7,426 research outputs found
Exact mean field inference in asymmetric kinetic Ising systems
We develop an elementary mean field approach for fully asymmetric kinetic
Ising models, which can be applied to a single instance of the problem. In the
case of the asymmetric SK model this method gives the exact values of the local
magnetizations and the exact relation between equal-time and time-delayed
correlations. It can also be used to solve efficiently the inverse problem,
i.e. determine the couplings and local fields from a set of patterns, also in
cases where the fields and couplings are time-dependent. This approach
generalizes some recent attempts to solve this dynamical inference problem,
which were valid in the limit of weak coupling. It provides the exact solution
to the problem also in strongly coupled problems. This mean field inference can
also be used as an efficient approximate method to infer the couplings and
fields in problems which are not infinite range, for instance in diluted
asymmetric spin glasses.Comment: 10 pages, 7 figure
Sentient Networks
In this paper we consider the question whether a distributed network of
sensors and data processors can form "perceptions" based on the sensory data.
Because sensory data can have exponentially many explanations, the use of a
central data processor to analyze the outputs from a large ensemble of sensors
will in general introduce unacceptable latencies for responding to dangerous
situations. A better idea is to use a distributed "Helmholtz machine"
architecture in which the collective state of the network as a whole provides
an explanation for the sensory data.Comment: PostScript, 14 page
Minimum Energy Information Fusion in Sensor Networks
In this paper we consider how to organize the sharing of information in a
distributed network of sensors and data processors so as to provide
explanations for sensor readings with minimal expenditure of energy. We point
out that the Minimum Description Length principle provides an approach to
information fusion that is more naturally suited to energy minimization than
traditional Bayesian approaches. In addition we show that for networks
consisting of a large number of identical sensors Kohonen self-organization
provides an exact solution to the problem of combining the sensor outputs into
minimal description length explanations.Comment: postscript, 8 pages. Paper 65 in Proceedings of The 2nd International
Conference on Information Fusio
Roles of Dry Friction in Fluctuating Motion of Adiabatic Piston
The motion of an adiabatic piston under dry friction is investigated to
clarify the roles of dry friction in non-equilibrium steady states. We clarify
that dry friction can reverse the direction of the piston motion and causes a
discontinuity or a cusp-like singularity for velocity distribution functions of
the piston. We also show that the heat fluctuation relation is modified under
dry friction.Comment: 8 pages, 4 figure
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