, Slide 11 Convolution in the time domain: Proof: Convolution in the Time Domain

EE 3512: Lecture 10, Slide 12 Multiplication in the time domain: Parseval’s Theorem: Duality: Note: please read the textbook carefully for the derivations and interpretation of these results. Other Important Properties

EE 3512: Lecture 10, Slide 13 Summary