Abstract
In this paper, a new kind of neural network is proposed by combining ridgelet with feed-forward neural network (FNN). The network adopts ridgelet as the activation function in hidden layer of a three-layer FNN. Ridgelet is a good basis for describing the directional information in high dimension and it proves to be optimal in representing the functions with hyperplane singularity. So the network can approximate quite a wide range of multivariate functions in a more stable and efficient way, especially those with certain kinds of spatial inhomogeneities. Both theoretical analysis and experimental results of function approximation prove its superiority to wavelet neural network.
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© 2005 Springer-Verlag Berlin Heidelberg
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Yang, S., Wang, M., Jiao, L. (2005). A New Adaptive Ridgelet Neural Network. In: Wang, J., Liao, X., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3496. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427391_61
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DOI: https://doi.org/10.1007/11427391_61
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25912-1
Online ISBN: 978-3-540-32065-4
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