Continuous Stochastic Cellular Automata that Have a Stationary Distribution and No Detailed Balance
dc.date.accessioned | 2004-10-04T14:35:49Z | |
dc.date.accessioned | 2018-11-24T10:11:31Z | |
dc.date.available | 2004-10-04T14:35:49Z | |
dc.date.available | 2018-11-24T10:11:31Z | |
dc.date.issued | 1990-12-01 | en_US |
dc.identifier.uri | http://hdl.handle.net/1721.1/6012 | |
dc.identifier.uri | http://repository.aust.edu.ng/xmlui/handle/1721.1/6012 | |
dc.description.abstract | 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. | en_US |
dc.format.extent | 6 p. | en_US |
dc.format.extent | 35936 bytes | |
dc.format.extent | 134518 bytes | |
dc.language.iso | en_US | |
dc.subject | MRFs | en_US |
dc.subject | cellular automata | en_US |
dc.subject | Fokker-Planck | en_US |
dc.subject | VLSI analog circuits | en_US |
dc.title | Continuous Stochastic Cellular Automata that Have a Stationary Distribution and No Detailed Balance | en_US |
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