Conventional damage detection techniques are gradually being replaced by state-of-the-art
smart monitoring and decision-making solutions. Near real-time and online damage …

During the past decades, significant efforts have been dedicated to develop reliable
methods in structural health monitoring. The health assessment for the target structure of …

A powerful way of gaining insight into biological systems is by creating a nonlinear
differential equation model, which usually contains many unknown parameters. Such a …

Observability is a modelling property that describes the possibility of inferring the internal
state of a system from observations of its output. A related property, structural identifiability …

In this paper, we address the system identification problem in the context of biological
modelling. We present and demonstrate a methodology for (i) assessing the possibility of …

The input-parameter-state estimation capabilities of a novel unscented Kalman filter is
examined herein on both linear and nonlinear systems. The unknown input is estimated in …

Ordinary differential equation models are nowadays widely used for the mechanistic
description of biological processes and their temporal evolution. These models typically …

A successive Bayesian filtering framework for addressing the joint input-state-parameter
estimation problem is proposed in this study. Following the notion of analytical, rather than …

A promising and attractive way of performing structural health monitoring (SHM) and
damage prognosis (DP) of engineering systems is through utilizing a nonlinear finite …

A bridge's natural frequencies are important dynamic properties reflecting the structural
condition of the bridge. Numerous studies have been conducted in the field to extract a …