A note on the identifiability of the conditional expectation for the mixtures of neural networks

  • We consider a generalized mixture of nonlinear AR models, a hidden Markov model for which the autoregressive functions are single layer feedforward neural networks. The non trivial problem of identifiability, which is usually postulated for hidden Markov models, is addressed here.

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Metadaten
Author:Jürgen Franke, Jean-Pierre Stockis, Joseph Tadjuidje Kamgaing
URN (permanent link):urn:nbn:de:hbz:386-kluedo-14760
Serie (Series number):Report in Wirtschaftsmathematik (WIMA Report) (104)
Document Type:Preprint
Language of publication:English
Year of Completion:2007
Year of Publication:2007
Publishing Institute:Technische Universität Kaiserslautern
Tag:Identifiability; Mixture Models ; Neural networks
Faculties / Organisational entities:Fachbereich Mathematik
DDC-Cassification:510 Mathematik

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