Random Telegraph Signal

Random telegraph signals (RTSs), characterized by abrupt transitions between discrete states, are found across diverse scientific domains. Current research focuses on accurately analyzing complex, multilevel RTSs, often employing deep neural networks with progressive knowledge transfer to overcome the challenges of high dimensionality and noise. These analyses are crucial for extracting meaningful information from noisy data, impacting fields ranging from speech analysis (detecting manipulated audio) to biological signal processing (understanding single-particle dynamics). A key challenge lies in distinguishing genuine signal features from spurious correlations within the data, necessitating robust methods for model interpretation and artifact detection.