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The main advantage of the proposed method is investigating a global approximation for the spatial and temporal discretizations.
Impact force is divided by the head mass, to produce a "global approximation", a single-generalised head response acceleration value.
In the following we establish a global approximation theorem by means of Ditzian-Totik modulus of smoothness.
A global approximation theorem by means of the Ditzian-Totik modulus of smoothness and a Voronovskaja type theorem are proved.
We establish a global approximation theorem in terms of second order modulus of continuity and a direct approximation theorem by means of the Ditzian Totik modulus of smoothness.
Due to the use of the fundamental solution as basis functions, the method leads to a global approximation scheme in both spatial and time domains.
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For this reason, a kernel-based local approximation, instead of a global approximator like a neural network, is used to interpolate the cost-to-go values.
Afterward, the derived modal approximation sets are used to compute global predominant modes by correlation of its temporal coefficients, which yields to a refined global approximation of local and inter-area oscillations, and a model-order reduction removing spurious modes.
As most of the matrices built for proteins, an empirical estimation gives a very good global approximation.
The compromise programming problem is solved by an efficient procedure that combines a local statistical linearization approach, modal analysis, global approximation concepts, and a sequential optimization scheme.
We paste all the local HDMR approximations together to form a global HDMR approximation.
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