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Multi-layered greedy network-growing algorithm: extension of greedy network-growing algorithm to multi-layered networks.

Ryotaro Kamimura
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Abstract

In this paper, we extend our greedy network-growing algorithm to multi-layered networks. With multi-layered networks, we can solve many complex problems that single-layered networks fail to solve. In addition, the network-growing algorithm is used in conjunction with teacher-directed learning that produces appropriate outputs without computing errors between targets and outputs. Thus, the present algorithm is a very efficient network-growing algorithm. The new algorithm was applied to three problems: the famous vertical-horizontal lines detection problem, a medical data problem and a road classification problem. In all these cases, experimental results confirmed that the method could solve problems that single-layered networks failed to. In addition, information maximization makes it possible to extract salient features in input patterns.

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AlgorithmsArtificial IntelligenceComputational BiologyElectronic Data ProcessingHemodynamicsHumansImage Processing, Computer-AssistedNeural Networks, ComputerProbability LearningJournal Article

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BibTeXRIS

Ryotaro Kamimura. 2004. Multi-layered greedy network-growing algorithm: extension of greedy network-growing algorithm to multi-layered networks.. https://doi.org/10.1142/s012906570400184x

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