Master the Fourier transform and its applications
Learn the Fourier transform in MATLAB and Python, and its applications in digital signal processing and image processing
Product Brand: Udemy
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Udemy Coupon Code for Master the Fourier transform and its applications Course. Learn the Fourier transform in MATLAB and Python, and its applications in digital signal processing and image processing
Created by Mike X Cohen | 6.5 hours on-demand video | 9 downloadable resources
Fourier Transform Course Overview
Master the Fourier transform and its applications
The Fourier transform is one of the most important operations in signal processing and modern technology, and therefore in modern human civilization. But how does it work, and why does it work? You will learn the theoretical and computational bases of the Fourier transform, with a strong focus on how the Fourier transform is used in modern applications in signal processing, data analysis, and image filtering. The course covers not only the basics, but also advanced topics including effects of non-stationarities, spectral resolution, normalization, filtering. All videos come with MATLAB and Python code for you to learn from and adapt!
This course is focused on implementations of the Fourier transform on computers, and applications in digital signal processing (1D) and image processing (2D). I don’t go into detail about setting up and solving integration problems to obtain analytical solutions. Thus, this course is more on the computer science/data science/engineering side of things, rather than on the pure mathematics/differential equations/infinite series side.
What you’ll learn
- Learn about one of the single most important equations in all of modern technology and therefore human civilization.
- The fundamental concepts underlying the Fourier transform
- Sine waves, complex numbers, dot products, sampling theorem, aliasing, and more!
- Interpret the results of the Fourier transform
- Apply the Fourier transform in MATLAB and Python!
- Use the fast Fourier transform in signal processing applications
- Improve your MATLAB and/or Python programming skills
- Know the limitations of interpreting the Fourier transform.
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The Signal processing problems, solved in MATLAB and Python course comes with over 10,000 lines of MATLAB and Python code, plus sample data sets, which you can use to learn from and to adapt to your own coursework or applications. In this course, you will also learn how to simulate signals in order to test and learn more about your signal processing and analysis methods.
Who this course is for:
- Students who need to know the Fourier transform for courses.
- Scientists who need to know the Fourier transform for research.
- Data scientists who need to do spectral analysis.
- Someone doing digital signal processing or image processing (filtering, signal separation, etc.)
- Someone who learned the FT by solving integral equations but wants more insight into what it means.
- Programmers looking for tips about optimizing code that involves FFT.
- Someone who is curious what the Fourier transform is and why it’s so important.
- Someone who uses the FFT but wants a better understanding of what it means, why it works, and how to interpret the results.
Taught by Mike X Cohen