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A wide class of problems in science and engineering requires mathematical formalization.
It is designed to solve a wide class of problems that arise in the context of theoretical physics.
The abilities of the method to solve a wide class of problems, such as parameter identification, structure identification, prediction, automatic fuzzy rule set generation, are studied.
The inherent capabilities of the design in handling short data records and low-frequency signals allow its applications to a wide class of problems.
The essential insight of Newton and Leibniz was to use Cartesian algebra to synthesize the earlier results and to develop algorithms that could be applied uniformly to a wide class of problems.
By adjusting the effective wavenumber region of the DSC filter, Gibbs oscillations can be removed effectively while the high resolution feature of the spectral method can be retained for a wide class of problems with various boundary conditions.
In the past, sensitivity analysis typically require laborious and error-prone manual computation of derivatives, but with modern automatic differentiation (autograd) and parameter wrapping (paragami), sensitivity analysis can be automated for a wide class of problems.
For example, a wide class of problems can be solved with sinusoidal inputs with the same number of excitation frequencies (over the frequency range as number of estimated parameters.
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This paper presents a generalization of these algorithms to a wider class of problems.
This paper presents a generalization of these algorithms to a wider class of problems, namely a class of parametric piecewise quadratic programs and related problems.
The algorithm is time saving, and it can solve a much wider class of problems with high dimension and complex topological structure.
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CEO of Professional Science Editing for Scientists @ prosciediting.com