Representing variable-length and continuous-indexed signals through a linear combination of basis functions poses a fundamental challenge in science and engineering. Current approaches resort to ...

This paper describes an identifier for a class of nonlinear systems based on continuous recurrent neural networks (CRNN). The identifier is proposed considering the approximation properties of ...