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Comparative Study of Radial Basis Function Neural Network with Estimation of Eigenvalue in Image Using MATLAB

  • Abhisek Paul
  • Paritosh Bhattacharya
  • Santi Prasad Maity
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 266)

Abstract

Radial Basis Functions (RBFs) are very important in neural network. In this paper various Radial Basis Functions of neural network such as Generalized Inverse Multi Quadratic, Generalized Multi Quadratic and Gaussian are compared with matrix of images. Mathematical calculation, comparative study and simulation of Eigen value of matrix show that Gaussian RBF performs better result and gives lesser error compared to the other Radial Basis Functions of neutral network.

Keywords

Gaussian Generalized-multi-quadratic Generalized-inverse-multi-quadratic Neural network Radial basis function 

Notes

Acknowledgments

The authors are so grateful to the anonymous referee for a careful checking of the details and for helpful comments and suggestions that improve this paper.

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Copyright information

© Springer India 2014

Authors and Affiliations

  • Abhisek Paul
    • 1
  • Paritosh Bhattacharya
    • 1
  • Santi Prasad Maity
    • 2
  1. 1.Department of Computer Science and EngineeringNational Institute of TechnologyAgartalaIndia
  2. 2.Department of Information TechnologyBengal Engineering and Science UniversityShibpurIndia

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