Research of the First Kind of Padé Weight Function Neural Networks

Dai Yuan Zhang; Yan Xu

doi:10.4028/www.scientific.net/AMR.989-994.2663

Paper Titles

An Efficient Methodology for Estimating Interconnect Crosstalk Noise in Deep-Submicron Technologies
p.2647

Feature-Based Real-Time Visual SLAM Using Kinect
p.2651

Research Progress in Topological Relations of Objects with Holes
p.2655

Complexity Research on Second Class Orthogonal Weight Function Neural Networks
p.2659

Research of the First Kind of Padé Weight Function Neural Networks
p.2663

Time Complexity Research on the Second Type Neural Networks of Padé Weight Functions
p.2667

Research on Safety Comprehensive Assessment Method for Air Traffic Control Based on RBF Neural Network
p.2671

On the Application of Ant Colony Neural Network for the Highway Traffic Safety Facilities System
p.2675

Numerical Simulation of Cook-Off for Passive RDX
p.2679

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 989-994Research of the First Kind of Padé Weight...

Research of the First Kind of Padé Weight Function Neural Networks

Abstract:

Traditional algorithms of training neural networks have some weakness. A new approach using weight function neural networks was proposed in recent years, which overcomes the shortcomings of traditional neural networks. This paper takes Padé approximation as weight functions and we get the method of how to find the Padé weight functions with given samples. Then complexity is also analysed in detailed in this paper. Finally simulation experiments are done to verify the results.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 989-994)

Pages:

2663-2666

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.989-994.2663

Citation:

Cite this paper

Online since:

July 2014

Authors:

Dai Yuan Zhang*, Yan Xu

Keywords:

Neural Network (NN), Pade Approximation, Spline Weight Function, Time Complexity

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] Daiyuan Zhang. Neural Network New Theory and Method [M]. Beijing: Tsinghua University Press, (2006).

Google Scholar

[2] Yi Ding, Qi Feng. A modular neural network architecture with concept [J]. Neurocomputing, 2014, 125( 11): 3-6.

Google Scholar

[3] Daiyuan Zhang. A new kind of algorithm in Spline weight function neural network [J]. Systems Engineering and Electronics, 2006, 28(9): 1434-1446.

Google Scholar

[4] Yu Yao. Research of Padé weight function neural network and the optimal routing algorithm[D]. Nanjing: NJUPT, (2010).

Google Scholar

[5] Paul Sablonnière. B-splines and Hermite-Padé approximants to the exponential function[J]. Journal of Computational and Applied Mathematics, 2008, 219( 2): 509-517.

DOI: 10.1016/j.cam.2007.05.014

Google Scholar

[6] Guido Claessens. On the Newton-Padé approximation problem[J]. Journal of Approximation Theory, 1978, 22: 150-160.

DOI: 10.1016/0021-9045(78)90062-x

Google Scholar

[7] Ognyan Kounchev, Hermann Render. Padé approximation for a multivariate Markov transform[J]. Journal of Computational and Applied Mathematics, 2008, 219( 2): 416-430.

DOI: 10.1016/j.cam.2007.05.004

Google Scholar