Fractional Fourier Transform

The Fractional Fourier Transform (FrFT) is a generalization of the standard Fourier transform, offering a unified representation of both spatial and frequency information, particularly beneficial for analyzing non-stationary signals. Current research focuses on leveraging FrFT within advanced architectures like neural operators (e.g., CoNO) and transformers (e.g., F2former) to improve signal processing tasks such as image deblurring, phase retrieval, and modeling continuous dynamical systems. These applications demonstrate FrFT's power in enhancing the accuracy and efficiency of various signal processing and machine learning algorithms, leading to improvements in diverse fields like optical communication and scientific computing.