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Fig. 3.6 Types of population extinction. (a) Extinction due to uctuations around a constant mean population size (a stochastic process). (b) Extinction due to a decreasing mean population size (a deterministic process). (c) A combination of (a) and (b).

Thus the more elaborate technique splits into two families: the rst one aims at obtaining a complexity smaller than the size of the graph (eg by restricting the class of Petri nets), and the second one aims at obtaining the same order of complexity as the size of the graph but for extended models The last section describes some of these methods in order to cover the diversity of approaches Two other methods, applicable to well-formed nets, are presented in the next chapters Those covered here are: research of a product form: a formula that expresses the stationary probability of a marking including the net parameters and the place marking as variables of the formula This method illustrates the extension of a technique rst applied in queueing networks research on bounds (eg on the rates) using the structure of the net.

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TDesC and TDes are abstract descriptor base classes. They are not abstract in the strictest C++ meaning of the word, in that they do not

Standard techniques for programming an algorithm to nd a local optimum of a function, which may or may not be the global optimum, typically involve examining the numerically calculated or analytic gradients of the likelihood function at the current guess for the solution, and then use these to determine a direction to head uphill Like other algorithms, bugs and oating point inaccuracies may cause problems for nonlinear optimization algorithms, and poorly scaled data can exacerbate inaccuracies in implementation Thus, numerical inaccuracies may prevent the location of local optima, even when the search algorithm itself is mathematically correct More important, nonlinear optimization algorithms suffer from a deeper limitation, that of nding the global optimum The conditions for global optima for some classes of problems are known (eg, quadratic functions).

Here we observe that linear programming eases the quantitative and qualitative analysis of Petri nets approximation methods that take advantage of a net decomposition or of a transformation of the stochastic process..

If we use the above definition of copolarization and cross-polarization and use (9.16), we can write T TE TE T TE TM cos Ecr sin cos T TM TE = Eco cos sin T TM TM cos sin cos cos sin Ecr Eco (9.18)

Potentiated Pairings Potentiated pairings (Millon, 1990, 1999) draw on two or more techniques applied simultaneously to overcome problematic characteristics that might be refractory were each technique administered separately. Such therapeutic composites pull and push for change on a variety of fronts, leading to a therapy of integrated techniques sufficient to address the tenacity of personality pathology itself. Catalytic Sequences Potentiated pairings are designed to be applied simultaneously. In contrast, catalytic sequences plan the order of interventions as a means of optimizing their impact. The catalytic sequence is the psychotherapeutic equivalent of the one-two punch in boxing. In effect, it is the opposite of a vicious circle, in that it constitutes a constructive arrangement of techniques designed to produce a spiral back toward psychological health. Designing Synergistic Arrangements The ability to borrow and interweave techniques from multiple perspectives gives synergistic psychotherapy tremendous scope: Because personality is cognitive, interpersonal, psychodynamic, and biological, the nature of the personality construct itself dictates that techniques can, should, and must be pulled from any of these perspectives as needed. Eclecticism is simply opportunistic concerning techniques, but the nature of personality

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