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Another work from Hu and Davis [14] uses co-occurrence matrices techniques and SVM to classify plankton.
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The delay-dependent criteria guaranteeing global asymptotical stability for the error dynamical complex networks in terms of Liner Matrix Inequalities (LMIs) are derived based on free-weighting matrices technique and Lyapunov function.
Concentrations were determined using a combination of singular value decomposition matrix techniques and fitting of rotational line sequences.
In order to effectively exploit efficient sparse matrix techniques and have minimum storage requirements, a two-loop iterative method is proposed.
Although we used ASReml to implement a PQL version of the DHGLM algorithm, any REML software that uses sparse matrix techniques and produces leverages should be suitable.
It uses four basic concepts, namely, goal based domain requirements analysis, Analytical Hierarchy Process, Matrix technique, and architecture styles.
The weight matrix W can be calculated by linear inverse matrix technique and used for mapping between the source and target feature vectors.
The numerical results indicate that the algorithms based on a preconditioned sparse matrix technique and on a specially designed algorithm for the particular problem under consideration perform best.
Then, based on novel matrix decoupling technique, improved free-weighting matrix technique and piecewise Lyapunov Krasovskii function (PLKF), a new delay-dependent H∞ fuzzy static output feedback controller design approach is first derived for the switching fuzzy stochastic system.
Due to the fact that the algorithm is based on GAs, we use a hierarchical structure to merge the conditions of Hurwitz testing matrix technique and average performance constraint into a fitness function which is called Hierarchical Fitness Function Structure (HFFS).
The design procedure involves Linear Matrix Inequality techniques and the generalized structured singular value μg.
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