Add to ORKG24th European Signal Processing Conference (EUSIPCO) -- AUG 28-SEP 02, 2016 -- Budapest, HUNGARYAltinkaya, Mustafa A/0000-0001-8048-5850; Karakus, Oktay/0000-0001-8009-9319WOS: 000391891900296Various real world phenomena such as optical communication channels, power amplifiers and movement of sea vessels exhibit nonlinear characteristics. The nonlinearity degree of such systems is assumed to be known as a general intention. In this paper, we contribute to the literature with a Bayesian estimation method based on reversible jump Markov chain Monte Carlo (RJMCMC) for polynomial moving average (PMA) models. Our use of RJMCMC is novel and unique in the way of estimating both model memory and the nonlinearity degree. This offers greater flexibil...
Sequential Monte Carlo (SMC) and Markov chain Monte Carlo (MCMC) methods provide computational tools...
The aim of this paper is to utilise the concept of “highly informative training data” such that, usi...
The development of techniques for identification and updating of nonlinear mechanical structures has...
Various real world phenomena such as optical communication channels, power amplifiers and movement o...
Despite the popularity of linear process models in signal and image processing, various real life ph...
Many prediction studies using real life measurements such as wind speed, power, electricity load and...
The aim of this paper is to demonstrate the potential of the Reversible Jump Markov Chain Monte Carl...
Volterra systems have had significant success in modelling nonlinear systems in various real-world a...
We propose a Bayesian test for nonlinearity of threshold moving average (TMA) models. First, we obta...
In this paper, the authors outline the general principles behind an approach to Bayesian system iden...
In this thesis, a Bayesian approach is adopted to handle parameter estimation and model uncertainty ...
A Markov chain Monte Carlo (MCMC) approach, called a reversible jump MCMC, is employed in model sele...
The Duffing oscillator remains a key benchmark in nonlinear systems analysis and poses interesting c...
The Bayesian approach is well recognised in the structural dynamics community as an attractive appro...
This work details the Bayesian identification of a nonlinear dynamical system using a novel MCMC alg...
Sequential Monte Carlo (SMC) and Markov chain Monte Carlo (MCMC) methods provide computational tools...
The aim of this paper is to utilise the concept of “highly informative training data” such that, usi...
The development of techniques for identification and updating of nonlinear mechanical structures has...
Various real world phenomena such as optical communication channels, power amplifiers and movement o...
Despite the popularity of linear process models in signal and image processing, various real life ph...
Many prediction studies using real life measurements such as wind speed, power, electricity load and...
The aim of this paper is to demonstrate the potential of the Reversible Jump Markov Chain Monte Carl...
Volterra systems have had significant success in modelling nonlinear systems in various real-world a...
We propose a Bayesian test for nonlinearity of threshold moving average (TMA) models. First, we obta...
In this paper, the authors outline the general principles behind an approach to Bayesian system iden...
In this thesis, a Bayesian approach is adopted to handle parameter estimation and model uncertainty ...
A Markov chain Monte Carlo (MCMC) approach, called a reversible jump MCMC, is employed in model sele...
The Duffing oscillator remains a key benchmark in nonlinear systems analysis and poses interesting c...
The Bayesian approach is well recognised in the structural dynamics community as an attractive appro...
This work details the Bayesian identification of a nonlinear dynamical system using a novel MCMC alg...
Sequential Monte Carlo (SMC) and Markov chain Monte Carlo (MCMC) methods provide computational tools...
The aim of this paper is to utilise the concept of “highly informative training data” such that, usi...
The development of techniques for identification and updating of nonlinear mechanical structures has...