NDLI: Delay-dependent filtering for stochastic nonlinear genetic regulatory networks with time-varying delays and extrinsic noises

Content Provider	IEEE Xplore Digital Library
Author	Hosseini, N.S. Ozgoli, S.
Copyright Year	2013
Description	Author affiliation: Sch. of Electr. & Comput. Eng., Tarbiat Modares Univ., Tehran, Iran (Hosseini, N.S.; Ozgoli, S.)
Abstract	In this paper, the delay-dependent filtering problem is investigated for a more realistic nonlinear genetic regulatory network (GRN) with time-varying delays, stochastic intrinsic noises and extrinsic noise, where the stochastic noises exist in both the state dynamics and measurement equations. The purpose of the addressed filtering problem is to estimate the true concentrations of gene products such as mRNAs and proteins. Specifically, we are interested in designing a delay-dependent $L_{2}-L_{∞}$ linear filter such that for all admissible nonlinearities, time-varying delays as well as intrinsic and extrinsic noises, the filtering error dynamics is asymptotically mean square stable with a prescribed $L_{2}-L_{∞}$ attenuation level. The delay decomposition approach is first used to derive sufficient conditions in the form of linear matrix inequalities (LMIs) that guarantee the desired filtering performance, and the filter gains are then characterized as the solution to a set of LMIs. Finally, a simulation example is given to verify the effectiveness of the theoretical results.
Starting Page	1
Ending Page	6
File Size	756018
Page Count	6
File Format	PDF
ISBN	9781467356343
DOI	10.1109/IranianCEE.2013.6599540
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-05-14
Publisher Place	Iran
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Proteins L2–L∞ filter Maximum likelihood detection Stochastic noise Genetic regulatory network Noise Time-varying delay Nonlinear filters Delays Mathematical model
Content Type	Text
Resource Type	Article

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