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Exact(10)
This approximation is based on a Taylor series approach.
This approximation is based on the fact that and in practice.
This approximation is based on the method described by DeCoursey (1982).
This approximation is based on the solution of the partial differential equations and multi-step estimator-processes of the unknown parameter.
This approximation is based on the observation that one could use a function g (u) to approximate an asymptotic function g∞ via g ∞ = lim s → 0 g s z : = sg s − 1 z.
This approximation is based on the assumption of many scatterers distributed randomly and sparsely (Ishimaru, 1978), and it is expected to give results accurate to the first order in the distribution density (Keller, 1964).
Similar(50)
The exact solution involves rather intricate Bessel functions, whereas the approximation is based on easily computable power series.
Here the approximation is based on shifted Legendre polynomials and the quadrature rule is treated on shifted Legendre Gauss-Lobatto points.
Because the approximation is based on second-order polynomials, it is possible that when the measurement function is not differentiable, the computed nonlinearity value does not represent the nonlinearity well.
The essence of the supercell approximation is based on this fact.
This is largely due to the fact that the analytical approximation is based on asymptotic analytical solution which ignores the stochastic effects due to the finite number of iterations.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com