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A novel manifold method of reconstructing dynamically evolving spatial fields is presented for assimilating data from sensor networks in integrated land surface – subsurface, oceanic/lake models.
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As a partition of unity method (PUM), the numerical manifold method (NMM) is capable of constructing global approximation by simply multiplying PU function with local approximation.
All three examples illustrate the superior performance of the manifold method over standard methods in terms of accuracy and computational efficiency.
Moreover, for a special nonlinearity (f x,u =lambda |u|^{q-2}u+|u|^{r-2}u) ((1< q< p< r< p^)), we prove that problem (P) has at least two nonnegative solutions via the Nehari manifold method and a sequence of solutions with negative energy by the dual fountain theorem.
By the theory of normal form and the center manifold method, the direction and stability of the bifurcating periodic solution are discussed.
The proof is similar to the argument of Nehari manifold method [16].
Stable manifold method provides numerical stabilizing solutions of Hamilton-Jacobi equations in nonlinear optimal control theory.
The stable manifold method provides approximate stabilizing solutions of Hamilton-Jacobi (HJ) equations in nonlinear optimal control theory.
The traditional numerical manifold method (NMM) has the advantage of simulating a continuum and a discontinuum in a unified framework based on a dual cover system.
In this study, we developed a FPM flow model by taking full advantage of numerical manifold method (NMM) with independent covers.
In this section, we shall investigate the solvability of boundary value problem (1.1) with the aid of the Nehari manifold method.
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