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This book offers an essential introduction to the latest advances in delayed genetic regulatory networks (GRNs) and presents cutting-edge work on the analysis and design of delayed GRNs in which the system parameters are subject to uncertain, stochastic and/or parameter-varying changes. Specifically, the types examined include delayed switching GRNs, delayed stochastic GRNs, delayed reaction-diffusion GRNs, delayed discrete-time GRNs, etc. In addition, the solvability of stability analysis, control and estimation problems involving delayed GRNs are addressed in terms of linear matrix inequality or M-matrix tests. The book offers a comprehensive reference guide for researchers and practitioners working in system sciences and applied mathematics, and a valuable source of information for senior undergraduates and graduates in these areas. Further, it addresses a gap in the literature by providing a unified and concise framework for the analysis and design of delayed GRNs.
This book offers an essential introduction to the latest advances in delayed genetic regulatory networks (GRNs) and presents cutting-edge work on the analysis and design of delayed GRNs in which the system parameters are subject to uncertain, stochastic and/or parameter-varying changes. Specifically, the types examined include delayed switching GRNs, delayed stochastic GRNs, delayed reaction-diffusion GRNs, delayed discrete-time GRNs, etc. In addition, the solvability of stability analysis, control and estimation problems involving delayed GRNs are addressed in terms of linear matrix inequality or M-matrix tests. The book offers a comprehensive reference guide for researchers and practitioners working in system sciences and applied mathematics, and a valuable source of information for senior undergraduates and graduates in these areas. Further, it addresses a gap in the literature by providing a unified and concise framework for the analysis and design of delayed GRNs.
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