Covers subquadratic attention mechanisms and state space models, focusing on their theoretical foundations and practical implementations in machine learning.
Explores the discrete-time Fourier transform, its properties, and signal transformations, including examples like the rectangular pulse and unit impulse.
Covers the Fast Fourier Transform (FFT) algorithm and its applications in computational physics, including image processing, experimental techniques, filters, and analysis of microscopy images.
