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Based on this model the robust H∞ control design is proposed to achieve the robust control of NSPDSs via solving linear matrix inequalities (LMIs) instead of an HJII.
We examine the approximation concern for the discrete-time stochastic GRNs with the leakage delays, distributed delays, and probabilistic measurement delays into the problem and model the robust (H_{infty}) state estimator for a class of discrete-time stochastic GRNs.
Compared with the standard PCA neural network model, the robust PCA neural network model has a number of numerical advantages such as the stability and robustness to noise-injected data and the faster convergence of iterations in the training stages than the existing neural network technique.
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Both the deterministic model and the robust model are demonstrated with a real-world bus system.
Spiegelman and Hertzmark recommend using the log-binomial models over the robust Poisson models when convergence is not an issue [ 21].
The next section introduces the WC model and the robust and Lin's variance estimators.
Z-tests were performed using the coefficients of the Poisson model and the robust standard errors.
Another striking feature of the IKMV short-term model is the robust proliferative response induced after NF-κB activation.
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