Pages that link to "Item:Q2431028"

The following pages link to \(\mathcal L_{2}-\mathcal L_{\infty }\) nonlinear system identification via recurrent neural networks (Q2431028):

Displaying 7 items.

• Peak-to-peak exponential direct learning of continuous-time recurrent neural network models: a matrix inequality approach (Q395779) (← links)
• Nonlinear system identification using discrete-time recurrent neural networks with stable learning algorithms. (Q1429837) (← links)
• Sets of generalized \(\mathcal H_2\) exponential stability criteria for switched multilayer dynamic neural networks (Q1690818) (← links)
• Input-to-state stability for dynamical neural networks with time-varying delays (Q1938179) (← links)
• \(l_2\) Induced norm analysis of discrete-time LTI systems for nonnegative input signals and its application to stability analysis of recurrent neural networks (Q2068566) (← links)
• A levenberg-marquardt learning applied for recurrent neural identification and control of a wastewater treatment bioprocess (Q3401320) (← links)
• Deep subspace encoders for nonlinear system identification (Q6136161) (← links)