Time Frequency Information

Time-frequency information analysis focuses on extracting meaningful patterns from signals by simultaneously considering their temporal and spectral characteristics. Current research emphasizes developing deep learning models, such as convolutional neural networks (CNNs) and transformers, often incorporating techniques like wavelet packet transforms or short-time Fourier transforms for preprocessing, to improve feature extraction and classification accuracy across diverse applications. These advancements are significantly impacting fields ranging from speech enhancement and fault diagnosis to person re-identification, enabling more robust and efficient signal processing in various domains. The interpretability of these models is also a growing area of focus, aiming to improve trust and understanding of their decision-making processes.