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Artificial neural networks as approximators of stochastic processes

Autor: M. R. Belli, Massimo Conti, Paolo Crippa, Claudio Turchetti

Publikováno v: Neural networks : the official journal of the International Neural Network Society. 12(4-5)

Artificial Neural Networks (ANNs) must be able to learn by experience from environment. This property can be considered as being closely related to the approximating capabilities of the networks. Unfortunately at present only the ability of ANNs in a

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::68e10c9a51b7e923f9941f94da31a7d5
https://pubmed.ncbi.nlm.nih.gov/12662675

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Artificial Neural Networks as Approximators of Stochastic Processes

Autor: M. R. Belli, Massimo Conti, Claudio Turchetti, Simone Orcioni, Paolo Crippa

Publikováno v: ICANN 98 ISBN: 9783540762638

Artificial (or biological) Neural Networks must be able to form by learning internal memory of the environment to determine decisions and subsequent actions to stimuli. By assuming that environment is essentially stochastic it follows that the mathem

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::6144c9b2dbcc19005d3bc03b666935c5
https://doi.org/10.1007/978-1-4471-1599-1_95

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[Nuclear DNA content of human embryonal fibroblasts (RU-1) in cultures infected with virulent and attenuated strains of rubella virus]

Autor: G, Gerna, C A, Redi, A, Fraschini, M R, Belli

Publikováno v: Rivista di istochimica, normale e patologica. 19(1-4)

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=pmid________::4e807c09a994ab3a83ef3060971a9dd0
https://pubmed.ncbi.nlm.nih.gov/1233676

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