Nonlinearity Compensation

Nonlinearity compensation aims to mitigate the detrimental effects of non-linear distortions in various systems, improving signal quality and system performance. Current research focuses on developing and applying advanced techniques, including neural networks (like convolutional and recurrent architectures, and transformers), Volterra series, and even unconventional computing methods, to effectively model and compensate for these nonlinearities across diverse applications. These efforts are significant because they enhance the accuracy and efficiency of systems ranging from optical communication and acoustic actuation to language processing and speaker recognition, leading to improvements in data transmission, device performance, and machine learning capabilities.