Fourier Transform

The Fourier Transform is a mathematical tool that decomposes signals into their constituent frequencies, enabling efficient analysis and manipulation of data across various domains. Current research focuses on leveraging the Fourier Transform within neural networks, particularly through architectures like Fourier Neural Operators and adaptations of existing models (e.g., Transformers) to incorporate Fourier-based feature extraction or parameter-efficient fine-tuning. This approach enhances efficiency and performance in diverse applications, including image processing, time series forecasting, and solving partial differential equations, while also addressing challenges like computational cost and robustness to noise.