Lectures (Video)
- 1. The Fourier Series
- 2. Periodicity, Modeling A Signal
- 3. Convergence
- 4. Inner Product, Complex Exponentials
- 5. Fourier Transforms
- 6. Fourier Inversion
- 7. Duality Property
- 8. Stretch Theorem Formula, Convolution Formula
- 9. Continuing Convolution
- 10. Central Limit Theorem And Convolution
- 11. Best Class Of Signals For Fourier Transforms
- 12. Generalized Functions
- 13. Fourier Transform Of A Distribution
- 14. The Delta Function And Sampling
- 15. Application Of The Fourier Transform
- 16. Shah Function, Poisson Summation Formula
- 17. Interpolation Problem
- 18. Sampling Rate, Nyquist Rate, Aliasing
- 19. Discrete Version Of The Fourier Transform
- 20. Discrete Complex Exponential Vector
- 21. Review Of Basic DFT Definitions
- 22. FFT Algorithm
- 23. Linear Systems
- 24. Impulse Response, Schwarz Kernel Theorem
- 25. Fourier Transform For LTI Systems
- 26. Higher Dimensional Fourier Transform
- 27. Fourier Transforms Of Seperable Functions
- 28. Shift Theorem
- 29. Shahs, Lattices, And Crystallography
- 30. Tomography And Inverting The Radon Transform
Fourier Transform and its Applications - Lecture 3
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Lecture 3 - Convergence
Summary Of Previous Lecture (Analyzing General Periodic Phenomena As A Sum Of Simple Periodic Phenomena), Fourier Coefficients; Discussion Of How General The Fourier Series Can Be (Examples Of Discontinuous Signals), Discontinuity And Its Impact On The Generality Of The Fourier Series, Infinite Sums To Represent More General Periodic Signals, Summary Of Convergence Issues, Convergence: Continuous Case, Smooth Case (Fourier Series Converges To The Signal), Convergence: Jump Discontinuity, Convergence: General Case (Convergence On Average/ In Mean/ In Energy)
Prof. Brad G Osgood
The Fourier Transform and its Applications EE261 (Stanford University: Stanford Engineering Everywhere) http://see.stanford.edu Date accessed: 2009-09-24 License: Creative Commons Attribution 3.0 |
