Continuous Stochastic Cellular Automata that Have a Stationary Distribution and No Detailed Balance

dc.creator	Poggio, Tomaso
dc.creator	Girosi, Federico
dc.date	2004-10-04T14:35:49Z
dc.date	2004-10-04T14:35:49Z
dc.date	1990-12-01
dc.date.accessioned	2013-10-09T02:42:24Z
dc.date.available	2013-10-09T02:42:24Z
dc.date.issued	2013-10-09
dc.identifier	AIM-1168
dc.identifier	http://hdl.handle.net/1721.1/6012
dc.identifier.uri	http://koha.mediu.edu.my:8181/xmlui/handle/1721
dc.description	Marroquin and Ramirez (1990) have recently discovered a class of discrete stochastic cellular automata with Gibbsian invariant measures that have a non-reversible dynamic behavior. Practical applications include more powerful algorithms than the Metropolis algorithm to compute MRF models. In this paper we describe a large class of stochastic dynamical systems that has a Gibbs asymptotic distribution but does not satisfy reversibility. We characterize sufficient properties of a sub-class of stochastic differential equations in terms of the associated Fokker-Planck equation for the existence of an asymptotic probability distribution in the system of coordinates which is given. Practical implications include VLSI analog circuits to compute coupled MRF models.
dc.format	6 p.
dc.format	35936 bytes
dc.format	134518 bytes
dc.format	application/octet-stream
dc.format	application/pdf
dc.language	en_US
dc.relation	AIM-1168
dc.subject	MRFs
dc.subject	cellular automata
dc.subject	Fokker-Planck
dc.subject	VLSI analog circuits
dc.title	Continuous Stochastic Cellular Automata that Have a Stationary Distribution and No Detailed Balance

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