The estimate for approximation error of neural network with two weights.
The neural network with two weights is constructed and its approximation ability to any continuous functions is proved. For this neural network, the activation function is not confined to the odd functions. We prove that it can limitlessly approach any continuous function from limited close subset o...
| Publicado en: | Scientific World Journal pp. 935312 - 935313 |
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| Autores principales: | , |
| Formato: | Journal Article |
| Publicado: |
Wiley-Blackwell
2013
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=104012915&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104012915 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 1537744X 1BX5 jtl: Scientific World Journal issn: 1537744X maglogo: N pubinfo: dt: 2013 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 104012915 NLM24470796 2012459525 10.1155/2013/935312 NLM24470796 PMC3891538 104012915 ppf: 935312 ppct: 1 formats: tig: atl: The estimate for approximation error of neural network with two weights. aug: au: Zeng, Fanzi Tang, Yuting affil: Key Laboratory for Embedded and Network Computing of Hunan Province, Hunan University, Changsha 410082, China. sug: subj: Algorithms Neural Networks (Computer) ab: The neural network with two weights is constructed and its approximation ability to any continuous functions is proved. For this neural network, the activation function is not confined to the odd functions. We prove that it can limitlessly approach any continuous function from limited close subset of R(m) to R(n) and any continuous function, which has limit at infinite place, from limitless close subset of R(m) to R(n). This extends the nonlinear approximation ability of traditional BP neural network and RBF neural network. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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