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Fourier Transform of Signals

Track :

Mathematics

Lessons no : 49

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What will you learn in this course?
  • Master how to apply Fourier Transform to analyze time-domain signals and extract frequency information effectively
  • Identify different types of Fourier Transforms, including Fourier Series, Fourier Transform, and Discrete Fourier Transform (DFT)
  • Calculate and interpret the magnitude and phase spectra of signals using Fourier analysis techniques
  • Utilize Fourier Transform to filter noise and enhance signal clarity in practical applications
  • Implement Fourier Transform algorithms in software tools like MATLAB or Python for signal processing tasks
  • Understand the relationship between time-domain signals and their frequency-domain representations
  • Analyze real-world signals such as audio, communication, and biomedical signals using Fourier methods
  • Design filters based on Fourier analysis to improve signal quality in engineering systems
  • Apply Fourier Transform concepts to solve problems in communications, audio engineering, and image processing
  • Evaluate the effects of signal windowing and sampling on Fourier Transform accuracy and resolution
  • Use Fourier Transform to identify dominant frequencies and spectral components in complex signals
  • Develop skills to troubleshoot and optimize Fourier-based signal analysis in practical scenarios

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Lessons | 49
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Fourier Transform course, In this course we'll explore Fourier Transform—a mathematical tool for analyzing signals by decomposing them into frequency components.