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A novel particle filter parameter prediction scheme for failure prognosis
(
Institute of Electrical and Electronics Engineers Inc.
, 2014 , Conference Paper)
Particle filters are well-known as powerful tools for accomplishing state and parameter estimation and their propagation prediction in nonlinear dynamical systems. Their ability to include system model parameters as part ...
An IV-SVM-based approach for identification of state-space LPV models under generic noise conditions
(
Institute of Electrical and Electronics Engineers Inc.
, 2015 , Conference Paper)
This paper presents a nonparametric identification method for state-space linear parameter-varying (LPV) models using a modified support vector machine (SVM) approach. While most LPV identification schemes in the state-space ...
Output-feedback model predictive control of biological phenomena modeled by S-systems
(
Institute of Electrical and Electronics Engineers Inc.
, 2012 , Conference Paper)
Recent years have witnessed extensive research activity in modeling biological phenomena as well as in developing intervention strategies for them. S-systems, which offer a good compromise between accuracy and mathematical ...
Parameter estimation of biological phenomena: An unscented kalman filter approach
(
IEEE
, 2013 , Article)
Recent advances in high-throughput technologies for biological data acquisition have spurred a broad interest in the construction of mathematical models for biological phenomena. The development of such mathematical models ...