Convergence, i.e., similarity between organisms that is not the direct result of shared phylogenetic history (and that may instead result from independent adaptations to similar environments), is a fundamental issue that lies at the interface of systematics and evolutionary biology. Although convergence is often cited as an important problem in morphological phylogenetics, there have been few w...

this paper has examined the phenomenon of convergence of per capita out put levels across the ic countries for the 1960-1998 periods. three concepts of convergence, i.e., sigma beta and relative beta, have been used. the estimated beta values reveals only a very weak convergence (?=.0014) across ic for 1960-1998 period. but when a more homogeneous group of countries were selected, the results s...

In this paper, we discuss the equivalent conditions of pretopological and topological $L$-fuzzy Q-convergence structures and define $T_{0},~T_{1},~T_{2}$-separation axioms in $L$-fuzzy Q-convergence space. {Furthermore, $L$-ordered Q-convergence structure is introduced and its relation with $L$-fuzzy Q-convergence structure is studied in a categorical sense}.

The paper studies a large class of bounded-rationality, probabilistic learning models on strategic-form games. The main assumption is that players ‘‘recognize’’ cyclic patterns in the observed history of play. The main result is convergence with probability one to a fixed pattern of pure strategy Nash equilibria, in a large class of ‘‘simple games’’ in which the pure equilibria are nicely sprea...

Article history: Received 14 May 2014 Accepted after revision 26 September 2014 Available online 11 October 2014 Presented by Olivier Pironneau We prove asymptotic convergence results for some analytical expansions of solutions to degenerate PDEs with applications to financial mathematics. In particular, we combine short-time and global-in-space error estimates, previously obtained in the unifo...

The construction of anosognosia as a clinical 'disorder' resulted from the convergence (in the work of various writers and culminating in Babinski) of a name, a concept, and a clinical phenomenon. During the early stages of this convergence, unawareness of neurological dysfunction was not considered as an independent clinical phenomenon. Started in the work of Anton, the process of separating i...

The steepest descent method has a rich history and is one of the simplest and best known methods for minimizing a function. While the method is not commonly used in practice due to its slow convergence rate, understanding the convergence properties of this method can lead to a better understanding of many of the more sophisticated optimization methods. Here, we give a short introduction and dis...

Adaptive evolutionary algorithms require a more sophisticated modeling than their static-parameter counterparts. Taking into account the current population is not enough when implementing parameter-adaptation rules based on success rates (evolution strategies) or on premature convergence (genetic algorithms). Instead of Markov chains, we use random systems with complete connections - accounting...

Newton’s method is a basic tool in numerical analysis and numerous applications, including operations research and data mining. We survey the history of the method, its main ideas, convergence results, modifications, its global behavior. We focus on applications of the method for various classes of optimization problems, such as unconstrained minimization, equality constrained problems, convex ...