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According to the Lyapunov function method and mathematical analysis technique, the results are analytically proved.
Based on the Lyapunov function method and mathematical analysis technique, several synchronization criteria are derived.
Two sufficient conditions for achieving synchronization are derived based on Lyapunov function method and mathematical analysis technique.
Based on the Lyapunov function method and mathematical analysis technique, several sufficient conditions for achieving synchronization are derived.
Based on the Lyapunov function method and mathematical analysis technique, two synchronization criteria with respect to the impulsive gains and intervals are analytically derived.
In this section a mathematical analysis technique based on the eigenvalue of the matrix is applied to verify condition on the stability for the meshless method.
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Statistical and mathematical analysis techniques are still important as they play a critical role in developing and testing the ABM.
Among mathematical analysis techniques, Artificial Neural Network (ANN) offers superior handling over inherent non-linearity of seismic data.
The algebraic procedures include differencing, ratioing, indexes (like Normalized Difference Vegetation Index – NDVI), while the mathematical analysis techniques include data transformations (like Principal Component Analysis - PCA, Tasselled Cap Transform – TCT, Multivariate Alteration Detector - MAD), Artificial Neural Network (ANN) analysis, fuzzy logic, Bayesian network and others.
Genetic algorithms (GA) is another important development in mathematical analysis; a stochastic technique for solving a variety of problems from engineering to finance.
The RSM optimization process involves the following steps: (1) performing statistically designed experiments, (2) estimating the coefficients of a mathematical model using regression analysis technique, and (3) predicting the response and checking the adequacy of the model.
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