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Titlebook: Statistical Physics, Automata Networks and Dynamical Systems; Eric Goles,Servet Martínez Book 1992 Springer Science+Business Media Dordrec

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樓主: Fatuous
11#
發(fā)表于 2025-3-23 09:41:17 | 只看該作者
Automata Networks Strategies for Optimization Problems,The goal of this work is to show that a positive automata iteration is the natural hill-climbing strategy of a subnorm or norm optimization problem.
12#
發(fā)表于 2025-3-23 14:58:43 | 只看該作者
On the R.E.M. and the G.R.E.M.,Random Energy model and generalized Random Energy model was introduced by B. Derrida [1], [2], [3], [4] as simple and solvable models for spin glasses.
13#
發(fā)表于 2025-3-23 19:30:25 | 只看該作者
Regular and Chaotic Behaviour of Dynamical Systems,me phase space which is usually a vector space or a manifold. The time evolution is then given by a vector field (continuous time) or a mapping (discrete time). The main goal is to understand qualitatively and if possible quantitatively the long time behaviour of these systems.
14#
發(fā)表于 2025-3-23 23:20:31 | 只看該作者
Shocks in the Burgers Equation and the Asymmetric Simple Exclusion Process, in the absence of other cars, the velocity of a single car is .. Due to the presence of other cars this velocity can be lower. The variation of density at . in an infinitesimal time interval . is given by the number of cars entering in the infinitesimal interval (., . + .) that is .(1 - .)) minus t
15#
發(fā)表于 2025-3-24 04:36:12 | 只看該作者
Two Chosen Examples for Fractals: One Deterministic, the Other Random,ion can arise in various contexts. One could imagine the wheels to be eddies on the surface of an incompressible fluid and then ask if the fluid motion can be totally decomposed into stable eddies. Or, one could think of mechanical roller bearings between two moving surfaces, like two tectonic plate
16#
發(fā)表于 2025-3-24 09:02:34 | 只看該作者
A Brief Account of Statistical Theories of Learning and Generalization in Neural Networks,mber of internal states σ.. At (discrete) time . the overall state .(.) of the network is defined as the set of states that the units take at this very time : .(.) = {σ.7,(.)}. The time evolution of the network is driven by a dynamics which depends on a number of parameters {.}. The parameters {.},
17#
發(fā)表于 2025-3-24 13:45:02 | 只看該作者
Shocks in the Burgers Equation and the Asymmetric Simple Exclusion Process,ty at . in an infinitesimal time interval . is given by the number of cars entering in the infinitesimal interval (., . + .) that is .(1 - .)) minus the number of cars exiting that interval: θ.(.)(1..(. + .,.)) (note that 1 - . is the density of free space in the interval). Hence the density must satisfy the equation
18#
發(fā)表于 2025-3-24 16:22:44 | 只看該作者
19#
發(fā)表于 2025-3-24 22:27:24 | 只看該作者
20#
發(fā)表于 2025-3-25 00:47:05 | 只看該作者
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