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We prove that the criterion of Yuan and Shu can be satisfied by a wide class of basis functions, including the well-known basis functions such as trigonometric and exponential polynomials.
We present a fast multipole algorithm for the evaluation of pairwise interaction through the radial basis functions such as 1/ra, √r2+a2 and 1/√r2+a2 (with a > 0) in both two and three dimensions.
The slip distributions are represented by the superposition of the basis functions such as the box-car basis (Suzuki et al., 2011; Yoshida et al., 2011) and the triangle basis (Ide et al., 2011; Miyazaki et al., 2011).
Within this context, whenever it is possible to exercise the option, the continuation value can be expressed as a linear combination of orthogonal basis functions, such as Power, Legendre and Laguerre polynomials.
The hidden layer nodes use radial basis functions such as a Gaussian membership while the output layer is a weighted sum of the outputs from the hidden layer nodes.
To allow for more interregional variation in HRFs, linear combinations of more general basis functions such as the Fourier set can be used [Friston et al., 1995a].
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The drawback of requiring a large number of parameters in the representation of these models can be circumvented by describing every kernel using an orthonormal basis of functions, such as the Kautz basis.
This trend of choosing thermodynamic functions for chemical reactions under specific controlled thermodynamic parameters is the basis for functions such as the free energy of Helmholtz and the enthalpy thermodynamic function.
It belongs to the group of special functions, so its testing is performed on the basis of known functions such as the -gamma, -psi, - beta, anderf- error function.
It belongs to the group of special functions, so its testing is being performed on the basis of known functions such as gamma, psi, and the like, so that its generalized, explicit form is the following [4].
This facilitation may represent the neural basis for important functions such as imitation or learning by observation.
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