Fourier Transform Basics
Learn about Fourier transform of waveforms, Parseval’s Theorem, Dirac Delta Function, Rectangular and Triangular Pulses, Convolution, and more. Explanation of properties, techniques, conditions, and spectral components.
Fourier Transform Basics
E N D
Presentation Transcript
Chapter 2 Fourier Transform and Spectra Topics: • Fourier transform (FT) of a waveform • Properties of Fourier Transforms • Parseval’s Theorem and Energy Spectral Density • Dirac Delta Function and Unit Step Function • Rectangular and Triangular Pulses • Convolution Erhan A. Ince Eeng360 Communication Systems I Department of Electrical and Electronic Engineering Eastern Mediterranean University
Fourier Transform of a Waveform • Definition: Fourier transform The Fourier Transform(FT) of a waveform w(t)is: where ℑ[.] denotes the Fourier transform of [.] f is the frequency parameter with units of Hz (1/s). • W(f) is also called two-sided spectrum of w(t), since both positive and negative frequency components are obtained from the definition
Evaluation Techniques for FT Integral • One of the following techniques can be used to evaluate a FT integral: • Direct integration. • Tables of Fourier transforms or Laplace transforms. • FT theorems. • Superposition to break the problem into two or more simple problems. • Differentiation or integration of w(t). • Numerical integration of the FT integral on the PC via MATLAB or MathCAD integration functions. • Fast Fourier transform (FFT) on the PC via MATLAB or MathCAD FFT functions.
Fourier Transform of a Waveform • Definition: Inverse Fourier transform The waveform w(t) can be obtained from the spectrum via the inverse Fourier transform(IFT) : • The functions w(t) and W(f)constitute a Fourier transform pair. Frequency Domain Description (FT) Time Domain Description (Inverse FT)
Quadrature components Phasor components
Fourier Transform - Sufficient Conditions • The waveform w(t) is Fourier transformable if it satisfies the Dirichlet conditions: • Over any time interval of finite length, the function w(t) is single valued with a finite number of maxima and minima, and the number of discontinuities (if any) is finite. • w(t) is absolutely integrable. That is, • Above conditions are sufficient, but not necessary. • A weaker sufficient condition for the existence of the Fourier transform is: Finite Energy • where E is the normalized energy. • This is the finite-energy condition that is satisfied by all physically realizable waveforms. • Conclusion:All physical waveforms encountered in engineering practice are Fourier transformable.
1 -1
Properties of Fourier Transforms asterisk denotes conjugate operation. • Theorem : Spectral symmetry of real signals If w(t) is real, then • Proof: Take the conjugate Substitute -f = Since w(t) is real, w*(t) = w(t), and it follows that W(-f) = W*(f). • If w(t) is real and is an even function of t, W(f) is real. • If w(t) is real and is an odd function of t, W(f) is imaginary.
Corollaries of Properties of Fourier Transforms • Spectral symmetry of real signals. If w(t) is real, then: • Magnitude spectrum is even about the origin. |W(-f)| = |W(f)| (A) • Phase spectrum is odd about the origin. θ(-f) = - θ(f)(B) Since, W(-f) = W*(f) We see that corollaries (A) and (B) are true.
Properties of Fourier Transform • f, called frequency and having units of hertz, is just a parameter of the FT that specifies what frequency we are interested in looking for in the waveform w(t). • The FT looks for the frequency f in the w(t)over all time, that is, over -∞ < t < ∞ • W(f )can be complex, even though w(t)is real. • If w(t)is real, then W(-f) = W*(f).
Parseval’s Theorem and Energy Spectral Density • Persaval’s theorem gives an alternative method to evaluate energy in frequency domain instead of time domain. • In other words energy is conserved in both domains. (2-41)
Parseval’s Theorem and Energy Spectral Density The total Normalized Energy E is given by the area under the Energy Spectral Density
Example 2-3: Spectrum of a Damped Sinusoid Variation of W(f) with f
d(x) x Dirac Delta Function • Definition: The Dirac deltafunctionδ(x) is defined by where w(x) is any function that is continuous at x = 0. An alternative definition of δ(x) is: The Sifting Propertyof the δ function is If δ(x) is an even function the integral of the δ function is given by:
Unit Step Function • Definition: The Unit Step function u(t) is: Because δ(λ) is zero, except at λ = 0, the Dirac delta function is related to the unit step function by
Ad(f-fc) Ad(f-fc) H(fc)d(f-fc) Aej2pfct d(f-fc) H(f) fc fc H(fc) ej2pfct Ad(f+fc) 2Acos(2pfct) -fc Spectrum of Sinusoids • Exponentials become a shifted delta • Sinusoids become two shifted deltas • The Fourier Transform of a periodic signal is a weighted train of deltas
Fourier Transform of an Impulse Train FT of any periodic signal can be represented as: An impulse train in time domain can be represented as: This signal is periodic hence (1) can be used to get its FT 2𝜋/𝑇 f t -3T -2T -T 0 T 2T 3T 0 4/T -2/T 2/T
https://web.sonoma.edu/users/f/farahman/sonoma/courses/es442/https://web.sonoma.edu/users/f/farahman/sonoma/courses/es442/
https://web.sonoma.edu/users/f/farahman/sonoma/courses/es442/https://web.sonoma.edu/users/f/farahman/sonoma/courses/es442/
https://web.sonoma.edu/users/f/farahman/sonoma/courses/es442/https://web.sonoma.edu/users/f/farahman/sonoma/courses/es442/
https://web.sonoma.edu/users/f/farahman/sonoma/courses/es442/https://web.sonoma.edu/users/f/farahman/sonoma/courses/es442/
https://web.sonoma.edu/users/f/farahman/sonoma/courses/es442/https://web.sonoma.edu/users/f/farahman/sonoma/courses/es442/
https://web.sonoma.edu/users/f/farahman/sonoma/courses/es442/https://web.sonoma.edu/users/f/farahman/sonoma/courses/es442/