A Sampled-data Approach to Robust H∞ State Estimation for Genetic Regulatory Networks with Random Delays-Reference-Cited by-同舟云学术

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A Sampled-data Approach to Robust H∞ State Estimation for Genetic Regulatory Networks with Random Delays

Published:2018-04 Issue:2 Volume:16 Page:491-504
ISSN:1598-6446
Container-title:International Journal of Control, Automation and Systems
language:en
Short-container-title:Int. J. Control Autom. Syst.

Author:

Chen Weilu,Chen Dongyan,Hu Jun,Liang Jinling,Dobaie Abdullah M.

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Control and Systems Engineering

Link

http://link.springer.com/article/10.1007/s12555-017-0106-2/fulltext.html

Reference45 articles.

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2. R. Somogyi and C. A. Sniegoski, “Modeling the complexity of genetic networks: understanding multigenic and pleiotropic regulation,” Complexity, vol. 1, no. 6, pp. 45–63, July 1996.

3. P. Smolen, D. A. Baxter, and J. H. Byrne, “Mathematical modeling of gene networks,” Neuron, vol. 26, no. 3, pp. 567–580, July 2000.

4. J. Hu, Z. Wang, B. Shen, and H. Gao, “Gain-constrained recursive filtering with stochastic nonlinearities and probabilistic sensor delays,” IEEE Trans. on Signal Processing, vol. 61, no. 5, pp. 1230–1238, March 2013. [click]

5. H. R. Karimi, “A linear matrix inequality approach to robust fault detection filter design of linear systems with mixed time-varying delays and nonlinear perturbations,” Journal of Franklin Institute, vol. 347, no. 6, pp. 957–973, August 2010.

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