Buy Lecture Notes for EE The Fourier Transform and its Applications on ✓ FREE SHIPPING on qualified orders. Brad Osgood (Author). Lecture Notes for. The Fourier Transform and its Applications. Prof. Brad Osgood. Stanford University Fourier series, the Fourier transform of continuous and discrete signals and its author: Brad G. Osgood, Computer Science Department, Stanford University.
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The Fourier transform is a tool for solving physical problems. In this course the emphasis is on relating the theoretical principles to solving practical engineering and science problems.
Stanford Engineering Everywhere | EE – The Fourier Transform and its Applications
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. Diffraction Lecture 16 – Diffraction cont. Lecture 28 – Higher Dimensional Fourier Transforms cont. Lecture 03 – Fourier Series cont.
Lecture 04 – Fourier Series cont. Lecture 07 – Fourier Transform Properties and Examples cont.
Lecture 09 – Example of Convolution: Filtering, Interpreting Convolution in the Time Domain. Lecture 10 – Convolution and Central Limit Theorem. Lecture 11 – Discussion of the Convergence of Integrals. Lecture 13 – The Fourier Transform of a Distribution. Lecture 15 – Application of the Fourier Transform: Lecture 16 – Diffraction cont. Lecture 18 – Sampling, Interpolation and Aliasing.
Lecture 20 – The Discrete Fourier Transform. Lecture 21 – Properties fouriee Discrete Fourier Transform. Lecture 23 – Linear Systems: Basic Definitions, Eigenvectors brzd Eigenvalues. Lecture 24 – Linear Systems cont.
SEE EE261 – The Fourier Transform and its Applications (Fall, 2007)
Lecture 27 – Higher Dimensional Fourier Transforms cont. Shift Theorem, Stretch Theorem. Lecture 29 – Shahs, Lattices, and Crystallography.
Lecture 30 – Tomography and Inverting the Radon Transform.