# Publications

## Active control of time-varying broadband noise using on-line system identification with parallel fast-array recursive least squares filters KU Leuven

For broadband active noise control applications with rapidly changing transfer paths, it is desirable to find algorithms with rapid convergence, fast tracking performance, and low computational cost. Recently, a numerically stable algorithm has been presented: a convex mixing fast-array RLS filter. The algorithm exhibits the fast convergence, tracking properties and the linear calculation complexity of the fast-array RLS sliding window filter ...

## Output-only time-frequency-domain modal identification of time-varying structures using a recursive two-stage least square method KU Leuven

Real-time acquisition of modal parameters may contribute to the on-line structural dynamic research of time-varying structures, such as the health monitoring, the damage detection, the vibration control, etc. The recursive algorithms of modal parameter estimation supply the fundamental of acquiring modal parameters in real-time. This paper presents a recursive method of modal parameter estimation for time-varying structures, including the ...

## Bias and covariance of the least squares estimate in a structured errors-in-variables problem Vrije Universiteit Brussel

A structured errors-in-variables (EIV) problem arising in metrology is studied. The observations of a sensor response are subject to perturbation. The input estimation from the transient response leads to a structured EIV problem. Total least squares (TLS) is a typical estimation method to solve EIV problems. The TLS estimator of an EIV problem is consistent, and can be computed efficiently when the perturbations have zero mean, and are ...

## Fully constrained least squares spectral unmixing by simplex projection University of Antwerp KU Leuven

We present a new algorithm for linear spectral mixture analysis, which is capable of supervised unmixing of hyperspectral data while respecting the constraints on the abundance coefficients. This simplex-projection unmixing algorithm is based upon the equivalence of the fully constrained least squares problem and the problem of projecting a point onto a simplex. We introduce several geometrical properties of high-dimensional simplices and ...

## A recursive restricted total least-squares algorithm. Vrije Universiteit Brussel

We show that the generalized total least squares (GTLS) problem with a singular noise covariance matrix is equivalent to the restricted total least squares (RTLS) problem and propose a recursive method for its numerical solution. The method is based on the generalized inverse iteration. The estimation error covariance matrix and the estimated augmented correction are also characterized and computed recursively. The algorithm is cheap to compute ...

## Recursive Identification of Hammerstein Structure Vrije Universiteit Brussel

A novel recursive algorithm for identification of Hammerstein structures is developed. The linear and nonlinear parameters are separated and estimated recursively in a parallel manner, but each updating algorithm employs the estimation produced by the other at the previous time instant. Hence, it is termed the Alternately Recursive Least Square (ARLS) algorithm. When compared with Recursive Least Squares (RLS) algorithm applyed to the ...

## Recursive identification of Hammerstein systems with application to electrically stimulated muscle. Vrije Universiteit Brussel

Abstract: Modeling of electrically stimulated muscle is considered in this paper where a Hammerstein structure is selected to represent the isometric response. Motivated by the slowly time-varying properties of the muscle system, recursive identification of Hammerstein structures is investigated. A recursive algorithm is then developed to address limitations in the approaches currently available. The linear and nonlinear parameters are separated ...

## Recursive identification of Hammerstein systems with application to electrically stimulated muscle. Vrije Universiteit Brussel

## Stable parametric macromodeling using a recursive implementation of the vector fitting algorithm Ghent University

A novel least-squares fitting technique is presented for the macromodeling of parameterized frequency responses. Such parametric macromodel can be used. for the design, study, and optimization of microwave structures. A key benefit of the proposed method, is that the poles of the macromodel are guaranteed stable by construction. This can easily be enforced when using the presented macromodel representation.