Recurrence relations based on minimization and maximization
نویسندگان
چکیده
منابع مشابه
An asymptotic theory for recurrence relations based on minimization and maximization
We derive asymptotic approximations for the sequence f(n) de5ned recursively by f(n) = min16j¡n {f(j) + f(n− j)}+ g(n), when the asymptotic behavior of g(n) is known. Our tools are general enough and applicable to another sequence F(n) = max16j¡n {F(j) + F(n − j) + min{g(j); g(n− j)}}, also frequently encountered in divide-and-conquer problems. Applications of our results to algorithms, group t...
متن کاملRecurrence Relations for Quotient Moment of Generalized Pareto Distribution Based on Generalized Order Statistics and Characterization
Generalized Pareto distribution play an important role in reliability, extreme value theory, and other branches of applied probability and statistics. This family of distributions includes exponential distribution, Pareto distribution, and Power distribution. In this paper, we established exact expressions and recurrence relations satisfied by the quotient moments of generalized order statistic...
متن کاملturkish-israeli relations and their implication on iranian national security
this dissertation has six chapter and tree appendices. chapter 1 introduces the thesis proposal including description of problem, key questions, hypothesis, backgrounds and review of literature, research objectives, methodology and theoretical concepts (key terms) taken the literature and facilitate an understanding of national security, national interest and turkish- israeli relations concepts...
15 صفحه اولUnification of Information Maximization and Minimization
In the present paper, we propose a method to unify information maximization and minimization in hidden units. The information maximization and minimization are performed on two different levels: collective and individual level. Thus, two kinds of information: collective and individual information are defined. By maximizing collective information and by minimizing individual information, simple ...
متن کاملThe Expectation-Maximization and Alternating Minimization Algorithms
The Expectation-Maximization (EM) algorithm is a hill-climbing approach to finding a local maximum of a likelihood function [7, 8]. The EM algorithm alternates between finding a greatest lower bound to the likelihood function (the “E Step”), and then maximizing this bound (the “M Step”). The EM algorithm belongs to a broader class of alternating minimization algorithms [6], which includes the A...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Mathematical Analysis and Applications
سال: 1985
ISSN: 0022-247X
DOI: 10.1016/0022-247x(85)90170-2