IEEE

Interpretable Deep Learning for Nonlinear System Identification Using Frequency Response Functions With Ensemble Uncertainty Quantification

Abstract: Deep learning methods contain powerful tools for modelling nonlinear dynamic systems. However, whilst these models are useful for predicting outputs, they tend to be described by complicated ...
IEEE

Comprehensive Study on Zeroing Neural Network With High-Order Evolutionary Formula, Nonlinear Functions, and Variable Parameter for Time-Changing Matrix Cholesky Decomposition

Abstract: In this article, a low-order zeroing neural network (LZNN), a high-order ZNN (HZNN), and a variable-parameter ZNN (VZNN) are designed and applied to the time-changing Cholesky decomposition ...