A tiny bit of googling revealed this article: https://www.embedded.com/a-dsp-algorithm-for-frequency-analysis/ https://www.embedded.com/a-dsp-algorithm-for-freq

A tiny bit of googling revealed this article: https://www.embedded.com/a-dsp-algorithm-for-frequency-analysis/ https://www.embedded.com/a-dsp-algorithm-for-frequency-analy... > Engineers working in the field of digital signal processing often use the fast Fourier transform (FFT) algorithm to detect tones, frequencies, signatures, and other events. In specific situations, however, other algorithms may actually work better than the FFT. ... > Although most engineers would use the FFT, another, lesser-known algorithm gives you additional flexibility to specify both spectral analysis bandwidth and the resolution within that bandwidth and provides real and imaginary outputs from which you can compute spectral magnitude and phase. In this article, I'll introduce you to that algorithm, known as the Chirp-Z transform (CZT), and we'll compare it to the better known Goertzel and FFT. And the opening paragraph from wikipedia: > The chirp Z-transform (CZT) is a generalization of the discrete Fourier transform (DFT). While the DFT samples the Z plane at uniformly-spaced points along the unit circle, the chirp Z-transform samples along spiral arcs in the Z-plane, corresponding to straight lines in the S plane. The DFT, real DFT, and zoom DFT can be calculated as special cases of the CZT. https://en.wikipedia.org/wiki/Chirp_Z-transform https://en.wikipedia.org/wiki/Chirp_Z-transform Sounds like a pretty awesome milestone to me. So, perhaps in the near future, new compression schemes might allow for reduced mp3 and mp4 file sizes, which means that for the same bandwidth we could see increased resolution/ higher frame rates.