Advances in experimental techniques and the ever-increasing fidelity of numerical
simulations have led to an abundance of data describing fluid flows. This review discusses a …

Operational modal analysis deals with the estimation of modal parameters from vibration
data obtained in operational rather than laboratory conditions. This paper extensively …

This paper considers the creation of parametric surrogate models for applications in science
and engineering where the goal is to predict high-dimensional output quantities of interest …

This article focuses on the design of model predictive control (MPC) systems for nonlinear
processes that utilize an ensemble of recurrent neural network (RNN) models to predict …

We develop a new method which extends dynamic mode decomposition (DMD) to
incorporate the effect of control to extract low-order models from high-dimensional, complex …

In the conventional approaches to the design of fault diagnosis systems, little effort is usually
paid to the selection of the parity vectors. As a result, the systems' performance can be …

The quintessential goal of sensor array signal processing is the estimation of parameters by
fusing temporal and spatial information, captured via sampling a wavefield with a set of …

Spectral analysis considers the problem of determining the spectral content (ie, the
distribution of power over frequency) of a time series from a finite set of measurements, by …

This paper reviews stochastic system identification methods that have been used to estimate
the modal parameters of vibrating structures in operational conditions. It is found that many …

Part I deals with the mathematical preliminaries: numerical linear algebra; system theory;
stochastic processes; and Kalman filtering. Part II explains realization theory as applied to …