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 ...

This letter introduces a novel physics-informed approach for neural network-based 3-D electromagnetic modeling. The proposed method combines standard leap-frog time-stepping with neural network-driven ...

Recent research has employed chemical reaction networks (CRNs), which harness biochemical processes for computations that translate interactions involving biochemical species into graphical form.

For decades, scientists have looked to light as a way to speed up computing. Photonic neural networks—systems that use light ...