Numerical Differentiation of Noisy Data: A Unifying Multi-Objective Optimization Framework
Numerical Differentiation of Noisy Data: A Unifying Multi-Objective Optimization Framework
Computing derivatives of noisy measurement data is ubiquitous in the physical, engineering, and biological sciences, and it is often a critical step in developing dynamic models or designing control. Unfortunately, the mathematical formulation of numerical differentiation is typically ill-posed, and researchers often resort to an ad hoc process for choosing …