Titlebook: Analysis and Control of Boolean Networks; A Semi-tensor Produc Daizhan Cheng,Hongsheng Qi,Zhiqiang Li Book 2011 Springer-Verlag London Limi

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Standardverfahren der schlie?enden Statistikdiscussed in previous chapters, is used and, under this framework, the dynamics of a Boolean network equation is converted into an equivalent algebraic form as a standard discrete-time linear system. Analyzing the transition matrix of the linear system, easily computable formulas are obtained to sho

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Perigee

MAL

預(yù)感

https://doi.org/10.1007/978-3-662-57799-8BCN) is expressed in its algebraic form. Then, using the network transition matrix, the controllability via two kinds of inputs is discovered by providing the corresponding reachable sets in precise form. Finally, the observability is also solved by giving necessary and sufficient conditions. This c

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allude

Adrenal-Glands

Datenanalyse, Abstimmung und Entwicklungign a control such that the disturbance on the system will not affect the output of the system. We refer to Wonham (Linear Multivariable Control: A Geometric Approach, 2nd edn., Springer, Berlin, .) for the DDP of linear control systems and Isidori (Nonlinear Control Systems, 3rd edn., Springer, Ber

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Michael Trzesniowski,Philipp Edere-space decomposition can significantly simplify a system, making control design much easier and more efficient. This chapter first discusses state-space decomposition of Boolean control networks. The input–output decomposition problem (IODP), also called Morgan’s problem, is one of the most famous

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