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This paper addresses the parameter identification of friction-type hysteretic isolators based on the versatile Bouc Wen differential model.
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The present paper addresses the parameter-dependent H∞ filter design problem for output estimation in linear parameter varying (LPV) plants that include constant delays in the state.
Franek and Jiang [22] address the parameter selection problem in image segmentation and presents a novel unsupervised framework for automatically choosing parameters.
In this section, we use the method of maximum likelihood to address the parameter estimation and conduct a simulation to examine the performance of this method.
In this article, we address the parameter estimation of micromotion targets in synthetic aperture radar (SAR), where scattering parameters and micromotion parameters of targets are coupled resulting in a nonlinear parameter estimation problem.
In this paper, we borrow the notion of parameter adaptation with the objective of addressing the parameter setting dependencies mentioned above, using a strategy based on a Bayesian network.
The proposed method was extended to address the parameter identification for systems with topological constraints.
We would like to emphasise, however, that despite these shortcomings, we have used all the available data efficiently and parameterised a full demographic model for this species for the first time, simultaneously addressing the parameter uncertainty explicitly, and have therefore improved the current understanding of Speleomantes demography significantly.
This work focuses on this issue by addressing the parameters identification problem for third-order models for synchronous generators.
The parameters are classified, and subsequently the probability and interval methods are separately applied to address the parameters with sufficient and insufficient experimental samples.
Table 4 shows the main characteristics of bridge models developed to address the parameters.
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