Acceso abierto

Hyperbolic Tangent Like Relied Banach Space Valued Neural Network Multivariate Approximations


Cite

G.A. Anastassiou, Moments in Probability and Approximation Theory, Pitman Research Notes in Math., Vol. 287, Longman Sci. & Tech., Harlow, U.K., 1993.Search in Google Scholar

G.A. Anastassiou, Rate of convergence of some neural network operators to the unitunivariate case, J. Math. Anal. Appl. 212 (1997), 237-262.Search in Google Scholar

G.A. Anastassiou, Quantitative Approximations, Chapman&Hall/CRC, Boca Raton, New York, 2001.Search in Google Scholar

G.A. Anastassiou, Inteligent Systems: Approximation by Artificial Neural Networks, Intelligent Systems Reference Library, Vol. 19, Springer, Heidelberg, 2011.Search in Google Scholar

G.A. Anastassiou, Univariate hyperbolic tangent neural network approximation, Mathematics and Computer Modelling 53 (2011), 1111-1132.Search in Google Scholar

G.A. Anastassiou, Multivariate hyperbolic tangent neural network approximation, Computers and Mathematics 61 (2011), 809-821.Search in Google Scholar

G.A. Anastassiou, Multivariate sigmoidal neural network approximation, Neural Networks 24 (2011), 378-386.Search in Google Scholar

G.A. Anastassiou, Univariate sigmoidal neural network approximation, J. Comput. Anal. Appl. 14 (4) (2012), 659-690.Search in Google Scholar

G.A. Anastassiou, Approximation by neural networks iterates, Advances in Applied Mathematics and Approximation Theory, pp. 1-20, Springer Proceedings in Math. & Stat., Springer, New York, 2013, Eds. G. Anastassiou, O. Duman.Search in Google Scholar

G.A. Anastassiou, Intel ligent Systems II: Complete Approximation by Neural Network Operators, Springer, Heidelberg, New York, 2016.Search in Google Scholar

G.A. Anastassiou, Intelligent Computations: Abstract Fractional Calculus, Inequalities, Approximations, Springer, Heidelberg, New York, 2018.Search in Google Scholar

G.A. Anastassiou, General Multivariate arctangent function activated neural network approximations, J. Numer. Anal. Approx. Theory 51 (1) (2022), 37-66.Search in Google Scholar

G.A. Anastassiou, General sigmoid based Banach space valued neural network approximation, J. Comput. Anal. Appl., accepted for publication, 2022.Search in Google Scholar

H. Cartan, Differential Calculus, Hermann, Paris, 1971.Search in Google Scholar

Z. Chen, F. Cao, The approximation operators with sigmoidal functions, Computers and Mathematics with Applications 58 (2009), 758-765.Search in Google Scholar

D. Costarelli, R. Spigler, Approximation results for neural network operators activated by sigmoidal functions, Neural Networks 44 (2013), 101-106.Search in Google Scholar

D. Costarelli, R. Spigler, Multivariate neural network operators with sigmoidal activation functions, Neural Networks 48 (2013), 72-77.Search in Google Scholar

S. Haykin, Neural Networks: A Comprehensive Foundation (2 ed.), Prentice Hall, New York, 1998.Search in Google Scholar

W. McCulloch, W. Pitts, A logical calculus of the ideas immanent in nervous activity, Bulletin of Mathematical Biophysics 7 (1943), 115-133.Search in Google Scholar

T.M. Mitchell, Machine Learning, WCB-McGraw-Hill, New York, 1997.Search in Google Scholar

L.B. Rall, Computational Solution of Nonlinear Operator Equations, John Wiley & Sons, New York, 1969. Search in Google Scholar

eISSN:
1841-3307
Idioma:
Inglés
Calendario de la edición:
Volume Open
Temas de la revista:
Mathematics, General Mathematics