Title :
Sampled-Data Control for State Estimation of Static Neural Networks
Author :
Jung, H.Y. ; Park, Jae Hyo ; Lee, S.M.
Author_Institution :
Nonlinear Dynamics Group, Yeungnam Univ., Gyeongsan, South Korea
Abstract :
In this brief, the problem of sampled-data state estimation for static neural network is investigated. The state-feedback control design method we develop in this paper relies on the information from the sampled states. By constructing a class of Lyapunov function and combining with some inequality, a sufficient condition for the existence of state estimator is derived.
Keywords :
Lyapunov methods; control system synthesis; neural nets; state estimation; state feedback; Lyapunov function; sampled-data control; sampled-data state estimation; state estimator; state-feedback control design method; static neural networks; sufficient condition; Biological neural networks; Delays; Neurons; Stability analysis; State estimation; Vectors; Neural networks; Sampled-data; State estimation;
Conference_Titel :
Computational Science and Computational Intelligence (CSCI), 2014 International Conference on
Conference_Location :
Las Vegas, NV
DOI :
10.1109/CSCI.2014.144
