Time Frequency

Time-frequency analysis focuses on representing signals as a function of both time and frequency, aiming to reveal how a signal's frequency content changes over time. Current research emphasizes developing novel deep learning architectures, such as convolutional neural networks (CNNs) and transformers, often incorporating techniques like Constant-Q transforms and wavelet transforms, to improve signal processing tasks across diverse applications. These advancements are significantly impacting fields ranging from audio processing (speech enhancement, music separation, vocoding) to radar signal processing and medical signal analysis, enabling more robust and efficient solutions.