Title :
Nonlinear modeling of physiological systems with multiple inputs
Author :
Mitsis, Georgios D. ; Marmarelis, Vasilis Z.
Author_Institution :
Dept. of Biomed. Eng., Univ. of Southern California, Los Angeles, CA, USA
Abstract :
Effective modeling of nonlinear dynamic systems can be achieved by employing Laguerre expansions and feedforward artificial neural networks in the form of the Laguerre-Volterra network (LVN). In this paper an extension of the LVN methodology to multiple-input systems is presented. Results from simulated systems show that this method can yield accurate nonlinear models of multiple-input Volterra systems, even when considerable noise is present.
Keywords :
feedforward neural nets; noise; physiological models; Laguerre expansions; Laguerre-Volterra network; estimation accuracy; model compactness; multiple-input systems; nonlinear Volterra systems; physiological systems with multiple inputs; simulated systems; Artificial neural networks; Biomedical engineering; Convergence; Convolution; Kernel; Nonlinear dynamical systems; Nonlinear filters; Nonlinear systems; Parameter estimation; Polynomials;
Conference_Titel :
Engineering in Medicine and Biology, 2002. 24th Annual Conference and the Annual Fall Meeting of the Biomedical Engineering Society EMBS/BMES Conference, 2002. Proceedings of the Second Joint
Print_ISBN :
0-7803-7612-9
DOI :
10.1109/IEMBS.2002.1134351
