A hybrid training method for B-spline neural networks

Cabrita, Cristiano Lourenço; Botzheim, J.; Ruano, Antonio; Kóczy, László T.

http://hdl.handle.net/10400.1/87

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Authors

Cabrita, Cristiano Lourenço

Botzheim, J.

Ruano, Antonio

Kóczy, László T.

Abstract(s)

Current and past research has brought up new views related to the optimization of neural networks. For a fixed structure, second order methods are seen as the most promising. From previous works we have shown how second order methods are of easy applicability to a neural network. Namely, we have proved how the Levenberg-Marquard possesses not only better convergence but how it can assure the convergence to a local minima. However, as any gradient-based method, the results obtained depend on the startup point. In this work, a reformulated Evolutionary algorithm - the Bacterial Programming for Levenberg-Marquardt is proposed, as an heuristic which can be used to determine the most suitable starting points, therefore achieving, in most cases, the global optimum.