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In this subsection, based on the Lyapunov method, a sufficient criterion of exponential outer synchronization which is easily verifiable is established in the form of coefficients.
By using the Lyapunov stability theory and the adaptive control method, a sufficient projective synchronization criterion for this neutral-type neural network model is derived.
By using the Lyapunov method, a sufficient condition which guarantees that the filtering error system is stochastically stable and satisfies the passive performance is established.
Moreover, by applying the Lyapunov function method, a sufficient condition of couple-group consensus is established in terms of a matrix inequality when the communication topology is switching.
Based on the Lyapunov stability theory and some stochastic system analysis method, a sufficient condition is obtained such that the closed-loop system is asymptotically stable in the mean-square sense and achieves a prescribed H∞ performance level.
(2) using the average dwell time method, a sufficient condition ensuring the exponential stability is obtained, meanwhile, the minimum running time of each subsystem, i.e., the running time of each phase can be calculated.
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Based on the switched system approach and some stochastic system analysis methods, a sufficient condition is obtained such that the filtering error system is exponentially stable in the mean-square sense, and a prescribed H∞ performance level is guaranteed.
As the influence of the strength matching and welding width is ignored in the engineering method for J-integral calculation, the engineering method has a sufficient precision only if the width of welding is comparable to the crack depth.
While the first two methods are potentially applicable to other MHC allotypes, the latter method requires a sufficient number of experimental peptide-MHC structures for the allotype of interest in order to derive the PSSM and so is likely limited to DRB1*0101 at present.
The test resultantly indicated that the present method yielded a sufficient accuracy for any wavenumber.
The shape parameterization approach is based on the Class-Shape Transformation (CST) method with a sufficient degree of Bernstein polynomials to cover a wide range of shapes.
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