Abstract: State estimation from noisy observations is crucial across various fields. Traditional methods such as Kalman, Extended Kalman, and Unscented Kalman Filter often struggle with nonlinearities ...

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 ...

This Jupyter notebook demonstrates how modal decomposition methods can be used for flow feature extraction in fluid mechanics datasets. Modal decomposition techniques, such as Proper Orthogonal ...