Fourier's seminal work provided the mathematical foundation for Hilbert spaces, operator theory, approximation theory, and the subsequent revolution in analytical and computational mathematics. Fast forward two hundred years, and the fast Fourier transform has become the cornerstone of computational mathematics, enabling real-time image and audio compression, global communication networks, modern devices and hardware, numerical physics and engineering at scale, and advanced data analysis. Simply put, the fast Fourier transform has had a more significant and profound role in shaping the modern world than any other algorithm to date.
Youtube playlist: Fourier Analysis
 
Section 2.1: Fourier Series
  [ Overview ] [ Fourier Series Pt 1 ] [ Fourier Series Pt 2 ] [ Inner Producs ] [ Complex Fourier Series ] Code [ Matlab ] [ Python ] Gibbs Phenomena [ Matlab ] [ Python ]
Section 2.1: Fourier Transform
  [ Overview ] [ Fourier Transform & Derivatives ] [ Fourier Transform & Convolution ] [ Parseval's Theorem ]
 
Section 2.2: Fast Fourier Transform
  [ Overview ] [ Algorithm ] [ Denoising w/ FFT [Matlab] ] [ Denoising w/ FFT [Python] ] [ Derivatives w/ FFT [Matlab] ] [ Derivatives w/ FFT [Python] ]
 
Section 2.3: Solving PDEs with FFT
Section 2.4: The Spectorgram
  [ Spectrogram ] Examples [ Matlab ] [ Python ] [ Uncertainty Principles ]
 
 
 
  Additional Lectures
Section 2.1: Fourier Series and Transform
  [ Fourier series ] [ Hilbert space ] [ Fourier transforms ] [Properties]
Section 2.2: Discrete Fourier Transform
  [ Discrete Fourier transform ] [ DFT in Matlab ] [ DFT for audio signals ]
 
Section 2.3: FFT for Partial Differential Equations
  [ Fourier transforming PDEs ] [ Solving PDEs with FFT ] [ Solving PDEs with FFT, Part 2 ]