Improved Exponential Convergence Rates by Oversampling Near the Boundary

2013 ◽  
Vol 39 (2) ◽  
pp. 323-341 ◽  
Author(s):  
Christian Rieger ◽  
Barbara Zwicknagl
Keyword(s):  
Convergence Rates ◽  
Exponential Convergence

Exponential Convergence Rates in Classification

2005 ◽  
pp. 295-307 ◽  
Author(s):  
Vladimir Koltchinskii ◽  
Olexandra Beznosova
Keyword(s):  
Convergence Rates ◽  
Exponential Convergence

scholarly journals EXPONENTIAL CONVERGENCE OF hp-FEM FOR MAXWELL EQUATIONS WITH WEIGHTED REGULARIZATION IN POLYGONAL DOMAINS

2005 ◽  
Vol 15 (04) ◽  
pp. 575-622 ◽  
Author(s):  
MARTIN COSTABEL ◽  
MONIQUE DAUGE ◽  
CHRISTOPH SCHWAB
Keyword(s):  
Finite Element ◽  
Maxwell’S Equations ◽  
Maxwell Equations ◽  
Maxwell's Equations ◽  
Convergence Rates ◽  
Exponential Convergence ◽  
Polygonal Domains ◽  
Time Harmonic ◽  
Standard Tool ◽  
Optimal Convergence Rates

The time-harmonic Maxwell equations do not have an elliptic nature by themselves. Their regularization by a divergence term is a standard tool to obtain equivalent elliptic problems. Nodal finite element discretizations of Maxwell's equations obtained from such a regularization converge to wrong solutions in any non-convex polygon. Modification of the regularization term consisting in the introduction of a weight restores the convergence of nodal FEM, providing optimal convergence rates for the h version of finite elements. We prove exponential convergence of hp FEM for the weighted regularization of Maxwell's equations in plane polygonal domains provided the hp-FE spaces satisfy a series of axioms. We verify these axioms for several specific families of hp finite element spaces.

Exponential convergence rates for weighted sums in noncommutative probability space

2016 ◽  
Vol 19 (04) ◽  
pp. 1650027 ◽  
Author(s):  
Byoung Jin Choi ◽  
Un Cig Ji
Keyword(s):  
Probability Space ◽  
Von Neumann Algebra ◽  
Convergence Rates ◽  
Exponential Convergence ◽  
Large Deviation ◽  
Type Inequality ◽  
Independent Random Variables ◽  
Weighted Sums ◽  
Noncommutative Probability ◽  
Von Neumann

We study exponential convergence rates for weighted sums of successive independent random variables in a noncommutative probability space of which the weights are in a von Neumann algebra. Then we prove a noncommutative extension of the result for the exponential convergence rate by Baum, Katz and Read. As applications, we first study a large deviation type inequality for weighted sums in a noncommutative probability space, and secondly we study exponential convergence rates for weighted free additive convolution sums of probability measures.

scholarly journals Making the most of potential: potential games and genotypic convergence

2021 ◽  
Vol 8 (8) ◽  
pp. 210309
Author(s):  
Omer Edhan ◽  
Ziv Hellman ◽  
Ilan Nehama
Keyword(s):  
Growth Rate ◽  
Sexual Reproduction ◽  
Genetic Linkage ◽  
Convergence Rates ◽  
Exponential Convergence ◽  
Basins Of Attraction ◽  
Single Locus ◽  
Potential Game ◽  
Unified Theory ◽  
Varying Environments

We consider genotypic convergence of populations and show that under fixed fitness asexual and haploid sexual populations attain monomorphic convergence (even under genetic linkage between loci) to basins of attraction with locally exponential convergence rates; the same convergence obtains in single locus diploid sexual reproduction but to polymorphic populations. Furthermore, we show that there is a unified theory underlying these convergences: all of them can be interpreted as instantiations of players in a potential game implementing a multiplicative weights updating algorithm to converge to equilibrium, making use of the Baum–Eagon Theorem. To analyse varying environments, we introduce the concept of ‘virtual convergence’, under which, even if fixation is not attained, the population nevertheless achieves the fitness growth rate it would have had under convergence to an optimal genotype. Virtual convergence is attained by asexual, haploid sexual and multi-locus diploid reproducing populations, even if environments vary arbitrarily. We also study conditions for true monomorphic convergence in asexually reproducing populations in varying environments.

Time-asymptotic convergence rates towards discrete steady states of a nonlocal selection-mutation model

2019 ◽  
Vol 29 (11) ◽  
pp. 2063-2087
Author(s):  
Wenli Cai ◽  
Pierre-Emmanuel Jabin ◽  
Hailiang Liu
Keyword(s):  
Large Time ◽  
Convergence Rates ◽  
Exponential Convergence ◽  
Continuous Model ◽  
Large Time Behavior ◽  
Asymptotic Convergence ◽  
Time Behavior ◽  
Structured Population ◽  
Mutation Model ◽  
Globally Stable

This paper is concerned with large time behavior of solutions to a semi-discrete model involving nonlinear competition that describes the evolution of a trait-structured population. Under some threshold assumptions, the steady solution is shown unique and strictly positive, and also globally stable. The exponential convergence rate to the steady state is also established. These results are consistent with the results in [P.-E. Jabin, H. L. Liu. Nonlinearity 30 (2017) 4220–4238] for the continuous model.

scholarly journals Making the Most of Potential: Potential Games and Genotypic Convergence

2020 ◽  
Author(s):  
Omer Edhan ◽  
Ziv Hellman ◽  
Ilan Nehama
Keyword(s):  
Growth Rate ◽  
Linkage Disequilibrium ◽  
Sexual Reproduction ◽  
Convergence Rates ◽  
Exponential Convergence ◽  
Basins Of Attraction ◽  
Single Locus ◽  
Potential Game ◽  
Underlying Theory ◽  
Varying Environments

AbstractWe consider genotypic convergence of populations and show that under fixed fitness asexual and haploid sexual populations attain monomorphic convergence (even with linkage disequilibrium) to basins of attraction with locally exponential convergence rates; the same convergence obtains in single locus diploid sexual reproduction but to polymorphic populations. Furthermore, we show that there is a unified underlying theory underlying these convergences: all of them can be interpreted as instantiations of players in a potential game implementing a multiplicative weights updating algorithm to converge to equilibrium, making use of the Baum–Eagon Theorem. To analyse varying environments, we introduce the concept of ‘virtual convergence’, under which, even if fixation is not attained, the population nevertheless achieves the fitness growth rate it would have had under convergence to an optimal genotype. Virtual convergence is attained by asexual, haploid sexual, and multi-locus diploid reproducing populations, even if environments vary arbitrarily. We also study conditions for true monomorphic convergence in asexually reproducing populations in varying environments.

scholarly journals Several Types of Ergodicity for M/G/1-Type Markov Chains and Markov Processes

2006 ◽  
Vol 43 (1) ◽  
pp. 141-158 ◽  
Author(s):  
Yuanyuan Liu ◽  
Zhenting Hou
Keyword(s):  
Markov Chains ◽  
Markov Processes ◽  
Generating Function ◽  
Final Section ◽  
Convergence Rates ◽  
Exponential Convergence ◽  
Radius Of Convergence ◽  
Exponential Ergodicity ◽  
Return Probability ◽  
Explicit Bounds

In this paper we study polynomial and geometric (exponential) ergodicity for M/G/1-type Markov chains and Markov processes. First, practical criteria for M/G/1-type Markov chains are obtained by analyzing the generating function of the first return probability to level 0. Then the corresponding criteria for M/G/1-type Markov processes are given, using their h-approximation chains. Our method yields the radius of convergence of the generating function of the first return probability, which is very important in obtaining explicit bounds on geometric (exponential) convergence rates. Our results are illustrated, in the final section, in some examples.

Sign in / Sign up

Export Citation Format

Share Document