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.
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References
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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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Paul, A., Bhattacharya, P., Maity, S.P. (2014). Comparative Study of Radial Basis Function Neural Network with Estimation of Eigenvalue in Image Using MATLAB. In: Biswas, G., Mukhopadhyay, S. (eds) Recent Advances in Information Technology. Advances in Intelligent Systems and Computing, vol 266. Springer, New Delhi. https://doi.org/10.1007/978-81-322-1856-2_16
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DOI: https://doi.org/10.1007/978-81-322-1856-2_16
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