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On the Information Transmission Ability of Nonlinear Stochastic Dynamic Networks


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Lab of Control and System Biology, Department of Electrical Engineering, National Tsing Hua University, Hsinchu 30013, Taiwan





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Abstract The major function of dynamic networks is to sense information from the environment and process the information to the downstream. Therefore how to measure the information transmission ability of a dynamic network is an important topic to evaluate network performance. However, the dynamic behavior of a dynamic network is complex and, despite knowledge of network components, interactions and noises, it is a challenge to measure the information transmission ability of a dynamic network, especially a nonlinear stochastic dynamic network. Based on nonlinear stochastic dynamic system theory, the information transmission ability can be investigated by solving a Hamilton-Jacobi inequality HJI-constrained optimization problem. To avoid difficulties associated with solving a complex HJI-constrained optimization problem for information transmission ability, the Takagi-Sugeno T-S fuzzy model is introduced to approximate the nonlinear stochastic dynamic network by interpolating several local linear stochastic dynamic networks so that a HJI-constrained optimization problem can be replaced by the linear matrix inequalities LMIs-constrained optimization problem. The LMI problem can then be efficiently solved for measuring information transmission ability. We found that a more stable robust dynamic network has less information transmission ability, and vice versa. Finally, an example of a biochemical network in cellular communication is given to illustrate the measurement of information transmission ability and to confirm the results by using Monte Carlo simulations. View Full-Text

Keywords: information transmission ability; nonlinear stochastic dynamic network; HJI; LMI, T-S fuzzy model; network performance information transmission ability; nonlinear stochastic dynamic network; HJI; LMI, T-S fuzzy model; network performance





Autor: Bor-Sen Chen * and Ying-Po Lin

Fuente: http://mdpi.com/



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