Synthetic Signal

Synthetic signal generation and analysis is a rapidly expanding field focused on creating and utilizing artificial signals to address limitations in data acquisition, privacy concerns, and computational costs across various domains. Current research emphasizes the development of novel algorithms, including deep neural networks, generative adversarial networks (GANs), and support vector machines (SVMs), to generate realistic synthetic signals and extract meaningful information from them. This work has significant implications for diverse applications, ranging from improving the efficiency of human-robot interaction and railway maintenance to enhancing deepfake detection and advancing medical diagnostics through the use of synthetic ECGs and other biosignals.