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CourseEE26130 lectures25 h 37 min

The Fourier Transform and its Applications

Brad G Osgood · Stanford University

Start with lecture 1 At Stanford Engineering Everywhere

About

The goals for the course are to gain a facility with using the Fourier transform, both specific techniques and general principles, and learning to recognize when, why, and how it is used. Together with a great variety, the subject also has a great coherence, and the hope is students come to appreciate both.

Topics include: The Fourier transform as a tool for solving physical problems. Fourier series, the Fourier transform of continuous and discrete signals and its properties. The Dirac delta, distributions, and generalized transforms. Convolutions and correlations and applications; probability distributions, sampling theory, filters, and analysis of linear systems. The discrete Fourier transform and the FFT algorithm. Multidimensional Fourier transform and use in imaging. Further applications to optics, crystallography. Emphasis is on relating the theoretical principles to solving practical engineering and science problems.

Lectures

  1. Previous Knowledge Recommended (Matlab), The Fourier Series, Analysis V. Synthesis, Periodic Phenomena And The Fourier Series -Periodicity In Time And Space -Reciprocal Relationship Between Domains, The Reciprocal Relationship Between… Lecture 1 · 52 min · Video
  2. Periodicity; How Sine And Cosine Can Be Used To Model More Complex Functions, Example Of Periodizing A Signal, Discussion Of How To Model Signals With Sinusoids, "One Period, Many Frequencies" Idea In Modeling Signals, Modeling A Signal… Lecture 2 · 53 min · Video
  3. 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… Lecture 3 · 51 min · Video
  4. Wrapping Up Fourier Series; Making Sense Of Infinite Sums And Convergence, Integrability Of A Function (Implies Existence Of Fourier Coefficients, Convergence), Orthogonality Of Complex Exponentials (Review), The Inner Product, Norm Of F… Lecture 4 · 52 min · Video
  5. Continued Discussion Of Fourier Series And The Heat Equation, Transition From Fourier Series To Fourier Transforms (Periodic To Nonperiodic Phenomena), Fourier Series Analysis And Synthesis; Relation To Fourier Transform And Inverse… Lecture 5 · 52 min · Video
  6. Correction To Heat Equation Discussion, Setup For Fourier Transform Derivation From Fourier Series, Results Of The Derivation: Fourier Transform And Inverse Fourier Transform, Definition Of The Fourier Transform (Analysis), Definition Of… Lecture 6 · 48 min · Video
  7. Review Of Fourier Transform (And Inverse) Definitions, Notation, Review Of Rect And Triangle Transforms, Example: Fourier Transform Of A Gaussian, The Duality Property Of The Fourier Transform, Example Of An Application Of The Duality… Lecture 7 · 48 min · Video
  8. Effect On Fourier Transform Of Shifting A Signal, Resulting Delay Formula (Shift Theorem), Effect Of Scaling The Time Signal, Stretch Theorem Formula/ Interpretation, Convolution In Context Of Fourier Transforms; Multiplying Two Signals… Lecture 8 · 51 min · Video
  9. Continuing Convolution: Review Of The Formula, Situiation In Which It Arose, Example Of Convolution: Filtering, The Ideas Behind Filtering, Terminology, Interpreting Convolution In The Time Domain, General Properties Of Convolution In The… Lecture 9 · 54 min · Video
  10. Central Limit Theorem And Convolution; Main Idea, Introduction, Normalization Of The Gaussian, The Gaussian In Probability; Pictorial Demonstration With Convolution, The Setup For The CLT, Key Result: Distribution Of Sums And Convolution… Lecture 10 · 55 min · Video
  11. Correction To The End Of The CLT Proof, Discussion Of The Convergence Of Integrals; Approaches To Making A More Robust Definition Of The Fourier Transform, Examples Of Problematic Signals, How To Approach Solving The Problem; Choosing… Lecture 11 · 51 min · Video
  12. Cop Story, Review Of Rapidly Decreasing Functions, Generalized Functions (Distributions) (Delta Function, Etc.), Viewing Delta As A Limit V. Operationally, Definition Of A Distribution, Delta As A Distribution, Discussion Of How To… Lecture 12 · 53 min · Video
  13. Setting Up The Fourier Transform Of A Distribution, Example Of Delta As A Distribution, Distributions Induced By Functions (Includes Many Functions), The Fourier Transform Of A Distribution, The Class Of Tempered Distributions, FT Of A… Lecture 13 · 49 min · Video
  14. Derivative Of A Distribution, Example: Derivative Of A Unit Step, Example: Derivative Of Sgn(X), Applications To The Fourier Transform (Using The Derivative Theorem), Caveat To Distributions: Multiplying Distributions,… Lecture 14 · 54 min · Video
  15. Application Of The Fourier Transform: Diffraction: Setup, Representation Of Electric Field, Approach Using Huyghens' Principle, Discussion Of The Phase Change Associated With Different Paths, Use Of The Fraunhofer Approximation, Aperture… Lecture 15 · 52 min · Video
  16. More On Results From Last Lecture (Diffraction Patterns And The Fourier Transforms), Setup For Crystallography Discussion (History, Concepts), 1-Dimensional Version, The Fourier Transform Of The Shah Function, Trick: Poisson Summation… Lecture 16 · 50 min · Video
  17. Review Of Main Properties Of The Shah Function, Setup For The Interpolation Problem, Bandwidth Assumption, Solving For Exact Interpolation For Bandlimited Signals, Periodizing The Signal By Convolution With The Shah Function, Solution Of… Lecture 17 · 41 min · Video
  18. Review Of Sampling And Interpolation Results, Terminology: Sampling Rate, Nyquist Rate, Issues With The Interpolation Formula In Practical Applications, Aliasing And Interpolation, Main Argument In Aliasing, Example Of Aliasing: Cosine Lecture 18 · 51 min · Video
  19. Aliasing Demonstration With Music, Transition To Discrete! The DFT, The Plan For Transitioning To Discrete Time, Creating A Discrete Signal From F(T) Creating A Discrete Version Of The Fourier Transform Of The Sampled Version Of F(T),… Lecture 19 · 52 min · Video
  20. Review: Definition Of The DFT, Sample Points, Relationship Between N And Spacing In Time/Frequency, Complex Exponentials In The Discrete DFT, DFT Written With Discrete Complex Exponential Vector, Periodicity Of Inputs And Outputs In The… Lecture 20 · 53 min · Video
  21. Review Of Basic DFT Definitions, Special Case: Value Of The DFT At 0, Two Special Signals: One Vector, Delta Vector, DFT Of Deltas, Complex Exponentials, DFT As Nxn Matrix Multiplication, Periodicity Of Input/Output Signals In The DFT,… Lecture 21 · 53 min · Video
  22. FFT Algorithm: Setup: DFT Matrix Notation, One Intuition Behind FFT: Factoring Matrix, Our Approach: Split Order N Into Two Order N/2, Iterate, Notation (To Keep Track Of Powers Of Complex Exponentials), Plugging New Notation Into DFT;… Lecture 22 · 51 min · Video
  23. Linear Systems: Basic Definitions, Direct Proportionality As Example, Special Cases Of Linear Systems, Eigenvectors And Eigenvalues, The Spectral Theorem And Finding A Basis Of Eigenvectors, Matrix Multiplication = Only Example Of Finite… Lecture 23 · 51 min · Video
  24. Review Of Last Lecture: Discrete V. Continuous Linear Systems, Cascading Linear Systems, Derivation Of The Impulse Response, Schwarz Kernel Theorem, Example: Impulse Response For Fourier Transform, Example: Switch, Special Case:… Lecture 24 · 57 min · Video
  25. Review Of Last Lecture: LTI Systems And Convolution, Comment On Time Invariant Discrete Systems, The Fourier Transform For LTI Systems; Complex Exponentials As Eigenfunctions, Discussion Of Sine And Cosine V. Complex Exponentials As… Lecture 25 · 53 min · Video
  26. Approaching The Higher Dimensional Fourier Transform, Notation: Thinking In Terms Of Vectors, Definition Of The Higher Dimensional Fourier Transform, Inverse Fourier Transform, Reciprocal Relationship Between Spatial And Frequency Domain,… Lecture 26 · 54 min · Video
  27. Higher Dimensional Fourier Transforms- Review, Fourier Transforms Of Seperable Functions (Ex: 2-D Rect), Result: Formula For Fourier Transform Of A Seperable Function, Example: 2-D Gaussian, Radial Functions, Proof That The Fourier… Lecture 27 · 50 min · Video
  28. Shift Theorem In Higher Dimensions, Shift Theorem: Result, Stretch Theorem Derivation, Stretch Theorem Result, Special Case: Scaling, Special Case: Rotation, What Reciprocal Means In Higher Dimensions (Inverse Transpose), Deltas In Higher… Lecture 28 · 49 min · Video
  29. Shahs, Lattices, And Crystallography, 2-D Shah, Crystals As Lattices, The Fourier Transform Of The Shah Function Of An Oblique Lattice, Relation To Crystals; Notation, Concepts, And Results, Application To Medical Imaging: Tomography Lecture 29 · 50 min · Video
  30. Tips For Filling Out Evals, Tomography And Inverting The Radon Transform; Setup, Introducing Coordinates, Delta Along A Line, The Integral Of U Along A Line, Inverting The Radon Transform Lecture 30 · 47 min · Video

Syllabus and materials

At Stanford Engineering Everywhere, as the course publishes them.

Credits and licence

Institution
Stanford University
Department
Electrical Engineering
Teacher
Brad G Osgood
Level
Undergraduate
Language
English
Subjects
Engineering
Source
Stanford Engineering Everywhere
Licence
CC BY-NC-SA 4.0, as Stanford Engineering Everywhere states it. Non-commercial use only. Stanford Engineering Everywhere's terms
Attribution
Stanford Engineering Everywhere, Stanford University. Licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License, unless otherwise expressly indicated.
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