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Probabilistic rules

Let us first consider a general probabilistic rule defined on a neighborhood Af consisting of I A/ I sites and defined by the set of conditional probabilities P(l S, S2, , S j ). A little thought will show that these conditional probabilities can always be written in the form... [Pg.350]

Wolfram has elaborated on this description elsewhere [11,12], As we shall see, the restriction to deterministic rules is unnecessary, and we shall in fact make extensive use of probabilistic rules in our studies of real physical and chemical systems. [Pg.11]

The reaction transition probabilities in a cell are determined by birth-death probabilistic rules that model the changes in the species particle numbers in the reaction mechanism. Letting N = (iV(1, iV(2),..., iV(s)) be the set of all instantaneous cell species numbers, the reaction transition matrix can be written... [Pg.110]

Birth-death probabilistic rules, multiparticle collisions, reactive dynamics, 109-111... [Pg.277]

Probabilistic rules can be introduced into the CA in several ways. In "the speed of light," a rule that contains a random element leads to the propagation of a wavefront. When updating each cell, we could make a random choice between several different rules to introduce stochastic behavior, but we could also determine the future state of the cell by reference not to the... [Pg.184]

As we shall see, the fourth characteristic can be modified to include probabilistic rules as well as deterministic rules. An important feature sometimes observed in the evolution of these computational systems was the development of unanticipated patterns of ordered dynamical behavior, or emergent properties . As Kauffman has expressed it,22 Studies of large, randomly assembled cellular automata. .. have now demonstrated that such systems can spontaneously crystallize enormously ordered dynamical behavior. This crystallization hints that hitherto unexpected principles of order may be found, [and] that the order observed may have significant explanatory import in [biology and physics]. This proposal has borne considerable fruit, not only in biology and physics, but also in chemistry. Readers are referred to reviews for applications in physics23-26 and biology 27 selected physical and chemical applications have been reviewed by Chopard and co-workers.28... [Pg.209]

Almasy and Sztano [6] and Mah and his coworkers [12] have dealt with this problem and developed structural or probabilistic rules that will determine the location of the gross error. A throuth review of the related problems and the proposed solutions can be found in [15]. When all the measurements are corrected, then they can be used to estimate the value of the variables which are not directly measurable. Such situation entails the solution of a nonlinear estimation problem, in general. [Pg.155]

In much of statistics, the notion of a population is stressed and the subject is sometimes even defined as the science of making statements about populations using samples. However, the notion of a population can be extremely elusive. In survey work, for example, we often have a definite population of units in mind and a sample is taken from this population, sometimes according to some well-specified probabilistic rule. If this rule is used as the basis for calculation of parameter estimates and their standard errors, then this is referred to as design-based inference (Lehtonen and Pahkinen, 2004). Because there is a form of design-based inference which applies to experiments also, we shall refer to it when used for samples as sampling-based inference. [Pg.41]

Two other approaches treat a spatially distributed system as consisting of a grid or lattice. The cellular automaton technique looks at the numbers of particles, or values of some other variables, in small regions of space that interact by set rules that specify the chemistry. It is a deterministic and essentially macroscopic approach that is especially useful for studying excitable media. Lattice gas automata are mesoscopic (between microscopic and macroscopic). Like their cousins, the cellular automata, they use a fixed grid, but differ in that individual particles can move and react through probabilistic rules, making it possible to study fluctuations. [Pg.140]

Practical explication of LODs The combination of LODs must be done carefully according to basic probabilistic rules. For instance, in case of addition of LODs, common modes have to be excluded. The frequency of conadered initiators has to be considered in the final balance which is probabilistic. Safety strategy specifies a general requirement for LODs for the various fault frequencies as outlined in the following table ... [Pg.189]


See other pages where Probabilistic rules is mentioned: [Pg.348]    [Pg.355]    [Pg.401]    [Pg.18]    [Pg.199]    [Pg.397]    [Pg.214]    [Pg.215]    [Pg.125]    [Pg.15]    [Pg.1071]    [Pg.82]    [Pg.84]    [Pg.783]    [Pg.254]    [Pg.611]    [Pg.516]   
See also in sourсe #XX -- [ Pg.209 ]




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