Engineers have demonstrated a simple computational approach for supporting the classification performance of neural networks operating on sensor time series. The proposed technique involves feeding ...

A research team at Duke University has developed a new AI framework that can uncover simple, understandable rules that govern ...

In a new study, scientists have investigated the pervasive low-rank hypothesis in complex systems, demonstrating that despite high-dimensional nonlinear dynamics, many real networks exhibit rapidly ...

Example-oriented survey of nonlinear dynamical systems, including chaos. Combines numerical exploration of differential equations describing physical problems with analytic methods and geometric ...

As a follow-on course to "Linear Kalman Filter Deep Dive", this course derives the steps of the extended Kalman filter and the sigma-point Kalman filter for estimating the state of nonlinear dynamic ...

Develop a foundation of analytical mechanics and multiphysics modeling. Use individual and team exercises to build skills for a dynamic systems approach. Engineered systems increasingly must exploit ...