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Approximate Interpolation by Neural Networks with the Inverse Multiquadric Functions

2007
For approximate interpolation, a type of single-hidden layer feedforward neural networks with the inverse multiquadric activation function is presented in this paper. We give a new and quantitative proof of the fact that a single layer neural networks with n+1 hidden neurons can learn n + 1 distinct samples with zero error.
openaire   +1 more source

Solution of stokes flow problem using biharmonic equation formulation and multiquadrics method

Lobachevskii Journal of Mathematics, 2016
R F Mardanov, S K Zaripov
exaly  

Natural frequencies of FSDT cross-ply composite shells by multiquadrics

Composite Structures, 2007
C M C Roque, Renato Natal Jorge
exaly  

Modelling cross-ply laminated elastic shells by a higher-order theory and multiquadrics

Computers and Structures, 2006
C M C Roque, Renato Natal Jorge
exaly  

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