Wavelet Packet Transform

Wavelet packet transform (WPT) is a signal processing technique that decomposes data into multiple frequency bands, enabling multi-scale analysis of non-stationary signals. Current research focuses on integrating learnable WPTs into deep learning architectures, such as adaptive wavelet networks and multi-scale networks, to improve performance in tasks like time series analysis, image deblurring, and fault diagnosis. These advancements enhance the robustness and adaptability of WPT, leading to improved accuracy and efficiency in various applications across diverse fields, including healthcare, industrial monitoring, and image generation. The development of domain-agnostic metrics based on WPT, like the Fr\'echet Wavelet Distance, further contributes to the field's advancement by providing more robust and interpretable evaluation methods.