Model Structures and Fitting Criteria for System Identification with Neural Networks
Model Structures and Fitting Criteria for System Identification with Neural Networks
This paper focuses on the identification of dynamical systems with tailor-made model structures, where neural networks are used to approximate uncertain components and domain knowledge is retained, if available. These model structures are fitted to measured data using different criteria including a computationally efficient approach minimizing a regularized multi-step ahead …