Period-two cycles in a feedforward layered neutral network model with symmetric sequence processing

dc.contributor.author	Metz, Fernando Lucas	pt_BR
dc.contributor.author	Theumann, Walter Karl	pt_BR
dc.date.accessioned	2014-08-22T02:11:09Z	pt_BR
dc.date.issued	2007	pt_BR
dc.identifier.issn	1539-3755	pt_BR
dc.identifier.uri	http://hdl.handle.net/10183/101623	pt_BR
dc.description.abstract	The effects of dominant sequential interactions are investigated in an exactly solvable feedforward layered neural network model of binary units and patterns near saturation in which the interaction consists of a Hebbian part and a symmetric sequential term. Phase diagrams of stationary states are obtained and a phase of cyclic correlated states of period two is found for a weak Hebbian term, independently of the number of condensed patterns c.	en
dc.format.mimetype	application/pdf	pt_BR
dc.language.iso	eng	pt_BR
dc.relation.ispartof	Physical review. E, Statistical, nonlinear, and soft matter physics. Vol. 75, no. 4 (Apr. 2007), 041907, 7 p.	pt_BR
dc.rights	Open Access	en
dc.subject	Redes neurais	pt_BR
dc.title	Period-two cycles in a feedforward layered neutral network model with symmetric sequence processing	pt_BR
dc.type	Artigo de periódico	pt_BR
dc.identifier.nrb	000604046	pt_BR
dc.type.origin	Estrangeiro	pt_BR

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