The learning problem of multi-layer neural networks.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 23727442.
- Also identified by DOI 10.1016/j.neunet.2013.05.006.
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Abstract
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.
Medical subject headings
- Learning
- Models, Neurological
- Neural Networks, Computer