Artigo Revisado por pares

The learning problem of multi-layer neural networks

2013; Elsevier BV; Volume: 46; Linguagem: Inglês

10.1016/j.neunet.2013.05.006

ISSN

1879-2782

Autores

Jung-Chao Ban, Chih-Hung Chang,

Tópico(s)

Neural dynamics and brain function

Resumo

This manuscript considers the learning problem of multi-layer neural networks (MNNs) with an activation function which comes from cellular neural networks. A systematic investigation of the partition of the parameter space is provided. Furthermore, the recursive formula of the transition matrix of an MNN is obtained. By implementing the well-developed tools in the symbolic dynamical systems, the topological entropy of an MNN can be computed explicitly. A novel phenomenon, the asymmetry of a topological diagram that was seen in Ban, Chang, Lin, and Lin (2009) [J. Differential Equations 246, pp. 552–580, 2009], is revealed.

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