Fractional Order and non-linear System Identification algorithms for Biomedical applications

2nd International Conference on Mathematical Modeling in Physical Sciences 2013

物理学;数学

Hadjiloucas, S.^1 ; Galvão, R.K.H.^2

Cybernetics, School of Systems Engineering, University of Reading, RG6 6AY, United Kingdom^1

Divisão de Engenharia Eletrônica, Instituto Tecnológico de Aeronáutica, São José dos Campos, SP, 12228-900, Brazil^2

关键词: Biomedical applications;    Biomedical data analysis;    Dielectric response;    Impedance spectroscopy;    Non-linear system identification;    State;    space models;    Systems identification;    Transient spectroscopy;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/490/1/012141/pdf
DOI  :  10.1088/1742-6596/490/1/012141

来源: IOP

【 摘 要 】

We discuss the modelling of dielectric responses of amorphous biological samples. Such samples are commonly encountered in impedance spectroscopy studies as well as in UV, IR, optical and THz transient spectroscopy experiments and in pump-probe studies. In many occasions, the samples may display quenched absorption bands. A systems identification framework may be developed to provide parsimonious representations of such responses. To achieve this, it is appropriate to augment the standard models found in the identification literature to incorporate fractional order dynamics. Extensions of models using the forward shift operator, state space models as well as their non-linear Hammerstein-Wiener counterpart models are highlighted. We also discuss the need to extend the theory of electromagnetically excited networks which can account for fractional order behaviour in the non-linear regime by incorporating nonlinear elements to account for the observed non-linearities. The proposed approach leads to the development of a range of new chemometrics tools for biomedical data analysis and classification.