论文信息 - Probabilistic Cellular Automata

Probabilistic Cellular Automata

In spite of the recent progress made in understanding the non-linear dynamics of systems with few degrees of freedom, little is known about the time evolution of more complex structures. Systems with many degrees of freedom, which are pervasive in both the natural and artificial worlds, give rise to properties such as self-organization and computation which, in many cases, seem quite immune to external perturbations. Typical examples are found in biological organisms and modern computing structures, where the intractability of their dynamical behavior is partly linked to our limited knowledge about the global properties of solutions of non-linear partial differential equations.

B. A. Huberman | B. Huberman

[1] B. A. Huberman,et al. Adaptation and self-repair in parallel computing structures , 1984 .

[2] L. Knopoff,et al. A model for repetitive cycles of large earthquakes , 1983 .

[3] B. Huberman,et al. Digital dynamics and the simulation of magnetic systems , 1983 .

[4] B. A. Huberman,et al. Nature of time in Monte Carlo processes , 1984 .

[5] B. Huberman,et al. Dynamic behavior of nonlinear networks , 1983 .

[6] Ryogo Kubo,et al. Dynamics of the Ising Model near the Critical Point. I , 1968 .

[7] B. A. Huberman,et al. Theory of intermittency , 1982 .

[8] Kerry E Sieh,et al. Prehistoric large earthquakes produced by slip on the San Andreas Fault at Pallett Creek, California , 1978 .

[9] R. Glauber. Time‐Dependent Statistics of the Ising Model , 1963 .

[10] D. R. Smith,et al. Maintained Activity in Neural Nets , 1962, JACM.

[11] B. A. Huberman,et al. Power spectra of strange attractors , 1981 .

[12] W. D. Stuart,et al. Earthquake instability on a strike‐slip fault , 1979 .

[13] Françoise Fogelman-Soulié,et al. Specific roles of the different Boolean mappings in random networks , 1982 .