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Approximate Interpolation by Neural Networks with the Inverse Multiquadric Functions
2007For 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.
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Solution of stokes flow problem using biharmonic equation formulation and multiquadrics method
Lobachevskii Journal of Mathematics, 2016R F Mardanov, S K Zaripov
exaly
Inverse Multiquadrics with Optimal Shape Parameter for Stress Analysis of Functionally Graded Plates
Advanced Materials Research, 2015Wei Ping Zhao
exaly
Natural frequencies of FSDT cross-ply composite shells by multiquadrics
Composite Structures, 2007C M C Roque, Renato Natal Jorge
exaly
Modelling cross-ply laminated elastic shells by a higher-order theory and multiquadrics
Computers and Structures, 2006C M C Roque, Renato Natal Jorge
exaly

