Complexity Analysis of Neural Network Based on Rational Spline Weight Functions

Dai Yuan Zhang; Hai Nan Yang

doi:10.4028/www.scientific.net/AMM.644-650.1658

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 644-650Complexity Analysis of Neural Network Based on...

Complexity Analysis of Neural Network Based on Rational Spline Weight Functions

Abstract:

This paper aims to obtain the time complexity for a new kind of neural network using rational spline weight functions. In this paper, we introduce the architecture of the neural network, and analyze the time complexity in detail. Finally, some examples are also given to verify the theoretical analysis. The results show that the time complexity depends on the number of patterns, the input and out dimensions of the neural networks.

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Periodical:

Applied Mechanics and Materials (Volumes 644-650)

Pages:

1658-1661

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.644-650.1658

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Online since:

September 2014

Authors:

Dai Yuan Zhang*, Hai Nan Yang

Keywords:

Algorithm Complexity, Neural Network (NN), Rational Function, Time Complexity

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* - Corresponding Author

References

[1] Daiyuan Zhang. New Theories and Methods on Neural Networks[M]. Beijing: Tsinghua University Press, (2006).

Google Scholar

[2] Daiyuan Zhang. New Algorithm for Training Feed forward Neural Networks with Cubic Spline weight functions [J]. Beijing: Systems Engineering and Electronics, 2006(9): 1434-1437.

Google Scholar

[3] Serge Dubuc, Bin Han, Jean-Louis Merrien, QunMo. Dyadic C2 Hermite interpolation on a square mesh[J]. Computer Aided Geometric Design, 22 (2005) 727-752.

DOI: 10.1016/j.cagd.2005.03.001

Google Scholar

[4] Daiyuan Zhang. Computer Organization (Second Edition) [M]. Beijing: Tsinghua University Press, (2009).

Google Scholar