## On-line learning in radial basis functions networks

*Freeman, Jason*;

*Saad, David*;

- References (19) 19 references, page 1 of 2
- 1
- 2

Amari, S. (1993). Backpropagation and stochastic gradient descent learning. Neurocomputing, 5, 185-196.

Barber, D., Saad, D., & Sollich, P. (1996). Finite size effects in online learning of multilayer neural networks. Euro. Phys. Lett., 34, 151-156.

Biehl, M., & Schwarze, H. (1995). Learning by online gradient descent. J. Phys. A: Math. Gen., 28, 643.

Bishop, C. (1995). Neural networks for pattern recognition. Oxford: Oxford University Press.

Freeman, J., & Saad, D. (1995a). Learning and generalisation in radial basis function networks. Neural Computation, 7, 1000-1020.

Freeman, J., & Saad, D. (1995b). Radial basis function networks: Generalization in overrealizable and unrealizable scenarios. Neural Networks, 9, 1521- 1529.

Hartman, E., Keeler, J., & Kowalski, J. (1990). Layered neural networks with gaussian hidden units as universal approximators. Neural Computation, 2, 210-215.

Haussler, D. (1994). The probably approximately correct (PAC) and other learning models. In A. Meyrowitz & S. Chipman (Eds.), Foundations of knowledge acquisition: Machine learning (Chap. 9). Boston: Kluwer.

Hertz, J., Krogh, A., & Palmer, R. (1989). Introduction to the theory of neural computation. Reading, MA: Addison-Wesley.

Heskes, T., & Kappen, B. (1991). Learning processes in neural networks. Phys. Rev. A., 44, 2718-2726.

- Metrics 0views in OpenAIRE0views in local repository20downloads in local repository
The information is available from the following content providers:

From Number Of Views Number Of Downloads Aston Publications Explorer - IRUS-UK 0 20

- Download from

- Cite this publication