scholarly journals Learning to combine multi-sensor information for context dependent state estimation

Author(s):  
Alexandre Ravet ◽  
Simon Lacroix ◽  
Gautier Hattenberger ◽  
Bertrand Vandeportaele
2015 ◽  
Vol 2015 ◽  
pp. 1-18 ◽  
Author(s):  
M. J. Park ◽  
O. M. Kwon ◽  
Ju H. Park ◽  
S. M. Lee ◽  
E. J. Cha

This paper considers the problem of delay-dependent state estimation for neural networks with time-varying delays and stochastic parameter uncertainties. It is assumed that the parameter uncertainties are affected by the environment which is changed with randomly real situation, and its stochastic information such as mean and variance is utilized in the proposed method. By constructing a newly augmented Lyapunov-Krasovskii functional, a designing method of estimator for neural networks is introduced with the framework of linear matrix inequalities (LMIs) and a neural networks model with stochastic parameter uncertainties which have not been introduced yet. Two numerical examples are given to show the improvements over the existing ones and the effectiveness of the proposed idea.


2016 ◽  
Vol 51 (1) ◽  
pp. 259-285 ◽  
Author(s):  
Sarah Calderwood ◽  
Kevin McAreavey ◽  
Weiru Liu ◽  
Jun Hong

2014 ◽  
Vol 129 ◽  
pp. 392-400 ◽  
Author(s):  
S. Lakshmanan ◽  
K. Mathiyalagan ◽  
Ju H. Park ◽  
R. Sakthivel ◽  
Fathalla A. Rihan

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