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On asymptotic behaviors and convergence rates related to weak limiting distributions of geometric random sums

Tran Loc HungPhan Tri KienNguyen Tan Nhut — 2019

Kybernetika

Geometric random sums arise in various applied problems like physics, biology, economics, risk processes, stochastic finance, queuing theory, reliability models, regenerative models, etc. Their asymptotic behaviors with convergence rates become a big subject of interest. The main purpose of this paper is to study the asymptotic behaviors of normalized geometric random sums of independent and identically distributed random variables via Gnedenko's Transfer Theorem. Moreover, using the Zolotarev probability...

Modules which are invariant under idempotents of their envelopes

Le Van ThuyetPhan DanTruong Cong Quynh — 2016

Colloquium Mathematicae

We study the class of modules which are invariant under idempotents of their envelopes. We say that a module M is -idempotent-invariant if there exists an -envelope u : M → X such that for any idempotent g ∈ End(X) there exists an endomorphism f : M → M such that uf = gu. The properties of this class of modules are discussed. We prove that M is -idempotent-invariant if and only if for every decomposition X = i I X i , we have M = i I ( u - 1 ( X i ) M ) . Moreover, some generalizations of -idempotent-invariant modules are considered....

Sur la topologie de l'espace des systèmes linéaires hamiltoniens anti symétriques accessibles

Phan Nguyen Huynh — 1994

Annales de l'institut Fourier

Dans cet article nous donnons les formes normales des sytèmes linéaires hamiltoniens antisymétriques accessibles H A n , m , p . Nous construisons une stratification et une décomposition cellulaire analytique de H A n , m , p , puis nous prouvons que son groupe d’homotopie est isomorphe à celui d’une grassmanienne. Ensuite, nous démontrons que H A n , m , p est homotopiquement équivalent à l’espace des systèmes linéaires accessibles. En appliquant ces résultats topologiques, on peut prouver qu’il n’existe pas de paramétrisation continue...

Multicriterial optimization

Phan Quoc Khan — 1990

Mathematica Applicanda

This work is a survey. Basic notions, a few words on the history and a classification of problems in multicriterial optimization are presented. Optimality conditions of various types are discussed in more detail.

Solving the Minimum Independent Domination Set Problem in Graphs by Exact Algorithm and Greedy Heuristic

Christian LaforestRaksmey Phan — 2013

RAIRO - Operations Research - Recherche Opérationnelle

In this paper we present a new approach to solve the Minimum Independent Dominating Set problem in general graphs which is one of the hardest optimization problem. We propose a method using a clique partition of the graph, partition that can be obtained greedily. We provide conditions under which our method has a better complexity than the complexity of the previously known algorithms. Based on our theoretical method, we design in the second part of this paper an efficient algorithm by including...

Two sided Sand Piles Model and unimodal sequences

Thi Ha Duong Phan — 2008

RAIRO - Theoretical Informatics and Applications

We introduce natural generalizations of two well-known dynamical systems, the Sand Piles Model and the Brylawski's model. We describe their order structure, their reachable configuration's characterization, their fixed points and their maximal and minimal length's chains. Finally, we present an induced model generating the set of unimodal sequences which amongst other corollaries, implies that this set is equipped with a lattice structure.

Prediction problems

Nguyen Van Thu — 1980

CONTENTSIntroduction......................................................................................................................................... 5I. Prediction of strictly stationary random fields.................................................................................... 6II. Prediction of stationary-in-norm fields in Banach spaces of random variables........................ 23 § 1. Banach spaces of random variables...................................................................................

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