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

Author(s)
Poggio, Tomaso; Girosi, Federico
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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.
Date issued
1990-12-01
URI
http://hdl.handle.net/1721.1/6012
Other identifiers
AIM-1168
Series/Report no.
AIM-1168
Keywords
MRFs, cellular automata, Fokker-Planck, VLSI analog circuits

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