This course covers the fundamentals of the Fourier Transform, including its definition, properties, relationship to other transforms, and extension to two dimensions for image processing. Students will learn about orthogonal basis functions, negative frequency, time and frequency scaling, phase importance, duality, and the Gibbs Phenomenon. The course also explores the connection between Fourier Series, Fourier Transform, DTFT, DFT, FFT, LT, and ZT. The teaching method includes video explanations and examples. This course is intended for learners interested in signal processing, mathematics, or image processing.
Overview
Syllabus
What is the Fourier Transform?.
What is the Fourier Transform used for?.
Fourier Transform Equation Explained.
Fourier Transform of Cos.
Orthogonal Basis Functions in the Fourier Transform.
What is Negative Frequency?.
Time and Frequency Scaling.
Is Phase important in the Fourier Transform?.
Duality Example of Fourier Transforms.
Continuous Time and Discrete Time Fourier Transforms.
Fourier Transform of Discrete Time Signals are not Discrete.
2D Fourier Transform Explained with Examples.
How are the Fourier Series, Fourier Transform, DTFT, DFT, FFT, LT and ZT Related?.
What is the Gibbs Phenomenon?.
Fourier Trfm and Inv FT: What's the difference?.
Taught by
Iain Explains Signals, Systems, and Digital Comms
