ABSTRACT

Computing with neural networks (NNs) is one of the faster growing fields in the history of artificial intelligence (AI), largely because NNs can be trained to identify nonlinear patterns between input and output values and can solve complex problems much faster than digital computers. Owing to their wide range of applicability and their ability to learn complex and nonlinear relationships — including noisy or less precise information — NNs are very well suited to solving problems in biomedical engineering and, in particular, in analyzing biomedical signals.