The objective of this paper is to describe a new method for modeling aeroelastic system in time domain based on a modification of the Laguerre Polynomials to represent complex quantities. These polynomials are used to ...

In this paper, a new state-space model of the potential-radiation hydrodynamics in moored ocean engineering floating structures and its parameter identification are presented. The raw data for this goal are the added mass ...

The objective of this paper is to include the frequency dependence of the longitudinal parameters in the lumped parameters line model. The distributed nature of the transmission line was approximated by a cascade of π ...

Objectives: The aim of this study was to propose a state space-based approach to model perturbed pitch period sequences (PPSs), extracted from real sustained vowels, combining the principal features of disturbed real PPSs ...

1. Bayesian state-space movement models have been proposed as a method of inferring behavioural states from movement paths (Morales et al. 2004), thereby providing insight into the behavioural processes from which patterns ...

Specification and tuning of errors from dynamical models are important issues in data assimilation. In this work, we propose an iterative expectation-maximization (EM) algorithm to estimate the model-error covariances using ...

Accurate estimation of the glottal source from a voiced sound is a difficult blind separation problem in speech signal processing. In this work, state-space methods are investigated to enhance the joint estimation of the ...

This paper presents a state space description for wavelet FIR filter banks with perfect reconstruction using special orthonormal basis functions. The FIR structure guarantees the BIBO stability, robustness and improves the ...

The demands for improvement in sound quality and reduction of noise generated by vehicles are constantly increasing, as well as the penalties for space and weight of the control solutions. A promising approach to cope with ...