New concurrent iterative methods with monotonic convergence
Energy Technology Data Exchange (ETDEWEB)
Yao, Qingchuan [Michigan State Univ., East Lansing, MI (United States)
1996-12-31
This paper proposes the new concurrent iterative methods without using any derivatives for finding all zeros of polynomials simultaneously. The new methods are of monotonic convergence for both simple and multiple real-zeros of polynomials and are quadratically convergent. The corresponding accelerated concurrent iterative methods are obtained too. The new methods are good candidates for the application in solving symmetric eigenproblems.
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Chakkrid Klin-eam
2009-01-01
Full Text Available We prove strong convergence theorems for finding a common element of the zero point set of a maximal monotone operator and the fixed point set of a hemirelatively nonexpansive mapping in a Banach space by using monotone hybrid iteration method. By using these results, we obtain new convergence results for resolvents of maximal monotone operators and hemirelatively nonexpansive mappings in a Banach space.
Boski, Marcin; Paszke, Wojciech
2015-11-01
This paper deals with the problem of designing an iterative learning control algorithm for discrete linear systems using repetitive process stability theory. The resulting design produces a stabilizing output feedback controller in the time domain and a feedforward controller that guarantees monotonic convergence in the trial-to-trial domain. The results are also extended to limited frequency range design specification. New design procedure is introduced in terms of linear matrix inequality (LMI) representations, which guarantee the prescribed performances of ILC scheme. A simulation example is given to illustrate the theoretical developments.
Franklin, Elda
1981-01-01
Reviews studies on the etiology of monotonism, the monotone being that type of uncertain or inaccurate singer who cannot vocally match pitches and who has trouble accurately reproducing even a familiar song. Neurological factors (amusia, right brain abnormalities), age, and sex differences are considered. (Author/SJL)
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Jian Ding
2014-01-01
Full Text Available This paper addresses the problem of P-type iterative learning control for a class of multiple-input multiple-output linear discrete-time systems, whose aim is to develop robust monotonically convergent control law design over a finite frequency range. It is shown that the 2 D iterative learning control processes can be taken as 1 D state space model regardless of relative degree. With the generalized Kalman-Yakubovich-Popov lemma applied, it is feasible to describe the monotonically convergent conditions with the help of linear matrix inequality technique and to develop formulas for the control gain matrices design. An extension to robust control law design against systems with structured and polytopic-type uncertainties is also considered. Two numerical examples are provided to validate the feasibility and effectiveness of the proposed method.
Relatively Inexact Proximal Point Algorithm and Linear Convergence Analysis
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Ram U. Verma
2009-01-01
Full Text Available Based on a notion of relatively maximal (m-relaxed monotonicity, the approximation solvability of a general class of inclusion problems is discussed, while generalizing Rockafellar's theorem (1976 on linear convergence using the proximal point algorithm in a real Hilbert space setting. Convergence analysis, based on this new model, is simpler and compact than that of the celebrated technique of Rockafellar in which the Lipschitz continuity at 0 of the inverse of the set-valued mapping is applied. Furthermore, it can be used to generalize the Yosida approximation, which, in turn, can be applied to first-order evolution equations as well as evolution inclusions.
A simple algorithm for computing positively weighted straight skeletons of monotone polygons☆
Biedl, Therese; Held, Martin; Huber, Stefan; Kaaser, Dominik; Palfrader, Peter
2015-01-01
We study the characteristics of straight skeletons of monotone polygonal chains and use them to devise an algorithm for computing positively weighted straight skeletons of monotone polygons. Our algorithm runs in O(nlogn) time and O(n) space, where n denotes the number of vertices of the polygon. PMID:25648376
A simple algorithm for computing positively weighted straight skeletons of monotone polygons.
Biedl, Therese; Held, Martin; Huber, Stefan; Kaaser, Dominik; Palfrader, Peter
2015-02-01
We study the characteristics of straight skeletons of monotone polygonal chains and use them to devise an algorithm for computing positively weighted straight skeletons of monotone polygons. Our algorithm runs in [Formula: see text] time and [Formula: see text] space, where n denotes the number of vertices of the polygon.
International Nuclear Information System (INIS)
Nguyen Buong.
1992-11-01
The purpose of this paper is to investigate convergence rates for an operator version of Tikhonov regularization constructed by dual mapping for nonlinear ill-posed problems involving monotone operators in real reflective Banach spaces. The obtained results are considered in combination with finite-dimensional approximations for the space. An example is considered for illustration. (author). 15 refs
Convergence analysis of canonical genetic algorithms.
Rudolph, G
1994-01-01
This paper analyzes the convergence properties of the canonical genetic algorithm (CGA) with mutation, crossover and proportional reproduction applied to static optimization problems. It is proved by means of homogeneous finite Markov chain analysis that a CGA will never converge to the global optimum regardless of the initialization, crossover, operator and objective function. But variants of CGA's that always maintain the best solution in the population, either before or after selection, are shown to converge to the global optimum due to the irreducibility property of the underlying original nonconvergent CGA. These results are discussed with respect to the schema theorem.
The converged Sn algorithm for nuclear criticality
International Nuclear Information System (INIS)
Ganapol, B. D.; Hadad, K.
2009-01-01
A new discrete ordinates algorithm to determine the multiplication factor of a 1D nuclear reactor, based on Bengt Carlson's S n method, is presented. The algorithm applies the Romberg and Wynn-epsilon accelerators to accelerate a 1D, one-group S n solution to its asymptotic limit. We demonstrate the feasibility of the Converged Sn (CSn) solution on several one-group criticality benchmark compilations. The new formulation is especially convenient since it enables highly accurate critical fluxes and eigenvalues using the most fundamental transport algorithm. (authors)
Convergence of Batch Split-Complex Backpropagation Algorithm for Complex-Valued Neural Networks
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Huisheng Zhang
2009-01-01
Full Text Available The batch split-complex backpropagation (BSCBP algorithm for training complex-valued neural networks is considered. For constant learning rate, it is proved that the error function of BSCBP algorithm is monotone during the training iteration process, and the gradient of the error function tends to zero. By adding a moderate condition, the weights sequence itself is also proved to be convergent. A numerical example is given to support the theoretical analysis.
Exponentially Convergent Algorithms for Abstract Differential Equations
Gavrilyuk, Ivan; Vasylyk, Vitalii
2011-01-01
This book presents new accurate and efficient exponentially convergent methods for abstract differential equations with unbounded operator coefficients in Banach space. These methods are highly relevant for the practical scientific computing since the equations under consideration can be seen as the meta-models of systems of ordinary differential equations (ODE) as well as the partial differential equations (PDEs) describing various applied problems. The framework of functional analysis allows one to obtain very general but at the same time transparent algorithms and mathematical results which
A new efficient algorithm for computing the imprecise reliability of monotone systems
International Nuclear Information System (INIS)
Utkin, Lev V.
2004-01-01
Reliability analysis of complex systems by partial information about reliability of components and by different conditions of independence of components may be carried out by means of the imprecise probability theory which provides a unified framework (natural extension, lower and upper previsions) for computing the system reliability. However, the application of imprecise probabilities to reliability analysis meets with a complexity of optimization problems which have to be solved for obtaining the system reliability measures. Therefore, an efficient simplified algorithm to solve and decompose the optimization problems is proposed in the paper. This algorithm allows us to practically implement reliability analysis of monotone systems under partial and heterogeneous information about reliability of components and under conditions of the component independence or the lack of information about independence. A numerical example illustrates the algorithm
Convergence Analysis for the Multiplicative Schwarz Preconditioned Inexact Newton Algorithm
Liu, Lulu
2016-10-26
The multiplicative Schwarz preconditioned inexact Newton (MSPIN) algorithm, based on decomposition by field type rather than by subdomain, was recently introduced to improve the convergence of systems with unbalanced nonlinearities. This paper provides a convergence analysis of the MSPIN algorithm. Under reasonable assumptions, it is shown that MSPIN is locally convergent, and desired superlinear or even quadratic convergence can be obtained when the forcing terms are picked suitably.
Convergence Analysis for the Multiplicative Schwarz Preconditioned Inexact Newton Algorithm
Liu, Lulu; Keyes, David E.
2016-01-01
The multiplicative Schwarz preconditioned inexact Newton (MSPIN) algorithm, based on decomposition by field type rather than by subdomain, was recently introduced to improve the convergence of systems with unbalanced nonlinearities. This paper provides a convergence analysis of the MSPIN algorithm. Under reasonable assumptions, it is shown that MSPIN is locally convergent, and desired superlinear or even quadratic convergence can be obtained when the forcing terms are picked suitably.
Maximum-entropy clustering algorithm and its global convergence analysis
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
Constructing a batch of differentiable entropy functions touniformly approximate an objective function by means of the maximum-entropy principle, a new clustering algorithm, called maximum-entropy clustering algorithm, is proposed based on optimization theory. This algorithm is a soft generalization of the hard C-means algorithm and possesses global convergence. Its relations with other clustering algorithms are discussed.
International Nuclear Information System (INIS)
Huang Zhenghai; Gu Weizhe
2008-01-01
In this paper, we construct an augmented system of the standard monotone linear complementarity problem (LCP), and establish the relations between the augmented system and the LCP. We present a smoothing-type algorithm for solving the augmented system. The algorithm is shown to be globally convergent without assuming any prior knowledge of feasibility/infeasibility of the problem. In particular, if the LCP has a solution, then the algorithm either generates a maximal complementary solution of the LCP or detects correctly solvability of the LCP, and in the latter case, an existing smoothing-type algorithm can be directly applied to solve the LCP without any additional assumption and it generates a maximal complementary solution of the LCP; and that if the LCP is infeasible, then the algorithm detect correctly infeasibility of the LCP. To the best of our knowledge, such properties have not appeared in the existing literature for smoothing-type algorithms
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Agarwal RaviP
2009-01-01
Full Text Available We glance at recent advances to the general theory of maximal (set-valued monotone mappings and their role demonstrated to examine the convex programming and closely related field of nonlinear variational inequalities. We focus mostly on applications of the super-relaxed ( -proximal point algorithm to the context of solving a class of nonlinear variational inclusion problems, based on the notion of maximal ( -monotonicity. Investigations highlighted in this communication are greatly influenced by the celebrated work of Rockafellar (1976, while others have played a significant part as well in generalizing the proximal point algorithm considered by Rockafellar (1976 to the case of the relaxed proximal point algorithm by Eckstein and Bertsekas (1992. Even for the linear convergence analysis for the overrelaxed (or super-relaxed ( -proximal point algorithm, the fundamental model for Rockafellar's case does the job. Furthermore, we attempt to explore possibilities of generalizing the Yosida regularization/approximation in light of maximal ( -monotonicity, and then applying to first-order evolution equations/inclusions.
Convergence Performance of Adaptive Algorithms of L-Filters
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Robert Hudec
2003-01-01
Full Text Available This paper deals with convergence parameters determination of adaptive algorithms, which are used in adaptive L-filters design. Firstly the stability of adaptation process, convergence rate or adaptation time, and behaviour of convergence curve belong among basic properties of adaptive algorithms. L-filters with variety of adaptive algorithms were used to their determination. Convergence performances finding of adaptive filters is important mainly for their hardware applications, where filtration in real time or adaptation of coefficient filter with low capacity of input data are required.
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Watcharaporn Cholamjiak
2009-01-01
Full Text Available We prove a weak convergence theorem of the modified Mann iteration process for a uniformly Lipschitzian and generalized asymptotically quasi-nonexpansive mapping in a uniformly convex Banach space. We also introduce two kinds of new monotone hybrid methods and obtain strong convergence theorems for an infinitely countable family of uniformly Lipschitzian and generalized asymptotically quasi-nonexpansive mappings in a Hilbert space. The results improve and extend the corresponding ones announced by Kim and Xu (2006 and Nakajo and Takahashi (2003.
Convergence of Hybrid Space Mapping Algorithms
DEFF Research Database (Denmark)
Madsen, Kaj; Søndergaard, Jacob
2004-01-01
may be poor, or the method may even fail to converge to a stationary point. We consider a convex combination of the space mapping technique with a classical optimization technique. The function to be optimized has the form \\$H \\$\\backslash\\$circ f\\$ where \\$H: \\$\\backslash\\$dR\\^m \\$\\backslash......\\$mapsto \\$\\backslash\\$dR\\$ is convex and \\$f: \\$\\backslash\\$dR\\^n \\$\\backslash\\$mapsto \\$\\backslash\\$dR\\^m\\$ is smooth. Experience indicates that the combined method maintains the initial efficiency of the space mapping technique. We prove that the global convergence property of the classical technique is also...
A Globally Convergent Parallel SSLE Algorithm for Inequality Constrained Optimization
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Zhijun Luo
2014-01-01
Full Text Available A new parallel variable distribution algorithm based on interior point SSLE algorithm is proposed for solving inequality constrained optimization problems under the condition that the constraints are block-separable by the technology of sequential system of linear equation. Each iteration of this algorithm only needs to solve three systems of linear equations with the same coefficient matrix to obtain the descent direction. Furthermore, under certain conditions, the global convergence is achieved.
On the Convergence of Iterative Receiver Algorithms Utilizing Hard Decisions
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Jürgen F. Rößler
2009-01-01
Full Text Available The convergence of receivers performing iterative hard decision interference cancellation (IHDIC is analyzed in a general framework for ASK, PSK, and QAM constellations. We first give an overview of IHDIC algorithms known from the literature applied to linear modulation and DS-CDMA-based transmission systems and show the relation to Hopfield neural network theory. It is proven analytically that IHDIC with serial update scheme always converges to a stable state in the estimated values in course of iterations and that IHDIC with parallel update scheme converges to cycles of length 2. Additionally, we visualize the convergence behavior with the aid of convergence charts. Doing so, we give insight into possible errors occurring in IHDIC which turn out to be caused by locked error situations. The derived results can directly be applied to those iterative soft decision interference cancellation (ISDIC receivers whose soft decision functions approach hard decision functions in course of the iterations.
A globally convergent MC algorithm with an adaptive learning rate.
Peng, Dezhong; Yi, Zhang; Xiang, Yong; Zhang, Haixian
2012-02-01
This brief deals with the problem of minor component analysis (MCA). Artificial neural networks can be exploited to achieve the task of MCA. Recent research works show that convergence of neural networks based MCA algorithms can be guaranteed if the learning rates are less than certain thresholds. However, the computation of these thresholds needs information about the eigenvalues of the autocorrelation matrix of data set, which is unavailable in online extraction of minor component from input data stream. In this correspondence, we introduce an adaptive learning rate into the OJAn MCA algorithm, such that its convergence condition does not depend on any unobtainable information, and can be easily satisfied in practical applications.
Monotone piecewise bicubic interpolation
International Nuclear Information System (INIS)
Carlson, R.E.; Fritsch, F.N.
1985-01-01
In a 1980 paper the authors developed a univariate piecewise cubic interpolation algorithm which produces a monotone interpolant to monotone data. This paper is an extension of those results to monotone script C 1 piecewise bicubic interpolation to data on a rectangular mesh. Such an interpolant is determined by the first partial derivatives and first mixed partial (twist) at the mesh points. Necessary and sufficient conditions on these derivatives are derived such that the resulting bicubic polynomial is monotone on a single rectangular element. These conditions are then simplified to a set of sufficient conditions for monotonicity. The latter are translated to a system of linear inequalities, which form the basis for a monotone piecewise bicubic interpolation algorithm. 4 references, 6 figures, 2 tables
Groenwold, A.A.; Wood, D.W.; Etman, L.F.P.; Tosserams, S.
2009-01-01
We implement and test a globally convergent sequential approximate optimization algorithm based on (convexified) diagonal quadratic approximations. The algorithm resides in the class of globally convergent optimization methods based on conservative convex separable approximations developed by
A cascadic monotonic time-discretized algorithm for finite-level quantum control computation
Ditz, P.; Borzi`, A.
2008-03-01
A computer package (CNMS) is presented aimed at the solution of finite-level quantum optimal control problems. This package is based on a recently developed computational strategy known as monotonic schemes. Quantum optimal control problems arise in particular in quantum optics where the optimization of a control representing laser pulses is required. The purpose of the external control field is to channel the system's wavefunction between given states in its most efficient way. Physically motivated constraints, such as limited laser resources, are accommodated through appropriately chosen cost functionals. Program summaryProgram title: CNMS Catalogue identifier: ADEB_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADEB_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 770 No. of bytes in distributed program, including test data, etc.: 7098 Distribution format: tar.gz Programming language: MATLAB 6 Computer: AMD Athlon 64 × 2 Dual, 2:21 GHz, 1:5 GB RAM Operating system: Microsoft Windows XP Word size: 32 Classification: 4.9 Nature of problem: Quantum control Solution method: Iterative Running time: 60-600 sec
Further notes on convergence of the Weiszfeld algorithm
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Brimberg Jack
2003-01-01
Full Text Available The Fermat-Weber problem is one of the most widely studied problems in classical location theory. In his previous work, Brimberg (1995 attempts to resolve a conjecture posed by Chandrasekaran and Tamir (1989 on a convergence property of the Weiszfeld algorithm, a well-known iterative procedure used to solve this problem. More recently, Canovas, Marin and Canavate (2002 provide counterexamples that appear to reopen the question. However, they do not attempt to reconcile their counterexamples with the previous work. We now show that in the light of these counterexamples, the proof is readily modified and the conjecture of Chandrasekaran and Tamir reclosed. .
Accuracy, convergence and stability of finite element CFD algorithms
International Nuclear Information System (INIS)
Baker, A.J.; Iannelli, G.S.; Noronha, W.P.
1989-01-01
The requirement for artificial dissipation is well understood for shock-capturing CFD procedures in aerodynamics. However, numerical diffusion is widely utilized across the board in Navier-Stokes CFD algorithms, ranging from incompressible through supersonic flow applications. The Taylor weak statement (TWS) theory is applicable to any conservation law system containing an evolutionary component, wherein the analytical modifications becomes functionally dependent on the Jacobian of the corresponding equation system flux vector. The TWS algorithm is developed for a range of fluid mechanics conservation law systems including incompressible Navier-Stokes, depth-averaged free surface hydrodynamic Navier-Stokes, and the compressible Euler and Navier-Stokes equations. This paper presents the TWS statement for the problem class range and highlights the important theoretical issues of accuracy, convergence and stability. Numerical results for a variety of benchmark problems are presented to document key features. 8 refs
A System of Generalized Variational Inclusions Involving a New Monotone Mapping in Banach Spaces
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Jinlin Guan
2013-01-01
Full Text Available We introduce a new monotone mapping in Banach spaces, which is an extension of the -monotone mapping studied by Nazemi (2012, and we generalize the variational inclusion involving the -monotone mapping. Based on the new monotone mapping, we propose a new proximal mapping which combines the proximal mapping studied by Nazemi (2012 with the mapping studied by Lan et al. (2011 and show its Lipschitz continuity. Based on the new proximal mapping, we give an iterative algorithm. Furthermore, we prove the convergence of iterative sequences generated by the algorithm under some appropriate conditions. Our results improve and extend corresponding ones announced by many others.
A Superlinearly Convergent O(square root of nL)-Iteration Algorithm for Linear Programming
National Research Council Canada - National Science Library
Ye, Y; Tapia, Richard A; Zhang, Y
1991-01-01
.... We demonstrate that the modified algorithm maintains its O(square root of nL)-iteration complexity, while exhibiting superlinear convergence for general problems and quadratic convergence for nondegenerate problems...
Heckman, James J; Pinto, Rodrigo
2018-01-01
This paper defines and analyzes a new monotonicity condition for the identification of counterfactuals and treatment effects in unordered discrete choice models with multiple treatments, heterogenous agents and discrete-valued instruments. Unordered monotonicity implies and is implied by additive separability of choice of treatment equations in terms of observed and unobserved variables. These results follow from properties of binary matrices developed in this paper. We investigate conditions under which unordered monotonicity arises as a consequence of choice behavior. We characterize IV estimators of counterfactuals as solutions to discrete mixture problems.
Stochastic Reformulations of Linear Systems: Algorithms and Convergence Theory
Richtarik, Peter; Taká č, Martin
2017-01-01
We develop a family of reformulations of an arbitrary consistent linear system into a stochastic problem. The reformulations are governed by two user-defined parameters: a positive definite matrix defining a norm, and an arbitrary discrete or continuous distribution over random matrices. Our reformulation has several equivalent interpretations, allowing for researchers from various communities to leverage their domain specific insights. In particular, our reformulation can be equivalently seen as a stochastic optimization problem, stochastic linear system, stochastic fixed point problem and a probabilistic intersection problem. We prove sufficient, and necessary and sufficient conditions for the reformulation to be exact. Further, we propose and analyze three stochastic algorithms for solving the reformulated problem---basic, parallel and accelerated methods---with global linear convergence rates. The rates can be interpreted as condition numbers of a matrix which depends on the system matrix and on the reformulation parameters. This gives rise to a new phenomenon which we call stochastic preconditioning, and which refers to the problem of finding parameters (matrix and distribution) leading to a sufficiently small condition number. Our basic method can be equivalently interpreted as stochastic gradient descent, stochastic Newton method, stochastic proximal point method, stochastic fixed point method, and stochastic projection method, with fixed stepsize (relaxation parameter), applied to the reformulations.
Stochastic Reformulations of Linear Systems: Algorithms and Convergence Theory
Richtarik, Peter
2017-06-04
We develop a family of reformulations of an arbitrary consistent linear system into a stochastic problem. The reformulations are governed by two user-defined parameters: a positive definite matrix defining a norm, and an arbitrary discrete or continuous distribution over random matrices. Our reformulation has several equivalent interpretations, allowing for researchers from various communities to leverage their domain specific insights. In particular, our reformulation can be equivalently seen as a stochastic optimization problem, stochastic linear system, stochastic fixed point problem and a probabilistic intersection problem. We prove sufficient, and necessary and sufficient conditions for the reformulation to be exact. Further, we propose and analyze three stochastic algorithms for solving the reformulated problem---basic, parallel and accelerated methods---with global linear convergence rates. The rates can be interpreted as condition numbers of a matrix which depends on the system matrix and on the reformulation parameters. This gives rise to a new phenomenon which we call stochastic preconditioning, and which refers to the problem of finding parameters (matrix and distribution) leading to a sufficiently small condition number. Our basic method can be equivalently interpreted as stochastic gradient descent, stochastic Newton method, stochastic proximal point method, stochastic fixed point method, and stochastic projection method, with fixed stepsize (relaxation parameter), applied to the reformulations.
Weissman, Alexander
2013-01-01
Convergence of the expectation-maximization (EM) algorithm to a global optimum of the marginal log likelihood function for unconstrained latent variable models with categorical indicators is presented. The sufficient conditions under which global convergence of the EM algorithm is attainable are provided in an information-theoretic context by…
Convergence analysis of Chauvin's PCA learning algorithm with a constant learning rate
International Nuclear Information System (INIS)
Lv Jiancheng; Yi Zhang
2007-01-01
The convergence of Chauvin's PCA learning algorithm with a constant learning rate is studied in this paper by using a DDT method (deterministic discrete-time system method). Different from the DCT method (deterministic continuous-time system method), the DDT method does not require that the learning rate converges to zero. An invariant set of Chauvin's algorithm with a constant learning rate is obtained so that the non-divergence of this algorithm can be guaranteed. Rigorous mathematic proofs are provided to prove the local convergence of this algorithm
Convergence analysis of Chauvin's PCA learning algorithm with a constant learning rate
Energy Technology Data Exchange (ETDEWEB)
Lv Jiancheng [Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 610054 (China); Yi Zhang [Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 610054 (China)]. E-mail: zhangyi@uestc.edu.cn
2007-05-15
The convergence of Chauvin's PCA learning algorithm with a constant learning rate is studied in this paper by using a DDT method (deterministic discrete-time system method). Different from the DCT method (deterministic continuous-time system method), the DDT method does not require that the learning rate converges to zero. An invariant set of Chauvin's algorithm with a constant learning rate is obtained so that the non-divergence of this algorithm can be guaranteed. Rigorous mathematic proofs are provided to prove the local convergence of this algorithm.
System convergence in transport models: algorithms efficiency and output uncertainty
DEFF Research Database (Denmark)
Rich, Jeppe; Nielsen, Otto Anker
2015-01-01
of this paper is to analyse convergence performance for the external loop and to illustrate how an improper linkage between the converging parts can lead to substantial uncertainty in the final output. Although this loop is crucial for the performance of large-scale transport models it has not been analysed...... much in the literature. The paper first investigates several variants of the Method of Successive Averages (MSA) by simulation experiments on a toy-network. It is found that the simulation experiments produce support for a weighted MSA approach. The weighted MSA approach is then analysed on large......-scale in the Danish National Transport Model (DNTM). It is revealed that system convergence requires that either demand or supply is without random noise but not both. In that case, if MSA is applied to the model output with random noise, it will converge effectively as the random effects are gradually dampened...
International Nuclear Information System (INIS)
Du, Yi; Yu, Gongyi; Xiang, Xincheng; Wang, Xiangang; De Deene, Yves
2017-01-01
Computational simulations are used to investigate the convergence of a hybrid iterative algorithm for optical CT reconstruction, i.e. the simultaneous algebraic reconstruction technique (SART) integrated with ordered subsets (OS) iteration and total variation (TV) minimization regularization, or SART+OS+TV for short. The influence of parameter selection to reach convergence, spatial dose gradient integrity, MTF and convergent speed are discussed. It’s shown that the results of SART+OS+TV algorithm converge to the true values without significant bias, and MTF and convergent speed are affected by different parameter sets used for iterative calculation. In conclusion, the performance of the SART+OS+TV depends on parameter selection, which also implies that careful parameter tuning work is required and necessary for proper spatial performance and fast convergence. (paper)
A Low Delay and Fast Converging Improved Proportionate Algorithm for Sparse System Identification
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Benesty Jacob
2007-01-01
Full Text Available A sparse system identification algorithm for network echo cancellation is presented. This new approach exploits both the fast convergence of the improved proportionate normalized least mean square (IPNLMS algorithm and the efficient implementation of the multidelay adaptive filtering (MDF algorithm inheriting the beneficial properties of both. The proposed IPMDF algorithm is evaluated using impulse responses with various degrees of sparseness. Simulation results are also presented for both speech and white Gaussian noise input sequences. It has been shown that the IPMDF algorithm outperforms the MDF and IPNLMS algorithms for both sparse and dispersive echo path impulse responses. Computational complexity of the proposed algorithm is also discussed.
A Rapid Convergent Low Complexity Interference Alignment Algorithm for Wireless Sensor Networks
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Lihui Jiang
2015-07-01
Full Text Available Interference alignment (IA is a novel technique that can effectively eliminate the interference and approach the sum capacity of wireless sensor networks (WSNs when the signal-to-noise ratio (SNR is high, by casting the desired signal and interference into different signal subspaces. The traditional alternating minimization interference leakage (AMIL algorithm for IA shows good performance in high SNR regimes, however, the complexity of the AMIL algorithm increases dramatically as the number of users and antennas increases, posing limits to its applications in the practical systems. In this paper, a novel IA algorithm, called directional quartic optimal (DQO algorithm, is proposed to minimize the interference leakage with rapid convergence and low complexity. The properties of the AMIL algorithm are investigated, and it is discovered that the difference between the two consecutive iteration results of the AMIL algorithm will approximately point to the convergence solution when the precoding and decoding matrices obtained from the intermediate iterations are sufficiently close to their convergence values. Based on this important property, the proposed DQO algorithm employs the line search procedure so that it can converge to the destination directly. In addition, the optimal step size can be determined analytically by optimizing a quartic function. Numerical results show that the proposed DQO algorithm can suppress the interference leakage more rapidly than the traditional AMIL algorithm, and can achieve the same level of sum rate as that of AMIL algorithm with far less iterations and execution time.
A Rapid Convergent Low Complexity Interference Alignment Algorithm for Wireless Sensor Networks.
Jiang, Lihui; Wu, Zhilu; Ren, Guanghui; Wang, Gangyi; Zhao, Nan
2015-07-29
Interference alignment (IA) is a novel technique that can effectively eliminate the interference and approach the sum capacity of wireless sensor networks (WSNs) when the signal-to-noise ratio (SNR) is high, by casting the desired signal and interference into different signal subspaces. The traditional alternating minimization interference leakage (AMIL) algorithm for IA shows good performance in high SNR regimes, however, the complexity of the AMIL algorithm increases dramatically as the number of users and antennas increases, posing limits to its applications in the practical systems. In this paper, a novel IA algorithm, called directional quartic optimal (DQO) algorithm, is proposed to minimize the interference leakage with rapid convergence and low complexity. The properties of the AMIL algorithm are investigated, and it is discovered that the difference between the two consecutive iteration results of the AMIL algorithm will approximately point to the convergence solution when the precoding and decoding matrices obtained from the intermediate iterations are sufficiently close to their convergence values. Based on this important property, the proposed DQO algorithm employs the line search procedure so that it can converge to the destination directly. In addition, the optimal step size can be determined analytically by optimizing a quartic function. Numerical results show that the proposed DQO algorithm can suppress the interference leakage more rapidly than the traditional AMIL algorithm, and can achieve the same level of sum rate as that of AMIL algorithm with far less iterations and execution time.
Convergence of Algorithms for Reconstructing Convex Bodies and Directional Measures
DEFF Research Database (Denmark)
Gardner, Richard; Kiderlen, Markus; Milanfar, Peyman
2006-01-01
We investigate algorithms for reconstructing a convex body K in Rn from noisy measurements of its support function or its brightness function in k directions u1, . . . , uk. The key idea of these algorithms is to construct a convex polytope Pk whose support function (or brightness function) best...
Strong Convergence of Hybrid Algorithm for Asymptotically Nonexpansive Mappings in Hilbert Spaces
Directory of Open Access Journals (Sweden)
Juguo Su
2012-01-01
Full Text Available The hybrid algorithms for constructing fixed points of nonlinear mappings have been studied extensively in recent years. The advantage of this methods is that one can prove strong convergence theorems while the traditional iteration methods just have weak convergence. In this paper, we propose two types of hybrid algorithm to find a common fixed point of a finite family of asymptotically nonexpansive mappings in Hilbert spaces. One is cyclic Mann's iteration scheme, and the other is cyclic Halpern's iteration scheme. We prove the strong convergence theorems for both iteration schemes.
Convergence and Applications of a Gossip-Based Gauss-Newton Algorithm
Li, Xiao; Scaglione, Anna
2013-11-01
The Gauss-Newton algorithm is a popular and efficient centralized method for solving non-linear least squares problems. In this paper, we propose a multi-agent distributed version of this algorithm, named Gossip-based Gauss-Newton (GGN) algorithm, which can be applied in general problems with non-convex objectives. Furthermore, we analyze and present sufficient conditions for its convergence and show numerically that the GGN algorithm achieves performance comparable to the centralized algorithm, with graceful degradation in case of network failures. More importantly, the GGN algorithm provides significant performance gains compared to other distributed first order methods.
Strong convergence of an extragradient-type algorithm for the multiple-sets split equality problem.
Zhao, Ying; Shi, Luoyi
2017-01-01
This paper introduces a new extragradient-type method to solve the multiple-sets split equality problem (MSSEP). Under some suitable conditions, the strong convergence of an algorithm can be verified in the infinite-dimensional Hilbert spaces. Moreover, several numerical results are given to show the effectiveness of our algorithm.
Convergence of iterative image reconstruction algorithms for Digital Breast Tomosynthesis
DEFF Research Database (Denmark)
Sidky, Emil; Jørgensen, Jakob Heide; Pan, Xiaochuan
2012-01-01
Most iterative image reconstruction algorithms are based on some form of optimization, such as minimization of a data-fidelity term plus an image regularizing penalty term. While achieving the solution of these optimization problems may not directly be clinically relevant, accurate optimization s...
Darcie, Thomas E.; Doverspike, Robert; Zirngibl, Martin; Korotky, Steven K.
2005-09-01
Call for Papers: Convergence The Journal of Optical Networking (JON) invites submissions to a special issue on Convergence. Convergence has become a popular theme in telecommunications, one that has broad implications across all segments of the industry. Continual evolution of technology and applications continues to erase lines between traditionally separate lines of business, with dramatic consequences for vendors, service providers, and consumers. Spectacular advances in all layers of optical networking-leading to abundant, dynamic, cost-effective, and reliable wide-area and local-area connections-have been essential drivers of this evolution. As services and networks continue to evolve towards some notion of convergence, the continued role of optical networks must be explored. One vision of convergence renders all information in a common packet (especially IP) format. This vision is driven by the proliferation of data services. For example, time-division multiplexed (TDM) voice becomes VoIP. Analog cable-television signals become MPEG bits streamed to digital set-top boxes. T1 or OC-N private lines migrate to Ethernet virtual private networks (VPNs). All these packets coexist peacefully within a single packet-routing methodology built on an optical transport layer that combines the flexibility and cost of data networks with telecom-grade reliability. While this vision is appealing in its simplicity and shared widely, specifics of implementation raise many challenges and differences of opinion. For example, many seek to expand the role of Ethernet in these transport networks, while massive efforts are underway to make traditional TDM networks more data friendly within an evolved but backward-compatible SDH/SONET (synchronous digital hierarchy and synchronous optical network) multiplexing hierarchy. From this common underlying theme follow many specific instantiations. Examples include the convergence at the physical, logical, and operational levels of voice and
Laamiri, Imen; Khouaja, Anis; Messaoud, Hassani
2015-03-01
In this paper we provide a convergence analysis of the alternating RGLS (Recursive Generalized Least Square) algorithm used for the identification of the reduced complexity Volterra model describing stochastic non-linear systems. The reduced Volterra model used is the 3rd order SVD-PARAFC-Volterra model provided using the Singular Value Decomposition (SVD) and the Parallel Factor (PARAFAC) tensor decomposition of the quadratic and the cubic kernels respectively of the classical Volterra model. The Alternating RGLS (ARGLS) algorithm consists on the execution of the classical RGLS algorithm in alternating way. The ARGLS convergence was proved using the Ordinary Differential Equation (ODE) method. It is noted that the algorithm convergence canno׳t be ensured when the disturbance acting on the system to be identified has specific features. The ARGLS algorithm is tested in simulations on a numerical example by satisfying the determined convergence conditions. To raise the elegies of the proposed algorithm, we proceed to its comparison with the classical Alternating Recursive Least Squares (ARLS) presented in the literature. The comparison has been built on a non-linear satellite channel and a benchmark system CSTR (Continuous Stirred Tank Reactor). Moreover the efficiency of the proposed identification approach is proved on an experimental Communicating Two Tank system (CTTS). Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
Zhongbo Hu
2014-01-01
Full Text Available Many improved differential Evolution (DE algorithms have emerged as a very competitive class of evolutionary computation more than a decade ago. However, few improved DE algorithms guarantee global convergence in theory. This paper developed a convergent DE algorithm in theory, which employs a self-adaptation scheme for the parameters and two operators, that is, uniform mutation and hidden adaptation selection (haS operators. The parameter self-adaptation and uniform mutation operator enhance the diversity of populations and guarantee ergodicity. The haS can automatically remove some inferior individuals in the process of the enhancing population diversity. The haS controls the proposed algorithm to break the loop of current generation with a small probability. The breaking probability is a hidden adaptation and proportional to the changes of the number of inferior individuals. The proposed algorithm is tested on ten engineering optimization problems taken from IEEE CEC2011.
Directory of Open Access Journals (Sweden)
Yazheng Dang
2013-01-01
Full Text Available Inspired by the Moudafi (2010, we propose an algorithm for solving the split common fixed-point problem for a wide class of asymptotically quasi-nonexpansive operators and the weak and strong convergence of the algorithm are shown under some suitable conditions in Hilbert spaces. The algorithm and its convergence results improve and develop previous results for split feasibility problems.
DEFF Research Database (Denmark)
Madsen, Ole Brun; Nielsen, Jens Frederik Dalsgaard; Schiøler, Henrik
2002-01-01
Convergence trends between the WAN Internet area, characterized by best effort service provision, and the real time LAN domain, with requirements for guaranteed services, are identified and discussed. A bilateral evolution is identified, where typical bulk service applications from WAN, such as m......Convergence trends between the WAN Internet area, characterized by best effort service provision, and the real time LAN domain, with requirements for guaranteed services, are identified and discussed. A bilateral evolution is identified, where typical bulk service applications from WAN...... with the emergence of remote service provision, such as supervision and control of decentralized heating facilities and wind based electrical power production. The reliability issue is addressed from a structural viewpoint, where the concept of Structural QoS (SQoS) is defined to support reliability modelling...
DEFF Research Database (Denmark)
Prasad, Ramjee
2009-01-01
This paper presents the main conclusions which can be drawn from the discussions on Future Communication Systems and lessons on Unpredictable Future of Wireless Communication Systems. Future systems beyond the third generation are already under discussions in international bodies, such as ITU, WW...... and R&D programmes worldwide. The incoming era is characterized by the convergence of networks and access technology and the divergence of applications. Future mobile communication systems should bring something more than only faster data or wireless internet access....
Darcie, Thomas E.; Doverspike, Robert; Zirngibl, Martin; Korotky, Steven K.
2005-01-01
.p {padding-bottom:6px} Call for Papers: Convergence Guest Editors: Thomas E. Darcie, University of Victoria Robert Doverspike, AT&T Martin Zirngibl, Lucent Technologies Coordinating Associate Editor: Steven K. Korotky, Lucent Technologies The Journal of Optical Networking (JON) invites submissions to a special issue on Convergence. Convergence has become a popular theme in telecommunications, one that has broad implications across all segments of the industry. Continual evolution of technology and applications continues to erase lines between traditionally separate lines of business, with dramatic consequences for vendors, service providers, and consumers. Spectacular advances in all layers of optical networking-leading to abundant, dynamic, cost-effective, and reliable wide-area and local-area connections-have been essential drivers of this evolution. As services and networks continue to evolve towards some notion of convergence, the continued role of optical networks must be explored. One vision of convergence renders all information in a common packet (especially IP) format. This vision is driven by the proliferation of data services. For example, time-division multiplexed (TDM) voice becomes VoIP. Analog cable-television signals become MPEG bits streamed to digital set-top boxes. T1 or OC-N private lines migrate to Ethernet virtual private networks (VPNs). All these packets coexist peacefully within a single packet-routing methodology built on an optical transport layer that combines the flexibility and cost of data networks with telecom-grade reliability. While this vision is appealing in its simplicity and shared widely, specifics of implementation raise many challenges and differences of opinion. For example, many seek to expand the role of Ethernet in these transport networks, while massive efforts are underway to make traditional TDM networks more data friendly within an evolved but backward-compatible SDH/SONET (synchronous digital hierarchy and
International Nuclear Information System (INIS)
Jian Jinbao; Li Jianling; Mo Xingde
2006-01-01
This paper discusses a kind of optimization problem with linear complementarity constraints, and presents a sequential quadratic programming (SQP) algorithm for solving a stationary point of the problem. The algorithm is a modification of the SQP algorithm proposed by Fukushima et al. [Computational Optimization and Applications, 10 (1998),5-34], and is based on a reformulation of complementarity condition as a system of linear equations. At each iteration, one quadratic programming and one system of equations needs to be solved, and a curve search is used to yield the step size. Under some appropriate assumptions, including the lower-level strict complementarity, but without the upper-level strict complementarity for the inequality constraints, the algorithm is proved to possess strong convergence and superlinear convergence. Some preliminary numerical results are reported
Z-Q. Luo; J.F. Sturm; S. Zhang (Shuzhong)
1996-01-01
textabstractThis paper establishes the superlinear convergence of a symmetric primal-dual path following algorithm for semidefinite programming under the assumptions that the semidefinite program has a strictly complementary primal-dual optimal solution and that the size of the central path
Czech Academy of Sciences Publication Activity Database
Cullum, J. K.; Johnson, K.; Tůma, Miroslav
2003-01-01
Roč. 10, - (2003), s. 445-465 ISSN 1070-5325 R&D Projects: GA ČR GA201/02/0595; GA AV ČR IAA1030103 Institutional research plan: CEZ:AV0Z1030915 Keywords : parallel algorithms * graph partitioning * problem decomposition * rate of convergence Subject RIV: BA - General Mathematics Impact factor: 1.042, year: 2003
Czech Academy of Sciences Publication Activity Database
Michálek, Jan; Čapek, Martin
2013-01-01
Roč. 32, č. 5 (2013), s. 901-918 ISSN 0278-0062 R&D Projects: GA MŠk(CZ) LH13028; GA ČR(CZ) GAP501/10/0340; GA ČR(CZ) GAP108/11/0794; GA TA ČR(CZ) TA02011193 Institutional support: RVO:67985823 Keywords : convex optimization * image registration * subgradient algorithm * total variation Subject RIV: EA - Cell Biology Impact factor: 3.799, year: 2013
Jiang, Yulian; Liu, Jianchang; Tan, Shubin; Ming, Pingsong
2014-09-01
In this paper, a robust consensus algorithm is developed and sufficient conditions for convergence to consensus are proposed for a multi-agent system (MAS) with exogenous disturbances subject to partial information. By utilizing H∞ robust control, differential game theory and a design-based approach, the consensus problem of the MAS with exogenous bounded interference is resolved and the disturbances are restrained, simultaneously. Attention is focused on designing an H∞ robust controller (the robust consensus algorithm) based on minimisation of our proposed rational and individual cost functions according to goals of the MAS. Furthermore, sufficient conditions for convergence of the robust consensus algorithm are given. An example is employed to demonstrate that our results are effective and more capable to restrain exogenous disturbances than the existing literature.
Directory of Open Access Journals (Sweden)
Lu-Chuan Ceng
2014-01-01
Full Text Available We first introduce and analyze one iterative algorithm by using the composite shrinking projection method for finding a solution of the system of generalized equilibria with constraints of several problems: a generalized mixed equilibrium problem, finitely many variational inequalities, and the common fixed point problem of an asymptotically strict pseudocontractive mapping in the intermediate sense and infinitely many nonexpansive mappings in a real Hilbert space. We prove a strong convergence theorem for the iterative algorithm under suitable conditions. On the other hand, we also propose another iterative algorithm involving no shrinking projection method and derive its weak convergence under mild assumptions. Our results improve and extend the corresponding results in the earlier and recent literature.
Directory of Open Access Journals (Sweden)
Weitian Lin
2014-01-01
Full Text Available Particle swarm optimization algorithm (PSOA is an advantage optimization tool. However, it has a tendency to get stuck in a near optimal solution especially for middle and large size problems and it is difficult to improve solution accuracy by fine-tuning parameters. According to the insufficiency, this paper researches the local and global search combine particle swarm algorithm (LGSCPSOA, and its convergence and obtains its convergence qualification. At the same time, it is tested with a set of 8 benchmark continuous functions and compared their optimization results with original particle swarm algorithm (OPSOA. Experimental results indicate that the LGSCPSOA improves the search performance especially on the middle and large size benchmark functions significantly.
A generalization of Takane's algorithm for DEDICOM
Kiers, Henk A.L.; ten Berge, Jos M.F.; Takane, Yoshio; de Leeuw, Jan
An algorithm is described for fitting the DEDICOM model for the analysis of asymmetric data matrices. This algorithm generalizes an algorithm suggested by Takane in that it uses a damping parameter in the iterative process. Takane's algorithm does not always converge monotonically. Based on the
A PROOF OF CONVERGENCE OF THE HORN AND SCHUNCK OPTICAL FLOW ALGORITHM IN ARBITRARY DIMENSION
LE TARNEC, LOUIS; DESTREMPES, FRANÇOIS; CLOUTIER, GUY; GARCIA, DAMIEN
2013-01-01
The Horn and Schunck (HS) method, which amounts to the Jacobi iterative scheme in the interior of the image, was one of the first optical flow algorithms. In this article, we prove the convergence of the HS method, whenever the problem is well-posed. Our result is shown in the framework of a generalization of the HS method in dimension n ≥ 1, with a broad definition of the discrete Laplacian. In this context, the condition for the convergence is that the intensity gradients are not all contained in a same hyperplane. Two other articles ([17] and [13]) claimed to solve this problem in the case n = 2, but it appears that both of these proofs are erroneous. Moreover, we explain why some standard results on the convergence of the Jacobi method do not apply for the HS problem, unless n = 1. It is also shown that the convergence of the HS scheme implies the convergence of the Gauss-Seidel and SOR schemes for the HS problem. PMID:26097625
Bonito, Andrea
2012-09-01
We design and analyze variational and non-variational multigrid algorithms for the Laplace-Beltrami operator on a smooth and closed surface. In both cases, a uniform convergence for the V -cycle algorithm is obtained provided the surface geometry is captured well enough by the coarsest grid. The main argument hinges on a perturbation analysis from an auxiliary variational algorithm defined directly on the smooth surface. In addition, the vanishing mean value constraint is imposed on each level, thereby avoiding singular quadratic forms without adding additional computational cost. Numerical results supporting our analysis are reported. In particular, the algorithms perform well even when applied to surfaces with a large aspect ratio. © 2011 American Mathematical Society.
Auat Cheein, Fernando A.; Carelli, Ricardo
2011-01-01
This paper introduces several non-arbitrary feature selection techniques for a Simultaneous Localization and Mapping (SLAM) algorithm. The feature selection criteria are based on the determination of the most significant features from a SLAM convergence perspective. The SLAM algorithm implemented in this work is a sequential EKF (Extended Kalman filter) SLAM. The feature selection criteria are applied on the correction stage of the SLAM algorithm, restricting it to correct the SLAM algorithm with the most significant features. This restriction also causes a decrement in the processing time of the SLAM. Several experiments with a mobile robot are shown in this work. The experiments concern the map reconstruction and a comparison between the different proposed techniques performance. The experiments were carried out at an outdoor environment composed by trees, although the results shown herein are not restricted to a special type of features. PMID:22346568
A Quadratically Convergent O(square root of nL-Iteration Algorithm for Linear Programming
National Research Council Canada - National Science Library
Ye, Y; Gueler, O; Tapia, Richard A; Zhang, Y
1991-01-01
...)-iteration complexity while exhibiting superlinear convergence of the duality gap to zero under the assumption that the iteration sequence converges, and quadratic convergence of the duality gap...
Energy Technology Data Exchange (ETDEWEB)
Maglevanny, I.I., E-mail: sianko@list.ru [Volgograd State Social Pedagogical University, 27 Lenin Avenue, Volgograd 400131 (Russian Federation); Smolar, V.A. [Volgograd State Technical University, 28 Lenin Avenue, Volgograd 400131 (Russian Federation)
2016-01-15
We introduce a new technique of interpolation of the energy-loss function (ELF) in solids sampled by empirical optical spectra. Finding appropriate interpolation methods for ELFs poses several challenges. The sampled ELFs are usually very heterogeneous, can originate from various sources thus so called “data gaps” can appear, and significant discontinuities and multiple high outliers can be present. As a result an interpolation based on those data may not perform well at predicting reasonable physical results. Reliable interpolation tools, suitable for ELF applications, should therefore satisfy several important demands: accuracy and predictive power, robustness and computational efficiency, and ease of use. We examined the effect on the fitting quality due to different interpolation schemes with emphasis on ELF mesh optimization procedures and we argue that the optimal fitting should be based on preliminary log–log scaling data transforms by which the non-uniformity of sampled data distribution may be considerably reduced. The transformed data are then interpolated by local monotonicity preserving Steffen spline. The result is a piece-wise smooth fitting curve with continuous first-order derivatives that passes through all data points without spurious oscillations. Local extrema can occur only at grid points where they are given by the data, but not in between two adjacent grid points. It is found that proposed technique gives the most accurate results and also that its computational time is short. Thus, it is feasible using this simple method to address practical problems associated with interaction between a bulk material and a moving electron. A compact C++ implementation of our algorithm is also presented.
International Nuclear Information System (INIS)
Maglevanny, I.I.; Smolar, V.A.
2016-01-01
We introduce a new technique of interpolation of the energy-loss function (ELF) in solids sampled by empirical optical spectra. Finding appropriate interpolation methods for ELFs poses several challenges. The sampled ELFs are usually very heterogeneous, can originate from various sources thus so called “data gaps” can appear, and significant discontinuities and multiple high outliers can be present. As a result an interpolation based on those data may not perform well at predicting reasonable physical results. Reliable interpolation tools, suitable for ELF applications, should therefore satisfy several important demands: accuracy and predictive power, robustness and computational efficiency, and ease of use. We examined the effect on the fitting quality due to different interpolation schemes with emphasis on ELF mesh optimization procedures and we argue that the optimal fitting should be based on preliminary log–log scaling data transforms by which the non-uniformity of sampled data distribution may be considerably reduced. The transformed data are then interpolated by local monotonicity preserving Steffen spline. The result is a piece-wise smooth fitting curve with continuous first-order derivatives that passes through all data points without spurious oscillations. Local extrema can occur only at grid points where they are given by the data, but not in between two adjacent grid points. It is found that proposed technique gives the most accurate results and also that its computational time is short. Thus, it is feasible using this simple method to address practical problems associated with interaction between a bulk material and a moving electron. A compact C++ implementation of our algorithm is also presented.
A Design Algorithm using External Perturbation to Improve Iterative Feedback Tuning Convergence
DEFF Research Database (Denmark)
Huusom, Jakob Kjøbsted; Hjalmarsson, Håkan; Poulsen, Niels Kjølstad
2011-01-01
Iterative Feedback Tuning constitutes an attractive control loop tuning method for processes in the absence of process insight. It is a purely data driven approach for optimization of the loop performance. The standard formulation ensures an unbiased estimate of the loop performance cost function...... gradient, which is used in a search algorithm for minimizing the performance cost. A slow rate of convergence of the tuning method is often experienced when tuning for disturbance rejection. This is due to a poor signal to noise ratio in the process data. A method is proposed for increasing the data...
Study of the convergence behavior of the complex kernel least mean square algorithm.
Paul, Thomas K; Ogunfunmi, Tokunbo
2013-09-01
The complex kernel least mean square (CKLMS) algorithm is recently derived and allows for online kernel adaptive learning for complex data. Kernel adaptive methods can be used in finding solutions for neural network and machine learning applications. The derivation of CKLMS involved the development of a modified Wirtinger calculus for Hilbert spaces to obtain the cost function gradient. We analyze the convergence of the CKLMS with different kernel forms for complex data. The expressions obtained enable us to generate theory-predicted mean-square error curves considering the circularity of the complex input signals and their effect on nonlinear learning. Simulations are used for verifying the analysis results.
Directory of Open Access Journals (Sweden)
Narinder Singh
2017-01-01
Full Text Available A newly hybrid nature inspired algorithm called HPSOGWO is presented with the combination of Particle Swarm Optimization (PSO and Grey Wolf Optimizer (GWO. The main idea is to improve the ability of exploitation in Particle Swarm Optimization with the ability of exploration in Grey Wolf Optimizer to produce both variants’ strength. Some unimodal, multimodal, and fixed-dimension multimodal test functions are used to check the solution quality and performance of HPSOGWO variant. The numerical and statistical solutions show that the hybrid variant outperforms significantly the PSO and GWO variants in terms of solution quality, solution stability, convergence speed, and ability to find the global optimum.
International Nuclear Information System (INIS)
Klibanov, Michael V; Pantong, Natee; Fiddy, Michael A; Schenk, John; Beilina, Larisa
2010-01-01
A globally convergent algorithm by the first and third authors for a 3D hyperbolic coefficient inverse problem is verified on experimental data measured in the picosecond scale regime. Quantifiable images of dielectric abnormalities are obtained. The total measurement timing of a 100 ps pulse for one detector location was 1.2 ns with 20 ps (=0.02 ns) time step between two consecutive readings. Blind tests have consistently demonstrated an accurate imaging of refractive indexes of dielectric abnormalities. At the same time, it is shown that a modified gradient method is inapplicable to this kind of experimental data. This inverse algorithm is also applicable to other types of imaging modalities, e.g. acoustics. Potential applications are in airport security, imaging of land mines, imaging of defects in non-distractive testing, etc
International Nuclear Information System (INIS)
Korshunov, A D
2003-01-01
Monotone Boolean functions are an important object in discrete mathematics and mathematical cybernetics. Topics related to these functions have been actively studied for several decades. Many results have been obtained, and many papers published. However, until now there has been no sufficiently complete monograph or survey of results of investigations concerning monotone Boolean functions. The object of this survey is to present the main results on monotone Boolean functions obtained during the last 50 years
Effect of inlect swirl on the convergence behavior of a combustor flow computation algorithm
International Nuclear Information System (INIS)
Shyy, W.; Braaten, M.E.; Hwang, T.H.
1987-01-01
The flow in a single sector of gas-turbine combustor with dilution holes has been studied numerically. It is found that there are some distinctive differences between the numerical behavior of the solution algorithm for combusting and noncombusting flows in a single-cup gas turbine combustor enclosed by four-sided solid walls. With the use of an iterative solution procedure and the standard κ-ε turbulence model, converged steady-state solutions are obtained for noncombusting flows with or without the presence of swirl of dilution jets. However, for the combusting flows, the interaction between the strength of the swirl ratio and the jet-to-main flow velocity ratio affects the ability of the algorithm to achieve a converged steady-state solution. Increasing inlet swirl causes the flow field to oscillate as the iterations progress, and to fail to reach a steady-state solution, while increasing the flow through the dilution jets helps achieve a steady-state solution. The above phenomena are not observed for the flows with periodic boundary conditions along two side planes
Non-Interior Continuation Method for Solving the Monotone Semidefinite Complementarity Problem
International Nuclear Information System (INIS)
Huang, Z.H.; Han, J.
2003-01-01
Recently, Chen and Tseng extended non-interior continuation smoothing methods for solving linear/ nonlinear complementarity problems to semidefinite complementarity problems (SDCP). In this paper we propose a non-interior continuation method for solving the monotone SDCP based on the smoothed Fischer-Burmeister function, which is shown to be globally linearly and locally quadratically convergent under suitable assumptions. Our algorithm needs at most to solve a linear system of equations at each iteration. In addition, in our analysis on global linear convergence of the algorithm, we need not use the assumption that the Frechet derivative of the function involved in the SDCP is Lipschitz continuous. For non-interior continuation/ smoothing methods for solving the nonlinear complementarity problem, such an assumption has been used widely in the literature in order to achieve global linear convergence results of the algorithms
Directory of Open Access Journals (Sweden)
Xiangrong Li
Full Text Available It is generally acknowledged that the conjugate gradient (CG method achieves global convergence--with at most a linear convergence rate--because CG formulas are generated by linear approximations of the objective functions. The quadratically convergent results are very limited. We introduce a new PRP method in which the restart strategy is also used. Moreover, the method we developed includes not only n-step quadratic convergence but also both the function value information and gradient value information. In this paper, we will show that the new PRP method (with either the Armijo line search or the Wolfe line search is both linearly and quadratically convergent. The numerical experiments demonstrate that the new PRP algorithm is competitive with the normal CG method.
Li, Xiangrong; Zhao, Xupei; Duan, Xiabin; Wang, Xiaoliang
2015-01-01
It is generally acknowledged that the conjugate gradient (CG) method achieves global convergence--with at most a linear convergence rate--because CG formulas are generated by linear approximations of the objective functions. The quadratically convergent results are very limited. We introduce a new PRP method in which the restart strategy is also used. Moreover, the method we developed includes not only n-step quadratic convergence but also both the function value information and gradient value information. In this paper, we will show that the new PRP method (with either the Armijo line search or the Wolfe line search) is both linearly and quadratically convergent. The numerical experiments demonstrate that the new PRP algorithm is competitive with the normal CG method.
Directory of Open Access Journals (Sweden)
David Maldavsky
2013-08-01
Full Text Available The author first exposes a complement of a previous test about convergent validity, then a construct validity test and finally an external validity test of the David Liberman algorithm. The first part of the paper focused on a complementary aspect, the differential sensitivity of the DLA 1 in an external comparison (to other methods, and 2 in an internal comparison (between two ways of using the same method, the DLA. The construct validity test exposes the concepts underlined to DLA, their operationalization and some corrections emerging from several empirical studies we carried out. The external validity test examines the possibility of using the investigation of a single case and its relation with the investigation of a more extended sample.
Directory of Open Access Journals (Sweden)
Kriengsak Wattanawitoon
2011-01-01
Full Text Available We prove strong and weak convergence theorems of modified hybrid proximal-point algorithms for finding a common element of the zero point of a maximal monotone operator, the set of solutions of equilibrium problems, and the set of solution of the variational inequality operators of an inverse strongly monotone in a Banach space under different conditions. Moreover, applications to complementarity problems are given. Our results modify and improve the recently announced ones by Li and Song (2008 and many authors.
Directory of Open Access Journals (Sweden)
INTAN S. AHMAD
2008-04-01
Full Text Available This work presents the application of a primal-dual interior point method to minimax optimisation problems. The algorithm differs significantly from previous approaches as it involves a novel non-monotone line search procedure, which is based on the use of standard penalty methods as the merit function used for line search. The crucial novel concept is the discretisation of the penalty parameter used over a finite range of orders of magnitude and the provision of a memory list for each such order. An implementation within a logarithmic barrier algorithm for bounds handling is presented with capabilities for large scale application. Case studies presented demonstrate the capabilities of the proposed methodology, which relies on the reformulation of minimax models into standard nonlinear optimisation models. Some previously reported case studies from the open literature have been solved, and with significantly better optimal solutions identified. We believe that the nature of the non-monotone line search scheme allows the search procedure to escape from local minima, hence the encouraging results obtained.
International Nuclear Information System (INIS)
Lalush, D.S.; Tsui, B.M.W.; Karimi, S.S.
1996-01-01
We evaluate fast reconstruction algorithms including ordered subsets-EM (OS-EM) and Rescaled Block Iterative EM (RBI-EM) in fully 3D SPECT applications on the basis of their convergence and resolution recovery properties as iterations proceed. Using a 3D computer-simulated phantom consisting of 3D Gaussian objects, we simulated projection data that includes only the effects of sampling and detector response of a parallel-hole collimator. Reconstructions were performed using each of the three algorithms (ML-EM, OS-EM, and RBI-EM) modeling the 3D detector response in the projection function. Resolution recovery was evaluated by fitting Gaussians to each of the four objects in the iterated image estimates at selected intervals. Results show that OS-EM and RBI-EM behave identically in this case; their resolution recovery results are virtually indistinguishable. Their resolution behavior appears to be very similar to that of ML-EM, but accelerated by a factor of twenty. For all three algorithms, smaller objects take more iterations to converge. Next, we consider the effect noise has on convergence. For both noise-free and noisy data, we evaluate the log likelihood function at each subiteration of OS-EM and RBI-EM, and at each iteration of ML-EM. With noisy data, both OS-EM and RBI-EM give results for which the log-likelihood function oscillates. Especially for 180-degree acquisitions, RBI-EM oscillates less than OS-EM. Both OS-EM and RBI-EM appear to converge to solutions, but not to the ML solution. We conclude that both OS-EM and RBI-EM can be effective algorithms for fully 3D SPECT reconstruction. Both recover resolution similarly to ML-EM, only more quickly
Czech Academy of Sciences Publication Activity Database
Jeřábek, Emil
2012-01-01
Roč. 58, č. 3 (2012), s. 177-187 ISSN 0942-5616 R&D Projects: GA AV ČR IAA100190902; GA MŠk(CZ) 1M0545 Institutional support: RVO:67985840 Keywords : proof complexity * monotone sequent calculus Subject RIV: BA - General Mathematics Impact factor: 0.376, year: 2012 http://onlinelibrary.wiley.com/doi/10.1002/malq.201020071/full
Semi-convergence and relaxation parameters for a class of SIRT algorithms
DEFF Research Database (Denmark)
Elfving, Tommy; Nikazad, Touraj; Hansen, Per Christian
2010-01-01
This paper is concerned with the Simultaneous Iterative Reconstruction Technique (SIRT) class of iterative methods for solving inverse problems. Based on a careful analysis of the semi-convergence behavior of these methods, we propose two new techniques to specify the relaxation parameters...
Directory of Open Access Journals (Sweden)
Eyad K Almaita
2017-03-01
Keywords: Energy efficiency, Power quality, Radial basis function, neural networks, adaptive, harmonic. Article History: Received Dec 15, 2016; Received in revised form Feb 2nd 2017; Accepted 13rd 2017; Available online How to Cite This Article: Almaita, E.K and Shawawreh J.Al (2017 Improving Stability and Convergence for Adaptive Radial Basis Function Neural Networks Algorithm (On-Line Harmonics Estimation Application. International Journal of Renewable Energy Develeopment, 6(1, 9-17. http://dx.doi.org/10.14710/ijred.6.1.9-17
Large Airborne Full Tensor Gradient Data Inversion Based on a Non-Monotone Gradient Method
Sun, Yong; Meng, Zhaohai; Li, Fengting
2018-03-01
Following the development of gravity gradiometer instrument technology, the full tensor gravity (FTG) data can be acquired on airborne and marine platforms. Large-scale geophysical data can be obtained using these methods, making such data sets a number of the "big data" category. Therefore, a fast and effective inversion method is developed to solve the large-scale FTG data inversion problem. Many algorithms are available to accelerate the FTG data inversion, such as conjugate gradient method. However, the conventional conjugate gradient method takes a long time to complete data processing. Thus, a fast and effective iterative algorithm is necessary to improve the utilization of FTG data. Generally, inversion processing is formulated by incorporating regularizing constraints, followed by the introduction of a non-monotone gradient-descent method to accelerate the convergence rate of FTG data inversion. Compared with the conventional gradient method, the steepest descent gradient algorithm, and the conjugate gradient algorithm, there are clear advantages of the non-monotone iterative gradient-descent algorithm. Simulated and field FTG data were applied to show the application value of this new fast inversion method.
Directory of Open Access Journals (Sweden)
Shenghua Wang
2013-01-01
Full Text Available We first introduce the concept of Bregman asymptotically quasinonexpansive mappings and prove that the fixed point set of this kind of mappings is closed and convex. Then we construct an iterative scheme to find a common element of the set of solutions of an equilibrium problem and the set of common fixed points of a countable family of Bregman asymptotically quasinonexpansive mappings in reflexive Banach spaces and prove strong convergence theorems. Our results extend the recent ones of some others.
Matching by Monotonic Tone Mapping.
Kovacs, Gyorgy
2018-06-01
In this paper, a novel dissimilarity measure called Matching by Monotonic Tone Mapping (MMTM) is proposed. The MMTM technique allows matching under non-linear monotonic tone mappings and can be computed efficiently when the tone mappings are approximated by piecewise constant or piecewise linear functions. The proposed method is evaluated in various template matching scenarios involving simulated and real images, and compared to other measures developed to be invariant to monotonic intensity transformations. The results show that the MMTM technique is a highly competitive alternative of conventional measures in problems where possible tone mappings are close to monotonic.
BIMOND3, Monotone Bivariate Interpolation
International Nuclear Information System (INIS)
Fritsch, F.N.; Carlson, R.E.
2001-01-01
1 - Description of program or function: BIMOND is a FORTRAN-77 subroutine for piecewise bi-cubic interpolation to data on a rectangular mesh, which reproduces the monotonousness of the data. A driver program, BIMOND1, is provided which reads data, computes the interpolating surface parameters, and evaluates the function on a mesh suitable for plotting. 2 - Method of solution: Monotonic piecewise bi-cubic Hermite interpolation is used. 3 - Restrictions on the complexity of the problem: The current version of the program can treat data which are monotone in only one of the independent variables, but cannot handle piecewise monotone data
Bonito, Andrea; Pasciak, Joseph E.
2012-01-01
is captured well enough by the coarsest grid. The main argument hinges on a perturbation analysis from an auxiliary variational algorithm defined directly on the smooth surface. In addition, the vanishing mean value constraint is imposed on each level, thereby
Convergence properties of iterative algorithms for solving the nodal diffusion equations
International Nuclear Information System (INIS)
Azmy, Y.Y.; Kirk, B.L.
1990-01-01
We drive the five point form of the nodal diffusion equations in two-dimensional Cartesian geometry and develop three iterative schemes to solve the discrete-variable equations: the unaccelerated, partial Successive Over Relaxation (SOR), and the full SOR methods. By decomposing the iteration error into its Fourier modes, we determine the spectral radius of each method for infinite medium, uniform model problems, and for the unaccelerated and partial SOR methods for finite medium, uniform model problems. Also for the two variants of the SOR method we determine the optimal relaxation factor that results in the smallest number of iterations required for convergence. Our results indicate that the number of iterations for the unaccelerated and partial SOR methods is second order in the number of nodes per dimension, while, for the full SOR this behavior is first order, resulting in much faster convergence for very large problems. We successfully verify the results of the spectral analysis against those of numerical experiments, and we show that for the full SOR method the linear dependence of the number of iterations on the number of nodes per dimension is relatively insensitive to the value of the relaxation parameter, and that it remains linear even for heterogenous problems. 14 refs., 1 fig
Optimal Monotone Drawings of Trees
He, Dayu; He, Xin
2016-01-01
A monotone drawing of a graph G is a straight-line drawing of G such that, for every pair of vertices u,w in G, there exists abpath P_{uw} in G that is monotone in some direction l_{uw}. (Namely, the order of the orthogonal projections of the vertices of P_{uw} on l_{uw} is the same as the order they appear in P_{uw}.) The problem of finding monotone drawings for trees has been studied in several recent papers. The main focus is to reduce the size of the drawing. Currently, the smallest drawi...
Accelerated convergence of the steepest-descent method for magnetohydrodynamic equilibria
International Nuclear Information System (INIS)
Handy, C.R.; Hirshman, S.P.
1984-06-01
Iterative schemes based on the method of steepest descent have recently been used to obtain magnetohydrodynamic (MHD) equilibria. Such schemes generate asymptotic geometric vector sequences whose convergence rate can be improved through the use of the epsilon-algorithm. The application of this nonlinear recursive technique to stiff systems is discussed. In principle, the epsilon-algorithm is capable of yielding quadratic convergence and therefore represents an attractive alternative to other quadratic convergence schemes requiring Jacobian matrix inversion. Because the damped MHD equations have eigenvalues with negative real parts (in the neighborhood of a stable equilibrium), the epsilon-algorithm will generally be stable. Concern for residual monotonic sequences leads to consideration of alternative methods for implementing the algorithm
Monotonicity of social welfare optima
DEFF Research Database (Denmark)
Hougaard, Jens Leth; Østerdal, Lars Peter Raahave
2010-01-01
This paper considers the problem of maximizing social welfare subject to participation constraints. It is shown that for an income allocation method that maximizes a social welfare function there is a monotonic relationship between the incomes allocated to individual agents in a given coalition...
International Nuclear Information System (INIS)
Paszkowicz, Wojciech
2006-01-01
Genetic algorithms represent a powerful global-optimisation tool applicable in solving tasks of high complexity in science, technology, medicine, communication, etc. The usual genetic-algorithm calculation scheme is extended here by introduction of a quadratic self-learning operator, which performs a partial local search for randomly selected representatives of the population. This operator is aimed as a minor deterministic contribution to the (stochastic) genetic search. The population representing the trial solutions is split into two equal subpopulations allowed to exhibit different mutation rates (so called asymmetric mutation). The convergence is studied in detail exploiting a crystallographic-test example of indexing of powder diffraction data of orthorhombic lithium copper oxide, varying such parameters as mutation rates and the learning rate. It is shown through the averaged (over the subpopulation) fitness behaviour, how the genetic diversity in the population depends on the mutation rate of the given subpopulation. Conditions and algorithm parameter values favourable for convergence in the framework of proposed approach are discussed using the results for the mentioned example. Further data are studied with a somewhat modified algorithm using periodically varying mutation rates and a problem-specific operator. The chance of finding the global optimum and the convergence speed are observed to be strongly influenced by the effective mutation level and on the self-learning level. The optimal values of these two parameters are about 6 and 5%, respectively. The periodic changes of mutation rate are found to improve the explorative abilities of the algorithm. The results of the study confirm that the applied methodology leads to improvement of the classical genetic algorithm and, therefore, it is expected to be helpful in constructing of algorithms permitting to solve similar tasks of higher complexity
Guermond, Jean-Luc; Minev, Peter D.; Salgado, Abner J.
2012-01-01
We provide a convergence analysis for a new fractional timestepping technique for the incompressible Navier-Stokes equations based on direction splitting. This new technique is of linear complexity, unconditionally stable and convergent, and suitable for massive parallelization. © 2012 American Mathematical Society.
International Nuclear Information System (INIS)
Wilde, Juray de; Vierendeels, Jan; Heynderickx, Geraldine J.; Marin, Guy B.
2005-01-01
Simultaneous solution algorithms for Eulerian-Eulerian gas-solid flow models are presented and their stability analyzed. The integration algorithms are based on dual-time stepping with fourth-order Runge-Kutta in pseudo-time. The domain is solved point or plane wise. The discretization of the inviscid terms is based on a low-Mach limit of the multi-phase preconditioned advection upstream splitting method (MP-AUSMP). The numerical stability of the simultaneous solution algorithms is analyzed in 2D with the Fourier method. Stability results are compared with the convergence behaviour of 3D riser simulations. The impact of the grid aspect ratio, preconditioning, artificial dissipation, and the treatment of the source terms is investigated. A particular advantage of the simultaneous solution algorithms is that they allow a fully implicit treatment of the source terms which are of crucial importance for the Eulerian-Eulerian gas-solid flow models and their solution. The numerical stability of the optimal simultaneous solution algorithm is analyzed for different solids volume fractions and gas-solid slip velocities. Furthermore, the effect of the grid resolution on the convergence behaviour and the simulation results is investigated. Finally, simulations of the bottom zone of a pilot-scale riser with a side solids inlet are experimentally validated
Generalized monotone operators in Banach spaces
International Nuclear Information System (INIS)
Nanda, S.
1988-07-01
The concept of F-monotonicity was first introduced by Kato and this generalizes the notion of monotonicity introduced by Minty. The purpose of this paper is to define various types of F-monotonicities and discuss the relationships among them. (author). 6 refs
Computation of Optimal Monotonicity Preserving General Linear Methods
Ketcheson, David I.
2009-07-01
Monotonicity preserving numerical methods for ordinary differential equations prevent the growth of propagated errors and preserve convex boundedness properties of the solution. We formulate the problem of finding optimal monotonicity preserving general linear methods for linear autonomous equations, and propose an efficient algorithm for its solution. This algorithm reliably finds optimal methods even among classes involving very high order accuracy and that use many steps and/or stages. The optimality of some recently proposed methods is verified, and many more efficient methods are found. We use similar algorithms to find optimal strong stability preserving linear multistep methods of both explicit and implicit type, including methods for hyperbolic PDEs that use downwind-biased operators.
Monotone methods for solving a boundary value problem of second order discrete system
Directory of Open Access Journals (Sweden)
Wang Yuan-Ming
1999-01-01
Full Text Available A new concept of a pair of upper and lower solutions is introduced for a boundary value problem of second order discrete system. A comparison result is given. An existence theorem for a solution is established in terms of upper and lower solutions. A monotone iterative scheme is proposed, and the monotone convergence rate of the iteration is compared and analyzed. The numerical results are given.
Quantisation of monotonic twist maps
International Nuclear Information System (INIS)
Boasman, P.A.; Smilansky, U.
1993-08-01
Using an approach suggested by Moser, classical Hamiltonians are generated that provide an interpolating flow to the stroboscopic motion of maps with a monotonic twist condition. The quantum properties of these Hamiltonians are then studied in analogy with recent work on the semiclassical quantization of systems based on Poincare surfaces of section. For the generalized standard map, the correspondence with the usual classical and quantum results is shown, and the advantages of the quantum Moser Hamiltonian demonstrated. The same approach is then applied to the free motion of a particle on a 2-torus, and to the circle billiard. A natural quantization condition based on the eigenphases of the unitary time--development operator is applied, leaving the exact eigenvalues of the torus, but only the semiclassical eigenvalues for the billiard; an explanation for this failure is proposed. It is also seen how iterating the classical map commutes with the quantization. (authors)
A proximal point algorithm with generalized proximal distances to BEPs
Bento, G. C.; Neto, J. X. Cruz; Lopes, J. O.; Soares Jr, P. A.; Soubeyran, A.
2014-01-01
We consider a bilevel problem involving two monotone equilibrium bifunctions and we show that this problem can be solved by a proximal point method with generalized proximal distances. We propose a framework for the convergence analysis of the sequences generated by the algorithm. This class of problems is very interesting because it covers mathematical programs and optimization problems under equilibrium constraints. As an application, we consider the problem of the stability and change dyna...
Bui, Trong T.; Mankbadi, Reda R.
1995-01-01
Numerical simulation of a very small amplitude acoustic wave interacting with a shock wave in a quasi-1D convergent-divergent nozzle is performed using an unstructured finite volume algorithm with a piece-wise linear, least square reconstruction, Roe flux difference splitting, and second-order MacCormack time marching. First, the spatial accuracy of the algorithm is evaluated for steady flows with and without the normal shock by running the simulation with a sequence of successively finer meshes. Then the accuracy of the Roe flux difference splitting near the sonic transition point is examined for different reconstruction schemes. Finally, the unsteady numerical solutions with the acoustic perturbation are presented and compared with linear theory results.
Improved Bayesian optimization algorithm with fast convergence%一种快速收敛的改进贝叶斯优化算法
Institute of Scientific and Technical Information of China (English)
王翔; 郑建国; 张超群; 刘荣辉
2011-01-01
针对贝叶斯优化算法(BOA)中学习贝叶斯网络结构时间复杂度较高的问题,提出了一种可以快速收敛的基于K2的贝叶斯优化算法(K2-BOA).为了提升收敛速度,在学习贝叶斯网络结构的步骤中进行了2处改进:首先,随机生成n个变量的拓扑排序,加大了算法的随机性;其次,在排序的基础上利用K2算法学习贝叶斯网络结构,减少了整个算法的时问复杂度.针对3个标准Benchmark函数的仿真实验表明:采用K2-BOA算法和BOA算法解决简单分解函数问题时,寻找到最优值的适应度函数评价次数几乎相同,但是每次迭代K2-BOA算法运行速度提升明显;当解决比较复杂的6阶双极欺骗函数问题时,K2-BOA算法无论是运行时间还是适应度函数评价次数,都远小于BOA算法.%K2-Bayesian optimization algorithm (BOA) with fast convergence was proposed to enhance the convergence rate figuring out the problem that the time complexity of learning Bayesian networks was high in the Bayesian optimization algorithm. There were two improvements in learning Bayesian network of the new algorithm: the topological sort of n variables was randomly generated for increasing the randomness of the algorithm, and on the basis of the sort K2 algorithm was used to learn Bayesian network structure to reduce the time complexity of the new algorithm. The simulation results for three benchmark functions show two conclusions. Firstly, when 3-deceptive function and trap-5 function are solved, the number of fitness function evaluation of K2-Bayesian optimization algorithm is almost the same as that of Bayesian optimization algorithm; however the running time of K2-Bayesian optimization algorithm is less than that of Bayesian optimization algorithm. Secondly, when 6-bipolar function is solved, the number of fitness function evaluation and the running time of K2-Bayesian optimization algorithm are much better than those of Bayesian optimization algorithm.
On the size of monotone span programs
Nikov, V.S.; Nikova, S.I.; Preneel, B.; Blundo, C.; Cimato, S.
2005-01-01
Span programs provide a linear algebraic model of computation. Monotone span programs (MSP) correspond to linear secret sharing schemes. This paper studies the properties of monotone span programs related to their size. Using the results of van Dijk (connecting codes and MSPs) and a construction for
Edit Distance to Monotonicity in Sliding Windows
DEFF Research Database (Denmark)
Chan, Ho-Leung; Lam, Tak-Wah; Lee, Lap Kei
2011-01-01
Given a stream of items each associated with a numerical value, its edit distance to monotonicity is the minimum number of items to remove so that the remaining items are non-decreasing with respect to the numerical value. The space complexity of estimating the edit distance to monotonicity of a ...
Directory of Open Access Journals (Sweden)
San-Yang Liu
2014-01-01
Full Text Available Two unified frameworks of some sufficient descent conjugate gradient methods are considered. Combined with the hyperplane projection method of Solodov and Svaiter, they are extended to solve convex constrained nonlinear monotone equations. Their global convergence is proven under some mild conditions. Numerical results illustrate that these methods are efficient and can be applied to solve large-scale nonsmooth equations.
Nguyen, Dinh-Liem; Klibanov, Michael V.; Nguyen, Loc H.; Kolesov, Aleksandr E.; Fiddy, Michael A.; Liu, Hui
2017-09-01
We analyze in this paper the performance of a newly developed globally convergent numerical method for a coefficient inverse problem for the case of multi-frequency experimental backscatter data associated to a single incident wave. These data were collected using a microwave scattering facility at the University of North Carolina at Charlotte. The challenges for the inverse problem under the consideration are not only from its high nonlinearity and severe ill-posedness but also from the facts that the amount of the measured data is minimal and that these raw data are contaminated by a significant amount of noise, due to a non-ideal experimental setup. This setup is motivated by our target application in detecting and identifying explosives. We show in this paper how the raw data can be preprocessed and successfully inverted using our inversion method. More precisely, we are able to reconstruct the dielectric constants and the locations of the scattering objects with a good accuracy, without using any advanced a priori knowledge of their physical and geometrical properties.
Local Convergence and Radius of Convergence for Modified Newton Method
Directory of Open Access Journals (Sweden)
Măruşter Ştefan
2017-12-01
Full Text Available We investigate the local convergence of modified Newton method, i.e., the classical Newton method in which the derivative is periodically re-evaluated. Based on the convergence properties of Picard iteration for demicontractive mappings, we give an algorithm to estimate the local radius of convergence for considered method. Numerical experiments show that the proposed algorithm gives estimated radii which are very close to or even equal with the best ones.
DEFF Research Database (Denmark)
Nielson, Hanne Riis; Nielson, Flemming
2009-01-01
The calculus of communicating systems, CCS, was introduced by Robin Milner as a calculus for modelling concurrent systems. Subsequently several techniques have been developed for analysing such models in order to get further insight into their dynamic behaviour. In this paper we present a static...... a finite automaton that faithfully captures the control structure of a CCS model. Each state in the automaton records a multiset of the enabled actions and appropriate transfer functions are developed for transforming one state into another. A classical worklist algorithm governs the overall construction...
Indian Academy of Sciences (India)
polynomial) division have been found in Vedic Mathematics which are dated much before Euclid's algorithm. A programming language Is used to describe an algorithm for execution on a computer. An algorithm expressed using a programming.
The Monotonic Lagrangian Grid for Rapid Air-Traffic Evaluation
Kaplan, Carolyn; Dahm, Johann; Oran, Elaine; Alexandrov, Natalia; Boris, Jay
2010-01-01
The Air Traffic Monotonic Lagrangian Grid (ATMLG) is presented as a tool to evaluate new air traffic system concepts. The model, based on an algorithm called the Monotonic Lagrangian Grid (MLG), can quickly sort, track, and update positions of many aircraft, both on the ground (at airports) and in the air. The underlying data structure is based on the MLG, which is used for sorting and ordering positions and other data needed to describe N moving bodies and their interactions. Aircraft that are close to each other in physical space are always near neighbors in the MLG data arrays, resulting in a fast nearest-neighbor interaction algorithm that scales as N. Recent upgrades to ATMLG include adding blank place-holders within the MLG data structure, which makes it possible to dynamically change the MLG size and also improves the quality of the MLG grid. Additional upgrades include adding FAA flight plan data, such as way-points and arrival and departure times from the Enhanced Traffic Management System (ETMS), and combining the MLG with the state-of-the-art strategic and tactical conflict detection and resolution algorithms from the NASA-developed Stratway software. In this paper, we present results from our early efforts to couple ATMLG with the Stratway software, and we demonstrate that it can be used to quickly simulate air traffic flow for a very large ETMS dataset.
Indian Academy of Sciences (India)
First page Back Continue Last page Overview Graphics. Network Convergence. User is interested in application and content - not technical means of distribution. Boundaries between distribution channels fade out. Network convergence leads to seamless application and content solutions.
Existence, uniqueness, monotonicity and asymptotic behaviour of travelling waves for epidemic models
International Nuclear Information System (INIS)
Hsu, Cheng-Hsiung; Yang, Tzi-Sheng
2013-01-01
The purpose of this work is to investigate the existence, uniqueness, monotonicity and asymptotic behaviour of travelling wave solutions for a general epidemic model arising from the spread of an epidemic by oral–faecal transmission. First, we apply Schauder's fixed point theorem combining with a supersolution and subsolution pair to derive the existence of positive monotone monostable travelling wave solutions. Then, applying the Ikehara's theorem, we determine the exponential rates of travelling wave solutions which converge to two different equilibria as the moving coordinate tends to positive infinity and negative infinity, respectively. Finally, using the sliding method, we prove the uniqueness result provided the travelling wave solutions satisfy some boundedness conditions. (paper)
Kim, Chang-Goo; Ostriker, Eve C.
2017-09-01
We introduce TIGRESS, a novel framework for multi-physics numerical simulations of the star-forming interstellar medium (ISM) implemented in the Athena MHD code. The algorithms of TIGRESS are designed to spatially and temporally resolve key physical features, including: (1) the gravitational collapse and ongoing accretion of gas that leads to star formation in clusters; (2) the explosions of supernovae (SNe), both near their progenitor birth sites and from runaway OB stars, with time delays relative to star formation determined by population synthesis; (3) explicit evolution of SN remnants prior to the onset of cooling, which leads to the creation of the hot ISM; (4) photoelectric heating of the warm and cold phases of the ISM that tracks the time-dependent ambient FUV field from the young cluster population; (5) large-scale galactic differential rotation, which leads to epicyclic motion and shears out overdense structures, limiting large-scale gravitational collapse; (6) accurate evolution of magnetic fields, which can be important for vertical support of the ISM disk as well as angular momentum transport. We present tests of the newly implemented physics modules, and demonstrate application of TIGRESS in a fiducial model representing the solar neighborhood environment. We use a resolution study to demonstrate convergence and evaluate the minimum resolution {{Δ }}x required to correctly recover several ISM properties, including the star formation rate, wind mass-loss rate, disk scale height, turbulent and Alfvénic velocity dispersions, and volume fractions of warm and hot phases. For the solar neighborhood model, all these ISM properties are converged at {{Δ }}x≤slant 8 {pc}.
Multipartite classical and quantum secrecy monotones
International Nuclear Information System (INIS)
Cerf, N.J.; Massar, S.; Schneider, S.
2002-01-01
In order to study multipartite quantum cryptography, we introduce quantities which vanish on product probability distributions, and which can only decrease if the parties carry out local operations or public classical communication. These 'secrecy monotones' therefore measure how much secret correlation is shared by the parties. In the bipartite case we show that the mutual information is a secrecy monotone. In the multipartite case we describe two different generalizations of the mutual information, both of which are secrecy monotones. The existence of two distinct secrecy monotones allows us to show that in multipartite quantum cryptography the parties must make irreversible choices about which multipartite correlations they want to obtain. Secrecy monotones can be extended to the quantum domain and are then defined on density matrices. We illustrate this generalization by considering tripartite quantum cryptography based on the Greenberger-Horne-Zeilinger state. We show that before carrying out measurements on the state, the parties must make an irreversible decision about what probability distribution they want to obtain
International Nuclear Information System (INIS)
Mihaylov, I. B.; Siebers, J. V.
2008-01-01
The purpose of this study is to evaluate dose prediction errors (DPEs) and optimization convergence errors (OCEs) resulting from use of a superposition/convolution dose calculation algorithm in deliverable intensity-modulated radiation therapy (IMRT) optimization for head-and-neck (HN) patients. Thirteen HN IMRT patient plans were retrospectively reoptimized. The IMRT optimization was performed in three sequential steps: (1) fast optimization in which an initial nondeliverable IMRT solution was achieved and then converted to multileaf collimator (MLC) leaf sequences; (2) mixed deliverable optimization that used a Monte Carlo (MC) algorithm to account for the incident photon fluence modulation by the MLC, whereas a superposition/convolution (SC) dose calculation algorithm was utilized for the patient dose calculations; and (3) MC deliverable-based optimization in which both fluence and patient dose calculations were performed with a MC algorithm. DPEs of the mixed method were quantified by evaluating the differences between the mixed optimization SC dose result and a MC dose recalculation of the mixed optimization solution. OCEs of the mixed method were quantified by evaluating the differences between the MC recalculation of the mixed optimization solution and the final MC optimization solution. The results were analyzed through dose volume indices derived from the cumulative dose-volume histograms for selected anatomic structures. Statistical equivalence tests were used to determine the significance of the DPEs and the OCEs. Furthermore, a correlation analysis between DPEs and OCEs was performed. The evaluated DPEs were within ±2.8% while the OCEs were within 5.5%, indicating that OCEs can be clinically significant even when DPEs are clinically insignificant. The full MC-dose-based optimization reduced normal tissue dose by as much as 8.5% compared with the mixed-method optimization results. The DPEs and the OCEs in the targets had correlation coefficients greater
A unified framework of descent algorithms for nonlinear programs and variational inequalities
International Nuclear Information System (INIS)
Patriksson, M.
1993-01-01
We present a framework of algorithms for the solution of continuous optimization and variational inequality problems. In the general algorithm, a search direction finding auxiliary problems is obtained by replacing the original cost function with an approximating monotone cost function. The proposed framework encompasses algorithm classes presented earlier by Cohen, Dafermos, Migdalas, and Tseng, and includes numerous descent and successive approximation type methods, such as Newton methods, Jacobi and Gauss-Siedel type decomposition methods for problems defined over Cartesian product sets, and proximal point methods, among others. The auxiliary problem of the general algorithm also induces equivalent optimization reformulation and descent methods for asymmetric variational inequalities. We study the convergence properties of the general algorithm when applied to unconstrained optimization, nondifferentiable optimization, constrained differentiable optimization, and variational inequalities; the emphasis of the convergence analyses is placed on basic convergence results, convergence using different line search strategies and truncated subproblem solutions, and convergence rate results. This analysis offer a unification of known results; moreover, it provides strengthenings of convergence results for many existing algorithms, and indicates possible improvements of their realizations. 482 refs
Indian Academy of Sciences (India)
to as 'divide-and-conquer'. Although there has been a large effort in realizing efficient algorithms, there are not many universally accepted algorithm design paradigms. In this article, we illustrate algorithm design techniques such as balancing, greedy strategy, dynamic programming strategy, and backtracking or traversal of ...
Monotonicity and bounds on Bessel functions
Directory of Open Access Journals (Sweden)
Larry Landau
2000-07-01
Full Text Available survey my recent results on monotonicity with respect to order of general Bessel functions, which follow from a new identity and lead to best possible uniform bounds. Application may be made to the "spreading of the wave packet" for a free quantum particle on a lattice and to estimates for perturbative expansions.
Monotone Approximations of Minimum and Maximum Functions and Multi-objective Problems
International Nuclear Information System (INIS)
Stipanović, Dušan M.; Tomlin, Claire J.; Leitmann, George
2012-01-01
In this paper the problem of accomplishing multiple objectives by a number of agents represented as dynamic systems is considered. Each agent is assumed to have a goal which is to accomplish one or more objectives where each objective is mathematically formulated using an appropriate objective function. Sufficient conditions for accomplishing objectives are derived using particular convergent approximations of minimum and maximum functions depending on the formulation of the goals and objectives. These approximations are differentiable functions and they monotonically converge to the corresponding minimum or maximum function. Finally, an illustrative pursuit-evasion game example with two evaders and two pursuers is provided.
Monotone Approximations of Minimum and Maximum Functions and Multi-objective Problems
Energy Technology Data Exchange (ETDEWEB)
Stipanovic, Dusan M., E-mail: dusan@illinois.edu [University of Illinois at Urbana-Champaign, Coordinated Science Laboratory, Department of Industrial and Enterprise Systems Engineering (United States); Tomlin, Claire J., E-mail: tomlin@eecs.berkeley.edu [University of California at Berkeley, Department of Electrical Engineering and Computer Science (United States); Leitmann, George, E-mail: gleit@berkeley.edu [University of California at Berkeley, College of Engineering (United States)
2012-12-15
In this paper the problem of accomplishing multiple objectives by a number of agents represented as dynamic systems is considered. Each agent is assumed to have a goal which is to accomplish one or more objectives where each objective is mathematically formulated using an appropriate objective function. Sufficient conditions for accomplishing objectives are derived using particular convergent approximations of minimum and maximum functions depending on the formulation of the goals and objectives. These approximations are differentiable functions and they monotonically converge to the corresponding minimum or maximum function. Finally, an illustrative pursuit-evasion game example with two evaders and two pursuers is provided.
Monotonic Set-Extended Prefix Rewriting and Verification of Recursive Ping-Pong Protocols
DEFF Research Database (Denmark)
Delzanno, Giorgio; Esparza, Javier; Srba, Jiri
2006-01-01
of messages) some verification problems become decidable. In particular we give an algorithm to decide control state reachability, a problem related to security properties like secrecy and authenticity. The proof is via a reduction to a new prefix rewriting model called Monotonic Set-extended Prefix rewriting...
On utilization bounds for a periodic resource under rate monotonic scheduling
Renssen, van A.M.; Geuns, S.J.; Hausmans, J.P.H.M.; Poncin, W.; Bril, R.J.
2009-01-01
This paper revisits utilization bounds for a periodic resource under the rate monotonic (RM) scheduling algorithm. We show that the existing utilization bound, as presented in [8, 9], is optimistic. We subsequently show that by viewing the unavailability of the periodic resource as a deferrable
A note on monotone real circuits
Czech Academy of Sciences Publication Activity Database
Hrubeš, Pavel; Pudlák, Pavel
2018-01-01
Roč. 131, March (2018), s. 15-19 ISSN 0020-0190 EU Projects: European Commission(XE) 339691 - FEALORA Institutional support: RVO:67985840 Keywords : computational complexity * monotone real circuit * Karchmer-Wigderson game Subject RIV: BA - General Mathematics OBOR OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) Impact factor: 0.748, year: 2016 http ://www.sciencedirect.com/science/article/pii/S0020019017301965?via%3Dihub
A note on monotone real circuits
Czech Academy of Sciences Publication Activity Database
Hrubeš, Pavel; Pudlák, Pavel
2018-01-01
Roč. 131, March (2018), s. 15-19 ISSN 0020-0190 EU Projects: European Commission(XE) 339691 - FEALORA Institutional support: RVO:67985840 Keywords : computational complexity * monotone real circuit * Karchmer-Wigderson game Subject RIV: BA - General Mathematics OBOR OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) Impact factor: 0.748, year: 2016 http://www.sciencedirect.com/science/article/pii/S0020019017301965?via%3Dihub
Indian Academy of Sciences (India)
ticians but also forms the foundation of computer science. Two ... with methods of developing algorithms for solving a variety of problems but ... applications of computers in science and engineer- ... numerical calculus are as important. We will ...
Stepsize Restrictions for Boundedness and Monotonicity of Multistep Methods
Hundsdorfer, W.; Mozartova, A.; Spijker, M. N.
2011-01-01
In this paper nonlinear monotonicity and boundedness properties are analyzed for linear multistep methods. We focus on methods which satisfy a weaker boundedness condition than strict monotonicity for arbitrary starting values. In this way, many
Modeling non-monotonic properties under propositional argumentation
Wang, Geng; Lin, Zuoquan
2013-03-01
In the field of knowledge representation, argumentation is usually considered as an abstract framework for nonclassical logic. In this paper, however, we'd like to present a propositional argumentation framework, which can be used to closer simulate a real-world argumentation. We thereby argue that under a dialectical argumentation game, we can allow non-monotonic reasoning even under classical logic. We introduce two methods together for gaining nonmonotonicity, one by giving plausibility for arguments, the other by adding "exceptions" which is similar to defaults. Furthermore, we will give out an alternative definition for propositional argumentation using argumentative models, which is highly related to the previous reasoning method, but with a simple algorithm for calculation.
Testing Manifest Monotonicity Using Order-Constrained Statistical Inference
Tijmstra, Jesper; Hessen, David J.; van der Heijden, Peter G. M.; Sijtsma, Klaas
2013-01-01
Most dichotomous item response models share the assumption of latent monotonicity, which states that the probability of a positive response to an item is a nondecreasing function of a latent variable intended to be measured. Latent monotonicity cannot be evaluated directly, but it implies manifest monotonicity across a variety of observed scores,…
Indian Academy of Sciences (India)
algorithm design technique called 'divide-and-conquer'. One of ... Turtle graphics, September. 1996. 5. ... whole list named 'PO' is a pointer to the first element of the list; ..... Program for computing matrices X and Y and placing the result in C *).
Indian Academy of Sciences (India)
algorithm that it is implicitly understood that we know how to generate the next natural ..... Explicit comparisons are made in line (1) where maximum and minimum is ... It can be shown that the function T(n) = 3/2n -2 is the solution to the above ...
A Constrained Algorithm Based NMFα for Image Representation
Directory of Open Access Journals (Sweden)
Chenxue Yang
2014-01-01
Full Text Available Nonnegative matrix factorization (NMF is a useful tool in learning a basic representation of image data. However, its performance and applicability in real scenarios are limited because of the lack of image information. In this paper, we propose a constrained matrix decomposition algorithm for image representation which contains parameters associated with the characteristics of image data sets. Particularly, we impose label information as additional hard constraints to the α-divergence-NMF unsupervised learning algorithm. The resulted algorithm is derived by using Karush-Kuhn-Tucker (KKT conditions as well as the projected gradient and its monotonic local convergence is proved by using auxiliary functions. In addition, we provide a method to select the parameters to our semisupervised matrix decomposition algorithm in the experiment. Compared with the state-of-the-art approaches, our method with the parameters has the best classification accuracy on three image data sets.
Monotone Comparative Statics for the Industry Composition
DEFF Research Database (Denmark)
Laugesen, Anders Rosenstand; Bache, Peter Arendorf
2015-01-01
We let heterogeneous firms face decisions on a number of complementary activities in a monopolistically-competitive industry. The endogenous level of competition and selection regarding entry and exit of firms introduces a wedge between monotone comparative statics (MCS) at the firm level and MCS...... for the industry composition. The latter phenomenon is defined as first-order stochastic dominance shifts in the equilibrium distributions of all activities across active firms. We provide sufficient conditions for MCS at both levels of analysis and show that we may have either type of MCS without the other...
International Nuclear Information System (INIS)
Ohtsuki, Yukiyoshi
2010-01-01
In this paper, molecular quantum computation is numerically studied with the quantum search algorithm (Grover's algorithm) by means of optimal control simulation. Qubits are implemented in the vibronic states of I 2 , while gate operations are realized by optimally designed laser pulses. The methodological aspects of the simulation are discussed in detail. We show that the algorithm for solving a gate pulse-design problem has the same mathematical form as a state-to-state control problem in the density matrix formalism, which provides monotonically convergent algorithms as an alternative to the Krotov method. The sequential irradiation of separately designed gate pulses leads to the population distribution predicted by Grover's algorithm. The computational accuracy is reduced by the imperfect quality of the pulse design and by the electronic decoherence processes that are modeled by the non-Markovian master equation. However, as long as we focus on the population distribution of the vibronic qubits, we can search a target state with high probability without introducing error-correction processes during the computation. A generalized gate pulse-design scheme to explicitly include decoherence effects is outlined, in which we propose a new objective functional together with its solution algorithm that guarantees monotonic convergence.
Indian Academy of Sciences (India)
will become clear in the next article when we discuss a simple logo like programming language. ... Rod B may be used as an auxiliary store. The problem is to find an algorithm which performs this task. ... No disks are moved from A to Busing C as auxiliary rod. • move _disk (A, C);. (No + l)th disk is moved from A to C directly ...
The Monotonicity Puzzle: An Experimental Investigation of Incentive Structures
Directory of Open Access Journals (Sweden)
Jeannette Brosig
2010-05-01
Full Text Available Non-monotone incentive structures, which - according to theory - are able to induce optimal behavior, are often regarded as empirically less relevant for labor relationships. We compare the performance of a theoretically optimal non-monotone contract with a monotone one under controlled laboratory conditions. Implementing some features relevant to real-world employment relationships, our paper demonstrates that, in fact, the frequency of income-maximizing decisions made by agents is higher under the monotone contract. Although this observed behavior does not change the superiority of the non-monotone contract for principals, they do not choose this contract type in a significant way. This is what we call the monotonicity puzzle. Detailed investigations of decisions provide a clue for solving the puzzle and a possible explanation for the popularity of monotone contracts.
... is also found to be weak. If both accommodation and convergence are weak, reading glasses, sometimes with prism added, may be a great option for these patients. It is very difficult to improve accommodation with exercises. Updated 7/2017 Eye Terms & Conditions ...
Monotonicity of fitness landscapes and mutation rate control.
Belavkin, Roman V; Channon, Alastair; Aston, Elizabeth; Aston, John; Krašovec, Rok; Knight, Christopher G
2016-12-01
A common view in evolutionary biology is that mutation rates are minimised. However, studies in combinatorial optimisation and search have shown a clear advantage of using variable mutation rates as a control parameter to optimise the performance of evolutionary algorithms. Much biological theory in this area is based on Ronald Fisher's work, who used Euclidean geometry to study the relation between mutation size and expected fitness of the offspring in infinite phenotypic spaces. Here we reconsider this theory based on the alternative geometry of discrete and finite spaces of DNA sequences. First, we consider the geometric case of fitness being isomorphic to distance from an optimum, and show how problems of optimal mutation rate control can be solved exactly or approximately depending on additional constraints of the problem. Then we consider the general case of fitness communicating only partial information about the distance. We define weak monotonicity of fitness landscapes and prove that this property holds in all landscapes that are continuous and open at the optimum. This theoretical result motivates our hypothesis that optimal mutation rate functions in such landscapes will increase when fitness decreases in some neighbourhood of an optimum, resembling the control functions derived in the geometric case. We test this hypothesis experimentally by analysing approximately optimal mutation rate control functions in 115 complete landscapes of binding scores between DNA sequences and transcription factors. Our findings support the hypothesis and find that the increase of mutation rate is more rapid in landscapes that are less monotonic (more rugged). We discuss the relevance of these findings to living organisms.
Generalized convexity, generalized monotonicity recent results
Martinez-Legaz, Juan-Enrique; Volle, Michel
1998-01-01
A function is convex if its epigraph is convex. This geometrical structure has very strong implications in terms of continuity and differentiability. Separation theorems lead to optimality conditions and duality for convex problems. A function is quasiconvex if its lower level sets are convex. Here again, the geo metrical structure of the level sets implies some continuity and differentiability properties for quasiconvex functions. Optimality conditions and duality can be derived for optimization problems involving such functions as well. Over a period of about fifty years, quasiconvex and other generalized convex functions have been considered in a variety of fields including economies, man agement science, engineering, probability and applied sciences in accordance with the need of particular applications. During the last twenty-five years, an increase of research activities in this field has been witnessed. More recently generalized monotonicity of maps has been studied. It relates to generalized conve...
The Monotonic Lagrangian Grid for Fast Air-Traffic Evaluation
Alexandrov, Natalia; Kaplan, Carolyn; Oran, Elaine; Boris, Jay
2010-01-01
This paper describes the continued development of a dynamic air-traffic model, ATMLG, intended for rapid evaluation of rules and methods to control and optimize transport systems. The underlying data structure is based on the Monotonic Lagrangian Grid (MLG), which is used for sorting and ordering positions and other data needed to describe N moving bodies, and their interactions. In ATMLG, the MLG is combined with algorithms for collision avoidance and updating aircraft trajectories. Aircraft that are close to each other in physical space are always near neighbors in the MLG data arrays, resulting in a fast nearest-neighbor interaction algorithm that scales as N. In this paper, we use ATMLG to examine how the ability to maintain a required separation between aircraft decreases as the number of aircraft in the volume increases. This requires keeping track of the primary and subsequent collision avoidance maneuvers necessary to maintain a five mile separation distance between all aircraft. Simulation results show that the number of collision avoidance moves increases exponentially with the number of aircraft in the volume.
Lacunary ideal convergence of multiple sequences
Directory of Open Access Journals (Sweden)
Bipan Hazarika
2016-01-01
Full Text Available An ideal I is a family of subsets of N×N which is closed under taking finite unions and subsets of its elements. In this article, the concept of lacunary ideal convergence of double sequences has been introduced. Also the relation between lacunary ideal convergent and lacunary Cauchy double sequences has been established. Furthermore, the notions of lacunary ideal limit point and lacunary ideal cluster points have been introduced and find the relation between these two notions. Finally, we have studied the properties such as solidity, monotonic.
Type monotonic allocation schemes for multi-glove games
Brânzei, R.; Solymosi, T.; Tijs, S.H.
2007-01-01
Multiglove markets and corresponding games are considered.For this class of games we introduce the notion of type monotonic allocation scheme.Allocation rules for multiglove markets based on weight systems are introduced and characterized.These allocation rules generate type monotonic allocation schemes for multiglove games and are also helpful in proving that each core element of the corresponding game is extendable to a type monotonic allocation scheme.The T-value turns out to generate a ty...
Stability of dynamical systems on the role of monotonic and non-monotonic Lyapunov functions
Michel, Anthony N; Liu, Derong
2015-01-01
The second edition of this textbook provides a single source for the analysis of system models represented by continuous-time and discrete-time, finite-dimensional and infinite-dimensional, and continuous and discontinuous dynamical systems. For these system models, it presents results which comprise the classical Lyapunov stability theory involving monotonic Lyapunov functions, as well as corresponding contemporary stability results involving non-monotonicLyapunov functions.Specific examples from several diverse areas are given to demonstrate the applicability of the developed theory to many important classes of systems, including digital control systems, nonlinear regulator systems, pulse-width-modulated feedback control systems, and artificial neural networks. The authors cover the following four general topics: - Representation and modeling of dynamical systems of the types described above - Presentation of Lyapunov and Lagrange stability theory for dynamical sy...
Stepsize Restrictions for Boundedness and Monotonicity of Multistep Methods
Hundsdorfer, W.
2011-04-29
In this paper nonlinear monotonicity and boundedness properties are analyzed for linear multistep methods. We focus on methods which satisfy a weaker boundedness condition than strict monotonicity for arbitrary starting values. In this way, many linear multistep methods of practical interest are included in the theory. Moreover, it will be shown that for such methods monotonicity can still be valid with suitable Runge-Kutta starting procedures. Restrictions on the stepsizes are derived that are not only sufficient but also necessary for these boundedness and monotonicity properties. © 2011 Springer Science+Business Media, LLC.
Chen, Baojiang; Qin, Jing
2014-05-10
In statistical analysis, a regression model is needed if one is interested in finding the relationship between a response variable and covariates. When the response depends on the covariate, then it may also depend on the function of this covariate. If one has no knowledge of this functional form but expect for monotonic increasing or decreasing, then the isotonic regression model is preferable. Estimation of parameters for isotonic regression models is based on the pool-adjacent-violators algorithm (PAVA), where the monotonicity constraints are built in. With missing data, people often employ the augmented estimating method to improve estimation efficiency by incorporating auxiliary information through a working regression model. However, under the framework of the isotonic regression model, the PAVA does not work as the monotonicity constraints are violated. In this paper, we develop an empirical likelihood-based method for isotonic regression model to incorporate the auxiliary information. Because the monotonicity constraints still hold, the PAVA can be used for parameter estimation. Simulation studies demonstrate that the proposed method can yield more efficient estimates, and in some situations, the efficiency improvement is substantial. We apply this method to a dementia study. Copyright © 2013 John Wiley & Sons, Ltd.
Monotone measures of ergodicity for Markov chains
Directory of Open Access Journals (Sweden)
J. Keilson
1998-01-01
Full Text Available The following paper, first written in 1974, was never published other than as part of an internal research series. Its lack of publication is unrelated to the merits of the paper and the paper is of current importance by virtue of its relation to the relaxation time. A systematic discussion is provided of the approach of a finite Markov chain to ergodicity by proving the monotonicity of an important set of norms, each measures of egodicity, whether or not time reversibility is present. The paper is of particular interest because the discussion of the relaxation time of a finite Markov chain [2] has only been clean for time reversible chains, a small subset of the chains of interest. This restriction is not present here. Indeed, a new relaxation time quoted quantifies the relaxation time for all finite ergodic chains (cf. the discussion of Q1(t below Equation (1.7]. This relaxation time was developed by Keilson with A. Roy in his thesis [6], yet to be published.
A Penalization-Gradient Algorithm for Variational Inequalities
Directory of Open Access Journals (Sweden)
Abdellatif Moudafi
2011-01-01
Full Text Available This paper is concerned with the study of a penalization-gradient algorithm for solving variational inequalities, namely, find x̅∈C such that 〈Ax̅,y-x̅〉≥0 for all y∈C, where A:H→H is a single-valued operator, C is a closed convex set of a real Hilbert space H. Given Ψ:H→R ∪ {+∞} which acts as a penalization function with respect to the constraint x̅∈C, and a penalization parameter βk, we consider an algorithm which alternates a proximal step with respect to ∂Ψ and a gradient step with respect to A and reads as xk=(I+λkβk∂Ψ-1(xk-1-λkAxk-1. Under mild hypotheses, we obtain weak convergence for an inverse strongly monotone operator and strong convergence for a Lipschitz continuous and strongly monotone operator. Applications to hierarchical minimization and fixed-point problems are also given and the multivalued case is reached by replacing the multivalued operator by its Yosida approximate which is always Lipschitz continuous.
Convergence criteria for systems of nonlinear elliptic partial differential equations
International Nuclear Information System (INIS)
Sharma, R.K.
1986-01-01
This thesis deals with convergence criteria for a special system of nonlinear elliptic partial differential equations. A fixed-point algorithm is used, which iteratively solves one linearized elliptic partial differential equation at a time. Conditions are established that help foresee the convergence of the algorithm. Under reasonable hypotheses it is proved that the algorithm converges for such nonlinear elliptic systems. Extensive experimental results are reported and they show the algorithm converges in a wide variety of cases and the convergence is well correlated with the theoretical conditions introduced in this thesis
An Ensemble Approach in Converging Contents of LMS and KMS
Sabitha, A. Sai; Mehrotra, Deepti; Bansal, Abhay
2017-01-01
Currently the challenges in e-Learning are converging the learning content from various sources and managing them within e-learning practices. Data mining learning algorithms can be used and the contents can be converged based on the Metadata of the objects. Ensemble methods use multiple learning algorithms and it can be used to converge the…
Logarithmically completely monotonic functions involving the Generalized Gamma Function
Directory of Open Access Journals (Sweden)
Faton Merovci
2010-12-01
Full Text Available By a simple approach, two classes of functions involving generalization Euler's gamma function and originating from certain problems of traffic flow are proved to be logarithmically completely monotonic and a class of functions involving the psi function is showed to be completely monotonic.
Logarithmically completely monotonic functions involving the Generalized Gamma Function
Faton Merovci; Valmir Krasniqi
2010-01-01
By a simple approach, two classes of functions involving generalization Euler's gamma function and originating from certain problems of traffic flow are proved to be logarithmically completely monotonic and a class of functions involving the psi function is showed to be completely monotonic.
Testing manifest monotonicity using order-constrained statistical inference
Tijmstra, J.; Hessen, D.J.; van der Heijden, P.G.M.; Sijtsma, K.
2013-01-01
Most dichotomous item response models share the assumption of latent monotonicity, which states that the probability of a positive response to an item is a nondecreasing function of a latent variable intended to be measured. Latent monotonicity cannot be evaluated directly, but it implies manifest
Do convergent developmental mechanisms underlie convergent phenotypes?
Wray, Gregory A.
2002-01-01
Convergence is a pervasive evolutionary process, affecting many aspects of phenotype and even genotype. Relatively little is known about convergence in developmental processes, however, nor about the degree to which convergence in development underlies convergence in anatomy. A switch in the ecology of sea urchins from feeding to nonfeeding larvae illustrates how convergence in development can be associated with convergence in anatomy. Comparisons to more distantly related taxa, however, suggest that this association may be limited to relatively close phylogenetic comparisons. Similarities in gene expression during development provide another window into the association between convergence in developmental processes and convergence in anatomy. Several well-studied transcription factors exhibit likely cases of convergent gene expression in distantly related animal phyla. Convergence in regulatory gene expression domains is probably more common than generally acknowledged, and can arise for several different reasons. Copyright 2002 S. Karger AG, Basel.
Czech Academy of Sciences Publication Activity Database
Axelsson, Owe; Karátson, J.
2017-01-01
Roč. 210, January 2017 (2017), s. 155-164 ISSN 0377-0427 Institutional support: RVO:68145535 Keywords : finite difference method * error estimates * matrix splitting * preconditioning Subject RIV: BA - General Mathematics OBOR OECD: Applied mathematics Impact factor: 1.357, year: 2016 http://www. science direct.com/ science /article/pii/S0377042716301492?via%3Dihub
Czech Academy of Sciences Publication Activity Database
Axelsson, Owe; Karátson, J.
2017-01-01
Roč. 210, January 2017 (2017), s. 155-164 ISSN 0377-0427 Institutional support: RVO:68145535 Keywords : finite difference method * error estimates * matrix splitting * preconditioning Subject RIV: BA - General Mathematics OBOR OECD: Applied mathematics Impact factor: 1.357, year: 2016 http://www.sciencedirect.com/science/article/pii/S0377042716301492?via%3Dihub
Surface meshing with curvature convergence
Li, Huibin; Zeng, Wei; Morvan, Jean-Marie; Chen, Liming; Gu, Xianfengdavid
2014-01-01
Surface meshing plays a fundamental role in graphics and visualization. Many geometric processing tasks involve solving geometric PDEs on meshes. The numerical stability, convergence rates and approximation errors are largely determined by the mesh qualities. In practice, Delaunay refinement algorithms offer satisfactory solutions to high quality mesh generations. The theoretical proofs for volume based and surface based Delaunay refinement algorithms have been established, but those for conformal parameterization based ones remain wide open. This work focuses on the curvature measure convergence for the conformal parameterization based Delaunay refinement algorithms. Given a metric surface, the proposed approach triangulates its conformal uniformization domain by the planar Delaunay refinement algorithms, and produces a high quality mesh. We give explicit estimates for the Hausdorff distance, the normal deviation, and the differences in curvature measures between the surface and the mesh. In contrast to the conventional results based on volumetric Delaunay refinement, our stronger estimates are independent of the mesh structure and directly guarantee the convergence of curvature measures. Meanwhile, our result on Gaussian curvature measure is intrinsic to the Riemannian metric and independent of the embedding. In practice, our meshing algorithm is much easier to implement and much more efficient. The experimental results verified our theoretical results and demonstrated the efficiency of the meshing algorithm. © 2014 IEEE.
Surface meshing with curvature convergence
Li, Huibin
2014-06-01
Surface meshing plays a fundamental role in graphics and visualization. Many geometric processing tasks involve solving geometric PDEs on meshes. The numerical stability, convergence rates and approximation errors are largely determined by the mesh qualities. In practice, Delaunay refinement algorithms offer satisfactory solutions to high quality mesh generations. The theoretical proofs for volume based and surface based Delaunay refinement algorithms have been established, but those for conformal parameterization based ones remain wide open. This work focuses on the curvature measure convergence for the conformal parameterization based Delaunay refinement algorithms. Given a metric surface, the proposed approach triangulates its conformal uniformization domain by the planar Delaunay refinement algorithms, and produces a high quality mesh. We give explicit estimates for the Hausdorff distance, the normal deviation, and the differences in curvature measures between the surface and the mesh. In contrast to the conventional results based on volumetric Delaunay refinement, our stronger estimates are independent of the mesh structure and directly guarantee the convergence of curvature measures. Meanwhile, our result on Gaussian curvature measure is intrinsic to the Riemannian metric and independent of the embedding. In practice, our meshing algorithm is much easier to implement and much more efficient. The experimental results verified our theoretical results and demonstrated the efficiency of the meshing algorithm. © 2014 IEEE.
A Nonmonotone Line Search Filter Algorithm for the System of Nonlinear Equations
Directory of Open Access Journals (Sweden)
Zhong Jin
2012-01-01
Full Text Available We present a new iterative method based on the line search filter method with the nonmonotone strategy to solve the system of nonlinear equations. The equations are divided into two groups; some equations are treated as constraints and the others act as the objective function, and the two groups are just updated at the iterations where it is needed indeed. We employ the nonmonotone idea to the sufficient reduction conditions and filter technique which leads to a flexibility and acceptance behavior comparable to monotone methods. The new algorithm is shown to be globally convergent and numerical experiments demonstrate its effectiveness.
Optimal Monotonicity-Preserving Perturbations of a Given Runge–Kutta Method
Higueras, Inmaculada
2018-02-14
Perturbed Runge–Kutta methods (also referred to as downwind Runge–Kutta methods) can guarantee monotonicity preservation under larger step sizes relative to their traditional Runge–Kutta counterparts. In this paper we study the question of how to optimally perturb a given method in order to increase the radius of absolute monotonicity (a.m.). We prove that for methods with zero radius of a.m., it is always possible to give a perturbation with positive radius. We first study methods for linear problems and then methods for nonlinear problems. In each case, we prove upper bounds on the radius of a.m., and provide algorithms to compute optimal perturbations. We also provide optimal perturbations for many known methods.
Optimal Monotonicity-Preserving Perturbations of a Given Runge–Kutta Method
Higueras, Inmaculada; Ketcheson, David I.; Kocsis, Tihamé r A.
2018-01-01
Perturbed Runge–Kutta methods (also referred to as downwind Runge–Kutta methods) can guarantee monotonicity preservation under larger step sizes relative to their traditional Runge–Kutta counterparts. In this paper we study the question of how to optimally perturb a given method in order to increase the radius of absolute monotonicity (a.m.). We prove that for methods with zero radius of a.m., it is always possible to give a perturbation with positive radius. We first study methods for linear problems and then methods for nonlinear problems. In each case, we prove upper bounds on the radius of a.m., and provide algorithms to compute optimal perturbations. We also provide optimal perturbations for many known methods.
Strong monotonicity in mixed-state entanglement manipulation
International Nuclear Information System (INIS)
Ishizaka, Satoshi
2006-01-01
A strong entanglement monotone, which never increases under local operations and classical communications (LOCC), restricts quantum entanglement manipulation more strongly than the usual monotone since the usual one does not increase on average under LOCC. We propose strong monotones in mixed-state entanglement manipulation under LOCC. These are related to the decomposability and one-positivity of an operator constructed from a quantum state, and reveal geometrical characteristics of entangled states. These are lower bounded by the negativity or generalized robustness of entanglement
Monotonicity-based electrical impedance tomography for lung imaging
Zhou, Liangdong; Harrach, Bastian; Seo, Jin Keun
2018-04-01
This paper presents a monotonicity-based spatiotemporal conductivity imaging method for continuous regional lung monitoring using electrical impedance tomography (EIT). The EIT data (i.e. the boundary current-voltage data) can be decomposed into pulmonary, cardiac and other parts using their different periodic natures. The time-differential current-voltage operator corresponding to the lung ventilation can be viewed as either semi-positive or semi-negative definite owing to monotonic conductivity changes within the lung regions. We used these monotonicity constraints to improve the quality of lung EIT imaging. We tested the proposed methods in numerical simulations, phantom experiments and human experiments.
International Nuclear Information System (INIS)
Niu, Tianye; Fruhauf, Quentin; Petrongolo, Michael; Zhu, Lei; Ye, Xiaojing
2014-01-01
Recently, we proposed a new algorithm of accelerated barrier optimization compressed sensing (ABOCS) for iterative CT reconstruction. The previous implementation of ABOCS uses gradient projection (GP) with a Barzilai–Borwein (BB) step-size selection scheme (GP-BB) to search for the optimal solution. The algorithm does not converge stably due to its non-monotonic behavior. In this paper, we further improve the convergence of ABOCS using the unknown-parameter Nesterov (UPN) method and investigate the ABOCS reconstruction performance on clinical patient data. Comparison studies are carried out on reconstructions of computer simulation, a physical phantom and a head-and-neck patient. In all of these studies, the ABOCS results using UPN show more stable and faster convergence than those of the GP-BB method and a state-of-the-art Bregman-type method. As shown in the simulation study of the Shepp–Logan phantom, UPN achieves the same image quality as those of GP-BB and the Bregman-type methods, but reduces the iteration numbers by up to 50% and 90%, respectively. In the Catphan©600 phantom study, a high-quality image with relative reconstruction error (RRE) less than 3% compared to the full-view result is obtained using UPN with 17% projections (60 views). In the conventional filtered-backprojection reconstruction, the corresponding RRE is more than 15% on the same projection data. The superior performance of ABOCS with the UPN implementation is further demonstrated on the head-and-neck patient. Using 25% projections (91 views), the proposed method reduces the RRE from 21% as in the filtered backprojection (FBP) results to 7.3%. In conclusion, we propose UPN for ABOCS implementation. As compared to GP-BB and the Bregman-type methods, the new method significantly improves the convergence with higher stability and fewer iterations. (paper)
Risk-Sensitive Control with Near Monotone Cost
International Nuclear Information System (INIS)
Biswas, Anup; Borkar, V. S.; Suresh Kumar, K.
2010-01-01
The infinite horizon risk-sensitive control problem for non-degenerate controlled diffusions is analyzed under a 'near monotonicity' condition on the running cost that penalizes large excursions of the process.
An Examination of Cooper's Test for Monotonic Trend
Hsu, Louis
1977-01-01
A statistic for testing monotonic trend that has been presented in the literature is shown not to be the binomial random variable it is contended to be, but rather it is linearly related to Kendall's tau statistic. (JKS)
A Survey on Operator Monotonicity, Operator Convexity, and Operator Means
Directory of Open Access Journals (Sweden)
Pattrawut Chansangiam
2015-01-01
Full Text Available This paper is an expository devoted to an important class of real-valued functions introduced by Löwner, namely, operator monotone functions. This concept is closely related to operator convex/concave functions. Various characterizations for such functions are given from the viewpoint of differential analysis in terms of matrix of divided differences. From the viewpoint of operator inequalities, various characterizations and the relationship between operator monotonicity and operator convexity are given by Hansen and Pedersen. In the viewpoint of measure theory, operator monotone functions on the nonnegative reals admit meaningful integral representations with respect to Borel measures on the unit interval. Furthermore, Kubo-Ando theory asserts the correspondence between operator monotone functions and operator means.
Convergence in Multispecies Interactions
Bittleston, Leonora Sophia; Pierce, Naomi E.; Ellison, Aaron M.; Pringle, Anne
2016-01-01
The concepts of convergent evolution and community convergence highlight how selective pressures can shape unrelated organisms or communities in similar ways. We propose a related concept, convergent interactions, to describe the independent evolution of multispecies interactions with similar physiological or ecological functions. A focus on convergent interactions clarifies how natural selection repeatedly favors particular kinds of associations among species. Characterizing convergent inter...
Optimality Measures for Monotone Equivariant Cluster Techniques.
1980-09-01
complete linkage, u-clustering (u - .3, .5, .7), uv-clustering (uv = (.2,.4), (.2,.6), (.4,.6)) as well as the UPGMA algorithm. The idea will be to...Table 15. Notice that these measure-- do indeed pioduce difftxent verdicts. OPI rates UPGMA as best with uv = (.2,.4) R € second. By OP2, UPGMA is best...By OPI, UPGQA and uv = (.4,.6) are tied for first place, while by OP2, UPGMA is best with uv = (.2,.6), uv = (.2,.4) and uv = (.4,.6) close behind
Completely monotonic functions related to logarithmic derivatives of entire functions
DEFF Research Database (Denmark)
Pedersen, Henrik Laurberg
2011-01-01
The logarithmic derivative l(x) of an entire function of genus p and having only non-positive zeros is represented in terms of a Stieltjes function. As a consequence, (-1)p(xml(x))(m+p) is a completely monotonic function for all m ≥ 0. This generalizes earlier results on complete monotonicity...... of functions related to Euler's psi-function. Applications to Barnes' multiple gamma functions are given....
Monotonic Loading of Circular Surface Footings on Clay
DEFF Research Database (Denmark)
Ibsen, Lars Bo; Barari, Amin
2011-01-01
Appropriate modeling of offshore foundations under monotonic loading is a significant challenge in geotechnical engineering. This paper reports experimental and numerical analyses, specifically investigating the response of circular surface footings during monotonic loading and elastoplastic...... behavior during reloading. By using the findings presented in this paper, it is possible to extend the model to simulate the vertical-load displacement response of offshore bucket foundations....
Ghosh, Sayan; Das, Swagatam; Vasilakos, Athanasios V; Suresh, Kaushik
2012-02-01
Differential evolution (DE) is arguably one of the most powerful stochastic real-parameter optimization algorithms of current interest. Since its inception in the mid 1990s, DE has been finding many successful applications in real-world optimization problems from diverse domains of science and engineering. This paper takes a first significant step toward the convergence analysis of a canonical DE (DE/rand/1/bin) algorithm. It first deduces a time-recursive relationship for the probability density function (PDF) of the trial solutions, taking into consideration the DE-type mutation, crossover, and selection mechanisms. Then, by applying the concepts of Lyapunov stability theorems, it shows that as time approaches infinity, the PDF of the trial solutions concentrates narrowly around the global optimum of the objective function, assuming the shape of a Dirac delta distribution. Asymptotic convergence behavior of the population PDF is established by constructing a Lyapunov functional based on the PDF and showing that it monotonically decreases with time. The analysis is applicable to a class of continuous and real-valued objective functions that possesses a unique global optimum (but may have multiple local optima). Theoretical results have been substantiated with relevant computer simulations.
Moduli and Characteristics of Monotonicity in Some Banach Lattices
Directory of Open Access Journals (Sweden)
Miroslav Krbec
2010-01-01
Full Text Available First the characteristic of monotonicity of any Banach lattice X is expressed in terms of the left limit of the modulus of monotonicity of X at the point 1. It is also shown that for Köthe spaces the classical characteristic of monotonicity is the same as the characteristic of monotonicity corresponding to another modulus of monotonicity δ^m,E. The characteristic of monotonicity of Orlicz function spaces and Orlicz sequence spaces equipped with the Luxemburg norm are calculated. In the first case the characteristic is expressed in terms of the generating Orlicz function only, but in the sequence case the formula is not so direct. Three examples show why in the sequence case so direct formula is rather impossible. Some other auxiliary and complemented results are also presented. By the results of Betiuk-Pilarska and Prus (2008 which establish that Banach lattices X with ε0,m(X<1 and weak orthogonality property have the weak fixed point property, our results are related to the fixed point theory (Kirk and Sims (2001.
Specific non-monotonous interactions increase persistence of ecological networks.
Yan, Chuan; Zhang, Zhibin
2014-03-22
The relationship between stability and biodiversity has long been debated in ecology due to opposing empirical observations and theoretical predictions. Species interaction strength is often assumed to be monotonically related to population density, but the effects on stability of ecological networks of non-monotonous interactions that change signs have not been investigated previously. We demonstrate that for four kinds of non-monotonous interactions, shifting signs to negative or neutral interactions at high population density increases persistence (a measure of stability) of ecological networks, while for the other two kinds of non-monotonous interactions shifting signs to positive interactions at high population density decreases persistence of networks. Our results reveal a novel mechanism of network stabilization caused by specific non-monotonous interaction types through either increasing stable equilibrium points or reducing unstable equilibrium points (or both). These specific non-monotonous interactions may be important in maintaining stable and complex ecological networks, as well as other networks such as genes, neurons, the internet and human societies.
Bozkaya, Uǧur; Turney, Justin M.; Yamaguchi, Yukio; Schaefer, Henry F.; Sherrill, C. David
2011-09-01
Using a Lagrangian-based approach, we present a more elegant derivation of the equations necessary for the variational optimization of the molecular orbitals (MOs) for the coupled-cluster doubles (CCD) method and second-order Møller-Plesset perturbation theory (MP2). These orbital-optimized theories are referred to as OO-CCD and OO-MP2 (or simply "OD" and "OMP2" for short), respectively. We also present an improved algorithm for orbital optimization in these methods. Explicit equations for response density matrices, the MO gradient, and the MO Hessian are reported both in spin-orbital and closed-shell spin-adapted forms. The Newton-Raphson algorithm is used for the optimization procedure using the MO gradient and Hessian. Further, orbital stability analyses are also carried out at correlated levels. The OD and OMP2 approaches are compared with the standard MP2, CCD, CCSD, and CCSD(T) methods. All these methods are applied to H2O, three diatomics, and the O_4^+ molecule. Results demonstrate that the CCSD and OD methods give nearly identical results for H2O and diatomics; however, in symmetry-breaking problems as exemplified by O_4^+, the OD method provides better results for vibrational frequencies. The OD method has further advantages over CCSD: its analytic gradients are easier to compute since there is no need to solve the coupled-perturbed equations for the orbital response, the computation of one-electron properties are easier because there is no response contribution to the particle density matrices, the variational optimized orbitals can be readily extended to allow inactive orbitals, it avoids spurious second-order poles in its response function, and its transition dipole moments are gauge invariant. The OMP2 has these same advantages over canonical MP2, making it promising for excited state properties via linear response theory. The quadratically convergent orbital-optimization procedure converges quickly for OMP2, and provides molecular properties that
Pettersson, Per
2013-05-01
The stochastic Galerkin and collocation methods are used to solve an advection-diffusion equation with uncertain and spatially varying viscosity. We investigate well-posedness, monotonicity and stability for the extended system resulting from the Galerkin projection of the advection-diffusion equation onto the stochastic basis functions. High-order summation-by-parts operators and weak imposition of boundary conditions are used to prove stability of the semi-discrete system.It is essential that the eigenvalues of the resulting viscosity matrix of the stochastic Galerkin system are positive and we investigate conditions for this to hold. When the viscosity matrix is diagonalizable, stochastic Galerkin and stochastic collocation are similar in terms of computational cost, and for some cases the accuracy is higher for stochastic Galerkin provided that monotonicity requirements are met. We also investigate the total spatial operator of the semi-discretized system and its impact on the convergence to steady-state. © 2013 Elsevier B.V.
Pettersson, Per; Doostan, Alireza; Nordströ m, Jan
2013-01-01
The stochastic Galerkin and collocation methods are used to solve an advection-diffusion equation with uncertain and spatially varying viscosity. We investigate well-posedness, monotonicity and stability for the extended system resulting from the Galerkin projection of the advection-diffusion equation onto the stochastic basis functions. High-order summation-by-parts operators and weak imposition of boundary conditions are used to prove stability of the semi-discrete system.It is essential that the eigenvalues of the resulting viscosity matrix of the stochastic Galerkin system are positive and we investigate conditions for this to hold. When the viscosity matrix is diagonalizable, stochastic Galerkin and stochastic collocation are similar in terms of computational cost, and for some cases the accuracy is higher for stochastic Galerkin provided that monotonicity requirements are met. We also investigate the total spatial operator of the semi-discretized system and its impact on the convergence to steady-state. © 2013 Elsevier B.V.
Information flow in layered networks of non-monotonic units
Schittler Neves, Fabio; Martim Schubert, Benno; Erichsen, Rubem, Jr.
2015-07-01
Layered neural networks are feedforward structures that yield robust parallel and distributed pattern recognition. Even though much attention has been paid to pattern retrieval properties in such systems, many aspects of their dynamics are not yet well characterized or understood. In this work we study, at different temperatures, the memory activity and information flows through layered networks in which the elements are the simplest binary odd non-monotonic function. Our results show that, considering a standard Hebbian learning approach, the network information content has its maximum always at the monotonic limit, even though the maximum memory capacity can be found at non-monotonic values for small enough temperatures. Furthermore, we show that such systems exhibit rich macroscopic dynamics, including not only fixed point solutions of its iterative map, but also cyclic and chaotic attractors that also carry information.
Information flow in layered networks of non-monotonic units
International Nuclear Information System (INIS)
Neves, Fabio Schittler; Schubert, Benno Martim; Erichsen, Rubem Jr
2015-01-01
Layered neural networks are feedforward structures that yield robust parallel and distributed pattern recognition. Even though much attention has been paid to pattern retrieval properties in such systems, many aspects of their dynamics are not yet well characterized or understood. In this work we study, at different temperatures, the memory activity and information flows through layered networks in which the elements are the simplest binary odd non-monotonic function. Our results show that, considering a standard Hebbian learning approach, the network information content has its maximum always at the monotonic limit, even though the maximum memory capacity can be found at non-monotonic values for small enough temperatures. Furthermore, we show that such systems exhibit rich macroscopic dynamics, including not only fixed point solutions of its iterative map, but also cyclic and chaotic attractors that also carry information. (paper)
Estimating monotonic rates from biological data using local linear regression.
Olito, Colin; White, Craig R; Marshall, Dustin J; Barneche, Diego R
2017-03-01
Accessing many fundamental questions in biology begins with empirical estimation of simple monotonic rates of underlying biological processes. Across a variety of disciplines, ranging from physiology to biogeochemistry, these rates are routinely estimated from non-linear and noisy time series data using linear regression and ad hoc manual truncation of non-linearities. Here, we introduce the R package LoLinR, a flexible toolkit to implement local linear regression techniques to objectively and reproducibly estimate monotonic biological rates from non-linear time series data, and demonstrate possible applications using metabolic rate data. LoLinR provides methods to easily and reliably estimate monotonic rates from time series data in a way that is statistically robust, facilitates reproducible research and is applicable to a wide variety of research disciplines in the biological sciences. © 2017. Published by The Company of Biologists Ltd.
Iterates of piecewise monotone mappings on an interval
Preston, Chris
1988-01-01
Piecewise monotone mappings on an interval provide simple examples of discrete dynamical systems whose behaviour can be very complicated. These notes are concerned with the properties of the iterates of such mappings. The material presented can be understood by anyone who has had a basic course in (one-dimensional) real analysis. The account concentrates on the topological (as opposed to the measure theoretical) aspects of the theory of piecewise monotone mappings. As well as offering an elementary introduction to this theory, these notes also contain a more advanced treatment of the problem of classifying such mappings up to topological conjugacy.
The regularized monotonicity method: detecting irregular indefinite inclusions
DEFF Research Database (Denmark)
Garde, Henrik; Staboulis, Stratos
2018-01-01
inclusions, where the conductivity distribution has both more and less conductive parts relative to the background conductivity; one such method is the monotonicity method of Harrach, Seo, and Ullrich. We formulate the method for irregular indefinite inclusions, meaning that we make no regularity assumptions...
Generalized monotonicity from global minimization in fourth-order ODEs
M.A. Peletier (Mark)
2000-01-01
textabstractWe consider solutions of the stationary Extended Fisher-Kolmogorov equation with general potential that are global minimizers of an associated variational problem. We present results that relate the global minimization property to a generalized concept of monotonicity of the solutions.
Monotone difference schemes for weakly coupled elliptic and parabolic systems
P. Matus (Piotr); F.J. Gaspar Lorenz (Franscisco); L. M. Hieu (Le Minh); V.T.K. Tuyen (Vo Thi Kim)
2017-01-01
textabstractThe present paper is devoted to the development of the theory of monotone difference schemes, approximating the so-called weakly coupled system of linear elliptic and quasilinear parabolic equations. Similarly to the scalar case, the canonical form of the vector-difference schemes is
Pathwise duals of monotone and additive Markov processes
Czech Academy of Sciences Publication Activity Database
Sturm, A.; Swart, Jan M.
-, - (2018) ISSN 0894-9840 R&D Projects: GA ČR GAP201/12/2613 Institutional support: RVO:67985556 Keywords : pathwise duality * monotone Markov process * additive Markov process * interacting particle system Subject RIV: BA - General Mathematics Impact factor: 0.854, year: 2016 http://library.utia.cas.cz/separaty/2016/SI/swart-0465436.pdf
Statistical analysis of sediment toxicity by additive monotone regression splines
Boer, de W.J.; Besten, den P.J.; Braak, ter C.J.F.
2002-01-01
Modeling nonlinearity and thresholds in dose-effect relations is a major challenge, particularly in noisy data sets. Here we show the utility of nonlinear regression with additive monotone regression splines. These splines lead almost automatically to the estimation of thresholds. We applied this
Interval Routing and Minor-Monotone Graph Parameters
Bakker, E.M.; Bodlaender, H.L.; Tan, R.B.; Leeuwen, J. van
2006-01-01
We survey a number of minor-monotone graph parameters and their relationship to the complexity of routing on graphs. In particular we compare the interval routing parameters κslir(G) and κsir(G) with Colin de Verdi`ere’s graph invariant μ(G) and its variants λ(G) and κ(G). We show that for all the
On monotonic solutions of an integral equation of Abel type
International Nuclear Information System (INIS)
Darwish, Mohamed Abdalla
2007-08-01
We present an existence theorem of monotonic solutions for a quadratic integral equation of Abel type in C[0, 1]. The famous Chandrasekhar's integral equation is considered as a special case. The concept of measure of noncompactness and a fi xed point theorem due to Darbo are the main tools in carrying out our proof. (author)
Rational functions with maximal radius of absolute monotonicity
Loczi, Lajos; Ketcheson, David I.
2014-01-01
-Kutta methods for initial value problems and the radius of absolute monotonicity governs the numerical preservation of properties like positivity and maximum-norm contractivity. We construct a function with p=2 and R>2s, disproving a conjecture of van de Griend
POLARIZED LINE FORMATION IN NON-MONOTONIC VELOCITY FIELDS
Energy Technology Data Exchange (ETDEWEB)
Sampoorna, M.; Nagendra, K. N., E-mail: sampoorna@iiap.res.in, E-mail: knn@iiap.res.in [Indian Institute of Astrophysics, Koramangala, Bengaluru 560034 (India)
2016-12-10
For a correct interpretation of the observed spectro-polarimetric data from astrophysical objects such as the Sun, it is necessary to solve the polarized line transfer problems taking into account a realistic temperature structure, the dynamical state of the atmosphere, a realistic scattering mechanism (namely, the partial frequency redistribution—PRD), and the magnetic fields. In a recent paper, we studied the effects of monotonic vertical velocity fields on linearly polarized line profiles formed in isothermal atmospheres with and without magnetic fields. However, in general the velocity fields that prevail in dynamical atmospheres of astrophysical objects are non-monotonic. Stellar atmospheres with shocks, multi-component supernova atmospheres, and various kinds of wave motions in solar and stellar atmospheres are examples of non-monotonic velocity fields. Here we present studies on the effect of non-relativistic non-monotonic vertical velocity fields on the linearly polarized line profiles formed in semi-empirical atmospheres. We consider a two-level atom model and PRD scattering mechanism. We solve the polarized transfer equation in the comoving frame (CMF) of the fluid using a polarized accelerated lambda iteration method that has been appropriately modified for the problem at hand. We present numerical tests to validate the CMF method and also discuss the accuracy and numerical instabilities associated with it.
Modelling Embedded Systems by Non-Monotonic Refinement
Mader, Angelika H.; Marincic, J.; Wupper, H.
2008-01-01
This paper addresses the process of modelling embedded sys- tems for formal verification. We propose a modelling process built on non-monotonic refinement and a number of guidelines. The outcome of the modelling process is a model, together with a correctness argument that justifies our modelling
Escalated convergent artificial bee colony
Jadon, Shimpi Singh; Bansal, Jagdish Chand; Tiwari, Ritu
2016-03-01
Artificial bee colony (ABC) optimisation algorithm is a recent, fast and easy-to-implement population-based meta heuristic for optimisation. ABC has been proved a rival algorithm with some popular swarm intelligence-based algorithms such as particle swarm optimisation, firefly algorithm and ant colony optimisation. The solution search equation of ABC is influenced by a random quantity which helps its search process in exploration at the cost of exploitation. In order to find a fast convergent behaviour of ABC while exploitation capability is maintained, in this paper basic ABC is modified in two ways. First, to improve exploitation capability, two local search strategies, namely classical unidimensional local search and levy flight random walk-based local search are incorporated with ABC. Furthermore, a new solution search strategy, namely stochastic diffusion scout search is proposed and incorporated into the scout bee phase to provide more chance to abandon solution to improve itself. Efficiency of the proposed algorithm is tested on 20 benchmark test functions of different complexities and characteristics. Results are very promising and they prove it to be a competitive algorithm in the field of swarm intelligence-based algorithms.
Convergence theorems for certain classes of nonlinear mappings
International Nuclear Information System (INIS)
Chidume, C.E.
1992-01-01
Recently, Xinlong Weng announced a convergence theorem for the iterative approximation of fixed points of local strictly pseudo-contractive mappings in uniformly smooth Banach spaces, (Proc. Amer. Math. Soc. Vol.113, No.3 (1991) 727-731). An example is presented which shows that this theorem of Weng is false. Then, a convergence theorem is proved, in certain real Banach spaces, for approximation a solution of the inclusion f is an element of x + Tx, where T is a set-valued monotone operator. An explicit error estimate is also presented. (author). 26 refs
Directory of Open Access Journals (Sweden)
Wiyada Kumam
2016-05-01
Full Text Available In this article, we introduce a new multi-step iteration for approximating a common fixed point of a finite class of multi-valued Bregman relatively nonexpansive mappings in the setting of reflexive Banach spaces. We prove a strong convergence theorem for the proposed iterative algorithm under certain hypotheses. Additionally, we also use our results for the solution of variational inequality problems and to find the zero points of maximal monotone operators. The theorems furnished in this work are new and well-established and generalize many well-known recent research works in this field.
Monotonicity properties of keff with shape change and with nesting
International Nuclear Information System (INIS)
Arzhanov, V.
2002-01-01
It was found that, contrary to expectations based on physical intuition, k eff can both increase and decrease when changing the shape of an initially regular critical system, while preserving its volume. Physical intuition would only allow for a decrease of k eff when the surface/volume ratio increases. The unexpected behaviour of increasing k eff was found through numerical investigation. For a convincing demonstration of the possibility of the non-monotonic behaviour, a simple geometrical proof was constructed. This latter proof, in turn, is based on the assumption that k eff can only increase (or stay constant) in the case of nesting, i.e. when adding extra volume to a system. Since we found no formal proof of the nesting theorem for the general case, we close the paper by a simple formal proof of the monotonic behaviour of k eff by nesting
A Hybrid Approach to Proving Memory Reference Monotonicity
Oancea, Cosmin E.
2013-01-01
Array references indexed by non-linear expressions or subscript arrays represent a major obstacle to compiler analysis and to automatic parallelization. Most previous proposed solutions either enhance the static analysis repertoire to recognize more patterns, to infer array-value properties, and to refine the mathematical support, or apply expensive run time analysis of memory reference traces to disambiguate these accesses. This paper presents an automated solution based on static construction of access summaries, in which the reference non-linearity problem can be solved for a large number of reference patterns by extracting arbitrarily-shaped predicates that can (in)validate the reference monotonicity property and thus (dis)prove loop independence. Experiments on six benchmarks show that our general technique for dynamic validation of the monotonicity property can cover a large class of codes, incurs minimal run-time overhead and obtains good speedups. © 2013 Springer-Verlag.
Rational functions with maximal radius of absolute monotonicity
Loczi, Lajos
2014-05-19
We study the radius of absolute monotonicity R of rational functions with numerator and denominator of degree s that approximate the exponential function to order p. Such functions arise in the application of implicit s-stage, order p Runge-Kutta methods for initial value problems and the radius of absolute monotonicity governs the numerical preservation of properties like positivity and maximum-norm contractivity. We construct a function with p=2 and R>2s, disproving a conjecture of van de Griend and Kraaijevanger. We determine the maximum attainable radius for functions in several one-parameter families of rational functions. Moreover, we prove earlier conjectured optimal radii in some families with 2 or 3 parameters via uniqueness arguments for systems of polynomial inequalities. Our results also prove the optimality of some strong stability preserving implicit and singly diagonally implicit Runge-Kutta methods. Whereas previous results in this area were primarily numerical, we give all constants as exact algebraic numbers.
Monotonicity and Logarithmic Concavity of Two Functions Involving Exponential Function
Liu, Ai-Qi; Li, Guo-Fu; Guo, Bai-Ni; Qi, Feng
2008-01-01
The function 1 divided by "x"[superscript 2] minus "e"[superscript"-x"] divided by (1 minus "e"[superscript"-x"])[superscript 2] for "x" greater than 0 is proved to be strictly decreasing. As an application of this monotonicity, the logarithmic concavity of the function "t" divided by "e"[superscript "at"] minus "e"[superscript"(a-1)""t"] for "a"…
Estimation of Poisson-Dirichlet Parameters with Monotone Missing Data
Directory of Open Access Journals (Sweden)
Xueqin Zhou
2017-01-01
Full Text Available This article considers the estimation of the unknown numerical parameters and the density of the base measure in a Poisson-Dirichlet process prior with grouped monotone missing data. The numerical parameters are estimated by the method of maximum likelihood estimates and the density function is estimated by kernel method. A set of simulations was conducted, which shows that the estimates perform well.
Sampling from a Discrete Distribution While Preserving Monotonicity.
1982-02-01
in a table beforehand, this procedure, known as the inverse transform method, requires n storage spaces and EX comparisons on average, which may prove...limitations that deserve attention: a. In general, the alias method does not preserve a monotone relationship between U and X as does the inverse transform method...uses the inverse transform approach but with more information computed beforehand, as in the alias method. The proposed method is not new having been
On a strong law of large numbers for monotone measures
Czech Academy of Sciences Publication Activity Database
Agahi, H.; Mohammadpour, A.; Mesiar, Radko; Ouyang, Y.
2013-01-01
Roč. 83, č. 4 (2013), s. 1213-1218 ISSN 0167-7152 R&D Projects: GA ČR GAP402/11/0378 Institutional support: RVO:67985556 Keywords : capacity * Choquet integral * strong law of large numbers Subject RIV: BA - General Mathematics Impact factor: 0.531, year: 2013 http://library.utia.cas.cz/separaty/2013/E/mesiar-on a strong law of large numbers for monotone measures.pdf
Monotonous braking of high energy hadrons in nuclear matter
International Nuclear Information System (INIS)
Strugalski, Z.
1979-01-01
Propagation of high energy hadrons in nuclear matter is discussed. The possibility of the existence of the monotonous energy losses of hadrons in nuclear matter is considered. In favour of this hypothesis experimental facts such as pion-nucleus interactions (proton emission spectra, proton multiplicity distributions in these interactions) and other data are presented. The investigated phenomenon in the framework of the hypothesis is characterized in more detail
Assessing the Health of LiFePO4 Traction Batteries through Monotonic Echo State Networks
Anseán, David; Otero, José; Couso, Inés
2017-01-01
A soft sensor is presented that approximates certain health parameters of automotive rechargeable batteries from on-vehicle measurements of current and voltage. The sensor is based on a model of the open circuit voltage curve. This last model is implemented through monotonic neural networks and estimate over-potentials arising from the evolution in time of the Lithium concentration in the electrodes of the battery. The proposed soft sensor is able to exploit the information contained in operational records of the vehicle better than the alternatives, this being particularly true when the charge or discharge currents are between moderate and high. The accuracy of the neural model has been compared to different alternatives, including data-driven statistical models, first principle-based models, fuzzy observers and other recurrent neural networks with different topologies. It is concluded that monotonic echo state networks can outperform well established first-principle models. The algorithms have been validated with automotive Li-FePO4 cells. PMID:29267219
Assessing the Health of LiFePO4 Traction Batteries through Monotonic Echo State Networks
Directory of Open Access Journals (Sweden)
Luciano Sánchez
2017-12-01
Full Text Available A soft sensor is presented that approximates certain health parameters of automotive rechargeable batteries from on-vehicle measurements of current and voltage. The sensor is based on a model of the open circuit voltage curve. This last model is implemented through monotonic neural networks and estimate over-potentials arising from the evolution in time of the Lithium concentration in the electrodes of the battery. The proposed soft sensor is able to exploit the information contained in operational records of the vehicle better than the alternatives, this being particularly true when the charge or discharge currents are between moderate and high. The accuracy of the neural model has been compared to different alternatives, including data-driven statistical models, first principle-based models, fuzzy observers and other recurrent neural networks with different topologies. It is concluded that monotonic echo state networks can outperform well established first-principle models. The algorithms have been validated with automotive Li-FePO4 cells.
Evaluation of the Monotonic Lagrangian Grid and Lat-Long Grid for Air Traffic Management
Kaplan, Carolyn; Dahm, Johann; Oran, Elaine; Alexandrov, Natalia; Boris, Jay
2011-01-01
The Air Traffic Monotonic Lagrangian Grid (ATMLG) is used to simulate a 24 hour period of air traffic flow in the National Airspace System (NAS). During this time period, there are 41,594 flights over the United States, and the flight plan information (departure and arrival airports and times, and waypoints along the way) are obtained from an Federal Aviation Administration (FAA) Enhanced Traffic Management System (ETMS) dataset. Two simulation procedures are tested and compared: one based on the Monotonic Lagrangian Grid (MLG), and the other based on the stationary Latitude-Longitude (Lat- Long) grid. Simulating one full day of air traffic over the United States required the following amounts of CPU time on a single processor of an SGI Altix: 88 s for the MLG method, and 163 s for the Lat-Long grid method. We present a discussion of the amount of CPU time required for each of the simulation processes (updating aircraft trajectories, sorting, conflict detection and resolution, etc.), and show that the main advantage of the MLG method is that it is a general sorting algorithm that can sort on multiple properties. We discuss how many MLG neighbors must be considered in the separation assurance procedure in order to ensure a five-mile separation buffer between aircraft, and we investigate the effect of removing waypoints from aircraft trajectories. When aircraft choose their own trajectory, there are more flights with shorter duration times and fewer CD&R maneuvers, resulting in significant fuel savings.
Foundations of genetic algorithms 1991
1991-01-01
Foundations of Genetic Algorithms 1991 (FOGA 1) discusses the theoretical foundations of genetic algorithms (GA) and classifier systems.This book compiles research papers on selection and convergence, coding and representation, problem hardness, deception, classifier system design, variation and recombination, parallelization, and population divergence. Other topics include the non-uniform Walsh-schema transform; spurious correlations and premature convergence in genetic algorithms; and variable default hierarchy separation in a classifier system. The grammar-based genetic algorithm; condition
Directory of Open Access Journals (Sweden)
Feng Qi
2014-10-01
Full Text Available The authors find the absolute monotonicity and complete monotonicity of some functions involving trigonometric functions and related to estimates the lower bounds of the first eigenvalue of Laplace operator on Riemannian manifolds.
Directory of Open Access Journals (Sweden)
Chowdhury Molhammad SR
2000-01-01
Full Text Available Results are obtained on existence theorems of generalized bi-quasi-variational inequalities for quasi-semi-monotone and bi-quasi-semi-monotone operators in both compact and non-compact settings. We shall use the concept of escaping sequences introduced by Border (Fixed Point Theorem with Applications to Economics and Game Theory, Cambridge University Press, Cambridge, 1985 to obtain results in non-compact settings. Existence theorems on non-compact generalized bi-complementarity problems for quasi-semi-monotone and bi-quasi-semi-monotone operators are also obtained. Moreover, as applications of some results of this paper on generalized bi-quasi-variational inequalities, we shall obtain existence of solutions for some kind of minimization problems with quasi- semi-monotone and bi-quasi-semi-monotone operators.
Convergence in Multispecies Interactions.
Bittleston, Leonora S; Pierce, Naomi E; Ellison, Aaron M; Pringle, Anne
2016-04-01
The concepts of convergent evolution and community convergence highlight how selective pressures can shape unrelated organisms or communities in similar ways. We propose a related concept, convergent interactions, to describe the independent evolution of multispecies interactions with similar physiological or ecological functions. A focus on convergent interactions clarifies how natural selection repeatedly favors particular kinds of associations among species. Characterizing convergent interactions in a comparative context is likely to facilitate prediction of the ecological roles of organisms (including microbes) in multispecies interactions and selective pressures acting in poorly understood or newly discovered multispecies systems. We illustrate the concept of convergent interactions with examples: vertebrates and their gut bacteria; ectomycorrhizae; insect-fungal-bacterial interactions; pitcher-plant food webs; and ants and ant-plants. Copyright © 2016 Elsevier Ltd. All rights reserved.
An Optimal Augmented Monotonic Tracking Controller for Aircraft Engines with Output Constraints
Directory of Open Access Journals (Sweden)
Jiakun Qin
2017-01-01
Full Text Available This paper proposes a novel min-max control scheme for aircraft engines, with the aim of transferring a set of regulated outputs between two set-points, while ensuring a set of auxiliary outputs remain within prescribed constraints. In view of this, an optimal augmented monotonic tracking controller (OAMTC is proposed, by considering a linear plant with input integration, to enhance the ability of the control system to reject uncertainty in system parameters and ensure no crossing limits. The key idea is to use the eigenvalue and eigenvector placement method and genetic algorithms to shape the output responses. The approach is validated by numerical simulation. The results show that the designed OAMTC controller can achieve a satisfactory dynamic and steady performance and keep the auxiliary outputs within constraints in the transient regime.
International Nuclear Information System (INIS)
Wan Li; Zhou Qinghua
2007-01-01
The stability property of stochastic hybrid bidirectional associate memory (BAM) neural networks with discrete delays is considered. Without assuming the symmetry of synaptic connection weights and the monotonicity and differentiability of activation functions, the delay-independent sufficient conditions to guarantee the exponential stability of the equilibrium solution for such networks are given by using the nonnegative semimartingale convergence theorem
Wan, Li; Zhou, Qinghua
2007-10-01
The stability property of stochastic hybrid bidirectional associate memory (BAM) neural networks with discrete delays is considered. Without assuming the symmetry of synaptic connection weights and the monotonicity and differentiability of activation functions, the delay-independent sufficient conditions to guarantee the exponential stability of the equilibrium solution for such networks are given by using the nonnegative semimartingale convergence theorem.
Converged Registries Solution (CRS)
Department of Veterans Affairs — The Converged Registries platform is a hardware and software architecture designed to host individual patient registries and eliminate duplicative development effort...
A non-parametric test for partial monotonicity in multiple regression
van Beek, M.; Daniëls, H.A.M.
Partial positive (negative) monotonicity in a dataset is the property that an increase in an independent variable, ceteris paribus, generates an increase (decrease) in the dependent variable. A test for partial monotonicity in datasets could (1) increase model performance if monotonicity may be
In some symmetric spaces monotonicity properties can be reduced to the cone of rearrangements
Czech Academy of Sciences Publication Activity Database
Hudzik, H.; Kaczmarek, R.; Krbec, Miroslav
2016-01-01
Roč. 90, č. 1 (2016), s. 249-261 ISSN 0001-9054 Institutional support: RVO:67985840 Keywords : symmetric spaces * K-monotone symmetric Banach spaces * strict monotonicity * lower local uniform monotonicity Subject RIV: BA - General Mathematics Impact factor: 0.826, year: 2016 http://link.springer.com/article/10.1007%2Fs00010-015-0379-6
Directory of Open Access Journals (Sweden)
Evgeni V Nikolaev
2016-04-01
Full Text Available Synthetic constructs in biotechnology, biocomputing, and modern gene therapy interventions are often based on plasmids or transfected circuits which implement some form of "on-off" switch. For example, the expression of a protein used for therapeutic purposes might be triggered by the recognition of a specific combination of inducers (e.g., antigens, and memory of this event should be maintained across a cell population until a specific stimulus commands a coordinated shut-off. The robustness of such a design is hampered by molecular ("intrinsic" or environmental ("extrinsic" noise, which may lead to spontaneous changes of state in a subset of the population and is reflected in the bimodality of protein expression, as measured for example using flow cytometry. In this context, a "majority-vote" correction circuit, which brings deviant cells back into the required state, is highly desirable, and quorum-sensing has been suggested as a way for cells to broadcast their states to the population as a whole so as to facilitate consensus. In this paper, we propose what we believe is the first such a design that has mathematically guaranteed properties of stability and auto-correction under certain conditions. Our approach is guided by concepts and theory from the field of "monotone" dynamical systems developed by M. Hirsch, H. Smith, and others. We benchmark our design by comparing it to an existing design which has been the subject of experimental and theoretical studies, illustrating its superiority in stability and self-correction of synchronization errors. Our stability analysis, based on dynamical systems theory, guarantees global convergence to steady states, ruling out unpredictable ("chaotic" behaviors and even sustained oscillations in the limit of convergence. These results are valid no matter what are the values of parameters, and are based only on the wiring diagram. The theory is complemented by extensive computational bifurcation analysis
Non-monotonic behaviour in relaxation dynamics of image restoration
International Nuclear Information System (INIS)
Ozeki, Tomoko; Okada, Masato
2003-01-01
We have investigated the relaxation dynamics of image restoration through a Bayesian approach. The relaxation dynamics is much faster at zero temperature than at the Nishimori temperature where the pixel-wise error rate is minimized in equilibrium. At low temperature, we observed non-monotonic development of the overlap. We suggest that the optimal performance is realized through premature termination in the relaxation processes in the case of the infinite-range model. We also performed Markov chain Monte Carlo simulations to clarify the underlying mechanism of non-trivial behaviour at low temperature by checking the local field distributions of each pixel
An iterative method for nonlinear demiclosed monotone-type operators
International Nuclear Information System (INIS)
Chidume, C.E.
1991-01-01
It is proved that a well known fixed point iteration scheme which has been used for approximating solutions of certain nonlinear demiclosed monotone-type operator equations in Hilbert spaces remains applicable in real Banach spaces with property (U, α, m+1, m). These Banach spaces include the L p -spaces, p is an element of [2,∞]. An application of our results to the approximation of a solution of a certain linear operator equation in this general setting is also given. (author). 19 refs
Convergence of mayer expansions
International Nuclear Information System (INIS)
Brydges, D.C.
1986-01-01
The tree graph bound of Battle and Federbush is extended and used to provide a simple criterion for the convergence of (iterated) Mayer expansions. As an application estimates on the radius of convergence of the Mayer expansion for the two-dimensional Yukawa gas (nonstable interaction) are obtained
Modified Clipped LMS Algorithm
Directory of Open Access Journals (Sweden)
Lotfizad Mojtaba
2005-01-01
Full Text Available Abstract A new algorithm is proposed for updating the weights of an adaptive filter. The proposed algorithm is a modification of an existing method, namely, the clipped LMS, and uses a three-level quantization ( scheme that involves the threshold clipping of the input signals in the filter weight update formula. Mathematical analysis shows the convergence of the filter weights to the optimum Wiener filter weights. Also, it can be proved that the proposed modified clipped LMS (MCLMS algorithm has better tracking than the LMS algorithm. In addition, this algorithm has reduced computational complexity relative to the unmodified one. By using a suitable threshold, it is possible to increase the tracking capability of the MCLMS algorithm compared to the LMS algorithm, but this causes slower convergence. Computer simulations confirm the mathematical analysis presented.
Experimental quantum control landscapes: Inherent monotonicity and artificial structure
International Nuclear Information System (INIS)
Roslund, Jonathan; Rabitz, Herschel
2009-01-01
Unconstrained searches over quantum control landscapes are theoretically predicted to generally exhibit trap-free monotonic behavior. This paper makes an explicit experimental demonstration of this intrinsic monotonicity for two controlled quantum systems: frequency unfiltered and filtered second-harmonic generation (SHG). For unfiltered SHG, the landscape is randomly sampled and interpolation of the data is found to be devoid of landscape traps up to the level of data noise. In the case of narrow-band-filtered SHG, trajectories are taken on the landscape to reveal a lack of traps. Although the filtered SHG landscape is trap free, it exhibits a rich local structure. A perturbation analysis around the top of these landscapes provides a basis to understand their topology. Despite the inherent trap-free nature of the landscapes, practical constraints placed on the controls can lead to the appearance of artificial structure arising from the resultant forced sampling of the landscape. This circumstance and the likely lack of knowledge about the detailed local landscape structure in most quantum control applications suggests that the a priori identification of globally successful (un)constrained curvilinear control variables may be a challenging task.
Positivity and monotonicity properties of C0-semigroups. Pt. 1
International Nuclear Information System (INIS)
Bratteli, O.; Kishimoto, A.; Robinson, D.W.
1980-01-01
If exp(-tH), exp(-tK), are self-adjoint, positivity preserving, contraction semigroups on a Hilbert space H = L 2 (X;dμ) we write esup(-tH) >= esup(-tK) >= 0 whenever exp(-tH) - exp(-tK) is positivity preserving for all t >= 0 and then we characterize the class of positive functions for which (*) always implies esup(-tf(H)) >= esup(-tf(K)) >= 0. This class consists of the f epsilon Csup(infinitely)(0, infinitely) with (-1)sup(n)fsup((n + 1))(x) >= 0, x epsilon(0, infinitely), n = 0, 1, 2, ... In particular it contains the class of monotone operator functions. Furthermore if exp(-tH) is Lsup(P)(X;dμ) contractive for all p epsilon[1, infinitely] and all t > 0 (or, equivalently, for p = infinitely and t > 0) then exp(-tf(H)) has the same property. Various applications to monotonicity properties of Green's functions are given. (orig.)
Theoretical and experimental study of non-monotonous effects
International Nuclear Information System (INIS)
Delforge, J.
1977-01-01
In recent years, the study of the effects of low dose rates has expanded considerably, especially in connection with current problems concerning the environment and health physics. After having made a precise definition of the different types of non-monotonous effect which may be encountered, for each the main experimental results known are indicated, as well as the principal consequences which may be expected. One example is the case of radiotherapy, where there is a chance of finding irradiation conditions such that the ratio of destructive action on malignant cells to healthy cells is significantly improved. In the second part of the report, the appearance of these phenomena, especially at low dose rates are explained. For this purpose, the theory of transformation systems of P. Delattre is used as a theoretical framework. With the help of a specific example, it is shown that non-monotonous effects are frequently encountered, especially when the overall effect observed is actually the sum of several different elementary effects (e.g. in survival curves, where death may be due to several different causes), or when the objects studied possess inherent kinetics not limited to restoration phenomena alone (e.g. cellular cycle) [fr
On the premature convergence of particle swarm optimization
DEFF Research Database (Denmark)
Larsen, Rie B.; Jouffroy, Jerome; Lassen, Benny
2016-01-01
This paper discusses convergence issues of the basic particle swarm optimization algorithm for different pa- rameters. For the one-dimensional case, it is shown that, for a specific range of parameters, the particles will converge prematurely, i.e. away from the actual minimum of the objective...
Almost convergence of triple sequences
Ayhan Esi; M.Necdet Catalbas
2013-01-01
In this paper we introduce and study the concepts of almost convergence and almost Cauchy for triple sequences. Weshow that the set of almost convergent triple sequences of 0's and 1's is of the first category and also almost everytriple sequence of 0's and 1's is not almost convergent.Keywords: almost convergence, P-convergent, triple sequence.
Log-binomial models: exploring failed convergence.
Williamson, Tyler; Eliasziw, Misha; Fick, Gordon Hilton
2013-12-13
Relative risk is a summary metric that is commonly used in epidemiological investigations. Increasingly, epidemiologists are using log-binomial models to study the impact of a set of predictor variables on a single binary outcome, as they naturally offer relative risks. However, standard statistical software may report failed convergence when attempting to fit log-binomial models in certain settings. The methods that have been proposed in the literature for dealing with failed convergence use approximate solutions to avoid the issue. This research looks directly at the log-likelihood function for the simplest log-binomial model where failed convergence has been observed, a model with a single linear predictor with three levels. The possible causes of failed convergence are explored and potential solutions are presented for some cases. Among the principal causes is a failure of the fitting algorithm to converge despite the log-likelihood function having a single finite maximum. Despite these limitations, log-binomial models are a viable option for epidemiologists wishing to describe the relationship between a set of predictors and a binary outcome where relative risk is the desired summary measure. Epidemiologists are encouraged to continue to use log-binomial models and advocate for improvements to the fitting algorithms to promote the widespread use of log-binomial models.
Noise can speed convergence in Markov chains.
Franzke, Brandon; Kosko, Bart
2011-10-01
A new theorem shows that noise can speed convergence to equilibrium in discrete finite-state Markov chains. The noise applies to the state density and helps the Markov chain explore improbable regions of the state space. The theorem ensures that a stochastic-resonance noise benefit exists for states that obey a vector-norm inequality. Such noise leads to faster convergence because the noise reduces the norm components. A corollary shows that a noise benefit still occurs if the system states obey an alternate norm inequality. This leads to a noise-benefit algorithm that requires knowledge of the steady state. An alternative blind algorithm uses only past state information to achieve a weaker noise benefit. Simulations illustrate the predicted noise benefits in three well-known Markov models. The first model is a two-parameter Ehrenfest diffusion model that shows how noise benefits can occur in the class of birth-death processes. The second model is a Wright-Fisher model of genotype drift in population genetics. The third model is a chemical reaction network of zeolite crystallization. A fourth simulation shows a convergence rate increase of 64% for states that satisfy the theorem and an increase of 53% for states that satisfy the corollary. A final simulation shows that even suboptimal noise can speed convergence if the noise applies over successive time cycles. Noise benefits tend to be sharpest in Markov models that do not converge quickly and that do not have strong absorbing states.
Recursive automatic classification algorithms
Energy Technology Data Exchange (ETDEWEB)
Bauman, E V; Dorofeyuk, A A
1982-03-01
A variational statement of the automatic classification problem is given. The dependence of the form of the optimal partition surface on the form of the classification objective functional is investigated. A recursive algorithm is proposed for maximising a functional of reasonably general form. The convergence problem is analysed in connection with the proposed algorithm. 8 references.
Multipartite entangled quantum states: Transformation, Entanglement monotones and Application
Cui, Wei
Entanglement is one of the fundamental features of quantum information science. Though bipartite entanglement has been analyzed thoroughly in theory and shown to be an important resource in quantum computation and communication protocols, the theory of entanglement shared between more than two parties, which is called multipartite entanglement, is still not complete. Specifically, the classification of multipartite entanglement and the transformation property between different multipartite states by local operators and classical communications (LOCC) are two fundamental questions in the theory of multipartite entanglement. In this thesis, we present results related to the LOCC transformation between multipartite entangled states. Firstly, we investigate the bounds on the LOCC transformation probability between multipartite states, especially the GHZ class states. By analyzing the involvement of 3-tangle and other entanglement measures under weak two-outcome measurement, we derive explicit upper and lower bound on the transformation probability between GHZ class states. After that, we also analyze the transformation between N-party W type states, which is a special class of multipartite entangled states that has an explicit unique expression and a set of analytical entanglement monotones. We present a necessary and sufficient condition for a known upper bound of transformation probability between two N-party W type states to be achieved. We also further investigate a novel entanglement transformation protocol, the random distillation, which transforms multipartite entanglement into bipartite entanglement ii shared by a non-deterministic pair of parties. We find upper bounds for the random distillation protocol for general N-party W type states and find the condition for the upper bounds to be achieved. What is surprising is that the upper bounds correspond to entanglement monotones that can be increased by Separable Operators (SEP), which gives the first set of
Convergence of Nelson diffusions
International Nuclear Information System (INIS)
Dell'Antonio, G.; Posilicano, A.
1991-01-01
Let ψ t , ψ t n , n≥1, be solutions of Schroedinger equations with potentials form-bounded by -1/2 Δ and initial data in H 1 (R d ). Let P, P n , n≥1, be the probability measures on the path space Ω=C(R + , R d ) given by the corresponding Nelson diffusions. We show that if {ψ t n } n≥1 converges to ψ t in H 2 (R d ), uniformly in t over compact intervals, then {P n } n≥1 converges to P in total variation. Moreover, if the potentials are in the Kato class K d , we show that the above result follows from H 1 -convergence of initial data, and K d -convergence of potentials. (orig.)
Fixed mobile convergence handbook
Ahson, Syed A
2010-01-01
From basic concepts to future directions, this handbook provides technical information on all aspects of fixed-mobile convergence (FMC). The book examines such topics as integrated management architecture, business trends and strategic implications for service providers, personal area networks, mobile controlled handover methods, SIP-based session mobility, and supervisory and notification aggregator service. Case studies are used to illustrate technical and systematic implementation of unified and rationalized internet access by fixed-mobile network convergence. The text examines the technolo
Sampling dynamics: an alternative to payoff-monotone selection dynamics
DEFF Research Database (Denmark)
Berkemer, Rainer
payoff-monotone nor payoff-positive which has interesting consequences. This can be demonstrated by application to the travelers dilemma, a deliberately constructed social dilemma. The game has just one symmetric Nash equilibrium which is Pareto inefficient. Especially when the travelers have many......'' of the standard game theory result. Both, analytical tools and agent based simulation are used to investigate the dynamic stability of sampling equilibria in a generalized travelers dilemma. Two parameters are of interest: the number of strategy options (m) available to each traveler and an experience parameter...... (k), which indicates the number of samples an agent would evaluate before fixing his decision. The special case (k=1) can be treated analytically. The stationary points of the dynamics must be sampling equilibria and one can calculate that for m>3 there will be an interior solution in addition...
Monotonic childhoods: representations of otherness in research writing
Directory of Open Access Journals (Sweden)
Denise Marcos Bussoletti
2011-12-01
Full Text Available This paper is part of a doctoral thesis entitled “Monotonic childhoods – a rhapsody of hope”. It follows the perspective of a critical psychosocial and cultural study, and aims at discussing the other’s representation in research writing, electing childhood as an allegorical and refl ective place. It takes into consideration, by means of analysis, the drawings and poems of children from the Terezin ghetto during the Second World War. The work is mostly based on Serge Moscovici’s Social Representation Theory, but it is also in constant dialogue with other theories and knowledge fi elds, especially Walter Benjamin’s and Mikhail Bakhtin’s contributions. At the end, the paper supports the thesis that conceives poetics as one of the translation axes of childhood cultures.
Convex analysis and monotone operator theory in Hilbert spaces
Bauschke, Heinz H
2017-01-01
This reference text, now in its second edition, offers a modern unifying presentation of three basic areas of nonlinear analysis: convex analysis, monotone operator theory, and the fixed point theory of nonexpansive operators. Taking a unique comprehensive approach, the theory is developed from the ground up, with the rich connections and interactions between the areas as the central focus, and it is illustrated by a large number of examples. The Hilbert space setting of the material offers a wide range of applications while avoiding the technical difficulties of general Banach spaces. The authors have also drawn upon recent advances and modern tools to simplify the proofs of key results making the book more accessible to a broader range of scholars and users. Combining a strong emphasis on applications with exceptionally lucid writing and an abundance of exercises, this text is of great value to a large audience including pure and applied mathematicians as well as researchers in engineering, data science, ma...
Expert system for failures detection and non-monotonic reasoning
International Nuclear Information System (INIS)
Assis, Abilio de; Schirru, Roberto
1997-01-01
This paper presents the development of a shell denominated TIGER that has the purpose to serve as environment to the development of expert systems in diagnosis of faults in industrial complex plants. A model of knowledge representation and an inference engine based on non monotonic reasoning has been developed in order to provide flexibility in the representation of complex plants as well as performance to satisfy restrictions of real time. The TIGER is able to provide both the occurred fault and a hierarchical view of the several reasons that caused the fault to happen. As a validation of the developed shell a monitoring system of the critical safety functions of Angra-1 has been developed. 7 refs., 7 figs., 2 tabs
International Nuclear Information System (INIS)
2012-12-01
This book explains IT-BT convergence technology as the future technology, which includes a prolog, easy IT-BT convergence technology that has infinite potentials for new value, policy of IT-BT convergence technology showing the potential of smart Korea, IT-BT convergence opening happy future, for the new future of IT powerful nation Korea with IT-BT convergence technology and an epilogue. This book reveals the conception, policy, performance and future of IT-BT convergence technology.
Convergence analysis for column-action methods in image reconstruction
DEFF Research Database (Denmark)
Elfving, Tommy; Hansen, Per Christian; Nikazad, Touraj
2016-01-01
Column-oriented versions of algebraic iterative methods are interesting alternatives to their row-version counterparts: they converge to a least squares solution, and they provide a basis for saving computational work by skipping small updates. In this paper we consider the case of noise-free data....... We present a convergence analysis of the column algorithms, we discuss two techniques (loping and flagging) for reducing the work, and we establish some convergence results for methods that utilize these techniques. The performance of the algorithms is illustrated with numerical examples from...
On the convergence of nonconvex minimization methods for image recovery.
Xiao, Jin; Ng, Michael Kwok-Po; Yang, Yu-Fei
2015-05-01
Nonconvex nonsmooth regularization method has been shown to be effective for restoring images with neat edges. Fast alternating minimization schemes have also been proposed and developed to solve the nonconvex nonsmooth minimization problem. The main contribution of this paper is to show the convergence of these alternating minimization schemes, based on the Kurdyka-Łojasiewicz property. In particular, we show that the iterates generated by the alternating minimization scheme, converges to a critical point of this nonconvex nonsmooth objective function. We also extend the analysis to nonconvex nonsmooth regularization model with box constraints, and obtain similar convergence results of the related minimization algorithm. Numerical examples are given to illustrate our convergence analysis.
Fractal aspects and convergence of Newton`s method
Energy Technology Data Exchange (ETDEWEB)
Drexler, M. [Oxford Univ. Computing Lab. (United Kingdom)
1996-12-31
Newton`s Method is a widely established iterative algorithm for solving non-linear systems. Its appeal lies in its great simplicity, easy generalization to multiple dimensions and a quadratic local convergence rate. Despite these features, little is known about its global behavior. In this paper, we will explain a seemingly random global convergence pattern using fractal concepts and show that the behavior of the residual is entirely explicable. We will also establish quantitative results for the convergence rates. Knowing the mechanism of fractal generation, we present a stabilization to the orthodox Newton method that remedies the fractal behavior and improves convergence.
Recursive forgetting algorithms
DEFF Research Database (Denmark)
Parkum, Jens; Poulsen, Niels Kjølstad; Holst, Jan
1992-01-01
In the first part of the paper, a general forgetting algorithm is formulated and analysed. It contains most existing forgetting schemes as special cases. Conditions are given ensuring that the basic convergence properties will hold. In the second part of the paper, the results are applied...... to a specific algorithm with selective forgetting. Here, the forgetting is non-uniform in time and space. The theoretical analysis is supported by a simulation example demonstrating the practical performance of this algorithm...
Reliability enhancement of Navier-Stokes codes through convergence acceleration
Merkle, Charles L.; Dulikravich, George S.
1995-01-01
Methods for enhancing the reliability of Navier-Stokes computer codes through improving convergence characteristics are presented. The improving of these characteristics decreases the likelihood of code unreliability and user interventions in a design environment. The problem referred to as a 'stiffness' in the governing equations for propulsion-related flowfields is investigated, particularly in regard to common sources of equation stiffness that lead to convergence degradation of CFD algorithms. Von Neumann stability theory is employed as a tool to study the convergence difficulties involved. Based on the stability results, improved algorithms are devised to ensure efficient convergence in different situations. A number of test cases are considered to confirm a correlation between stability theory and numerical convergence. The examples of turbulent and reacting flow are presented, and a generalized form of the preconditioning matrix is derived to handle these problems, i.e., the problems involving additional differential equations for describing the transport of turbulent kinetic energy, dissipation rate and chemical species. Algorithms for unsteady computations are considered. The extension of the preconditioning techniques and algorithms derived for Navier-Stokes computations to three-dimensional flow problems is discussed. New methods to accelerate the convergence of iterative schemes for the numerical integration of systems of partial differential equtions are developed, with a special emphasis on the acceleration of convergence on highly clustered grids.
Log-supermodularity of weight functions and the loading monotonicity of weighted insurance premiums
Hristo S. Sendov; Ying Wang; Ricardas Zitikis
2010-01-01
The paper is motivated by a problem concerning the monotonicity of insurance premiums with respect to their loading parameter: the larger the parameter, the larger the insurance premium is expected to be. This property, usually called loading monotonicity, is satisfied by premiums that appear in the literature. The increased interest in constructing new insurance premiums has raised a question as to what weight functions would produce loading-monotonic premiums. In this paper we demonstrate a...
Optimization, Monotonicity and the Determination of Nash Equilibria — An Algorithmic Analysis
Lozovanu, D.; Pickl, S. W.; Weber, G.-W.
2004-08-01
This paper is concerned with the optimization of a nonlinear time-discrete model exploiting the special structure of the underlying cost game and the property of inverse matrices. The costs are interlinked by a system of linear inequalities. It is shown that, if the players cooperate, i.e., minimize the sum of all the costs, they achieve a Nash equilibrium. In order to determine Nash equilibria, the simplex method can be applied with respect to the dual problem. An introduction into the TEM model and its relationship to an economic Joint Implementation program is given. The equivalence problem is presented. The construction of the emission cost game and the allocation problem is explained. The assumption of inverse monotony for the matrices leads to a new result in the area of such allocation problems. A generalization of such problems is presented.
Multicloud: Multigrid convergence with a meshless operator
International Nuclear Information System (INIS)
Katz, Aaron; Jameson, Antony
2009-01-01
The primary objective of this work is to develop and test a new convergence acceleration technique we call multicloud. Multicloud is well-founded in the mathematical basis of multigrid, but relies on a meshless operator on coarse levels. The meshless operator enables extremely simple and automatic coarsening procedures for arbitrary meshes using arbitrary fine level discretization schemes. The performance of multicloud is compared with established multigrid techniques for structured and unstructured meshes for the Euler equations on two-dimensional test cases. Results indicate comparable convergence rates per unit work for multicloud and multigrid. However, because of its mesh and scheme transparency, multicloud may be applied to a wide array of problems with no modification of fine level schemes as is often required with agglomeration techniques. The implication is that multicloud can be implemented in a completely modular fashion, allowing researchers to develop fine level algorithms independent of the convergence accelerator for complex three-dimensional problems.
Obliquely Propagating Non-Monotonic Double Layer in a Hot Magnetized Plasma
International Nuclear Information System (INIS)
Kim, T.H.; Kim, S.S.; Hwang, J.H.; Kim, H.Y.
2005-01-01
Obliquely propagating non-monotonic double layer is investigated in a hot magnetized plasma, which consists of a positively charged hot ion fluid and trapped, as well as free electrons. A model equation (modified Korteweg-de Vries equation) is derived by the usual reductive perturbation method from a set of basic hydrodynamic equations. A time stationary obliquely propagating non-monotonic double layer solution is obtained in a hot magnetized-plasma. This solution is an analytic extension of the monotonic double layer and the solitary hole. The effects of obliqueness, external magnetic field and ion temperature on the properties of the non-monotonic double layer are discussed
Improved multivariate polynomial factoring algorithm
International Nuclear Information System (INIS)
Wang, P.S.
1978-01-01
A new algorithm for factoring multivariate polynomials over the integers based on an algorithm by Wang and Rothschild is described. The new algorithm has improved strategies for dealing with the known problems of the original algorithm, namely, the leading coefficient problem, the bad-zero problem and the occurrence of extraneous factors. It has an algorithm for correctly predetermining leading coefficients of the factors. A new and efficient p-adic algorithm named EEZ is described. Bascially it is a linearly convergent variable-by-variable parallel construction. The improved algorithm is generally faster and requires less store then the original algorithm. Machine examples with comparative timing are included
Costin, Ovidiu; Dunne, Gerald V.
2018-01-01
We show how to convert divergent series, which typically occur in many applications in physics, into rapidly convergent inverse factorial series. This can be interpreted physically as a novel resummation of perturbative series. Being convergent, these new series allow rigorous extrapolation from an asymptotic region with a large parameter, to the opposite region where the parameter is small. We illustrate the method with various physical examples, and discuss how these convergent series relate to standard methods such as Borel summation, and also how they incorporate the physical Stokes phenomenon. We comment on the relation of these results to Dyson’s physical argument for the divergence of perturbation theory. This approach also leads naturally to a wide class of relations between bosonic and fermionic partition functions, and Klein-Gordon and Dirac determinants.
Directory of Open Access Journals (Sweden)
Abdul Hameed Q. A. Al-Tai
2011-01-01
Full Text Available The aim of this paper is to introduce and study the fuzzy neighborhood, the limit fuzzy number, the convergent fuzzy sequence, the bounded fuzzy sequence, and the Cauchy fuzzy sequence on the base which is adopted by Abdul Hameed (every real number r is replaced by a fuzzy number r¯ (either triangular fuzzy number or singleton fuzzy set (fuzzy point. And then, we will consider that some results respect effect of the upper sequence on the convergent fuzzy sequence, the bounded fuzzy sequence, and the Cauchy fuzzy sequence.
DEFF Research Database (Denmark)
Prasad, Ramjee; Ruggieri, Marina
2008-01-01
The paper focuses on the revolutionary changes that could characterise the future of networks. Those changes involve many aspects in the conceivement and exploitation of networks: architecture, services, technologies and modeling. The convergence of wired and wireless technologies along...... with the integration of system componennts and the convergence of services (e.g. communications and navigation) are only some of the elements that shape the perpsected mosaic. Authors delineate this vision, highlighting the presence of the space and stratospheric components and the related services as building block...
Composite Differential Search Algorithm
Directory of Open Access Journals (Sweden)
Bo Liu
2014-01-01
Full Text Available Differential search algorithm (DS is a relatively new evolutionary algorithm inspired by the Brownian-like random-walk movement which is used by an organism to migrate. It has been verified to be more effective than ABC, JDE, JADE, SADE, EPSDE, GSA, PSO2011, and CMA-ES. In this paper, we propose four improved solution search algorithms, namely “DS/rand/1,” “DS/rand/2,” “DS/current to rand/1,” and “DS/current to rand/2” to search the new space and enhance the convergence rate for the global optimization problem. In order to verify the performance of different solution search methods, 23 benchmark functions are employed. Experimental results indicate that the proposed algorithm performs better than, or at least comparable to, the original algorithm when considering the quality of the solution obtained. However, these schemes cannot still achieve the best solution for all functions. In order to further enhance the convergence rate and the diversity of the algorithm, a composite differential search algorithm (CDS is proposed in this paper. This new algorithm combines three new proposed search schemes including “DS/rand/1,” “DS/rand/2,” and “DS/current to rand/1” with three control parameters using a random method to generate the offspring. Experiment results show that CDS has a faster convergence rate and better search ability based on the 23 benchmark functions.
Surfactants non-monotonically modify the onset of Faraday waves
Strickland, Stephen; Shearer, Michael; Daniels, Karen
2017-11-01
When a water-filled container is vertically vibrated, subharmonic Faraday waves emerge once the driving from the vibrations exceeds viscous dissipation. In the presence of an insoluble surfactant, a viscous boundary layer forms at the contaminated surface to balance the Marangoni and Boussinesq stresses. For linear gravity-capillary waves in an undriven fluid, the surfactant-induced boundary layer increases the amount of viscous dissipation. In our analysis and experiments, we consider whether similar effects occur for nonlinear Faraday (gravity-capillary) waves. Assuming a finite-depth, infinite-breadth, low-viscosity fluid, we derive an analytic expression for the onset acceleration up to second order in ɛ =√{ 1 / Re } . This expression allows us to include fluid depth and driving frequency as parameters, in addition to the Marangoni and Boussinesq numbers. For millimetric fluid depths and driving frequencies of 30 to 120 Hz, our analysis recovers prior numerical results and agrees with our measurements of NBD-PC surfactant on DI water. In both case, the onset acceleration increases non-monotonically as a function of Marangoni and Boussinesq numbers. For shallower systems, our model predicts that surfactants could decrease the onset acceleration. DMS-0968258.
Dynamical zeta functions for piecewise monotone maps of the interval
Ruelle, David
2004-01-01
Consider a space M, a map f:M\\to M, and a function g:M \\to {\\mathbb C}. The formal power series \\zeta (z) = \\exp \\sum ^\\infty _{m=1} \\frac {z^m}{m} \\sum _{x \\in \\mathrm {Fix}\\,f^m} \\prod ^{m-1}_{k=0} g (f^kx) yields an example of a dynamical zeta function. Such functions have unexpected analytic properties and interesting relations to the theory of dynamical systems, statistical mechanics, and the spectral theory of certain operators (transfer operators). The first part of this monograph presents a general introduction to this subject. The second part is a detailed study of the zeta functions associated with piecewise monotone maps of the interval [0,1]. In particular, Ruelle gives a proof of a generalized form of the Baladi-Keller theorem relating the poles of \\zeta (z) and the eigenvalues of the transfer operator. He also proves a theorem expressing the largest eigenvalue of the transfer operator in terms of the ergodic properties of (M,f,g).
The resource theory of quantum reference frames: manipulations and monotones
International Nuclear Information System (INIS)
Gour, Gilad; Spekkens, Robert W
2008-01-01
Every restriction on quantum operations defines a resource theory, determining how quantum states that cannot be prepared under the restriction may be manipulated and used to circumvent the restriction. A superselection rule (SSR) is a restriction that arises through the lack of a classical reference frame and the states that circumvent it (the resource) are quantum reference frames. We consider the resource theories that arise from three types of SSRs, associated respectively with lacking: (i) a phase reference, (ii) a frame for chirality, and (iii) a frame for spatial orientation. Focusing on pure unipartite quantum states (and in some cases restricting our attention even further to subsets of these), we explore single-copy and asymptotic manipulations. In particular, we identify the necessary and sufficient conditions for a deterministic transformation between two resource states to be possible and, when these conditions are not met, the maximum probability with which the transformation can be achieved. We also determine when a particular transformation can be achieved reversibly in the limit of arbitrarily many copies and find the maximum rate of conversion. A comparison of the three resource theories demonstrates that the extent to which resources can be interconverted decreases as the strength of the restriction increases. Along the way, we introduce several measures of frameness and prove that these are monotonically non-increasing under various classes of operations that are permitted by the SSR
The Marotto Theorem on planar monotone or competitive maps
International Nuclear Information System (INIS)
Yu Huang
2004-01-01
In 1978, Marotto generalized Li-Yorke's results on the criterion for chaos from one-dimensional discrete dynamical systems to n-dimensional discrete dynamical systems, showing that the existence of a non-degenerate snap-back repeller implies chaos in the sense of Li-Yorke. This theorem is very useful in predicting and analyzing discrete chaos in multi-dimensional dynamical systems. Yet, besides it is well known that there exists an error in the conditions of the original Marotto Theorem, and several authors had tried to correct it in different way, Chen, Hsu and Zhou pointed out that the verification of 'non-degeneracy' of a snap-back repeller is the most difficult in general and expected, 'almost beyond reasonable doubt', that the existence of only degenerate snap-back repeller still implies chaotic, which was posed as a conjecture by them. In this paper, we shall give necessary and sufficient conditions of chaos in the sense of Li-Yorke for planar monotone or competitive discrete dynamical systems and solve Chen-Hsu-Zhou Conjecture for such kinds of systems
Recognition algorithms in knot theory
International Nuclear Information System (INIS)
Dynnikov, I A
2003-01-01
In this paper the problem of constructing algorithms for comparing knots and links is discussed. A survey of existing approaches and basic results in this area is given. In particular, diverse combinatorial methods for representing links are discussed, the Haken algorithm for recognizing a trivial knot (the unknot) and a scheme for constructing a general algorithm (using Haken's ideas) for comparing links are presented, an approach based on representing links by closed braids is described, the known algorithms for solving the word problem and the conjugacy problem for braid groups are described, and the complexity of the algorithms under consideration is discussed. A new method of combinatorial description of knots is given together with a new algorithm (based on this description) for recognizing the unknot by using a procedure for monotone simplification. In the conclusion of the paper several problems are formulated whose solution could help to advance towards the 'algorithmization' of knot theory
Convergent Difference Schemes for Hamilton-Jacobi equations
Duisembay, Serikbolsyn
2018-05-07
In this thesis, we consider second-order fully nonlinear partial differential equations of elliptic type. Our aim is to develop computational methods using convergent difference schemes for stationary Hamilton-Jacobi equations with Dirichlet and Neumann type boundary conditions in arbitrary two-dimensional domains. First, we introduce the notion of viscosity solutions in both continuous and discontinuous frameworks. Next, we review Barles-Souganidis approach using monotone, consistent, and stable schemes. In particular, we show that these schemes converge locally uniformly to the unique viscosity solution of the first-order Hamilton-Jacobi equations under mild assumptions. To solve the scheme numerically, we use Euler map with some initial guess. This iterative method gives the viscosity solution as a limit. Moreover, we illustrate our numerical approach in several two-dimensional examples.
Directory of Open Access Journals (Sweden)
Coghetto Roland
2015-09-01
Full Text Available We are inspired by the work of Henri Cartan [16], Bourbaki [10] (TG. I Filtres and Claude Wagschal [34]. We define the base of filter, image filter, convergent filter bases, limit filter and the filter base of tails (fr: filtre des sections.
Branca, Mario
2013-01-01
Why does a lens magnify? Why does it shrink objects? Why does this happen? The activities that we propose here are useful in helping us to understand how lenses work, and they show that the same lens can have different magnification capabilities. A converging lens can also act as a diverging lens. (Contains 4 figures.)
Language Convergence Infrastructure
V. Zaytsev (Vadim); J.M. Fernandes; R. Lämmel (Ralf); J.M.W. Visser (Joost); J. Saraiva
2011-01-01
htmlabstractThe process of grammar convergence involves grammar extraction and transformation for structural equivalence and contains a range of technical challenges. These need to be addressed in order for the method to deliver useful results. The paper describes a DSL and the infrastructure behind
Kolodzy, Janet; Grant, August E.; DeMars, Tony R.; Wilkinson, Jeffrey S.
2014-01-01
The emergence of the Internet, social media, and digital technologies in the twenty-first century accelerated an evolution in journalism and communication that fit under the broad term of convergence. That evolution changed the relationship between news producers and consumers. It broke down the geographical boundaries in defining our communities,…
On a correspondence between regular and non-regular operator monotone functions
DEFF Research Database (Denmark)
Gibilisco, P.; Hansen, Frank; Isola, T.
2009-01-01
We prove the existence of a bijection between the regular and the non-regular operator monotone functions satisfying a certain functional equation. As an application we give a new proof of the operator monotonicity of certain functions related to the Wigner-Yanase-Dyson skew information....
Tijs, S.H.; Moretti, S.; Brânzei, R.; Norde, H.W.
2005-01-01
A new way is presented to define for minimum cost spanning tree (mcst-) games the irreducible core, which is introduced by Bird in 1976.The Bird core correspondence turns out to have interesting monotonicity and additivity properties and each stable cost monotonic allocation rule for mcst-problems
An analysis of the stability and monotonicity of a kind of control models
Directory of Open Access Journals (Sweden)
LU Yifa
2013-06-01
Full Text Available The stability and monotonicity of control systems with parameters are considered.By the iterative relationship of the coefficients of characteristic polynomials and the Mathematica software,some sufficient conditions for the monotonicity and stability of systems are given.
Generalized Yosida Approximations Based on Relatively A-Maximal m-Relaxed Monotonicity Frameworks
Directory of Open Access Journals (Sweden)
Heng-you Lan
2013-01-01
Full Text Available We introduce and study a new notion of relatively A-maximal m-relaxed monotonicity framework and discuss some properties of a new class of generalized relatively resolvent operator associated with the relatively A-maximal m-relaxed monotone operator and the new generalized Yosida approximations based on relatively A-maximal m-relaxed monotonicity framework. Furthermore, we give some remarks to show that the theory of the new generalized relatively resolvent operator and Yosida approximations associated with relatively A-maximal m-relaxed monotone operators generalizes most of the existing notions on (relatively maximal monotone mappings in Hilbert as well as Banach space and can be applied to study variational inclusion problems and first-order evolution equations as well as evolution inclusions.
Local Monotonicity and Isoperimetric Inequality on Hypersurfaces in Carnot groups
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Francesco Paolo Montefalcone
2010-12-01
Full Text Available Let G be a k-step Carnot group of homogeneous dimension Q. Later on we shall present some of the results recently obtained in [32] and, in particular, an intrinsic isoperimetric inequality for a C2-smooth compact hypersurface S with boundary @S. We stress that S and @S are endowed with the homogeneous measures n????1 H and n????2 H , respectively, which are actually equivalent to the intrinsic (Q - 1-dimensional and (Q - 2-dimensional Hausdor measures with respect to a given homogeneous metric % on G. This result generalizes a classical inequality, involving the mean curvature of the hypersurface, proven by Michael and Simon [29] and Allard [1], independently. One may also deduce some related Sobolev-type inequalities. The strategy of the proof is inspired by the classical one and will be discussed at the rst section. After reminding some preliminary notions about Carnot groups, we shall begin by proving a linear isoperimetric inequality. The second step is a local monotonicity formula. Then we may achieve the proof by a covering argument.We stress however that there are many dierences, due to our non-Euclidean setting.Some of the tools developed ad hoc are, in order, a \\blow-up" theorem, which holds true also for characteristic points, and a smooth Coarea Formula for the HS-gradient. Other tools are the horizontal integration by parts formula and the 1st variation formula for the H-perimeter n????1H already developed in [30, 31] and then generalized to hypersurfaces having non-empty characteristic set in [32]. These results can be useful in the study of minimal and constant horizontal mean curvature hypersurfaces in Carnot groups.
Summable series and convergence factors
Moore, Charles N
1938-01-01
Fairly early in the development of the theory of summability of divergent series, the concept of convergence factors was recognized as of fundamental importance in the subject. One of the pioneers in this field was C. N. Moore, the author of the book under review.... Moore classifies convergence factors into two types. In type I he places the factors which have only the property that they preserve convergence for a convergent series or produce convergence for a summable series. In type II he places the factors which not only maintain or produce convergence but have the additional property that
A Self-Adaptive Fuzzy c-Means Algorithm for Determining the Optimal Number of Clusters
Wang, Zhihao; Yi, Jing
2016-01-01
For the shortcoming of fuzzy c-means algorithm (FCM) needing to know the number of clusters in advance, this paper proposed a new self-adaptive method to determine the optimal number of clusters. Firstly, a density-based algorithm was put forward. The algorithm, according to the characteristics of the dataset, automatically determined the possible maximum number of clusters instead of using the empirical rule n and obtained the optimal initial cluster centroids, improving the limitation of FCM that randomly selected cluster centroids lead the convergence result to the local minimum. Secondly, this paper, by introducing a penalty function, proposed a new fuzzy clustering validity index based on fuzzy compactness and separation, which ensured that when the number of clusters verged on that of objects in the dataset, the value of clustering validity index did not monotonically decrease and was close to zero, so that the optimal number of clusters lost robustness and decision function. Then, based on these studies, a self-adaptive FCM algorithm was put forward to estimate the optimal number of clusters by the iterative trial-and-error process. At last, experiments were done on the UCI, KDD Cup 1999, and synthetic datasets, which showed that the method not only effectively determined the optimal number of clusters, but also reduced the iteration of FCM with the stable clustering result. PMID:28042291
DEFF Research Database (Denmark)
Kjeldsen, Lars Peter; Kjærgaard, Hanne Wacher
networks are still more prominently expected by students. Against this backdrop, an action research project has worked with the definition and testing of the hypothesized constituents of the Convergent Learning Space and how it challenges our traditional conceptions of learning spaces. The article...... describes this pilot study involving teachers in conscious, documented reflection on methods, approaches, and procedures conducive to learning processes in this new learning space. As a perspective, the article briefly outlines an intervention study aimed at investigating how students benefit from......The concept of the Convergent Learning Space has been hypothesized and explored in an ongoing action research project carried out at undergraduate level in select bachelor programs at a Danish University College, where classrooms are technology rich and students bring their own devices. The changes...
The Convergent Learning Space:
DEFF Research Database (Denmark)
Kjærgaard, Hanne Wacher; Kjeldsen, Lars Peter; Asmussen, Jørgen Bering
is described as well as the theoretical construct and hypotheses surrounding the emergence of the concept in technology-rich classrooms, where students bring their own devices and involve their personal learning spaces and networks. The need for new ways of approaching concepts like choice, learning resources......This paper describes the concept of “The Convergent Learning Space” as it is being explored in an ongoing action research project carried out at undergraduate level in select bachelor programs at a Danish University College. The background nature, design, and beginning of this work in progress......, trajectories of participation etc. calls for new action and new pedagogies by teachers in order to secure alignment between students’ worlds and expectations and aims and plans of the teacher. Action research methods are being used to define and test the constituents and variables of the convergent learning...
Convolutional Dictionary Learning: Acceleration and Convergence
Chun, Il Yong; Fessler, Jeffrey A.
2018-04-01
Convolutional dictionary learning (CDL or sparsifying CDL) has many applications in image processing and computer vision. There has been growing interest in developing efficient algorithms for CDL, mostly relying on the augmented Lagrangian (AL) method or the variant alternating direction method of multipliers (ADMM). When their parameters are properly tuned, AL methods have shown fast convergence in CDL. However, the parameter tuning process is not trivial due to its data dependence and, in practice, the convergence of AL methods depends on the AL parameters for nonconvex CDL problems. To moderate these problems, this paper proposes a new practically feasible and convergent Block Proximal Gradient method using a Majorizer (BPG-M) for CDL. The BPG-M-based CDL is investigated with different block updating schemes and majorization matrix designs, and further accelerated by incorporating some momentum coefficient formulas and restarting techniques. All of the methods investigated incorporate a boundary artifacts removal (or, more generally, sampling) operator in the learning model. Numerical experiments show that, without needing any parameter tuning process, the proposed BPG-M approach converges more stably to desirable solutions of lower objective values than the existing state-of-the-art ADMM algorithm and its memory-efficient variant do. Compared to the ADMM approaches, the BPG-M method using a multi-block updating scheme is particularly useful in single-threaded CDL algorithm handling large datasets, due to its lower memory requirement and no polynomial computational complexity. Image denoising experiments show that, for relatively strong additive white Gaussian noise, the filters learned by BPG-M-based CDL outperform those trained by the ADMM approach.
Simpson, Seamus
2015-01-01
The Broadcasting, Information Technology and Telecommunications sectors have in recent years been the subject of notable transformation, one important feature of which is their coming closer together in a number of ways - it is now commonplace to speak of a new hybrid sector, Information and Communications Technologies (ICTs). This convergence is of considerable interest to policy-makers in industry and government at the national and international level, as well as the academic community and,...
Convergence semigroup categories
Directory of Open Access Journals (Sweden)
Gary Richardson
2013-09-01
Full Text Available Properties of the category consisting of all objects of the form (X, S, λ are investigated, where X is a convergence space, S is a commutative semigroup, and λ: X × S → X is a continuous action. A “generalized quotient” of each object is defined without making the usual assumption that for each fixed g ∈ S, λ(., g : X → X is an injection.
Multiplier convergent series and uniform convergence of mapping ...
Indian Academy of Sciences (India)
MS received 14 April 2011; revised 17 November 2012. Abstract. In this paper, we introduce the frame property of complex sequence sets and study the uniform convergence of nonlinear mapping series in β-dual of spaces consisting of multiplier convergent series. Keywords. Multiplier convergent series; mapping series. 1.
Convergence Analysis of a Class of Computational Intelligence Approaches
Directory of Open Access Journals (Sweden)
Junfeng Chen
2013-01-01
Full Text Available Computational intelligence approaches is a relatively new interdisciplinary field of research with many promising application areas. Although the computational intelligence approaches have gained huge popularity, it is difficult to analyze the convergence. In this paper, a computational model is built up for a class of computational intelligence approaches represented by the canonical forms of generic algorithms, ant colony optimization, and particle swarm optimization in order to describe the common features of these algorithms. And then, two quantification indices, that is, the variation rate and the progress rate, are defined, respectively, to indicate the variety and the optimality of the solution sets generated in the search process of the model. Moreover, we give four types of probabilistic convergence for the solution set updating sequences, and their relations are discussed. Finally, the sufficient conditions are derived for the almost sure weak convergence and the almost sure strong convergence of the model by introducing the martingale theory into the Markov chain analysis.
Existence and convergence theorems for evolutionary hemivariational inequalities of second order
Directory of Open Access Journals (Sweden)
Zijia Peng
2015-03-01
Full Text Available This article concerns with a class of evolutionary hemivariational inequalities in the framework of evolution triple. Based on the Rothe method, monotonicity-compactness technique and the properties of Clarke's generalized derivative and gradient, the existence and convergence theorems to these problems are established. The main idea in the proof is using the time difference to construct the approximate problems. The work generalizes the existence results on evolution inclusions and hemivariational inequalities of second order.
Maximal monotone model with delay term of convolution
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Claude-Henri Lamarque
2005-01-01
Full Text Available Mechanical models are governed either by partial differential equations with boundary conditions and initial conditions (e.g., in the frame of continuum mechanics or by ordinary differential equations (e.g., after discretization via Galerkin procedure or directly from the model description with the initial conditions. In order to study dynamical behavior of mechanical systems with a finite number of degrees of freedom including nonsmooth terms (e.g., friction, we consider here problems governed by differential inclusions. To describe effects of particular constitutive laws, we add a delay term. In contrast to previous papers, we introduce delay via a Volterra kernel. We provide existence and uniqueness results by using an Euler implicit numerical scheme; then convergence with its order is established. A few numerical examples are given.
A Hybrid Chaotic Quantum Evolutionary Algorithm
DEFF Research Database (Denmark)
Cai, Y.; Zhang, M.; Cai, H.
2010-01-01
A hybrid chaotic quantum evolutionary algorithm is proposed to reduce amount of computation, speed up convergence and restrain premature phenomena of quantum evolutionary algorithm. The proposed algorithm adopts the chaotic initialization method to generate initial population which will form a pe...... tests. The presented algorithm is applied to urban traffic signal timing optimization and the effect is satisfied....
Convergence semigroup actions: generalized quotients
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H. Boustique
2009-10-01
Full Text Available Continuous actions of a convergence semigroup are investigated in the category of convergence spaces. Invariance properties of actions as well as properties of a generalized quotient space are presented
IT Convergence and Security 2012
Chung, Kyung-Yong
2013-01-01
The proceedings approaches the subject matter with problems in technical convergence and convergences of security technology. This approach is new because we look at new issues that arise from techniques converging. The general scope of the proceedings content is convergence security and the latest information technology. The intended readership are societies, enterprises, and research institutes, and intended content level is mid- to highly educated personals. The most important features and benefits of the proceedings are the introduction of the most recent information technology and its related ideas, applications and problems related to technology convergence, and its case studies and finally an introduction of converging existing security techniques through convergence security. Overall, through the proceedings, authors will be able to understand the most state of the art information strategies and technologies of convergence security.
International Nuclear Information System (INIS)
Liao Xiaofeng; Wong, K.-W.; Yang Shizhong
2003-01-01
In this Letter, the characteristics of the convergence dynamics of hybrid bidirectional associative memory neural networks with distributed transmission delays are studied. Without assuming the symmetry of synaptic connection weights and the monotonicity and differentiability of activation functions, the Lyapunov functionals are constructed and the generalized Halanay-type inequalities are employed to derive the delay-independent sufficient conditions under which the networks converge exponentially to the equilibria associated with temporally uniform external inputs. Some examples are given to illustrate the correctness of our results
Quick fuzzy backpropagation algorithm.
Nikov, A; Stoeva, S
2001-03-01
A modification of the fuzzy backpropagation (FBP) algorithm called QuickFBP algorithm is proposed, where the computation of the net function is significantly quicker. It is proved that the FBP algorithm is of exponential time complexity, while the QuickFBP algorithm is of polynomial time complexity. Convergence conditions of the QuickFBP, resp. the FBP algorithm are defined and proved for: (1) single output neural networks in case of training patterns with different targets; and (2) multiple output neural networks in case of training patterns with equivalued target vector. They support the automation of the weights training process (quasi-unsupervised learning) establishing the target value(s) depending on the network's input values. In these cases the simulation results confirm the convergence of both algorithms. An example with a large-sized neural network illustrates the significantly greater training speed of the QuickFBP rather than the FBP algorithm. The adaptation of an interactive web system to users on the basis of the QuickFBP algorithm is presented. Since the QuickFBP algorithm ensures quasi-unsupervised learning, this implies its broad applicability in areas of adaptive and adaptable interactive systems, data mining, etc. applications.
International Nuclear Information System (INIS)
Defrise, Michel; Rezaei, Ahmadreza; Nuyts, Johan
2014-01-01
The maximum likelihood attenuation correction factors (MLACF) algorithm has been developed to calculate the maximum-likelihood estimate of the activity image and the attenuation sinogram in time-of-flight (TOF) positron emission tomography, using only emission data without prior information on the attenuation. We consider the case of a Poisson model of the data, in the absence of scatter or random background. In this case the maximization with respect to the attenuation factors can be achieved in a closed form and the MLACF algorithm works by updating the activity. Despite promising numerical results, the convergence of this algorithm has not been analysed. In this paper we derive the algorithm and demonstrate that the MLACF algorithm monotonically increases the likelihood, is asymptotically regular, and that the limit points of the iteration are stationary points of the likelihood. Because the problem is not convex, however, the limit points might be saddle points or local maxima. To obtain some empirical insight into the latter question, we present data obtained by applying MLACF to 2D simulated TOF data, using a large number of iterations and different initializations. (paper)
Energy Technology Data Exchange (ETDEWEB)
Karlsen, Kenneth Hvistendal; Risebro, Nils Henrik
2000-09-01
We consider the initial value problem for degenerate viscous and inviscid scalar conservation laws where the flux function depends on the spatial location through a ''rough'' coefficient function k(x). we show that the Engquist-Osher (and hence all monotone) finite difference approximations converge to the unique entropy solution of the governing equation if, among other demands, k' is in BV, thereby providing alternative (new) existence proofs for entropy solutions of degenerate convection-diffusion equations as well as new convergence results for their finite difference approximations. In the inviscid case, we also provide a rate of convergence. Our convergence proofs are based on deriving a series of a priori estimates and using a general L{sup p} compactness criterion. (author)
Directory of Open Access Journals (Sweden)
Rogério Christofoletti
2008-12-01
Full Text Available Three ideas would suffice for the reading of “Cultura da Convergência” (Culture of Convergence by Henry Jenkins to be of interest to journalists and researchers in the area: media convergence as a cultural process; the strengthening of an emotional economy which guides consumers of symbolic goods and media creators; the expansion of trans-media narrative forms.
Directory of Open Access Journals (Sweden)
Rogério Christofoletti
2011-02-01
Full Text Available Three ideas would suffice for the reading of “Cultura da Convergência” (Culture of Convergence by Henry Jenkins to be of interest to journalists and researchers in the area: media convergence as a cultural process; the strengthening of an emotional economy which guides consumers of symbolic goods and media creators; the expansion of trans-media narrative forms.
Eigenvalue Decomposition-Based Modified Newton Algorithm
Directory of Open Access Journals (Sweden)
Wen-jun Wang
2013-01-01
Full Text Available When the Hessian matrix is not positive, the Newton direction may not be the descending direction. A new method named eigenvalue decomposition-based modified Newton algorithm is presented, which first takes the eigenvalue decomposition of the Hessian matrix, then replaces the negative eigenvalues with their absolute values, and finally reconstructs the Hessian matrix and modifies the searching direction. The new searching direction is always the descending direction. The convergence of the algorithm is proven and the conclusion on convergence rate is presented qualitatively. Finally, a numerical experiment is given for comparing the convergence domains of the modified algorithm and the classical algorithm.
Directory of Open Access Journals (Sweden)
Mervan Pašić
2016-10-01
Full Text Available We study non-monotone positive solutions of the second-order linear differential equations: $(p(tx'' + q(t x = e(t$, with positive $p(t$ and $q(t$. For the first time, some criteria as well as the existence and nonexistence of non-monotone positive solutions are proved in the framework of some properties of solutions $\\theta (t$ of the corresponding integrable linear equation: $(p(t\\theta''=e(t$. The main results are illustrated by many examples dealing with equations which allow exact non-monotone positive solutions not necessarily periodic. Finally, we pose some open questions.
A Multiscale Enrichment Procedure for Nonlinear Monotone Operators
Efendiev, Yalchin R.
2014-03-11
In this paper, multiscale finite element methods (MsFEMs) and domain decomposition techniques are developed for a class of nonlinear elliptic problems with high-contrast coefficients. In the process, existing work on linear problems [Y. Efendiev, J. Galvis, R. Lazarov, S. Margenov and J. Ren, Robust two-level domain decomposition preconditioners for high-contrast anisotropic flows in multiscale media. Submitted.; Y. Efendiev, J. Galvis and X. Wu, J. Comput. Phys. 230 (2011) 937–955; J. Galvis and Y. Efendiev, SIAM Multiscale Model. Simul. 8 (2010) 1461–1483.] is extended to treat a class of nonlinear elliptic operators. The proposed method requires the solutions of (small dimension and local) nonlinear eigenvalue problems in order to systematically enrich the coarse solution space. Convergence of the method is shown to relate to the dimension of the coarse space (due to the enrichment procedure) as well as the coarse mesh size. In addition, it is shown that the coarse mesh spaces can be effectively used in two-level domain decomposition preconditioners. A number of numerical results are presented to complement the analysis.
Logarithmically complete monotonicity of a function related to the Catalan-Qi function
Directory of Open Access Journals (Sweden)
Qi Feng
2016-08-01
Full Text Available In the paper, the authors find necessary and sufficient conditions such that a function related to the Catalan-Qi function, which is an alternative generalization of the Catalan numbers, is logarithmically complete monotonic.
Monotone matrix transformations defined by the group inverse and simultaneous diagonalizability
International Nuclear Information System (INIS)
Bogdanov, I I; Guterman, A E
2007-01-01
Bijective linear transformations of the matrix algebra over an arbitrary field that preserve simultaneous diagonalizability are characterized. This result is used for the characterization of bijective linear monotone transformations . Bibliography: 28 titles.
Totally Optimal Decision Trees for Monotone Boolean Functions with at Most Five Variables
Chikalov, Igor; Hussain, Shahid; Moshkov, Mikhail
2013-01-01
In this paper, we present the empirical results for relationships between time (depth) and space (number of nodes) complexity of decision trees computing monotone Boolean functions, with at most five variables. We use Dagger (a tool for optimization
Guaranteed convergence of the Hough transform
Soffer, Menashe; Kiryati, Nahum
1995-01-01
The straight-line Hough Transform using normal parameterization with a continuous voting kernel is considered. It transforms the colinearity detection problem to a problem of finding the global maximum of a two dimensional function above a domain in the parameter space. The principle is similar to robust regression using fixed scale M-estimation. Unlike standard M-estimation procedures the Hough Transform does not rely on a good initial estimate of the line parameters: The global optimization problem is approached by exhaustive search on a grid that is usually as fine as computationally feasible. The global maximum of a general function above a bounded domain cannot be found by a finite number of function evaluations. Only if sufficient a-priori knowledge about the smoothness of the objective function is available, convergence to the global maximum can be guaranteed. The extraction of a-priori information and its efficient use are the main challenges in real global optimization problems. The global optimization problem in the Hough Transform is essentially how fine should the parameter space quantization be in order not to miss the true maximum. More than thirty years after Hough patented the basic algorithm, the problem is still essentially open. In this paper an attempt is made to identify a-priori information on the smoothness of the objective (Hough) function and to introduce sufficient conditions for the convergence of the Hough Transform to the global maximum. An image model with several application dependent parameters is defined. Edge point location errors as well as background noise are accounted for. Minimal parameter space quantization intervals that guarantee convergence are obtained. Focusing policies for multi-resolution Hough algorithms are developed. Theoretical support for bottom- up processing is provided. Due to the randomness of errors and noise, convergence guarantees are probabilistic.
Global Attractivity Results for Mixed-Monotone Mappings in Partially Ordered Complete Metric Spaces
Directory of Open Access Journals (Sweden)
Kalabušić S
2009-01-01
Full Text Available We prove fixed point theorems for mixed-monotone mappings in partially ordered complete metric spaces which satisfy a weaker contraction condition than the classical Banach contraction condition for all points that are related by given ordering. We also give a global attractivity result for all solutions of the difference equation , where satisfies mixed-monotone conditions with respect to the given ordering.
Reduction theorems for weighted integral inequalities on the cone of monotone functions
International Nuclear Information System (INIS)
Gogatishvili, A; Stepanov, V D
2013-01-01
This paper surveys results related to the reduction of integral inequalities involving positive operators in weighted Lebesgue spaces on the real semi-axis and valid on the cone of monotone functions, to certain more easily manageable inequalities valid on the cone of non-negative functions. The case of monotone operators is new. As an application, a complete characterization for all possible integrability parameters is obtained for a number of Volterra operators. Bibliography: 118 titles
Totally Optimal Decision Trees for Monotone Boolean Functions with at Most Five Variables
Chikalov, Igor
2013-01-01
In this paper, we present the empirical results for relationships between time (depth) and space (number of nodes) complexity of decision trees computing monotone Boolean functions, with at most five variables. We use Dagger (a tool for optimization of decision trees and decision rules) to conduct experiments. We show that, for each monotone Boolean function with at most five variables, there exists a totally optimal decision tree which is optimal with respect to both depth and number of nodes.
Directory of Open Access Journals (Sweden)
Heinz Werner Höppel
2012-02-01
Full Text Available The monotonic and cyclic deformation behavior of ultrafine-grained metastable austenitic steel AISI 304L, produced by severe plastic deformation, was investigated. Under monotonic loading, the martensitic phase transformation in the ultrafine-grained state is strongly favored. Under cyclic loading, the martensitic transformation behavior is similar to the coarse-grained condition, but the cyclic stress response is three times larger for the ultrafine-grained condition.
International Nuclear Information System (INIS)
Duan Shukai; Liao Xiaofeng
2007-01-01
A new chaotic delayed neuron model with non-monotonously increasing transfer function, called as chaotic Liao's delayed neuron model, was recently reported and analyzed. An electronic implementation of this model is described in detail. At the same time, some methods in circuit design, especially for circuit with time delayed unit and non-monotonously increasing activation unit, are also considered carefully. We find that the dynamical behaviors of the designed circuits are closely similar to the results predicted by numerical experiments
Streaming Algorithms for Line Simplification
DEFF Research Database (Denmark)
Abam, Mohammad; de Berg, Mark; Hachenberger, Peter
2010-01-01
this problem in a streaming setting, where we only have a limited amount of storage, so that we cannot store all the points. We analyze the competitive ratio of our algorithms, allowing resource augmentation: we let our algorithm maintain a simplification with 2k (internal) points and compare the error of our...... simplification to the error of the optimal simplification with k points. We obtain the algorithms with O(1) competitive ratio for three cases: convex paths, where the error is measured using the Hausdorff distance (or Fréchet distance), xy-monotone paths, where the error is measured using the Hausdorff distance...... (or Fréchet distance), and general paths, where the error is measured using the Fréchet distance. In the first case the algorithm needs O(k) additional storage, and in the latter two cases the algorithm needs O(k 2) additional storage....
International Nuclear Information System (INIS)
Xu, Meng; Droguett, Enrique López; Lins, Isis Didier; Chagas Moura, Márcio das
2017-01-01
The q-Weibull model is based on the Tsallis non-extensive entropy and is able to model various behaviors of the hazard rate function, including bathtub curves, by using a single set of parameters. Despite its flexibility, the q-Weibull has not been widely used in reliability applications partly because of the complicated parameters estimation. In this work, the parameters of the q-Weibull are estimated by the maximum likelihood (ML) method. Due to the intricate system of nonlinear equations, derivative-based optimization methods may fail to converge. Thus, the heuristic optimization method of artificial bee colony (ABC) is used instead. To deal with the slow convergence of ABC, it is proposed an adaptive hybrid ABC (AHABC) algorithm that dynamically combines Nelder-Mead simplex search method with ABC for the ML estimation of the q-Weibull parameters. Interval estimates for the q-Weibull parameters, including confidence intervals based on the ML asymptotic theory and on bootstrap methods, are also developed. The AHABC is validated via numerical experiments involving the q-Weibull ML for reliability applications and results show that it produces faster and more accurate convergence when compared to ABC and similar approaches. The estimation procedure is applied to real reliability failure data characterized by a bathtub-shaped hazard rate. - Highlights: • Development of an Adaptive Hybrid ABC (AHABC) algorithm for q-Weibull distribution. • AHABC combines local Nelder-Mead simplex method with ABC to enhance local search. • AHABC efficiently finds the optimal solution for the q-Weibull ML problem. • AHABC outperforms ABC and self-adaptive hybrid ABC in accuracy and convergence speed. • Useful model for reliability data with non-monotonic hazard rate.
A discrete wavelet spectrum approach for identifying non-monotonic trends in hydroclimate data
Sang, Yan-Fang; Sun, Fubao; Singh, Vijay P.; Xie, Ping; Sun, Jian
2018-01-01
The hydroclimatic process is changing non-monotonically and identifying its trends is a great challenge. Building on the discrete wavelet transform theory, we developed a discrete wavelet spectrum (DWS) approach for identifying non-monotonic trends in hydroclimate time series and evaluating their statistical significance. After validating the DWS approach using two typical synthetic time series, we examined annual temperature and potential evaporation over China from 1961-2013 and found that the DWS approach detected both the warming and the warming hiatus in temperature, and the reversed changes in potential evaporation. Further, the identified non-monotonic trends showed stable significance when the time series was longer than 30 years or so (i.e. the widely defined climate timescale). The significance of trends in potential evaporation measured at 150 stations in China, with an obvious non-monotonic trend, was underestimated and was not detected by the Mann-Kendall test. Comparatively, the DWS approach overcame the problem and detected those significant non-monotonic trends at 380 stations, which helped understand and interpret the spatiotemporal variability in the hydroclimatic process. Our results suggest that non-monotonic trends of hydroclimate time series and their significance should be carefully identified, and the DWS approach proposed has the potential for wide use in the hydrological and climate sciences.
A discrete wavelet spectrum approach for identifying non-monotonic trends in hydroclimate data
Directory of Open Access Journals (Sweden)
Y.-F. Sang
2018-01-01
Full Text Available The hydroclimatic process is changing non-monotonically and identifying its trends is a great challenge. Building on the discrete wavelet transform theory, we developed a discrete wavelet spectrum (DWS approach for identifying non-monotonic trends in hydroclimate time series and evaluating their statistical significance. After validating the DWS approach using two typical synthetic time series, we examined annual temperature and potential evaporation over China from 1961–2013 and found that the DWS approach detected both the warming and the warming hiatus in temperature, and the reversed changes in potential evaporation. Further, the identified non-monotonic trends showed stable significance when the time series was longer than 30 years or so (i.e. the widely defined climate timescale. The significance of trends in potential evaporation measured at 150 stations in China, with an obvious non-monotonic trend, was underestimated and was not detected by the Mann–Kendall test. Comparatively, the DWS approach overcame the problem and detected those significant non-monotonic trends at 380 stations, which helped understand and interpret the spatiotemporal variability in the hydroclimatic process. Our results suggest that non-monotonic trends of hydroclimate time series and their significance should be carefully identified, and the DWS approach proposed has the potential for wide use in the hydrological and climate sciences.
Kang, Hyeon-Ah; Su, Ya-Hui; Chang, Hua-Hua
2018-03-08
A monotone relationship between a true score (τ) and a latent trait level (θ) has been a key assumption for many psychometric applications. The monotonicity property in dichotomous response models is evident as a result of a transformation via a test characteristic curve. Monotonicity in polytomous models, in contrast, is not immediately obvious because item response functions are determined by a set of response category curves, which are conceivably non-monotonic in θ. The purpose of the present note is to demonstrate strict monotonicity in ordered polytomous item response models. Five models that are widely used in operational assessments are considered for proof: the generalized partial credit model (Muraki, 1992, Applied Psychological Measurement, 16, 159), the nominal model (Bock, 1972, Psychometrika, 37, 29), the partial credit model (Masters, 1982, Psychometrika, 47, 147), the rating scale model (Andrich, 1978, Psychometrika, 43, 561), and the graded response model (Samejima, 1972, A general model for free-response data (Psychometric Monograph no. 18). Psychometric Society, Richmond). The study asserts that the item response functions in these models strictly increase in θ and thus there exists strict monotonicity between τ and θ under certain specified conditions. This conclusion validates the practice of customarily using τ in place of θ in applied settings and provides theoretical grounds for one-to-one transformations between the two scales. © 2018 The British Psychological Society.
Medialogy - convergence and transdisciplinarity
DEFF Research Database (Denmark)
Nordahl, Rolf
2007-01-01
Art and design have many qualities which intuitively by society are appreciated. But on daily basis they are also assessed and evaluated. Some communities also share common understandings that norms, standards, conventions evolve, both from artistic desire as well as from more physical needs...... for changes in society, developments in taste etc. However, it certainly seems fair to say, that available technology makes a great difference to the development of any art form or practice. With the up rise of new educations such as Medialogy, new aspects of convergence and different forms...... of interdisciplinarity and transdisciplinarity is a pre-requisite for both researchers and students. In this talk we will demonstrate our approach through concrete examples of student productions and projects. We will also display the pedagogical method (problem based learning), that enables students to bridge gaps...
An improved VSS NLMS algorithm for active noise cancellation
Sun, Yunzhuo; Wang, Mingjiang; Han, Yufei; Zhang, Congyan
2017-08-01
In this paper, an improved variable step size NLMS algorithm is proposed. NLMS has fast convergence rate and low steady state error compared to other traditional adaptive filtering algorithm. But there is a contradiction between the convergence speed and steady state error that affect the performance of the NLMS algorithm. Now, we propose a new variable step size NLMS algorithm. It dynamically changes the step size according to current error and iteration times. The proposed algorithm has simple formulation and easily setting parameters, and effectively solves the contradiction in NLMS. The simulation results show that the proposed algorithm has a good tracking ability, fast convergence rate and low steady state error simultaneously.
Directory of Open Access Journals (Sweden)
Notermans Ton
2015-02-01
Full Text Available As economic stagnation continues to mark the EU in the fifth year of the euro zone crisis, political support for integration is waning. The European Parliament elections of 2014 returned a hitherto unparalleled number of Eurosceptic MEPs, with EU-critical parties becoming the largest ones in several Member States. Much of this Euroscepticism is driven by economic polarisation between core and peripheral countries. While an increasing number of voters in the northwestern creditor countries resent having to foot the bill for what they consider economic mismanagement in the periphery, voters in peripheral countries increasingly rebel against what they deem to be an economically catastrophic Diktat from Germany and its allies. Continued political support for European integration will hinge on successful income convergence in the EU but the current dilemma is that such policies might not be politically feasible. Periods of rapid convergence would seem to suggest that success depends on two main policy strategies. First, a monetary policy that promotes credit for productive purposes, leaves inflation control to other instruments, and employs selective credit rationing to prevent asset booms. Second, a vertical industrial policy prioritising selected industrial sectors. The first policy conflicts with the present framework of euro zone monetary policy, but that framework was only installed in the first place because many peripheral countries were desperately in search of an external constraint on domestic distributional conflict. Industrial policies, in turn, require a sufficient degree of state autonomy from business elites in order to be effective, but it is highly questionable whether most states in the EU possess such autonomy. Though there are, as yet hesitant, signs of a reorientation of both monetary and cohesion policy in the EU, the question of the institutional and political preconditions for their successful implementation has been largely
Convergence of a random walk method for the Burgers equation
International Nuclear Information System (INIS)
Roberts, S.
1985-10-01
In this paper we consider a random walk algorithm for the solution of Burgers' equation. The algorithm uses the method of fractional steps. The non-linear advection term of the equation is solved by advecting ''fluid'' particles in a velocity field induced by the particles. The diffusion term of the equation is approximated by adding an appropriate random perturbation to the positions of the particles. Though the algorithm is inefficient as a method for solving Burgers' equation, it does model a similar method, the random vortex method, which has been used extensively to solve the incompressible Navier-Stokes equations. The purpose of this paper is to demonstrate the strong convergence of our random walk method and so provide a model for the proof of convergence for more complex random walk algorithms; for instance, the random vortex method without boundaries
The Convergence Acceleration of Two-Dimensional Fourier Interpolation
Directory of Open Access Journals (Sweden)
Anry Nersessian
2008-07-01
Full Text Available Hereby, the convergence acceleration of two-dimensional trigonometric interpolation for a smooth functions on a uniform mesh is considered. Together with theoretical estimates some numerical results are presented and discussed that reveal the potential of this method for application in image processing. Experiments show that suggested algorithm allows acceleration of conventional Fourier interpolation even for sparse meshes that can lead to an efficient image compression/decompression algorithms and also to applications in image zooming procedures.
Failure mechanisms of closed-cell aluminum foam under monotonic and cyclic loading
International Nuclear Information System (INIS)
Amsterdam, E.; De Hosson, J.Th.M.; Onck, P.R.
2006-01-01
This paper concentrates on the differences in failure mechanisms of Alporas closed-cell aluminum foam under either monotonic or cyclic loading. The emphasis lies on aspects of crack nucleation and crack propagation in relation to the microstructure. The cell wall material consists of Al dendrites and an interdendritic network of Al 4 Ca and Al 22 CaTi 2 precipitates. In situ scanning electron microscopy monotonic tensile tests were performed on small samples to study crack nucleation and propagation. Digital image correlation was employed to map the strain in the cell wall on the characteristic microstructural length scale. Monotonic tensile tests and tension-tension fatigue tests were performed on larger samples to observe the overall fracture behavior and crack path in monotonic and cyclic loading. The crack nucleation and propagation path in both loading conditions are revealed and it can be concluded that during monotonic tension cracks nucleate in and propagate partly through the Al 4 Ca interdendritic network, whereas under cyclic loading cracks nucleate and propagate through the Al dendrites
Convergent systems vs. incremental stability
Rüffer, B.S.; Wouw, van de N.; Mueller, M.
2013-01-01
Two similar stability notions are considered; one is the long established notion of convergent systems, the other is the younger notion of incremental stability. Both notions require that any two solutions of a system converge to each other. Yet these stability concepts are different, in the sense
Strong Convergence Theorems for a Pair of Strictly Pseudononspreading Mappings
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Bin-Chao Deng
2013-01-01
Full Text Available Let H be a real Hilbert space. Let T1,T2:H→H be k1-, k2-strictly pseudononspreading mappings; let αn and βn be two real sequences in (0,1. For given x0∈H, the sequence xn is generated iteratively by xn+1=βnxn+1-βnTw1αnγfxn+I-μαnBTw2xn, ∀n∈N, where Twi=1−wiI+wiTi with i=1,2 and B:H→H is strongly monotone and Lipschitzian. Under some mild conditions on parameters αn and βn, we prove that the sequence xn converges strongly to the set FixT1∩FixT2 of fixed points of a pair of strictly pseudononspreading mappings T1 and T2.
Giant lobelias exemplify convergent evolution
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Givnish Thomas J
2010-01-01
Full Text Available Abstract Giant lobeliads on tropical mountains in East Africa and Hawaii have highly unusual, giant-rosette growth forms that appear to be convergent on each other and on those of several independently evolved groups of Asteraceae and other families. A recent phylogenetic analysis by Antonelli, based on sequencing the widest selection of lobeliads to date, raises doubts about this paradigmatic example of convergent evolution. Here I address the kinds of evidence needed to test for convergent evolution and argue that the analysis by Antonelli fails on four points. Antonelli's analysis makes several important contributions to our understanding of lobeliad evolution and geographic spread, but his claim regarding convergence appears to be invalid. Giant lobeliads in Hawaii and Africa represent paradigmatic examples of convergent evolution.
Strong Convergence Theorems for Variational Inequalities and Split Equality Problem
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Yu Jing Wu
2013-01-01
Full Text Available Let H1, H2, and H3 be real Hilbert spaces, let C⊆H1, Q⊆H2 be two nonempty closed convex sets, and let A:H1→H3, B:H2→H3 be two bounded linear operators. The split equality problem (SEP is to find x∈C, y∈Q such that Ax=By. Let H=H1×H2; consider f:H→H a contraction with coefficient 00, and M:H→H is a β-inverse strongly monotone mapping. Let 0<γ<γ̅/α, S=C×Q and G:H→H3 be defined by restricting to H1 is A and restricting to H2 is -B, that is, G has the matrix form G=[A,-B]. It is proved that the sequence {wn}={(xn,yn}⊆H generated by the iterative method wn+1=PS[αnγf(wn+(I-αnTPS(I-γnG*GPS(wn-λnMwn] converges strongly to w̃ which solves the SEP and the following variational inequality: 〈(T-λfw̃,w-w̃〉≥0 and 〈Mw̃,w-w̃〉≥0 for all w∈S. Moreover, if we take M=G*G:H→H, γn=0, then M is a β-inverse strongly monotone mapping, and the sequence {wn} generated by the iterative method wn+1=αnγf(wn+(I-αnTPS(wn-λnG*Gwn converges strongly to w̃ which solves the SEP and the following variational inequality: 〈(T-λfw̃,w-w̃〉≥0 for all w∈S.
Comparison of boundedness and monotonicity properties of one-leg and linear multistep methods
Mozartova, A.; Savostianov, I.; Hundsdorfer, W.
2015-01-01
© 2014 Elsevier B.V. All rights reserved. One-leg multistep methods have some advantage over linear multistep methods with respect to storage of the past results. In this paper boundedness and monotonicity properties with arbitrary (semi-)norms or convex functionals are analyzed for such multistep methods. The maximal stepsize coefficient for boundedness and monotonicity of a one-leg method is the same as for the associated linear multistep method when arbitrary starting values are considered. It will be shown, however, that combinations of one-leg methods and Runge-Kutta starting procedures may give very different stepsize coefficients for monotonicity than the linear multistep methods with the same starting procedures. Detailed results are presented for explicit two-step methods.
Energy Technology Data Exchange (ETDEWEB)
Erol, V. [Department of Computer Engineering, Institute of Science, Okan University, Istanbul (Turkey); Netas Telecommunication Inc., Istanbul (Turkey)
2016-04-21
Entanglement has been studied extensively for understanding the mysteries of non-classical correlations between quantum systems. In the bipartite case, there are well known monotones for quantifying entanglement such as concurrence, relative entropy of entanglement (REE) and negativity, which cannot be increased via local operations. The study on these monotones has been a hot topic in quantum information [1-7] in order to understand the role of entanglement in this discipline. It can be observed that from any arbitrary quantum pure state a mixed state can obtained. A natural generalization of this observation would be to consider local operations classical communication (LOCC) transformations between general pure states of two parties. Although this question is a little more difficult, a complete solution has been developed using the mathematical framework of the majorization theory [8]. In this work, we analyze the relation between entanglement monotones concurrence and negativity with respect to majorization for general two-level quantum systems of two particles.
Bornkamp, Björn; Ickstadt, Katja
2009-03-01
In this article, we consider monotone nonparametric regression in a Bayesian framework. The monotone function is modeled as a mixture of shifted and scaled parametric probability distribution functions, and a general random probability measure is assumed as the prior for the mixing distribution. We investigate the choice of the underlying parametric distribution function and find that the two-sided power distribution function is well suited both from a computational and mathematical point of view. The model is motivated by traditional nonlinear models for dose-response analysis, and provides possibilities to elicitate informative prior distributions on different aspects of the curve. The method is compared with other recent approaches to monotone nonparametric regression in a simulation study and is illustrated on a data set from dose-response analysis.
Comparison of boundedness and monotonicity properties of one-leg and linear multistep methods
Mozartova, A.
2015-05-01
© 2014 Elsevier B.V. All rights reserved. One-leg multistep methods have some advantage over linear multistep methods with respect to storage of the past results. In this paper boundedness and monotonicity properties with arbitrary (semi-)norms or convex functionals are analyzed for such multistep methods. The maximal stepsize coefficient for boundedness and monotonicity of a one-leg method is the same as for the associated linear multistep method when arbitrary starting values are considered. It will be shown, however, that combinations of one-leg methods and Runge-Kutta starting procedures may give very different stepsize coefficients for monotonicity than the linear multistep methods with the same starting procedures. Detailed results are presented for explicit two-step methods.
Directory of Open Access Journals (Sweden)
R. Siriram
2012-01-01
Full Text Available
ENGLISH ABSTRACT: Technology is a catalyst for competitive advantage. However, it is how technology is used that leads to a firm’s improved performance. In this article, an investigative framework is constructed to understand better what strategically drives new technology adoption. The strategic drivers include technology and business strategy alignment, better technology planning and selection of new technologies, the effects on a firm’s culture and climate, links to a firm’s organisational and environmental evolution, and benefits through convergence and collaboration. Using an investigative framework, it is shown how the strategic drivers link to improve a firm’s performance, producing competitive advantage. The investigative framework is tested using structural equation modelling. Various hypotheses are formed, and recommendations for further research are made.
AFRIKAANSE OPSOMMING: Tegnologie is ‘n katalisator vir mededingende voordeel. Dit is egter hoe tegnologie aangewend word wat aanleiding gee tot ‘n onderneming se verbeterde prestasie. In hierdie artikel word ‘n ondersoekende raamwerk gekonstrueer om insig te kry in dit wat die aanvaarding van nuwe tegnologie strategies dryf. Die strategiese dryfvere sluit in die belyning van tegnologie en ondernemingstrategie, beter tegnologiebeplanning en seleksie van nuwe tegnologieë, die effek op ‘n onderneming se kultuur en klimaat, koppeling na ‘n onderneming se organisatoriese en omgewingsevolusie, en voordele verkry deur konvergensie en samewerking. Deur ‘n ondersoekende raamwerk te gebruik, word daar getoon dat die strategiese dryfvere koppel om ‘n onderneming se prestasie te verbeter en sodoende ‘n mededingende voordeel te skep. Die raamwerk word getoets en hipoteses geformuleer waarna aanbevelings oor verdere navorsing aan die hand gedoen word.
Optimizing graph algorithms on pregel-like systems
Salihoglu, Semih; Widom, Jennifer
2014-01-01
We study the problem of implementing graph algorithms efficiently on Pregel-like systems, which can be surprisingly challenging. Standard graph algorithms in this setting can incur unnecessary inefficiencies such as slow convergence or high
Characterizing quantum correlations. The genuine multiparticle negativity as entanglement monotone
International Nuclear Information System (INIS)
Hofmann, Martin
2014-01-01
divergence is observed in the first derivative of the genuine multiparticle negativity. It is then shown that genuine three- and fourparticle entanglement obeys finite-size scaling and that the genuine three-particle entanglement has a finite spatial range. In the third part, a generalisation to the so-called stabiliser formalism is introduced. The idea of characterising pure stabiliser states via a maximal commuting group of local symmetries is extended to mixed states. These so-called stabilised states are then characterised by a not necessarily maximal commuting group of local symmetries and unite graph diagonal states and X-states in a single framework. Finally, the ambiguity of local base change is studied and a method to obtain a classification of the underlying symmetry groups into equivalence classes under local Clifford operations is provided. In the last part of this thesis, it is shown how symmetries of a state may be used to simplify the optimisation problem defining the genuine multiparticle negativity. A relationship between the symmetry of a state and the internal structure of the optimisation is established that can be used to reduce the number of variables in the optimisation problem. The latter is an instance of a semidefinite programming problem for which efficient numerical optimisation algorithms with a certified solution exist.
A note on the convergence of the Zakharov-Kuznetsov equation by homotopy analysis method
Directory of Open Access Journals (Sweden)
Amir Fallahzadeh
2014-07-01
Full Text Available In this paper, the convergence of Zakharov-Kuznetsov (ZK equation by homotopy analysis method (HAM is investigated. A theorem is proved to guarantee the convergence of HAMand to find the series solution of this equation via a reliable algorithm.
Optimizer convergence and local minima errors and their clinical importance
International Nuclear Information System (INIS)
Jeraj, Robert; Wu, Chuan; Mackie, Thomas R
2003-01-01
Two of the errors common in the inverse treatment planning optimization have been investigated. The first error is the optimizer convergence error, which appears because of non-perfect convergence to the global or local solution, usually caused by a non-zero stopping criterion. The second error is the local minima error, which occurs when the objective function is not convex and/or the feasible solution space is not convex. The magnitude of the errors, their relative importance in comparison to other errors as well as their clinical significance in terms of tumour control probability (TCP) and normal tissue complication probability (NTCP) were investigated. Two inherently different optimizers, a stochastic simulated annealing and deterministic gradient method were compared on a clinical example. It was found that for typical optimization the optimizer convergence errors are rather small, especially compared to other convergence errors, e.g., convergence errors due to inaccuracy of the current dose calculation algorithms. This indicates that stopping criteria could often be relaxed leading into optimization speed-ups. The local minima errors were also found to be relatively small and typically in the range of the dose calculation convergence errors. Even for the cases where significantly higher objective function scores were obtained the local minima errors were not significantly higher. Clinical evaluation of the optimizer convergence error showed good correlation between the convergence of the clinical TCP or NTCP measures and convergence of the physical dose distribution. On the other hand, the local minima errors resulted in significantly different TCP or NTCP values (up to a factor of 2) indicating clinical importance of the local minima produced by physical optimization
Converging cylindrical shocks in ideal magnetohydrodynamics
International Nuclear Information System (INIS)
Pullin, D. I.; Mostert, W.; Wheatley, V.; Samtaney, R.
2014-01-01
We consider a cylindrically symmetrical shock converging onto an axis within the framework of ideal, compressible-gas non-dissipative magnetohydrodynamics (MHD). In cylindrical polar co-ordinates we restrict attention to either constant axial magnetic field or to the azimuthal but singular magnetic field produced by a line current on the axis. Under the constraint of zero normal magnetic field and zero tangential fluid speed at the shock, a set of restricted shock-jump conditions are obtained as functions of the shock Mach number, defined as the ratio of the local shock speed to the unique magnetohydrodynamic wave speed ahead of the shock, and also of a parameter measuring the local strength of the magnetic field. For the line current case, two approaches are explored and the results compared in detail. The first is geometrical shock-dynamics where the restricted shock-jump conditions are applied directly to the equation on the characteristic entering the shock from behind. This gives an ordinary-differential equation for the shock Mach number as a function of radius which is integrated numerically to provide profiles of the shock implosion. Also, analytic, asymptotic results are obtained for the shock trajectory at small radius. The second approach is direct numerical solution of the radially symmetric MHD equations using a shock-capturing method. For the axial magnetic field case the shock implosion is of the Guderley power-law type with exponent that is not affected by the presence of a finite magnetic field. For the axial current case, however, the presence of a tangential magnetic field ahead of the shock with strength inversely proportional to radius introduces a length scale R=√(μ 0 /p 0 ) I/(2 π) where I is the current, μ 0 is the permeability, and p 0 is the pressure ahead of the shock. For shocks initiated at r ≫ R, shock convergence is first accompanied by shock strengthening as for the strictly gas-dynamic implosion. The diverging magnetic field
Converging cylindrical shocks in ideal magnetohydrodynamics
Pullin, D. I.
2014-09-01
We consider a cylindrically symmetrical shock converging onto an axis within the framework of ideal, compressible-gas non-dissipative magnetohydrodynamics (MHD). In cylindrical polar co-ordinates we restrict attention to either constant axial magnetic field or to the azimuthal but singular magnetic field produced by a line current on the axis. Under the constraint of zero normal magnetic field and zero tangential fluid speed at the shock, a set of restricted shock-jump conditions are obtained as functions of the shock Mach number, defined as the ratio of the local shock speed to the unique magnetohydrodynamic wave speed ahead of the shock, and also of a parameter measuring the local strength of the magnetic field. For the line current case, two approaches are explored and the results compared in detail. The first is geometrical shock-dynamics where the restricted shock-jump conditions are applied directly to the equation on the characteristic entering the shock from behind. This gives an ordinary-differential equation for the shock Mach number as a function of radius which is integrated numerically to provide profiles of the shock implosion. Also, analytic, asymptotic results are obtained for the shock trajectory at small radius. The second approach is direct numerical solution of the radially symmetric MHD equations using a shock-capturing method. For the axial magnetic field case the shock implosion is of the Guderley power-law type with exponent that is not affected by the presence of a finite magnetic field. For the axial current case, however, the presence of a tangential magnetic field ahead of the shock with strength inversely proportional to radius introduces a length scale R = √μ0/p0 I/(2π) where I is the current, μ0 is the permeability, and p0 is the pressure ahead of the shock. For shocks initiated at r ≫ R, shock convergence is first accompanied by shock strengthening as for the strictly gas-dynamic implosion. The diverging magnetic field then
Converging cylindrical shocks in ideal magnetohydrodynamics
Pullin, D. I.; Mostert, W.; Wheatley, V.; Samtaney, Ravi
2014-01-01
We consider a cylindrically symmetrical shock converging onto an axis within the framework of ideal, compressible-gas non-dissipative magnetohydrodynamics (MHD). In cylindrical polar co-ordinates we restrict attention to either constant axial magnetic field or to the azimuthal but singular magnetic field produced by a line current on the axis. Under the constraint of zero normal magnetic field and zero tangential fluid speed at the shock, a set of restricted shock-jump conditions are obtained as functions of the shock Mach number, defined as the ratio of the local shock speed to the unique magnetohydrodynamic wave speed ahead of the shock, and also of a parameter measuring the local strength of the magnetic field. For the line current case, two approaches are explored and the results compared in detail. The first is geometrical shock-dynamics where the restricted shock-jump conditions are applied directly to the equation on the characteristic entering the shock from behind. This gives an ordinary-differential equation for the shock Mach number as a function of radius which is integrated numerically to provide profiles of the shock implosion. Also, analytic, asymptotic results are obtained for the shock trajectory at small radius. The second approach is direct numerical solution of the radially symmetric MHD equations using a shock-capturing method. For the axial magnetic field case the shock implosion is of the Guderley power-law type with exponent that is not affected by the presence of a finite magnetic field. For the axial current case, however, the presence of a tangential magnetic field ahead of the shock with strength inversely proportional to radius introduces a length scale R = √μ0/p0 I/(2π) where I is the current, μ0 is the permeability, and p0 is the pressure ahead of the shock. For shocks initiated at r ≫ R, shock convergence is first accompanied by shock strengthening as for the strictly gas-dynamic implosion. The diverging magnetic field then
Converging cylindrical shocks in ideal magnetohydrodynamics
Energy Technology Data Exchange (ETDEWEB)
Pullin, D. I. [Graduate Aerospace Laboratories, California Institute of Technology, Pasadena, California 91125 (United States); Mostert, W.; Wheatley, V. [School of Mechanical and Mining Engineering, University of Queensland, Queensland 4072 (Australia); Samtaney, R. [Mechanical Engineering, Physical Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal (Saudi Arabia)
2014-09-15
We consider a cylindrically symmetrical shock converging onto an axis within the framework of ideal, compressible-gas non-dissipative magnetohydrodynamics (MHD). In cylindrical polar co-ordinates we restrict attention to either constant axial magnetic field or to the azimuthal but singular magnetic field produced by a line current on the axis. Under the constraint of zero normal magnetic field and zero tangential fluid speed at the shock, a set of restricted shock-jump conditions are obtained as functions of the shock Mach number, defined as the ratio of the local shock speed to the unique magnetohydrodynamic wave speed ahead of the shock, and also of a parameter measuring the local strength of the magnetic field. For the line current case, two approaches are explored and the results compared in detail. The first is geometrical shock-dynamics where the restricted shock-jump conditions are applied directly to the equation on the characteristic entering the shock from behind. This gives an ordinary-differential equation for the shock Mach number as a function of radius which is integrated numerically to provide profiles of the shock implosion. Also, analytic, asymptotic results are obtained for the shock trajectory at small radius. The second approach is direct numerical solution of the radially symmetric MHD equations using a shock-capturing method. For the axial magnetic field case the shock implosion is of the Guderley power-law type with exponent that is not affected by the presence of a finite magnetic field. For the axial current case, however, the presence of a tangential magnetic field ahead of the shock with strength inversely proportional to radius introduces a length scale R=√(μ{sub 0}/p{sub 0}) I/(2 π) where I is the current, μ{sub 0} is the permeability, and p{sub 0} is the pressure ahead of the shock. For shocks initiated at r ≫ R, shock convergence is first accompanied by shock strengthening as for the strictly gas-dynamic implosion. The
Monotone numerical methods for finite-state mean-field games
Gomes, Diogo A.; Saude, Joao
2017-01-01
Here, we develop numerical methods for finite-state mean-field games (MFGs) that satisfy a monotonicity condition. MFGs are determined by a system of differential equations with initial and terminal boundary conditions. These non-standard conditions are the main difficulty in the numerical approximation of solutions. Using the monotonicity condition, we build a flow that is a contraction and whose fixed points solve the MFG, both for stationary and time-dependent problems. We illustrate our methods in a MFG modeling the paradigm-shift problem.
Monotone numerical methods for finite-state mean-field games
Gomes, Diogo A.
2017-04-29
Here, we develop numerical methods for finite-state mean-field games (MFGs) that satisfy a monotonicity condition. MFGs are determined by a system of differential equations with initial and terminal boundary conditions. These non-standard conditions are the main difficulty in the numerical approximation of solutions. Using the monotonicity condition, we build a flow that is a contraction and whose fixed points solve the MFG, both for stationary and time-dependent problems. We illustrate our methods in a MFG modeling the paradigm-shift problem.
Nonlinear convergence active vibration absorber for single and multiple frequency vibration control
Wang, Xi; Yang, Bintang; Guo, Shufeng; Zhao, Wenqiang
2017-12-01
This paper presents a nonlinear convergence algorithm for active dynamic undamped vibration absorber (ADUVA). The damping of absorber is ignored in this algorithm to strengthen the vibration suppressing effect and simplify the algorithm at the same time. The simulation and experimental results indicate that this nonlinear convergence ADUVA can help significantly suppress vibration caused by excitation of both single and multiple frequency. The proposed nonlinear algorithm is composed of equivalent dynamic modeling equations and frequency estimator. Both the single and multiple frequency ADUVA are mathematically imitated by the same mechanical structure with a mass body and a voice coil motor (VCM). The nonlinear convergence estimator is applied to simultaneously satisfy the requirements of fast convergence rate and small steady state frequency error, which are incompatible for linear convergence estimator. The convergence of the nonlinear algorithm is mathematically proofed, and its non-divergent characteristic is theoretically guaranteed. The vibration suppressing experiments demonstrate that the nonlinear ADUVA can accelerate the convergence rate of vibration suppressing and achieve more decrement of oscillation attenuation than the linear ADUVA.
Convergence and Consistency Analysis for A 3D Invariant-EKF SLAM
Zhang, Teng; Wu, Kanzhi; Song, Jingwei; Huang, Shoudong; Dissanayake, Gamini
2017-01-01
In this paper, we investigate the convergence and consistency properties of an Invariant-Extended Kalman Filter (RI-EKF) based Simultaneous Localization and Mapping (SLAM) algorithm. Basic convergence properties of this algorithm are proven. These proofs do not require the restrictive assumption that the Jacobians of the motion and observation models need to be evaluated at the ground truth. It is also shown that the output of RI-EKF is invariant under any stochastic rigid body transformation...
Masuyama, Hiroyuki
2014-01-01
In this paper we study the augmented truncation of discrete-time block-monotone Markov chains under geometric drift conditions. We first present a bound for the total variation distance between the stationary distributions of an original Markov chain and its augmented truncation. We also obtain such error bounds for more general cases, where an original Markov chain itself is not necessarily block monotone but is blockwise dominated by a block-monotone Markov chain. Finally,...
International Nuclear Information System (INIS)
Friedberg, R.; Lee, T.D.
2003-01-01
We present a new and simpler proof for the convergent iterative solution of the one-dimensional degenerate double-well potential. This new proof depends on a general theorem, called the hierarchy theorem, that shows the successive stages in the iteration to form a monotonically increasing sequence of approximations to the energy and to the wavefunction at any point x. This important property makes possible a much simpler proof of convergence than the one given before in the literature. The hierarchy theorem proven in this paper is applicable to a much wider class of potentials which includes the quartic potential
The Convergence in Spatial Tasks
Directory of Open Access Journals (Sweden)
Vladimir P. Kulagin
2013-01-01
Full Text Available The article reveals the problem of convergence of direct and inverse problems in Earth Sciences, describes the features and application of these problems, discloses analytical features of direct and inverse problems. The convergence criteria and conditions for convergence were presented. This work is supported by the Grant of the Government of the Russian Federation for support of scientific research, implemented under the supervision of leading scientists in Russian institutions of higher education in the field "Space Research and Technologies" in 2011–2013.
International Nuclear Information System (INIS)
Lenoir, A.
2008-01-01
We focus in this thesis, on the optimization process of large systems under uncertainty, and more specifically on solving the class of so-called deterministic equivalents with the help of splitting methods. The underlying application we have in mind is the electricity unit commitment problem under climate, market and energy consumption randomness, arising at EDF. We set the natural time-space-randomness couplings related to this application and we propose two new discretization schemes to tackle the randomness one, each of them based on non-parametric estimation of conditional expectations. This constitute an alternative to the usual scenario tree construction. We use the mathematical model consisting of the sum of two convex functions, a separable one and a coupling one. On the one hand, this simplified model offers a general framework to study decomposition-coordination algorithms by elapsing technicality due to a particular choice of subsystems. On the other hand, the convexity assumption allows to take advantage of monotone operators theory and to identify proximal methods as fixed point algorithms. We underlie the differential properties of the generalized reactions we are looking for a fixed point in order to derive bounds on the speed of convergence. Then we examine two families of decomposition-coordination algorithms resulting from operator splitting methods, namely Forward-Backward and Rachford methods. We suggest some practical method of acceleration of the Rachford class methods. To this end, we analyze the method from a theoretical point of view, furnishing as a byproduct explanations to some numerical observations. Then we propose as a response some improvements. Among them, an automatic updating strategy of scaling factors can correct a potential bad initial choice. The convergence proof is made easier thanks to stability results of some operator composition with respect to graphical convergence provided before. We also submit the idea of introducing
Cagnetti, Filippo
2013-11-01
We consider a numerical scheme for the one dimensional time dependent Hamilton-Jacobi equation in the periodic setting. This scheme consists in a semi-discretization using monotone approximations of the Hamiltonian in the spacial variable. From classical viscosity solution theory, these schemes are known to converge. In this paper we present a new approach to the study of the rate of convergence of the approximations based on the nonlinear adjoint method recently introduced by L.C. Evans. We estimate the rate of convergence for convex Hamiltonians and recover the O(h) convergence rate in terms of the L∞ norm and O(h) in terms of the L1 norm, where h is the size of the spacial grid. We discuss also possible generalizations to higher dimensional problems and present several other additional estimates. The special case of quadratic Hamiltonians is considered in detail in the end of the paper. © 2013 IMACS.
Cagnetti, Filippo; Gomes, Diogo A.; Tran, Hung Vinh
2013-01-01
We consider a numerical scheme for the one dimensional time dependent Hamilton-Jacobi equation in the periodic setting. This scheme consists in a semi-discretization using monotone approximations of the Hamiltonian in the spacial variable. From classical viscosity solution theory, these schemes are known to converge. In this paper we present a new approach to the study of the rate of convergence of the approximations based on the nonlinear adjoint method recently introduced by L.C. Evans. We estimate the rate of convergence for convex Hamiltonians and recover the O(h) convergence rate in terms of the L∞ norm and O(h) in terms of the L1 norm, where h is the size of the spacial grid. We discuss also possible generalizations to higher dimensional problems and present several other additional estimates. The special case of quadratic Hamiltonians is considered in detail in the end of the paper. © 2013 IMACS.
Approximation by Chebyshevian Bernstein Operators versus Convergence of Dimension Elevation
Ait-Haddou, Rachid; Mazure, Marie-Laurence
2016-01-01
On a closed bounded interval, consider a nested sequence of Extended Chebyshev spaces possessing Bernstein bases. This situation automatically generates an infinite dimension elevation algorithm transforming control polygons of any given level into control polygons of the next level. The convergence of these infinite sequences of polygons towards the corresponding curves is a classical issue in computer-aided geometric design. Moreover, according to recent work proving the existence of Bernstein-type operators in such Extended Chebyshev spaces, this nested sequence is automatically associated with an infinite sequence of Bernstein operators which all reproduce the same two-dimensional space. Whether or not this sequence of operators converges towards the identity on the space of all continuous functions is a natural issue in approximation theory. In the present article, we prove that the two issues are actually equivalent. Not only is this result interesting on the theoretical side, but it also has practical implications. For instance, it provides us with a Korovkin-type theorem of convergence of any infinite dimension elevation algorithm. It also enables us to tackle the question of convergence of the dimension elevation algorithm for any nested sequence obtained by repeated integration of the kernel of a given linear differential operator with constant coefficients. © 2016 Springer Science+Business Media New York
Approximation by Chebyshevian Bernstein Operators versus Convergence of Dimension Elevation
Ait-Haddou, Rachid
2016-03-18
On a closed bounded interval, consider a nested sequence of Extended Chebyshev spaces possessing Bernstein bases. This situation automatically generates an infinite dimension elevation algorithm transforming control polygons of any given level into control polygons of the next level. The convergence of these infinite sequences of polygons towards the corresponding curves is a classical issue in computer-aided geometric design. Moreover, according to recent work proving the existence of Bernstein-type operators in such Extended Chebyshev spaces, this nested sequence is automatically associated with an infinite sequence of Bernstein operators which all reproduce the same two-dimensional space. Whether or not this sequence of operators converges towards the identity on the space of all continuous functions is a natural issue in approximation theory. In the present article, we prove that the two issues are actually equivalent. Not only is this result interesting on the theoretical side, but it also has practical implications. For instance, it provides us with a Korovkin-type theorem of convergence of any infinite dimension elevation algorithm. It also enables us to tackle the question of convergence of the dimension elevation algorithm for any nested sequence obtained by repeated integration of the kernel of a given linear differential operator with constant coefficients. © 2016 Springer Science+Business Media New York
Algorithms for parallel computers
International Nuclear Information System (INIS)
Churchhouse, R.F.
1985-01-01
Until relatively recently almost all the algorithms for use on computers had been designed on the (usually unstated) assumption that they were to be run on single processor, serial machines. With the introduction of vector processors, array processors and interconnected systems of mainframes, minis and micros, however, various forms of parallelism have become available. The advantage of parallelism is that it offers increased overall processing speed but it also raises some fundamental questions, including: (i) which, if any, of the existing 'serial' algorithms can be adapted for use in the parallel mode. (ii) How close to optimal can such adapted algorithms be and, where relevant, what are the convergence criteria. (iii) How can we design new algorithms specifically for parallel systems. (iv) For multi-processor systems how can we handle the software aspects of the interprocessor communications. Aspects of these questions illustrated by examples are considered in these lectures. (orig.)
An improved affine projection algorithm for active noise cancellation
Zhang, Congyan; Wang, Mingjiang; Han, Yufei; Sun, Yunzhuo
2017-08-01
Affine projection algorithm is a signal reuse algorithm, and it has a good convergence rate compared to other traditional adaptive filtering algorithm. There are two factors that affect the performance of the algorithm, which are step factor and the projection length. In the paper, we propose a new variable step size affine projection algorithm (VSS-APA). It dynamically changes the step size according to certain rules, so that it can get smaller steady-state error and faster convergence speed. Simulation results can prove that its performance is superior to the traditional affine projection algorithm and in the active noise control (ANC) applications, the new algorithm can get very good results.
A new adaptive blind channel identification algorithm
International Nuclear Information System (INIS)
Peng Dezhong; Xiang Yong; Yi Zhang
2009-01-01
This paper addresses the blind identification of single-input multiple-output (SIMO) finite-impulse-response (FIR) systems. We first propose a new adaptive algorithm for the blind identification of SIMO FIR systems. Then, its convergence property is analyzed systematically. It is shown that under some mild conditions, the proposed algorithm is guaranteed to converge in the mean to the true channel impulse responses in both noisy and noiseless cases. Simulations are carried out to demonstrate the theoretical results.
Directory of Open Access Journals (Sweden)
Dazhi Jiang
2015-01-01
Full Text Available At present there is a wide range of evolutionary algorithms available to researchers and practitioners. Despite the great diversity of these algorithms, virtually all of the algorithms share one feature: they have been manually designed. A fundamental question is “are there any algorithms that can design evolutionary algorithms automatically?” A more complete definition of the question is “can computer construct an algorithm which will generate algorithms according to the requirement of a problem?” In this paper, a novel evolutionary algorithm based on automatic designing of genetic operators is presented to address these questions. The resulting algorithm not only explores solutions in the problem space like most traditional evolutionary algorithms do, but also automatically generates genetic operators in the operator space. In order to verify the performance of the proposed algorithm, comprehensive experiments on 23 well-known benchmark optimization problems are conducted. The results show that the proposed algorithm can outperform standard differential evolution algorithm in terms of convergence speed and solution accuracy which shows that the algorithm designed automatically by computers can compete with the algorithms designed by human beings.
Ecomorphological convergence in planktivorous surgeonfishes
Friedman, S. T.; Price, S. A.; Hoey, Andrew; Wainwright, P. C.
2016-01-01
two diet regimes: zooplanktivores and nonzooplanktivorous grazers. Accounting for phylogenetic relationships, the best-fitting model indicates that zooplanktivorous species are converging on a separate adaptive peak from their grazing relatives
Weak entropy inequalities and entropic convergence
Institute of Scientific and Technical Information of China (English)
2008-01-01
A criterion for algebraic convergence of the entropy is presented and an algebraic convergence result for the entropy of an exclusion process is improved. A weak entropy inequality is considered and its relationship to entropic convergence is discussed.
Directory of Open Access Journals (Sweden)
Rogério Christofoletti
2008-12-01
Full Text Available Três idéias já seriam suficientes para que a leitura de “Culturada Convergência”, de Henry Jenkins, interessasse a jornalistas epesquisadores da área: a convergência midiática como um processo cultural; o fortalecimento de uma economia afetiva que orienta consumidores de bens simbólicos e criadores midiáticos; a expansão de formas narrativas transmidiáticas.
Luo, Shunlong; Sun, Yuan
2017-08-01
Quantifications of coherence are intensively studied in the context of completely decoherent operations (i.e., von Neuamnn measurements, or equivalently, orthonormal bases) in recent years. Here we investigate partial coherence (i.e., coherence in the context of partially decoherent operations such as Lüders measurements). A bona fide measure of partial coherence is introduced. As an application, we address the monotonicity problem of K -coherence (a quantifier for coherence in terms of Wigner-Yanase skew information) [Girolami, Phys. Rev. Lett. 113, 170401 (2014), 10.1103/PhysRevLett.113.170401], which is introduced to realize a measure of coherence as axiomatized by Baumgratz, Cramer, and Plenio [Phys. Rev. Lett. 113, 140401 (2014), 10.1103/PhysRevLett.113.140401]. Since K -coherence fails to meet the necessary requirement of monotonicity under incoherent operations, it is desirable to remedy this monotonicity problem. We show that if we modify the original measure by taking skew information with respect to the spectral decomposition of an observable, rather than the observable itself, as a measure of coherence, then the problem disappears, and the resultant coherence measure satisfies the monotonicity. Some concrete examples are discussed and related open issues are indicated.
On the Computation of Optimal Monotone Mean-Variance Portfolios via Truncated Quadratic Utility
Ales Cerný; Fabio Maccheroni; Massimo Marinacci; Aldo Rustichini
2008-01-01
We report a surprising link between optimal portfolios generated by a special type of variational preferences called divergence preferences (cf. [8]) and optimal portfolios generated by classical expected utility. As a special case we connect optimization of truncated quadratic utility (cf. [2]) to the optimal monotone mean-variance portfolios (cf. [9]), thus simplifying the computation of the latter.
Monotonous property of non-oscillations of the damped Duffing's equation
International Nuclear Information System (INIS)
Feng Zhaosheng
2006-01-01
In this paper, we give a qualitative study to the damped Duffing's equation by means of the qualitative theory of planar systems. Under certain parametric conditions, the monotonous property of the bounded non-oscillations is obtained. Explicit exact solutions are obtained by a direct method and application of this approach to a reaction-diffusion equation is presented
A note on profit maximization and monotonicity for inbound call centers
Koole, G.M.; Pot, S.A.
2011-01-01
We consider an inbound call center with a fixed reward per call and communication and agent costs. By controlling the number of lines and the number of agents, we can maximize the profit. Abandonments are included in our performance model. Monotonicity results for the maximization problem are
DEFF Research Database (Denmark)
Garde, Henrik
2018-01-01
. For a fair comparison, exact matrix characterizations are used when probing the monotonicity relations to avoid errors from numerical solution to PDEs and numerical integration. Using a special factorization of the Neumann-to-Dirichlet map also makes the non-linear method as fast as the linear method...
ON AN EXPONENTIAL INEQUALITY AND A STRONG LAW OF LARGE NUMBERS FOR MONOTONE MEASURES
Czech Academy of Sciences Publication Activity Database
Agahi, H.; Mesiar, Radko
2014-01-01
Roč. 50, č. 5 (2014), s. 804-813 ISSN 0023-5954 Institutional support: RVO:67985556 Keywords : Choquet expectation * a strong law of large numbers * exponential inequality * monotone probability Subject RIV: BA - General Mathematics Impact factor: 0.541, year: 2014 http://library.utia.cas.cz/separaty/2014/E/mesiar-0438052.pdf
A note on monotone solutions for a nonconvex second-order functional differential inclusion
Directory of Open Access Journals (Sweden)
Aurelian Cernea
2011-12-01
Full Text Available The existence of monotone solutions for a second-order functional differential inclusion with Carath\\'{e}odory perturbation is obtained in the case when the multifunction that define the inclusion is upper semicontinuous compact valued and contained in the Fr\\'{e}chet subdifferential of a $\\phi $-convex function of order two.
Almost monotonicity formulas for elliptic and parabolic operators with variable coefficients
Matevosyan, Norayr; Petrosyan, Arshak
2010-01-01
In this paper we extend the results of Caffarelli, Jerison, and Kenig [Ann. of Math. (2)155 (2002)] and Caffarelli and Kenig [Amer. J. Math.120 (1998)] by establishing an almost monotonicity estimate for pairs of continuous functions satisfying u
Directory of Open Access Journals (Sweden)
Boubakari Ibrahimou
2013-01-01
maximal monotone with and . Using the topological degree theory developed by Kartsatos and Quarcoo we study the eigenvalue problem where the operator is a single-valued of class . The existence of continuous branches of eigenvectors of infinite length then could be easily extended to the case where the operator is multivalued and is investigated.
Characteristic of monotonicity of Orlicz function spaces equipped with the Orlicz norm
Czech Academy of Sciences Publication Activity Database
Foralewski, P.; Hudzik, H.; Kaczmarek, R.; Krbec, Miroslav
2013-01-01
Roč. 53, č. 2 (2013), s. 421-432 ISSN 0373-8299 R&D Projects: GA ČR GAP201/10/1920 Institutional support: RVO:67985840 Keywords : Orlicz space * Köthe space * characteristic of monotonicity Subject RIV: BA - General Mathematics
Non-monotonic reasoning in conceptual modeling and ontology design: A proposal
CSIR Research Space (South Africa)
Casini, G
2013-06-01
Full Text Available -1 2nd International Workshop on Ontologies and Conceptual Modeling (Onto.Com 2013), Valencia, Spain, 17-21 June 2013 Non-monotonic reasoning in conceptual modeling and ontology design: A proposal Giovanni Casini1 and Alessandro Mosca2 1...
CFD simulation of simultaneous monotonic cooling and surface heat transfer coefficient
International Nuclear Information System (INIS)
Mihálka, Peter; Matiašovský, Peter
2016-01-01
The monotonic heating regime method for determination of thermal diffusivity is based on the analysis of an unsteady-state (stabilised) thermal process characterised by an independence of the space-time temperature distribution on initial conditions. At the first kind of the monotonic regime a sample of simple geometry is heated / cooled at constant ambient temperature. The determination of thermal diffusivity requires the determination rate of a temperature change and simultaneous determination of the first eigenvalue. According to a characteristic equation the first eigenvalue is a function of the Biot number defined by a surface heat transfer coefficient and thermal conductivity of an analysed material. Knowing the surface heat transfer coefficient and the first eigenvalue the thermal conductivity can be determined. The surface heat transport coefficient during the monotonic regime can be determined by the continuous measurement of long-wave radiation heat flow and the photoelectric measurement of the air refractive index gradient in a boundary layer. CFD simulation of the cooling process was carried out to analyse local convective and radiative heat transfer coefficients more in detail. Influence of ambient air flow was analysed. The obtained eigenvalues and corresponding surface heat transfer coefficient values enable to determine thermal conductivity of the analysed specimen together with its thermal diffusivity during a monotonic heating regime.
Alternans by non-monotonic conduction velocity restitution, bistability and memory
International Nuclear Information System (INIS)
Kim, Tae Yun; Hong, Jin Hee; Heo, Ryoun; Lee, Kyoung J
2013-01-01
Conduction velocity (CV) restitution is a key property that characterizes any medium supporting traveling waves. It reflects not only the dynamics of the individual constituents but also the coupling mechanism that mediates their interaction. Recent studies have suggested that cardiac tissues, which have a non-monotonic CV-restitution property, can support alternans, a period-2 oscillatory response of periodically paced cardiac tissue. This study finds that single-hump, non-monotonic, CV-restitution curves are a common feature of in vitro cultures of rat cardiac cells. We also find that the Fenton–Karma model, one of the well-established mathematical models of cardiac tissue, supports a very similar non-monotonic CV restitution in a physiologically relevant parameter regime. Surprisingly, the mathematical model as well as the cell cultures support bistability and show cardiac memory that tends to work against the generation of an alternans. Bistability was realized by adopting two different stimulation protocols, ‘S1S2’, which produces a period-1 wave train, and ‘alternans-pacing’, which favors a concordant alternans. Thus, we conclude that the single-hump non-monotonicity in the CV-restitution curve is not sufficient to guarantee a cardiac alternans, since cardiac memory interferes and the way the system is paced matters. (paper)
On the Monotonicity and Log-Convexity of a Four-Parameter Homogeneous Mean
Directory of Open Access Journals (Sweden)
Yang Zhen-Hang
2008-01-01
Full Text Available Abstract A four-parameter homogeneous mean is defined by another approach. The criterion of its monotonicity and logarithmically convexity is presented, and three refined chains of inequalities for two-parameter mean values are deduced which contain many new and classical inequalities for means.
Transformation-invariant and nonparametric monotone smooth estimation of ROC curves.
Du, Pang; Tang, Liansheng
2009-01-30
When a new diagnostic test is developed, it is of interest to evaluate its accuracy in distinguishing diseased subjects from non-diseased subjects. The accuracy of the test is often evaluated by receiver operating characteristic (ROC) curves. Smooth ROC estimates are often preferable for continuous test results when the underlying ROC curves are in fact continuous. Nonparametric and parametric methods have been proposed by various authors to obtain smooth ROC curve estimates. However, there are certain drawbacks with the existing methods. Parametric methods need specific model assumptions. Nonparametric methods do not always satisfy the inherent properties of the ROC curves, such as monotonicity and transformation invariance. In this paper we propose a monotone spline approach to obtain smooth monotone ROC curves. Our method ensures important inherent properties of the underlying ROC curves, which include monotonicity, transformation invariance, and boundary constraints. We compare the finite sample performance of the newly proposed ROC method with other ROC smoothing methods in large-scale simulation studies. We illustrate our method through a real life example. Copyright (c) 2008 John Wiley & Sons, Ltd.
A Min-max Relation for Monotone Path Systems in Simple Regions
DEFF Research Database (Denmark)
Cameron, Kathleen
1996-01-01
A monotone path system (MPS) is a finite set of pairwise disjointpaths (polygonal arcs) in the plane such that every horizontal line intersectseach of the paths in at most one point. We consider a simple polygon in thexy-plane which bounds the simple polygonal (closed) region D. Let T and B betwo...
Monotonicity of the von Neumann entropy expressed as a function of R\\'enyi entropies
Fannes, Mark
2013-01-01
The von Neumann entropy of a density matrix of dimension d, expressed in terms of the first d-1 integer order R\\'enyi entropies, is monotonically increasing in R\\'enyi entropies of even order and decreasing in those of odd order.
Diversity-Guided Evolutionary Algorithms
DEFF Research Database (Denmark)
Ursem, Rasmus Kjær
2002-01-01
Population diversity is undoubtably a key issue in the performance of evolutionary algorithms. A common hypothesis is that high diversity is important to avoid premature convergence and to escape local optima. Various diversity measures have been used to analyze algorithms, but so far few...... algorithms have used a measure to guide the search. The diversity-guided evolutionary algorithm (DGEA) uses the wellknown distance-to-average-point measure to alternate between phases of exploration (mutation) and phases of exploitation (recombination and selection). The DGEA showed remarkable results...
Globalization and Contemporary Fertility Convergence.
Hendi, Arun S
2017-09-01
The rise of the global network of nation-states has precipitated social transformations throughout the world. This article examines the role of political and economic globalization in driving fertility convergence across countries between 1965 and 2009. While past research has typically conceptualized fertility change as a country-level process, this study instead employs a theoretical and methodological framework that examines differences in fertility between pairs of countries over time. Convergence in fertility between pairs of countries is hypothesized to result from increased cross-country connectedness and cross-national transmission of fertility-related schemas. I investigate the impact of various cross-country ties, including ties through bilateral trade, intergovernmental organizations, and regional trade blocs, on fertility convergence. I find that globalization acts as a form of social interaction to produce fertility convergence. There is significant heterogeneity in the effects of different cross-country ties. In particular, trade with rich model countries, joint participation in the UN and UNESCO, and joining a free trade agreement all contribute to fertility convergence between countries. Whereas the prevailing focus in fertility research has been on factors producing fertility declines, this analysis highlights specific mechanisms-trade and connectedness through organizations-leading to greater similarity in fertility across countries. Globalization is a process that propels the spread of culturally laden goods and schemas impinging on fertility, which in turn produces fertility convergence.
A Multistrategy Optimization Improved Artificial Bee Colony Algorithm
Directory of Open Access Journals (Sweden)
Wen Liu
2014-01-01
Full Text Available Being prone to the shortcomings of premature and slow convergence rate of artificial bee colony algorithm, an improved algorithm was proposed. Chaotic reverse learning strategies were used to initialize swarm in order to improve the global search ability of the algorithm and keep the diversity of the algorithm; the similarity degree of individuals of the population was used to characterize the diversity of population; population diversity measure was set as an indicator to dynamically and adaptively adjust the nectar position; the premature and local convergence were avoided effectively; dual population search mechanism was introduced to the search stage of algorithm; the parallel search of dual population considerably improved the convergence rate. Through simulation experiments of 10 standard testing functions and compared with other algorithms, the results showed that the improved algorithm had faster convergence rate and the capacity of jumping out of local optimum faster.
Iterative methods used in overlap astrometric reduction techniques do not always converge
Rapaport, M.; Ducourant, C.; Colin, J.; Le Campion, J. F.
1993-04-01
In this paper we prove that the classical Gauss-Seidel type iterative methods used for the solution of the reduced normal equations occurring in overlapping reduction methods of astrometry do not always converge. We exhibit examples of divergence. We then analyze an alternative algorithm proposed by Wang (1985). We prove the consistency of this algorithm and verify that it can be convergent while the Gauss-Seidel method is divergent. We conjecture the convergence of Wang method for the solution of astrometric problems using overlap techniques.
Convergence of the Quasi-static Antenna Design Algorithm
2013-04-01
was the first antenna design with quasi-static methods. In electrostatics, a perfect conductor is the same as an equipotential surface . A line of...which can cause the equipotential surface to terminate on the disk or feed wire. This requires an additional step in the solution process; the... equipotential surface is sampled to verify that the charge is enclosed by the equipotential surface . The final solution must be verified with a detailed
On the Convergence of Biogeography-Based Optimization for Binary Problems
Directory of Open Access Journals (Sweden)
Haiping Ma
2014-01-01
Full Text Available Biogeography-based optimization (BBO is an evolutionary algorithm inspired by biogeography, which is the study of the migration of species between habitats. A finite Markov chain model of BBO for binary problems was derived in earlier work, and some significant theoretical results were obtained. This paper analyzes the convergence properties of BBO on binary problems based on the previously derived BBO Markov chain model. Analysis reveals that BBO with only migration and mutation never converges to the global optimum. However, BBO with elitism, which maintains the best candidate in the population from one generation to the next, converges to the global optimum. In spite of previously published differences between genetic algorithms (GAs and BBO, this paper shows that the convergence properties of BBO are similar to those of the canonical GA. In addition, the convergence rate estimate of BBO with elitism is obtained in this paper and is confirmed by simulations for some simple representative problems.
An Improved Harmony Search Algorithm for Power Distribution Network Planning
Directory of Open Access Journals (Sweden)
Wei Sun
2015-01-01
Full Text Available Distribution network planning because of involving many variables and constraints is a multiobjective, discrete, nonlinear, and large-scale optimization problem. Harmony search (HS algorithm is a metaheuristic algorithm inspired by the improvisation process of music players. HS algorithm has several impressive advantages, such as easy implementation, less adjustable parameters, and quick convergence. But HS algorithm still has some defects such as premature convergence and slow convergence speed. According to the defects of the standard algorithm and characteristics of distribution network planning, an improved harmony search (IHS algorithm is proposed in this paper. We set up a mathematical model of distribution network structure planning, whose optimal objective function is to get the minimum annual cost and constraint conditions are overload and radial network. IHS algorithm is applied to solve the complex optimization mathematical model. The empirical results strongly indicate that IHS algorithm can effectively provide better results for solving the distribution network planning problem compared to other optimization algorithms.
Trophic convergence drives morphological convergence in marine tetrapods.
Kelley, Neil P; Motani, Ryosuke
2015-01-01
Marine tetrapod clades (e.g. seals, whales) independently adapted to marine life through the Mesozoic and Caenozoic, and provide iconic examples of convergent evolution. Apparent morphological convergence is often explained as the result of adaptation to similar ecological niches. However, quantitative tests of this hypothesis are uncommon. We use dietary data to classify the feeding ecology of extant marine tetrapods and identify patterns in skull and tooth morphology that discriminate trophic groups across clades. Mapping these patterns onto phylogeny reveals coordinated evolutionary shifts in diet and morphology in different marine tetrapod lineages. Similarities in morphology between species with similar diets-even across large phylogenetic distances-are consistent with previous hypotheses that shared functional constraints drive convergent evolution in marine tetrapods.
DEFF Research Database (Denmark)
Foglia, Aligi; Gottardi, Guido; Govoni, Laura
2015-01-01
The response of bucket foundations on sand subjected to planar monotonic and cyclic loading is investigated in the paper. Thirteen monotonic and cyclic laboratory tests on a skirted footing model having a 0.3 m diameter and embedment ratio equal to 1 are presented. The loading regime reproduces t...
Neutronic rebalance algorithms for SIMMER
International Nuclear Information System (INIS)
Soran, P.D.
1976-05-01
Four algorithms to solve the two-dimensional neutronic rebalance equations in SIMMER are investigated. Results of the study are presented and indicate that a matrix decomposition technique with a variable convergence criterion is the best solution algorithm in terms of accuracy and calculational speed. Rebalance numerical stability problems are examined. The results of the study can be applied to other neutron transport codes which use discrete ordinates techniques
A fast iterative soft-thresholding algorithm for few-view CT reconstruction
Energy Technology Data Exchange (ETDEWEB)
Wu, Junfeng; Mou, Xuanqin; Zhang, Yanbo [Jiaotong Univ., Xi' an (China). Inst. of Image Processing and Pattern Recognition
2011-07-01
Iterative soft-thresholding algorithms with total variation regularization can produce high-quality reconstructions from few views and even in the presence of noise. However, these algorithms are known to converge quite slowly, with a proven theoretically global convergence rate O(1/k), where k is iteration number. In this paper, we present a fast iterative soft-thresholding algorithm for few-view fan beam CT reconstruction with a global convergence rate O(1/k{sup 2}), which is significantly faster than the iterative soft-thresholding algorithm. Simulation results demonstrate the superior performance of the proposed algorithm in terms of convergence speed and reconstruction quality. (orig.)
Thermal effects on the enhanced ductility in non-monotonic uniaxial tension of DP780 steel sheet
Majidi, Omid; Barlat, Frederic; Korkolis, Yannis P.; Fu, Jiawei; Lee, Myoung-Gyu
2016-11-01
To understand the material behavior during non-monotonic loading, uniaxial tension tests were conducted in three modes, namely, the monotonic loading, loading with periodic relaxation and periodic loading-unloadingreloading, at different strain rates (0.001/s to 0.01/s). In this study, the temperature gradient developing during each test and its contribution to increasing the apparent ductility of DP780 steel sheets were considered. In order to assess the influence of temperature, isothermal uniaxial tension tests were also performed at three temperatures (298 K, 313 K and 328 K (25 °C, 40 °C and 55 °C)). A digital image correlation system coupled with an infrared thermography was used in the experiments. The results show that the non-monotonic loading modes increased the apparent ductility of the specimens. It was observed that compared with the monotonic loading, the temperature gradient became more uniform when a non-monotonic loading was applied.
Model-Free Adaptive Control Algorithm with Data Dropout Compensation
Directory of Open Access Journals (Sweden)
Xuhui Bu
2012-01-01
Full Text Available The convergence of model-free adaptive control (MFAC algorithm can be guaranteed when the system is subject to measurement data dropout. The system output convergent speed gets slower as dropout rate increases. This paper proposes a MFAC algorithm with data compensation. The missing data is first estimated using the dynamical linearization method, and then the estimated value is introduced to update control input. The convergence analysis of the proposed MFAC algorithm is given, and the effectiveness is also validated by simulations. It is shown that the proposed algorithm can compensate the effect of the data dropout, and the better output performance can be obtained.
Generalization of the Fourier Convergence Analysis in the Neutron Diffusion Eigenvalue Problem
International Nuclear Information System (INIS)
Lee, Hyun Chul; Noh, Jae Man; Joo, Hyung Kook
2005-01-01
Fourier error analysis has been a standard technique for the stability and convergence analysis of linear and nonlinear iterative methods. Lee et al proposed new 2- D/1-D coupling methods and demonstrated several advantages of the new methods by performing a Fourier convergence analysis of the methods as well as two existing methods for a fixed source problem. We demonstrated the Fourier convergence analysis of one of the 2-D/1-D coupling methods applied to a neutron diffusion eigenvalue problem. However, the technique cannot be used directly to analyze the convergence of the other 2-D/1-D coupling methods since some algorithm-specific features were used in our previous study. In this paper we generalized the Fourier convergence analysis technique proposed and analyzed the convergence of the 2-D/1-D coupling methods applied to a neutron diffusion Eigenvalue problem using the generalized technique
DEFF Research Database (Denmark)
Mahnke, Martina; Uprichard, Emma
2014-01-01
Imagine sailing across the ocean. The sun is shining, vastness all around you. And suddenly [BOOM] you’ve hit an invisible wall. Welcome to the Truman Show! Ever since Eli Pariser published his thoughts on a potential filter bubble, this movie scenario seems to have become reality, just with slight...... changes: it’s not the ocean, it’s the internet we’re talking about, and it’s not a TV show producer, but algorithms that constitute a sort of invisible wall. Building on this assumption, most research is trying to ‘tame the algorithmic tiger’. While this is a valuable and often inspiring approach, we...
Digital Convergence and Content Regulation
Directory of Open Access Journals (Sweden)
Michael John Starks
2014-12-01
Full Text Available Broadcasting, Press and Internet journalism systems of distribution are converging: the same infrastructure can deliver all three historically separate services. Reception devices mirror this: the Connected TV, the tablet and the smart phone overlap in their functionality. Service overlaps are evident too, with broadcasters providing online and on-demand services and newspapers developing electronic versions. Does this mean that media regulation policies must converge too?My argument is that they should, though only where historically different communications are now fulfilling a similar function, e.g. broadcaster online services and electronic versions of newspapers. Convergence requires a degree of harmonisation and, to this end, I advocate a review of UK broadcasting's 'due impartiality' requirement and of the UK's application of the public service concept. I also argue for independent self-regulation (rather than state-based regulation of non-public-service broadcasting journalism.
Directory of Open Access Journals (Sweden)
Rogério Christofoletti
2008-12-01
Full Text Available Três idéias já seriam suficientes para que a leitura de “Cultura da Convergência”, de Henry Jenkins, interessasse a jornalistas e pesquisadores da área: a convergência midiática como um processo cultural; o fortalecimento de uma economia afetiva que orienta consumidores de bens simbólicos e criadores midiáticos; a expansão de formas narrativas transmidiáticas.
DEFF Research Database (Denmark)
Schjær-Jacobsen, Hans
2012-01-01
uncertainty can be calculated. The possibility approach is particular well suited for representation of uncertainty of a non-statistical nature due to lack of knowledge and requires less information than the probability approach. Based on the kind of uncertainty and knowledge present, these aspects...... to the understanding of similarities and differences of the two approaches as well as practical applications. The probability approach offers a good framework for representation of randomness and variability. Once the probability distributions of uncertain parameters and their correlations are known the resulting...... are thoroughly discussed in the case of rectangular representation of uncertainty by the uniform probability distribution and the interval, respectively. Also triangular representations are dealt with and compared. Calculation of monotonic as well as non-monotonic functions of variables represented...
Monotonic and Cyclic Behavior of DIN 34CrNiMo6 Tempered Alloy Steel
Directory of Open Access Journals (Sweden)
Ricardo Branco
2016-04-01
Full Text Available This paper aims at studying the monotonic and cyclic plastic deformation behavior of DIN 34CrNiMo6 high strength steel. Monotonic and low-cycle fatigue tests are conducted in ambient air, at room temperature, using standard 8-mm diameter specimens. The former tests are carried out under position control with constant displacement rate. The latter are performed under fully-reversed strain-controlled conditions, using the single-step test method, with strain amplitudes lying between ±0.4% and ±2.0%. After the tests, the fracture surfaces are examined by scanning electron microscopy in order to characterize the surface morphologies and identify the main failure mechanisms. Regardless of the strain amplitude, a softening behavior was observed throughout the entire life. Total strain energy density, defined as the sum of both tensile elastic and plastic strain energies, was revealed to be an adequate fatigue damage parameter for short and long lives.
A Mathematical Model for Non-monotonic Deposition Profiles in Deep Bed Filtration Systems
DEFF Research Database (Denmark)
Yuan, Hao; Shapiro, Alexander
2011-01-01
A mathematical model for suspension/colloid flow in porous media and non-monotonic deposition is proposed. It accounts for the migration of particles associated with the pore walls via the second energy minimum (surface associated phase). The surface associated phase migration is characterized...... by advection and diffusion/dispersion. The proposed model is able to produce a nonmonotonic deposition profile. A set of methods for estimating the modeling parameters is provided in the case of minimal particle release. The estimation can be easily performed with available experimental information....... The numerical modeling results highly agree with the experimental observations, which proves the ability of the model to catch a non-monotonic deposition profile in practice. An additional equation describing a mobile population behaving differently from the injected population seems to be a sufficient...
Directory of Open Access Journals (Sweden)
SAEID ZAHEDI VAHID
2013-08-01
Full Text Available Recently steel extended end plate connections are commonly used in rigid steel frame due to its good ductility and ability for energy dissipation. This connection system is recommended to be widely used in special moment-resisting frame subjected to vertical monotonic and cyclic loads. However improper design of beam to column connection can leads to collapses and fatalities. Therefore extensive study of beam to column connection design must be carried out, particularly when the connection is exposed to cyclic loadings. This paper presents a Finite Element Analysis (FEA approach as an alternative method in studying the behavior of such connections. The performance of castellated beam-column end plate connections up to failure was investigated subjected to monotonic and cyclic loading in vertical and horizontal direction. The study was carried out through a finite element analysis using the multi-purpose software package LUSAS. The effect of arranging the geometry and location of openings were also been investigated.
Estimation of a monotone percentile residual life function under random censorship.
Franco-Pereira, Alba M; de Uña-Álvarez, Jacobo
2013-01-01
In this paper, we introduce a new estimator of a percentile residual life function with censored data under a monotonicity constraint. Specifically, it is assumed that the percentile residual life is a decreasing function. This assumption is useful when estimating the percentile residual life of units, which degenerate with age. We establish a law of the iterated logarithm for the proposed estimator, and its n-equivalence to the unrestricted estimator. The asymptotic normal distribution of the estimator and its strong approximation to a Gaussian process are also established. We investigate the finite sample performance of the monotone estimator in an extensive simulation study. Finally, data from a clinical trial in primary biliary cirrhosis of the liver are analyzed with the proposed methods. One of the conclusions of our work is that the restricted estimator may be much more efficient than the unrestricted one. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Non-monotonic relationships between emotional arousal and memory for color and location.
Boywitt, C Dennis
2015-01-01
Recent research points to the decreased diagnostic value of subjective retrieval experience for memory accuracy for emotional stimuli. While for neutral stimuli rich recollective experiences are associated with better context memory than merely familiar memories this association appears questionable for emotional stimuli. The present research tested the implicit assumption that the effect of emotional arousal on memory is monotonic, that is, steadily increasing (or decreasing) with increasing arousal. In two experiments emotional arousal was manipulated in three steps using emotional pictures and subjective retrieval experience as well as context memory were assessed. The results show an inverted U-shape relationship between arousal and recognition memory but for context memory and retrieval experience the relationship was more complex. For frame colour, context memory decreased linearly while for spatial location it followed the inverted U-shape function. The complex, non-monotonic relationships between arousal and memory are discussed as possible explanations for earlier divergent findings.
Monte Carlo source convergence and the Whitesides problem
International Nuclear Information System (INIS)
Blomquist, R. N.
2000-01-01
The issue of fission source convergence in Monte Carlo eigenvalue calculations is of interest because of the potential consequences of erroneous criticality safety calculations. In this work, the authors compare two different techniques to improve the source convergence behavior of standard Monte Carlo calculations applied to challenging source convergence problems. The first method, super-history powering, attempts to avoid discarding important fission sites between generations by delaying stochastic sampling of the fission site bank until after several generations of multiplication. The second method, stratified sampling of the fission site bank, explicitly keeps the important sites even if conventional sampling would have eliminated them. The test problems are variants of Whitesides' Criticality of the World problem in which the fission site phase space was intentionally undersampled in order to induce marginally intolerable variability in local fission site populations. Three variants of the problem were studied, each with a different degree of coupling between fissionable pieces. Both the superhistory powering method and the stratified sampling method were shown to improve convergence behavior, although stratified sampling is more robust for the extreme case of no coupling. Neither algorithm completely eliminates the loss of the most important fissionable piece, and if coupling is absent, the lost piece cannot be recovered unless its sites from earlier generations have been retained. Finally, criteria for measuring source convergence reliability are proposed and applied to the test problems
Convergence Analysis of the Graph Allen-Cahn Scheme
2016-02-01
steps Fdt(x) follows the same idea as above and involves only elementary calculations, we omit some of the details later. Next, we prove our main... linear as predicted by the 0.5 bound. Fig. 6.3: Two Moons Segmentation Problem. Left: Maximum stepsize for convergence, fixing = 1 varying N...semi- algebraic and tame problems: proximal algorithms, forward–backward splitting, and regularized Gauss–Seidel methods. Mathematical Programming, 137
Risk-Sensitive Control of Pure Jump Process on Countable Space with Near Monotone Cost
International Nuclear Information System (INIS)
Suresh Kumar, K.; Pal, Chandan
2013-01-01
In this article, we study risk-sensitive control problem with controlled continuous time pure jump process on a countable space as state dynamics. We prove multiplicative dynamic programming principle, elliptic and parabolic Harnack’s inequalities. Using the multiplicative dynamic programing principle and the Harnack’s inequalities, we prove the existence and a characterization of optimal risk-sensitive control under the near monotone condition
Asian Option Pricing with Monotonous Transaction Costs under Fractional Brownian Motion
Directory of Open Access Journals (Sweden)
Di Pan
2013-01-01
Full Text Available Geometric-average Asian option pricing model with monotonous transaction cost rate under fractional Brownian motion was established. The method of partial differential equations was used to solve this model and the analytical expressions of the Asian option value were obtained. The numerical experiments show that Hurst exponent of the fractional Brownian motion and transaction cost rate have a significant impact on the option value.
Asymptotic estimates and exponential stability for higher-order monotone difference equations
Directory of Open Access Journals (Sweden)
Pituk Mihály
2005-01-01
Full Text Available Asymptotic estimates are established for higher-order scalar difference equations and inequalities the right-hand sides of which generate a monotone system with respect to the discrete exponential ordering. It is shown that in some cases the exponential estimates can be replaced with a more precise limit relation. As corollaries, a generalization of discrete Halanay-type inequalities and explicit sufficient conditions for the global exponential stability of the zero solution are given.
Asymptotic estimates and exponential stability for higher-order monotone difference equations
Directory of Open Access Journals (Sweden)
Mihály Pituk
2005-03-01
Full Text Available Asymptotic estimates are established for higher-order scalar difference equations and inequalities the right-hand sides of which generate a monotone system with respect to the discrete exponential ordering. It is shown that in some cases the exponential estimates can be replaced with a more precise limit relation. As corollaries, a generalization of discrete Halanay-type inequalities and explicit sufficient conditions for the global exponential stability of the zero solution are given.
Diagnosis of constant faults in iteration-free circuits over monotone basis
Alrawaf, Saad Abdullah; Chikalov, Igor; Hussain, Shahid; Moshkov, Mikhail
2014-01-01
We show that for each iteration-free combinatorial circuit S over a basis B containing only monotone Boolean functions with at most five variables, there exists a decision tree for diagnosis of constant faults on inputs of gates with depth at most 7L(S) where L(S) is the number of gates in S. © 2013 Elsevier B.V. All rights reserved.
Inelastic behavior of materials and structures under monotonic and cyclic loading
Brünig, Michael
2015-01-01
This book presents studies on the inelastic behavior of materials and structures under monotonic and cyclic loads. It focuses on the description of new effects like purely thermal cycles or cases of non-trivial damages. The various models are based on different approaches and methods and scaling aspects are taken into account. In addition to purely phenomenological models, the book also presents mechanisms-based approaches. It includes contributions written by leading authors from a host of different countries.
Reduction theorems for weighted integral inequalities on the cone of monotone functions
Czech Academy of Sciences Publication Activity Database
Gogatishvili, Amiran; Stepanov, V.D.
2013-01-01
Roč. 68, č. 4 (2013), s. 597-664 ISSN 0036-0279 R&D Projects: GA ČR GA201/08/0383; GA ČR GA13-14743S Institutional support: RVO:67985840 Keywords : weighted Lebesgue space * cone of monotone functions * duality principle Subject RIV: BA - General Mathematics Impact factor: 1.357, year: 2013 http://iopscience.iop.org/0036-0279/68/4/597
On-line learning of non-monotonic rules by simple perceptron
Inoue, Jun-ichi; Nishimori, Hidetoshi; Kabashima, Yoshiyuki
1997-01-01
We study the generalization ability of a simple perceptron which learns unlearnable rules. The rules are presented by a teacher perceptron with a non-monotonic transfer function. The student is trained in the on-line mode. The asymptotic behaviour of the generalization error is estimated under various conditions. Several learning strategies are proposed and improved to obtain the theoretical lower bound of the generalization error.
ASPMT(QS): Non-Monotonic Spatial Reasoning with Answer Set Programming Modulo Theories
Wałęga, Przemysław Andrzej; Bhatt, Mehul; Schultz, Carl
2015-01-01
The systematic modelling of \\emph{dynamic spatial systems} [9] is a key requirement in a wide range of application areas such as comonsense cognitive robotics, computer-aided architecture design, dynamic geographic information systems. We present ASPMT(QS), a novel approach and fully-implemented prototype for non-monotonic spatial reasoning ---a crucial requirement within dynamic spatial systems-- based on Answer Set Programming Modulo Theories (ASPMT). ASPMT(QS) consists of a (qualitative) s...
Non-Monotonic Spatial Reasoning with Answer Set Programming Modulo Theories
Wałęga, Przemysław Andrzej; Schultz, Carl; Bhatt, Mehul
2016-01-01
The systematic modelling of dynamic spatial systems is a key requirement in a wide range of application areas such as commonsense cognitive robotics, computer-aided architecture design, and dynamic geographic information systems. We present ASPMT(QS), a novel approach and fully-implemented prototype for non-monotonic spatial reasoning -a crucial requirement within dynamic spatial systems- based on Answer Set Programming Modulo Theories (ASPMT). ASPMT(QS) consists of a (qualitative) spatial re...
The non-monotonic shear-thinning flow of two strongly cohesive concentrated suspensions
Buscall, Richard; Kusuma, Tiara E.; Stickland, Anthony D.; Rubasingha, Sayuri; Scales, Peter J.; Teo, Hui-En; Worrall, Graham L.
2014-01-01
The behaviour in simple shear of two concentrated and strongly cohesive mineral suspensions showing highly non-monotonic flow curves is described. Two rheometric test modes were employed, controlled stress and controlled shear-rate. In controlled stress mode the materials showed runaway flow above a yield stress, which, for one of the suspensions, varied substantially in value and seemingly at random from one run to the next, such that the up flow-curve appeared to be quite irreproducible. Th...
Diagnosis of constant faults in iteration-free circuits over monotone basis
Alrawaf, Saad Abdullah
2014-03-01
We show that for each iteration-free combinatorial circuit S over a basis B containing only monotone Boolean functions with at most five variables, there exists a decision tree for diagnosis of constant faults on inputs of gates with depth at most 7L(S) where L(S) is the number of gates in S. © 2013 Elsevier B.V. All rights reserved.
Lagarde, Fabien; Beausoleil, Claire; Belcher, Scott M; Belzunces, Luc P; Emond, Claude; Guerbet, Michel; Rousselle, Christophe
2015-01-01
International audience; Experimental studies investigating the effects of endocrine disruptors frequently identify potential unconventional dose-response relationships called non-monotonic dose-response (NMDR) relationships. Standardized approaches for investigating NMDR relationships in a risk assessment context are missing. The aim of this work was to develop criteria for assessing the strength of NMDR relationships. A literature search was conducted to identify published studies that repor...
Isochronous relaxation curves for type 304 stainless steel after monotonic and cyclic strain
International Nuclear Information System (INIS)
Swindeman, R.W.
1978-01-01
Relaxation tests to 100 hr were performed on type 304 stainless steel in the temperature range 480 to 650 0 C and were used to develop isochronous relaxation curves. Behavior after monotonic and cyclic strain was compared. Relaxation differed only slightly as a consequence of the type of previous strain, provided that plastic flow preceded the relaxation period. We observed that the short-time relaxation behavior did not manifest strong heat-to-heat variation in creep strength
Bagci, Hakan
2014-11-11
We study sweeping preconditioners for symmetric and positive definite block tridiagonal systems of linear equations. The algorithm provides an approximate inverse that can be used directly or in a preconditioned iterative scheme. These algorithms are based on replacing the Schur complements appearing in a block Gaussian elimination direct solve by hierarchical matrix approximations with reduced off-diagonal ranks. This involves developing low rank hierarchical approximations to inverses. We first provide a convergence analysis for the algorithm for reduced rank hierarchical inverse approximation. These results are then used to prove convergence and preconditioning estimates for the resulting sweeping preconditioner.
Bagci, Hakan; Pasciak, Joseph E.; Sirenko, Kostyantyn
2014-01-01
We study sweeping preconditioners for symmetric and positive definite block tridiagonal systems of linear equations. The algorithm provides an approximate inverse that can be used directly or in a preconditioned iterative scheme. These algorithms are based on replacing the Schur complements appearing in a block Gaussian elimination direct solve by hierarchical matrix approximations with reduced off-diagonal ranks. This involves developing low rank hierarchical approximations to inverses. We first provide a convergence analysis for the algorithm for reduced rank hierarchical inverse approximation. These results are then used to prove convergence and preconditioning estimates for the resulting sweeping preconditioner.
Performance Analyses of IDEAL Algorithm on Highly Skewed Grid System
Directory of Open Access Journals (Sweden)
Dongliang Sun
2014-03-01
Full Text Available IDEAL is an efficient segregated algorithm for the fluid flow and heat transfer problems. This algorithm has now been extended to the 3D nonorthogonal curvilinear coordinates. Highly skewed grids in the nonorthogonal curvilinear coordinates can decrease the convergence rate and deteriorate the calculating stability. In this study, the feasibility of the IDEAL algorithm on highly skewed grid system is analyzed by investigating the lid-driven flow in the inclined cavity. It can be concluded that the IDEAL algorithm is more robust and more efficient than the traditional SIMPLER algorithm, especially for the highly skewed and fine grid system. For example, at θ = 5° and grid number = 70 × 70 × 70, the convergence rate of the IDEAL algorithm is 6.3 times faster than that of the SIMPLER algorithm, and the IDEAL algorithm can converge almost at any time step multiple.
Modified artificial bee colony algorithm for reactive power optimization
Sulaiman, Noorazliza; Mohamad-Saleh, Junita; Abro, Abdul Ghani
2015-05-01
Bio-inspired algorithms (BIAs) implemented to solve various optimization problems have shown promising results which are very important in this severely complex real-world. Artificial Bee Colony (ABC) algorithm, a kind of BIAs has demonstrated tremendous results as compared to other optimization algorithms. This paper presents a new modified ABC algorithm referred to as JA-ABC3 with the aim to enhance convergence speed and avoid premature convergence. The proposed algorithm has been simulated on ten commonly used benchmarks functions. Its performance has also been compared with other existing ABC variants. To justify its robust applicability, the proposed algorithm has been tested to solve Reactive Power Optimization problem. The results have shown that the proposed algorithm has superior performance to other existing ABC variants e.g. GABC, BABC1, BABC2, BsfABC dan IABC in terms of convergence speed. Furthermore, the proposed algorithm has also demonstrated excellence performance in solving Reactive Power Optimization problem.
Non-monotonic effect of growth temperature on carrier collection in SnS solar cells
International Nuclear Information System (INIS)
Chakraborty, R.; Steinmann, V.; Mangan, N. M.; Brandt, R. E.; Poindexter, J. R.; Jaramillo, R.; Mailoa, J. P.; Hartman, K.; Polizzotti, A.; Buonassisi, T.; Yang, C.; Gordon, R. G.
2015-01-01
We quantify the effects of growth temperature on material and device properties of thermally evaporated SnS thin-films and test structures. Grain size, Hall mobility, and majority-carrier concentration monotonically increase with growth temperature. However, the charge collection as measured by the long-wavelength contribution to short-circuit current exhibits a non-monotonic behavior: the collection decreases with increased growth temperature from 150 °C to 240 °C and then recovers at 285 °C. Fits to the experimental internal quantum efficiency using an opto-electronic model indicate that the non-monotonic behavior of charge-carrier collection can be explained by a transition from drift- to diffusion-assisted components of carrier collection. The results show a promising increase in the extracted minority-carrier diffusion length at the highest growth temperature of 285 °C. These findings illustrate how coupled mechanisms can affect early stage device development, highlighting the critical role of direct materials property measurements and simulation
Almost monotonicity formulas for elliptic and parabolic operators with variable coefficients
Matevosyan, Norayr
2010-10-21
In this paper we extend the results of Caffarelli, Jerison, and Kenig [Ann. of Math. (2)155 (2002)] and Caffarelli and Kenig [Amer. J. Math.120 (1998)] by establishing an almost monotonicity estimate for pairs of continuous functions satisfying u± ≥ 0 Lu± ≥ -1, u+ · u_ = 0 ;in an infinite strip (global version) or a finite parabolic cylinder (localized version), where L is a uniformly parabolic operator Lu = LA,b,cu := div(A(x, s)∇u) + b(x,s) · ∇u + c(x,s)u - δsu with double Dini continuous A and uniformly bounded b and c. We also prove the elliptic counterpart of this estimate.This closes the gap between the known conditions in the literature (both in the elliptic and parabolic case) imposed on u± in order to obtain an almost monotonicity estimate.At the end of the paper, we demonstrate how to use this new almost monotonicity formula to prove the optimal C1,1-regularity in a fairly general class of quasi-linear obstacle-type free boundary problems. © 2010 Wiley Periodicals, Inc.
International Nuclear Information System (INIS)
Kimberly, David A.; Salice, Christopher J.
2015-01-01
Generally, ecotoxicologists rely on short-term tests that assume populations to be static. Conversely, natural populations may be exposed to the same stressors for many generations, which can alter tolerance to the same (or other) stressors. The objective of this study was to improve our understanding of how multigenerational stressors alter life history traits and stressor tolerance. After continuously exposing Daphnia magna to cadmium for 120 days, we assessed life history traits and conducted a challenge at higher temperature and cadmium concentrations. Predictably, individuals exposed to cadmium showed an overall decrease in reproductive output compared to controls. Interestingly, control D. magna were the most cadmium tolerant to novel cadmium, followed by those exposed to high cadmium. Our data suggest that long-term exposure to cadmium alter tolerance traits in a non-monotonic way. Because we observed effects after one-generation removal from cadmium, transgenerational effects may be possible as a result of multigenerational exposure. - Highlights: • Daphnia magna exposed to cadmium for 120 days. • D. magna exposed to cadmium had decreased reproductive output. • Control D. magna were most cadmium tolerant to novel cadmium stress. • Long-term exposure to cadmium alter tolerance traits in a non-monotonic way. • Transgenerational effects observed as a result of multigenerational exposure. - Adverse effects of long-term cadmium exposure persist into cadmium free conditions, as seen by non-monotonic responses when exposed to novel stress one generation removed.
Corbetta, Matteo; Sbarufatti, Claudio; Giglio, Marco; Todd, Michael D.
2018-05-01
The present work critically analyzes the probabilistic definition of dynamic state-space models subject to Bayesian filters used for monitoring and predicting monotonic degradation processes. The study focuses on the selection of the random process, often called process noise, which is a key perturbation source in the evolution equation of particle filtering. Despite the large number of applications of particle filtering predicting structural degradation, the adequacy of the picked process noise has not been investigated. This paper reviews existing process noise models that are typically embedded in particle filters dedicated to monitoring and predicting structural damage caused by fatigue, which is monotonic in nature. The analysis emphasizes that existing formulations of the process noise can jeopardize the performance of the filter in terms of state estimation and remaining life prediction (i.e., damage prognosis). This paper subsequently proposes an optimal and unbiased process noise model and a list of requirements that the stochastic model must satisfy to guarantee high prognostic performance. These requirements are useful for future and further implementations of particle filtering for monotonic system dynamics. The validity of the new process noise formulation is assessed against experimental fatigue crack growth data from a full-scale aeronautical structure using dedicated performance metrics.
High Performance Parallel Multigrid Algorithms for Unstructured Grids
Frederickson, Paul O.
1996-01-01
We describe a high performance parallel multigrid algorithm for a rather general class of unstructured grid problems in two and three dimensions. The algorithm PUMG, for parallel unstructured multigrid, is related in structure to the parallel multigrid algorithm PSMG introduced by McBryan and Frederickson, for they both obtain a higher convergence rate through the use of multiple coarse grids. Another reason for the high convergence rate of PUMG is its smoother, an approximate inverse developed by Baumgardner and Frederickson.
Convergence accommodation to convergence CA/C ratio: convergence versus divergence.
Simmons, Joshua M; Firth, Alison Y
2014-09-01
To determine whether the convergence accommodation to convergence (CA/C) ratio during divergence with base-in (BI) prisms is of a similar or different magnitude to that measured during convergence with base-out (BO) prisms. Eighteen participants with normal binocular single vision were recruited. The participants viewed a pseudo-Gaussian target, which consisted of a light emitting diode (LED) behind a diffusing screen at 40 cm. After 5 minutes of dark adaptation, the refractive status of the eye was measured without any prism using a Shin-Nippon SRW-5000 autorefractor. The participant held the selected prism (5Δ or 10Δ BO or BI, counterbalanced) in front of their right eye and obtained a single, fused image of the target while refractive measures were taken with each. A 30-second rest period was given between measurements. The mean age of the participants was 20.6±3.22 years. The mean CA/C ratios for the 5Δ BO, 10Δ BO, 5Δ BI, and 10Δ BI were 0.108 (±0.074) D/Δ, 0.110 (±0.056) D/Δ, 0.100 (±0.090) D/Δ, and 0.089 (±0.055) D/Δ, respectively. A 2-factor repeated measures ANOVA found that the CA/C ratio did not significantly change with differing levels of prism-induced convergence and divergence (p=0.649). Change in accommodation induced by manipulating vergence is similar whether convergence or divergence are induced. The CA/C ratio did not show any change with differing levels of prism-induced convergence and divergence.
Design of convergent switched systems
Berg, van den R.A.; Pogromsky, A.Y.; Leonov, G.A.; Rooda, J.E.; Pettersen, K.Y.; Gravdahl, J.T.; Nijmeijer, H.
2006-01-01
In this paper we deal with the problem of rendering hybrid/nonlinear systems into convergent closed-loop systems by means of a feedback law or switching rules. We illustrate our approach to this problem by means of two examples: the anti-windup design for a marginally stable system with input
Convergence Patterns in Latin America
DEFF Research Database (Denmark)
Quiroga, Paola Andrea Barrientos
characteristics, and external shocks in the region. I study three important phases, following Thorp (1998): from 1900 to 1930, the exporting phase, from 1931 to 1974, the industrialization phase, and from 1975 to 2007, the globalization phase. During the last two phases, I find strong evidence of convergence...
Convergence of a Catalan Series
Koshy, Thomas; Gao, Zhenguang
2012-01-01
This article studies the convergence of the infinite series of the reciprocals of the Catalan numbers. We extract the sum of the series as well as some related ones, illustrating the power of the calculus in the study of the Catalan numbers.
Digital Convergence and Content Regulation
Starks, Michael John
2014-01-01
abstractBroadcasting, Press and Internet journalism systems of distribution are converging: the same infrastructure can deliver all three historically separate services. Reception devices mirror this: the Connected TV, the tablet and the smart phone overlap in their functionality. Service overlaps
Convergence and migration among provinces.
Helliwell, J F
1996-04-01
"Have regional disparities in Canada changed over the past thirty years? This paper assesses the robustness of earlier findings of convergence in the levels and growth rates of provincial per capita GDP, and then estimates the extent to which interprovincial and international migration is being influenced by regional differences in incomes and employment." excerpt
Revisiting convergence: A research note.
Clark, Rob
2015-09-01
A number of recent studies show that income inequality is declining between countries. In this research note, I question the significance of this trend by examining the role of initial conditions in producing convergence. An important (but neglected) property of inequality dynamics is the tendency for extreme distributions to become more moderate. When income disparities are large, the subsequent trend is biased toward convergence. Conversely, when initial conditions approach parity, divergence becomes the more likely long-term outcome. I apply this principle to trends in GDP PC across 127 countries during the 1980-2010 period. Using counterfactual analysis, I manipulate the initial level of inequality in GDP PC while holding constant each country's observed growth rate during the sample period. I find that the growth dynamics of GDP PC produce either convergence or divergence based simply on the initial distribution of income. The point of transition occurs at a moderate level of inequality, whether using population weights (Gini=.365) or not (Gini=.377). I conclude that the recent convergence observed in GDP PC is primarily a function of large income gaps between countries and would not have materialized at more moderate levels of initial inequality. By contrast, an examination of the pre-1950 period reveals divergent growth patterns that are not sensitive to initial conditions. Copyright © 2015 Elsevier Inc. All rights reserved.
Industrial Evolution Through Complementary Convergence
DEFF Research Database (Denmark)
Frøslev Christensen, Jens
2011-01-01
The article addresses the dynamics through which product markets become derailed from early product life cycle (PLC)-tracks and engaged in complementary convergence with other product markets or industries. We compare and contrast the theories that can explain, respectively, the PLC...
Privatization, convergence, and institutional autonomy
Rooijen, van M.
2011-01-01
Some of the trends incoming for 2011 – greater institutional autonomy, public/private convergence, entrepreneurial management, civic engagement – suggest innovation for hard times, with socio-economic and political rationales increasingly driving borderless developments. Others – open learning and
Converging Information and Communication Systems
DEFF Research Database (Denmark)
Øst, Alexander
2003-01-01
in the future to have - significant importance to the process and consequences of the convergence. The project focuses on the appliances, i.e. the TV sets, the computers and their peripheral equipment. It also takes into account the infrastructure and signals, which contain and deliver the information...
Evolution and convergence in telecommunications
Energy Technology Data Exchange (ETDEWEB)
Radicella, S; Grilli, D [Abdus Salam ICTP, Trieste (Italy)
2002-12-15
These lectures throw a spotlight on different aspects of the evolution of telecommunications networks, namely on the various facets of service and network convergence. The last years progress in data and telecommunications technologies, such as P-based networks, and the enormous potential of mobile communication systems and users' demands for comprehensive and network-independent have led to a convergence of data and telecommunications infrastructures in many aspects. In order to help the reader to an easier understanding of the phenomenon convergence, in the first two parts of this volume the evolution of the basic technologies is described one by one. This is done briefly and is focused on the principle topics, just to build a basis for the third part devoted to problems of convergence in telecommunications. These notes are addressed to those readers, who in a quick overview want to be informed on the future service and network landscape. The notes are equally suited for professionals with the desire to extend their horizon as well as for students looking for an introduction into telecommunications under more general aspects. The authors clearly understand the difficulties in writing a book devoted to the evolution in telecommunications. Today, telecom landscape varies at very high speed. Every few months new network technologies, new products and new services are developed. Attempts to present them in time can be accessible only for magazine publications or contributions to conferences. Therefore, in a number of areas, such as Voice over IP and new switching technologies not much more than the starting point of new paradigms is described. However, the content is up-to-date to a degree, that the phenomenon convergence can be fully understood. Partially, these notes are based on a number of lecture courses that were delivered during recent ICTP winter schools devoted to multimedia and digital communications.
Evolution and convergence in telecommunications
International Nuclear Information System (INIS)
Radicella, S.; Grilli, D.
2002-01-01
These lectures throw a spotlight on different aspects of the evolution of telecommunications networks, namely on the various facets of service and network convergence. The last years progress in data and telecommunications technologies, such as P-based networks, and the enormous potential of mobile communication systems and users' demands for comprehensive and network-independent have led to a convergence of data and telecommunications infrastructures in many aspects. In order to help the reader to an easier understanding of the phenomenon convergence, in the first two parts of this volume the evolution of the basic technologies is described one by one. This is done briefly and is focused on the principle topics, just to build a basis for the third part devoted to problems of convergence in telecommunications. These notes are addressed to those readers, who in a quick overview want to be informed on the future service and network landscape. The notes are equally suited for professionals with the desire to extend their horizon as well as for students looking for an introduction into telecommunications under more general aspects. The authors clearly understand the difficulties in writing a book devoted to the evolution in telecommunications. Today, telecom landscape varies at very high speed. Every few months new network technologies, new products and new services are developed. Attempts to present them in time can be accessible only for magazine publications or contributions to conferences. Therefore, in a number of areas, such as Voice over IP and new switching technologies not much more than the starting point of new paradigms is described. However, the content is up-to-date to a degree, that the phenomenon convergence can be fully understood. Partially, these notes are based on a number of lecture courses that were delivered during recent ICTP winter schools devoted to multimedia and digital communications
Cannon, Alex
2017-04-01
Estimating historical trends in short-duration rainfall extremes at regional and local scales is challenging due to low signal-to-noise ratios and the limited availability of homogenized observational data. In addition to being of scientific interest, trends in rainfall extremes are of practical importance, as their presence calls into question the stationarity assumptions that underpin traditional engineering and infrastructure design practice. Even with these fundamental challenges, increasingly complex questions are being asked about time series of extremes. For instance, users may not only want to know whether or not rainfall extremes have changed over time, they may also want information on the modulation of trends by large-scale climate modes or on the nonstationarity of trends (e.g., identifying hiatus periods or periods of accelerating positive trends). Efforts have thus been devoted to the development and application of more robust and powerful statistical estimators for regional and local scale trends. While a standard nonparametric method like the regional Mann-Kendall test, which tests for the presence of monotonic trends (i.e., strictly non-decreasing or non-increasing changes), makes fewer assumptions than parametric methods and pools information from stations within a region, it is not designed to visualize detected trends, include information from covariates, or answer questions about the rate of change in trends. As a remedy, monotone quantile regression (MQR) has been developed as a nonparametric alternative that can be used to estimate a common monotonic trend in extremes at multiple stations. Quantile regression makes efficient use of data by directly estimating conditional quantiles based on information from all rainfall data in a region, i.e., without having to precompute the sample quantiles. The MQR method is also flexible and can be used to visualize and analyze the nonlinearity of the detected trend. However, it is fundamentally a
Scaling laws for dislocation microstructures in monotonic and cyclic deformation of fcc metals
International Nuclear Information System (INIS)
Kubin, L.P.; Sauzay, M.
2011-01-01
This work reviews and critically discusses the current understanding of two scaling laws, which are ubiquitous in the modeling of monotonic plastic deformation in face-centered cubic metals. A compilation of the available data allows extending the domain of application of these scaling laws to cyclic deformation. The strengthening relation tells that the flow stress is proportional to the square root of the average dislocation density, whereas the similitude relation assumes that the flow stress is inversely proportional to the characteristic wavelength of dislocation patterns. The strengthening relation arises from short-range reactions of non-coplanar segments and applies all through the first three stages of the monotonic stress vs. strain curves. The value of the proportionality coefficient is calculated and simulated in good agreement with the bulk of experimental measurements published since the beginning of the 1960's. The physical origin of what is called similitude is not understood and the related coefficient is not predictable. Its value is determined from a review of the experimental literature. The generalization of these scaling laws to cyclic deformation is carried out on the base of a large collection of experimental results on single and polycrystals of various materials and on different microstructures. Surprisingly, for persistent slip bands (PSBs), both the strengthening and similitude coefficients appear to be more than two times smaller than the corresponding monotonic values, whereas their ratio is the same as in monotonic deformation. The similitude relation is also checked in cell structures and in labyrinth structures. Under low cyclic stresses, the strengthening coefficient is found even lower than in PSBs. A tentative explanation is proposed for the differences observed between cyclic and monotonic deformation. Finally, the influence of cross-slip on the temperature dependence of the saturation stress of PSBs is discussed in some detail
Some nonlinear space decomposition algorithms
Energy Technology Data Exchange (ETDEWEB)
Tai, Xue-Cheng; Espedal, M. [Univ. of Bergen (Norway)
1996-12-31
Convergence of a space decomposition method is proved for a general convex programming problem. The space decomposition refers to methods that decompose a space into sums of subspaces, which could be a domain decomposition or a multigrid method for partial differential equations. Two algorithms are proposed. Both can be used for linear as well as nonlinear elliptic problems and they reduce to the standard additive and multiplicative Schwarz methods for linear elliptic problems. Two {open_quotes}hybrid{close_quotes} algorithms are also presented. They converge faster than the additive one and have better parallelism than the multiplicative method. Numerical tests with a two level domain decomposition for linear, nonlinear and interface elliptic problems are presented for the proposed algorithms.
Masuyama, Hiroyuki
2015-01-01
This paper studies the last-column-block-augmented northwest-corner truncation (LC-block-augmented truncation, for short) of discrete-time block-monotone Markov chains under subgeometric drift conditions. The main result of this paper is to present an upper bound for the total variation distance between the stationary probability vectors of a block-monotone Markov chain and its LC-block-augmented truncation. The main result is extended to Markov chains that themselves may not be block monoton...
Principal component analysis networks and algorithms
Kong, Xiangyu; Duan, Zhansheng
2017-01-01
This book not only provides a comprehensive introduction to neural-based PCA methods in control science, but also presents many novel PCA algorithms and their extensions and generalizations, e.g., dual purpose, coupled PCA, GED, neural based SVD algorithms, etc. It also discusses in detail various analysis methods for the convergence, stabilizing, self-stabilizing property of algorithms, and introduces the deterministic discrete-time systems method to analyze the convergence of PCA/MCA algorithms. Readers should be familiar with numerical analysis and the fundamentals of statistics, such as the basics of least squares and stochastic algorithms. Although it focuses on neural networks, the book only presents their learning law, which is simply an iterative algorithm. Therefore, no a priori knowledge of neural networks is required. This book will be of interest and serve as a reference source to researchers and students in applied mathematics, statistics, engineering, and other related fields.
International Nuclear Information System (INIS)
Glashow, S.L.
1976-01-01
These are scattered remarks concerning what is happening to (not in) elementary particle physics. New developments are unfolding with unprecedented speed, so that one does not even attempt to give a comprehensive review at this time. Mostly charm is discussed, both its phenomenology and its impact on belief in quarks, chromodynamics, and unified theories. Beneath the newsworthy experimental discoveries of the last two years lies a quieter and more profound theoretical development: the emergence of a theory of particle physics
Quantifying convergence in the sciences
Directory of Open Access Journals (Sweden)
Sara Lumbreras
2016-02-01
Full Text Available Traditional epistemological models classify knowledge into separate disciplines with different objects of study and specific techniques, with some frameworks even proposing hierarchies (such as Comte’s. According to thinkers such as John Holland or Teilhard de Chardin, the advancement of science involves the convergence of disciplines. This proposed convergence can be studied in a number of ways, such as how works impact research outside a specific area (citation networks or how authors collaborate with other researchers in different fields (collaboration networks. While these studies are delivering significant new insights, they cannot easily show the convergence of different topics within a body of knowledge. This paper attempts to address this question in a quantitative manner, searching for evidence that supports the idea of convergence in the content of the sciences themselves (that is, whether the sciences are dealing with increasingly the same topics. We use Latent Dirichlet Analysis (LDA, a technique that is able to analyze texts and estimate the relative contributions of the topics that were used to generate them. We apply this tool to the corpus of the Santa Fe Institute (SFI working papers, which spans research on Complexity Science from 1989 to 2015. We then analyze the relatedness of the different research areas, the rise and demise of these sub-disciplines over time and, more broadly, the convergence of the research body as a whole. Combining the topic structure obtained from the collected publication history of the SFI community with techniques to infer hierarchy and clustering, we reconstruct a picture of a dynamic community which experiences trends, periodically recurring topics, and shifts in the closeness of scholarship over time. We find that there is support for convergence, and that the application of quantitative methods such as LDA to the study of knowledge can provide valuable insights that can help
Analysis of Known Linear Distributed Average Consensus Algorithms on Cycles and Paths
Directory of Open Access Journals (Sweden)
Jesús Gutiérrez-Gutiérrez
2018-03-01
Full Text Available In this paper, we compare six known linear distributed average consensus algorithms on a sensor network in terms of convergence time (and therefore, in terms of the number of transmissions required. The selected network topologies for the analysis (comparison are the cycle and the path. Specifically, in the present paper, we compute closed-form expressions for the convergence time of four known deterministic algorithms and closed-form bounds for the convergence time of two known randomized algorithms on cycles and paths. Moreover, we also compute a closed-form expression for the convergence time of the fastest deterministic algorithm considered on grids.
De Götzen , Amalia; Mion , Luca; Tache , Olivier
2007-01-01
International audience; We call sound algorithms the categories of algorithms that deal with digital sound signal. Sound algorithms appeared in the very infancy of computer. Sound algorithms present strong specificities that are the consequence of two dual considerations: the properties of the digital sound signal itself and its uses, and the properties of auditory perception.
Wang, Lui; Bayer, Steven E.
1991-01-01
Genetic algorithms are mathematical, highly parallel, adaptive search procedures (i.e., problem solving methods) based loosely on the processes of natural genetics and Darwinian survival of the fittest. Basic genetic algorithms concepts are introduced, genetic algorithm applications are introduced, and results are presented from a project to develop a software tool that will enable the widespread use of genetic algorithm technology.
Dynamic training algorithm for dynamic neural networks
International Nuclear Information System (INIS)
Tan, Y.; Van Cauwenberghe, A.; Liu, Z.
1996-01-01
The widely used backpropagation algorithm for training neural networks based on the gradient descent has a significant drawback of slow convergence. A Gauss-Newton method based recursive least squares (RLS) type algorithm with dynamic error backpropagation is presented to speed-up the learning procedure of neural networks with local recurrent terms. Finally, simulation examples concerning the applications of the RLS type algorithm to identification of nonlinear processes using a local recurrent neural network are also included in this paper
Economic convergence and climate policy
International Nuclear Information System (INIS)
Ciscar, J.C.; Soria, A.
2000-01-01
This paper addresses the relevance of the economic convergence hypotheses between the developing and the developed world in international greenhouse gas (GHG) emissions negotiations. The results are based on a two-region (the OECD and the rest of the world, ROW) neo-classical growth model with exogenous technical progress, different technological diffusion patterns, and a set of geophysical relationships that consider an environmental externality linked to GHG emissions. A game framework is taken into account in the model to capture the strategic interactions between agents. The outcome of the negotiations seems indeed to depend on the economic convergence hypotheses. Faster economic growth of the ROW countries would encourage them to further mitigate carbon emissions. (Author)
Voorspoels, Wouter; Navarro, Daniel J; Perfors, Amy; Ransom, Keith; Storms, Gert
2015-09-01
A robust finding in category-based induction tasks is for positive observations to raise the willingness to generalize to other categories while negative observations lower the willingness to generalize. This pattern is referred to as monotonic generalization. Across three experiments we find systematic non-monotonicity effects, in which negative observations raise the willingness to generalize. Experiments 1 and 2 show that this effect emerges in hierarchically structured domains when a negative observation from a different category is added to a positive observation. They also demonstrate that this is related to a specific kind of shift in the reasoner's hypothesis space. Experiment 3 shows that the effect depends on the assumptions that the reasoner makes about how inductive arguments are constructed. Non-monotonic reasoning occurs when people believe the facts were put together by a helpful communicator, but monotonicity is restored when they believe the observations were sampled randomly from the environment. Copyright © 2015 Elsevier Inc. All rights reserved.
Converging-barrel plasma accelerator
International Nuclear Information System (INIS)
Paine, T.O.
1971-01-01
The invention comprises a device for generating and accelerating plasma to extremely high velocity, while focusing the plasma to a decreasing cross section for attaining a very dense high-velocity plasma burst capable of causing nuclear fusion reactions. A converging coaxial accelerator-electrode configuration is employed with ''high-pressure'' gas injection in controlled amounts to achieve acceleration by deflagration and focusing by the shaped electromagnetic fields. (U.S.)
Kim, Seongho; Li, Lang
2014-02-01
The statistical identifiability of nonlinear pharmacokinetic (PK) models with the Michaelis-Menten (MM) kinetic equation is considered using a global optimization approach, which is particle swarm optimization (PSO). If a model is statistically non-identifiable, the conventional derivative-based estimation approach is often terminated earlier without converging, due to the singularity. To circumvent this difficulty, we develop a derivative-free global optimization algorithm by combining PSO with a derivative-free local optimization algorithm to improve the rate of convergence of PSO. We further propose an efficient approach to not only checking the convergence of estimation but also detecting the identifiability of nonlinear PK models. PK simulation studies demonstrate that the convergence and identifiability of the PK model can be detected efficiently through the proposed approach. The proposed approach is then applied to clinical PK data along with a two-compartmental model. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
Natural gas and electricity convergence
International Nuclear Information System (INIS)
Calger, C.
1998-01-01
Convergence between the gas and electricity industries was described as a means for creating an increasingly more efficient energy market where prices and fundamental relationships exist between gas and electricity. Convergence creates new opportunities for producers and consumers. Convergence will likely lead to the disaggregation of the electricity and gas industry into segments such as: (1) power generation and production, (2) transmission wires and pipelines, (3) wholesale merchants, (4) distribution wires and pipelines, and (5) retail marketing, services and administration. The de-integration of integrated utilities has already begun in the U.S. energy markets and retail open access is accelerating. This retail competition will create very demanding customers and the changing risk profile will create new issues for stakeholders. The pace of reform for the telecommunications, airlines, natural gas and electricity industries was graphically illustrated to serve as an example of what to expect. The different paths that the industry might take to deregulation (aggressively embrace reform, or defensively blocking it), and the likely consequences of each reaction were also described. A map indicating where U.S. electric and natural gas utility merger and acquisition activities have taken place between 1994-1997, was included. Another map showing the physical asset positions of the Enron grid, one of the largest independent oil and gas companies in the U.S., with increasing international operations, including an electric power transmission and distribution arm, was also provided as an illustration of a fully integrated energy market company of the future. 9 figs
Lv Yu-Pei; Sun Tian-Chuan; Chu Yu-Ming
2011-01-01
Abstract We prove that the function F α,β (x) = x α Γ β (x)/Γ(βx) is strictly logarithmically completely monotonic on (0, ∞) if and only if (α, β) ∈ {(α, β) : β > 0, β ≥ 2α + 1, β ≥ α + 1}{(α, β) : α = 0, β = 1} and that [F α,β (x)]-1 is strictly logarithmically completely monotonic on (0, ∞) if and only if (α, β) ∈ {(α, β ...
A theoretical analysis of the median LMF adaptive algorithm
DEFF Research Database (Denmark)
Bysted, Tommy Kristensen; Rusu, C.
1999-01-01
Higher order adaptive algorithms are sensitive to impulse interference. In the case of the LMF (Least Mean Fourth), an easy and effective way to reduce this is to median filter the instantaneous gradient of the LMF algorithm. Although previous published simulations have indicated that this reduces...... the speed of convergence, no analytical studies have yet been made to prove this. In order to enhance the usability, this paper presents a convergence and steady-state analysis of the median LMF adaptive algorithm. As expected this proves that the median LMF has a slower convergence and a lower steady...
a globally convergent hyperpl onvergent hyperplane
African Journals Online (AJOL)
userpc
Bayero Journal of Pure and App. ISSN 2006 – 6996 ... Globally Convergent Hyper plane-BFGS method for solving nonline. The attractive ... Numerical performance on some b rates there liability ..... convergence of a class of quasi methods on ...
Density by Moduli and Lacunary Statistical Convergence
Directory of Open Access Journals (Sweden)
Vinod K. Bhardwaj
2016-01-01
Full Text Available We have introduced and studied a new concept of f-lacunary statistical convergence, where f is an unbounded modulus. It is shown that, under certain conditions on a modulus f, the concepts of lacunary strong convergence with respect to a modulus f and f-lacunary statistical convergence are equivalent on bounded sequences. We further characterize those θ for which Sθf=Sf, where Sθf and Sf denote the sets of all f-lacunary statistically convergent sequences and f-statistically convergent sequences, respectively. A general description of inclusion between two arbitrary lacunary methods of f-statistical convergence is given. Finally, we give an Sθf-analog of the Cauchy criterion for convergence and a Tauberian theorem for Sθf-convergence is also proved.
Stable convergence and stable limit theorems
Häusler, Erich
2015-01-01
The authors present a concise but complete exposition of the mathematical theory of stable convergence and give various applications in different areas of probability theory and mathematical statistics to illustrate the usefulness of this concept. Stable convergence holds in many limit theorems of probability theory and statistics – such as the classical central limit theorem – which are usually formulated in terms of convergence in distribution. Originated by Alfred Rényi, the notion of stable convergence is stronger than the classical weak convergence of probability measures. A variety of methods is described which can be used to establish this stronger stable convergence in many limit theorems which were originally formulated only in terms of weak convergence. Naturally, these stronger limit theorems have new and stronger consequences which should not be missed by neglecting the notion of stable convergence. The presentation will be accessible to researchers and advanced students at the master's level...
Some completely monotonic properties for the $(p,q )$-gamma function
Krasniqi, Valmir; Merovci, Faton
2014-01-01
It is defined $\\Gamma_{p,q}$ function, a generalize of $\\Gamma$ function. Also, we defined $\\psi_{p,q}$-analogue of the psi function as the log derivative of $\\Gamma_{p,q}$. For the $\\Gamma_{p,q}$ -function, are given some properties related to convexity, log-convexity and completely monotonic function. Also, some properties of $\\psi_{p,q} $ analog of the $\\psi$ function have been established. As an application, when $p\\to \\infty, q\\to 1,$ we obtain all result of \\cite{Valmir1} and \\cite{SHA}.
Renormalization in charged colloids: non-monotonic behaviour with the surface charge
International Nuclear Information System (INIS)
Haro-Perez, C; Quesada-Perez, M; Callejas-Fernandez, J; Schurtenberger, P; Hidalgo-Alvarez, R
2006-01-01
The static structure factor S(q) is measured for a set of deionized latex dispersions with different numbers of ionizable surface groups per particle and similar diameters. For a given volume fraction, the height of the main peak of S(q), which is a direct measure of the spatial ordering of latex particles, does not increase monotonically with the number of ionizable groups. This behaviour cannot be described using the classical renormalization scheme based on the cell model. We analyse our experimental data using a renormalization model based on the jellium approximation, which predicts the weakening of the spatial order for moderate and large particle charges. (letter to the editor)
Monotonicity Conditions for Multirate and Partitioned Explicit Runge-Kutta Schemes
Hundsdorfer, Willem
2013-01-01
Multirate schemes for conservation laws or convection-dominated problems seem to come in two flavors: schemes that are locally inconsistent, and schemes that lack mass-conservation. In this paper these two defects are discussed for one-dimensional conservation laws. Particular attention will be given to monotonicity properties of the multirate schemes, such as maximum principles and the total variation diminishing (TVD) property. The study of these properties will be done within the framework of partitioned Runge-Kutta methods. It will also be seen that the incompatibility of consistency and mass-conservation holds for ‘genuine’ multirate schemes, but not for general partitioned methods.
Uniform persistence and upper Lyapunov exponents for monotone skew-product semiflows
International Nuclear Information System (INIS)
Novo, Sylvia; Obaya, Rafael; Sanz, Ana M
2013-01-01
Several results of uniform persistence above and below a minimal set of an abstract monotone skew-product semiflow are obtained. When the minimal set has a continuous separation the results are given in terms of the principal spectrum. In the case that the semiflow is generated by the solutions of a family of non-autonomous differential equations of ordinary, delay or parabolic type, the former results are strongly improved. A method of calculus of the upper Lyapunov exponent of the minimal set is also determined. (paper)
Oscillation of Nonlinear Delay Differential Equation with Non-Monotone Arguments
Directory of Open Access Journals (Sweden)
Özkan Öcalan
2017-07-01
Full Text Available Consider the first-order nonlinear retarded differential equation $$ x^{\\prime }(t+p(tf\\left( x\\left( \\tau (t\\right \\right =0, t\\geq t_{0} $$ where $p(t$ and $\\tau (t$ are function of positive real numbers such that $%\\tau (t\\leq t$ for$\\ t\\geq t_{0},\\ $and$\\ \\lim_{t\\rightarrow \\infty }\\tau(t=\\infty $. Under the assumption that the retarded argument is non-monotone, new oscillation results are given. An example illustrating the result is also given.
Application of non-monotonic logic to failure diagnosis of nuclear power plant
International Nuclear Information System (INIS)
Takahashi, M.; Kitamura, M.; Sugiyama, K.
1989-01-01
A prototype diagnosis system for nuclear power plants was developed based on Truth Maintenance systems: TMS and Dempster-Shafer probability theory. The purpose of this paper is to establish basic technique for more intelligent, man-computer cooperative diagnosis system. The developed system is capable of carrying out the diagnostic inference under the imperfect observation condition with the help of the proposed belief revision procedure with TMS and the systematic uncertainty treatment with Dempster-Shafer theory. The usefulness and potentiality of the present non-monotonic logic were demonstrated through simulation experiments
Effect of meal glycemic load and caffeine consumption on prolonged monotonous driving performance.
Bragg, Christopher; Desbrow, Ben; Hall, Susan; Irwin, Christopher
2017-11-01
Monotonous driving involves low levels of stimulation and high levels of repetition and is essentially an exercise in sustained attention and vigilance. The aim of this study was to determine the effects of consuming a high or low glycemic load meal on prolonged monotonous driving performance. The effect of consuming caffeine with a high glycemic load meal was also examined. Ten healthy, non-diabetic participants (7 males, age 51±7yrs, mean±SD) completed a repeated measures investigation involving 3 experimental trials. On separate occasions, participants were provided one of three treatments prior to undertaking a 90min computer-based simulated drive. The 3 treatment conditions involved consuming: (1) a low glycemic load meal+placebo capsules (LGL), (2) a high glycemic load meal+placebo capsules (HGL) and (3) a high glycemic load meal+caffeine capsules (3mgkg -1 body weight) (CAF). Measures of driving performance included lateral (standard deviation of lane position (SDLP), average lane position (AVLP), total number of lane crossings (LC)) and longitudinal (average speed (AVSP) and standard deviation of speed (SDSP)) vehicle control parameters. Blood glucose levels, plasma caffeine concentrations and subjective ratings of sleepiness, alertness, mood, hunger and simulator sickness were also collected throughout each trial. No difference in either lateral or longitudinal vehicle control parameters or subjective ratings were observed between HGL and LGL treatments. A significant reduction in SDLP (0.36±0.20m vs 0.41±0.19m, p=0.004) and LC (34.4±31.4 vs 56.7±31.5, p=0.018) was observed in the CAF trial compared to the HGL trial. However, no differences in AVLP, AVSP and SDSP or subjective ratings were detected between these two trials (p>0.05). Altering the glycemic load of a breakfast meal had no effect on measures of monotonous driving performance in non-diabetic adults. Individuals planning to undertake a prolonged monotonous drive following consumption of a
A note on monotonically star Lindelöf spaces | Song | Quaestiones ...
African Journals Online (AJOL)
A space X is monotonically star Lindelöf if one assign to for each open cover U a subspace s(U) ⊆ X, called a kernel, such that s(U) is a Lindelöf subset of X, and st(s(U); U) = X, and if V renes U then ∪ s(U) ⊆ s(V), where st(s(U); U) = ∪ {U ∈ U : U ∩ s(U) ≠ ∅}. In this paper, we investigate the relationship between ...
Technology assessment using NBIC convergence
International Nuclear Information System (INIS)
Vaseashta, Ashok
2009-01-01
Full text: Notwithstanding progress in the areas of nanotechnology/nanoscience, biotechnology, information technology, and cognitive sciences (NBIC), the synergy arising from convergence of these disciplines offers great potential for transformational, revolutionary, and embryonic opportunities with many technological applications. In addition, advances in synthesis and characterization methods have provided the means to study, understand, control, or even manipulate the transitional characteristics between isolated atoms and bulk material. In recent years, newly developed architectures in nanostructures and nanosystems with improved functionality, and ensuing unique characteristics have been developed with applications in chemical and biological sensors, nanobiotechnology, nanophotonics, and analysis of cellular processes. Novel convergence methodologies will integrate and advance next generation solutions to current and future technical challenges. Convergence in research methodologies transform the way research is conducted by overcoming specific barriers or filling existing knowledge gaps. NBIC Convergence and associated research methodologies has exceptionally high potential for transforming the manner in which state-of-the-art information is gathered, analyzed, and leveraged to enable future advances and applications. Examples of synergy of these disciplines include: label free, highly multiplexed over broad dynamic range, and decentralized nanotechnology based sensor platform for detection of biological and chemical agents; nucleic acid layers in conjunction with nanomaterials-based electrochemical or optical transducers as DNA Biosensor; potential targets for the next generation of vaccines, therapeutics and diagnostics to enhance human performance; basis for 'Gene Ontology' to provides an important link between gene function and systems biology to understand a global picture of host-microbe interactions - to name a few. Since the idea of 'Converging
Statistical convergence on intuitionistic fuzzy normed spaces
International Nuclear Information System (INIS)
Karakus, S.; Demirci, K.; Duman, O.
2008-01-01
Saadati and Park [Saadati R, Park JH, Chaos, Solitons and Fractals 2006;27:331-44] has recently introduced the notion of intuitionistic fuzzy normed space. In this paper, we study the concept of statistical convergence on intuitionistic fuzzy normed spaces. Then we give a useful characterization for statistically convergent sequences. Furthermore, we display an example such that our method of convergence is stronger than the usual convergence on intuitionistic fuzzy normed spaces
Convergence of barycentric coordinates to barycentric kernels
Kosinka, Jiří
2016-02-12
We investigate the close correspondence between barycentric coordinates and barycentric kernels from the point of view of the limit process when finer and finer polygons converge to a smooth convex domain. We show that any barycentric kernel is the limit of a set of barycentric coordinates and prove that the convergence rate is quadratic. Our convergence analysis extends naturally to barycentric interpolants and mappings induced by barycentric coordinates and kernels. We verify our theoretical convergence results numerically on several examples.
Convergence of barycentric coordinates to barycentric kernels
Kosinka, Jiří
2016-01-01
We investigate the close correspondence between barycentric coordinates and barycentric kernels from the point of view of the limit process when finer and finer polygons converge to a smooth convex domain. We show that any barycentric kernel is the limit of a set of barycentric coordinates and prove that the convergence rate is quadratic. Our convergence analysis extends naturally to barycentric interpolants and mappings induced by barycentric coordinates and kernels. We verify our theoretical convergence results numerically on several examples.
Semantic Convergence in the Bilingual Lexicon
Ameel, Eef; Malt, Barbara C.; Storms, Gert; Van Assche, Fons
2009-01-01
Bilinguals' lexical mappings for their two languages have been found to converge toward a common naming pattern. The present paper investigates in more detail how semantic convergence is manifested in bilingual lexical knowledge. We examined how semantic convergence affects the centers and boundaries of lexical categories for common household…
"Nanoselves": NBIC and the Culture of Convergence
Venkatesan, Priya
2010-01-01
The subject of this essay is NBIC convergence (nanotechnology, biotechnology, information technology and cognitive science convergence). NBIC convergence is a recurring trope that is dominated by the paradigm of integration of the sciences. It is largely influenced by the considerations of social and economic impact, and it assumes positivism in…
Convergence analysis of neutronic/thermohydraulic coupling behavior of SCWR
International Nuclear Information System (INIS)
Liu, Shichang; Cai, Jiejin
2013-01-01
The neutronic/thermohydraulic coupling (N–T coupling) calculations play an important role in core design and stability analysis. The traditional iterative method is not applicable for some new reactors (such as supercritical water-cooled reactor) which have intense N–T coupling behavior. In this paper, the mathematical model of N–T coupling based on fixed point theory is established firstly, with the convergent criterion, which can show the real-time convergence situation of iteration. Secondly, the self-adaptive relaxation factor and corresponding algorithm are proposed. Thirdly, the convergence analysis of the method of self-adaptive relaxation factor and common relaxation iteration has been performed, based on three calculation examples of SCWR fuel assembly. The results show that the proposed algorithm can efficiently reduce the calculation time and be adapted to different coupling cases and different initial distribution. It is easy to program, providing convenience for reactor design and analysis. This research also provides the theoretical basis for further study of N–T coupling behavior of new reactors such as SCWR
Joux, Antoine
2009-01-01
Illustrating the power of algorithms, Algorithmic Cryptanalysis describes algorithmic methods with cryptographically relevant examples. Focusing on both private- and public-key cryptographic algorithms, it presents each algorithm either as a textual description, in pseudo-code, or in a C code program.Divided into three parts, the book begins with a short introduction to cryptography and a background chapter on elementary number theory and algebra. It then moves on to algorithms, with each chapter in this section dedicated to a single topic and often illustrated with simple cryptographic applic
Semiparametric approach for non-monotone missing covariates in a parametric regression model
Sinha, Samiran
2014-02-26
Missing covariate data often arise in biomedical studies, and analysis of such data that ignores subjects with incomplete information may lead to inefficient and possibly biased estimates. A great deal of attention has been paid to handling a single missing covariate or a monotone pattern of missing data when the missingness mechanism is missing at random. In this article, we propose a semiparametric method for handling non-monotone patterns of missing data. The proposed method relies on the assumption that the missingness mechanism of a variable does not depend on the missing variable itself but may depend on the other missing variables. This mechanism is somewhat less general than the completely non-ignorable mechanism but is sometimes more flexible than the missing at random mechanism where the missingness mechansim is allowed to depend only on the completely observed variables. The proposed approach is robust to misspecification of the distribution of the missing covariates, and the proposed mechanism helps to nullify (or reduce) the problems due to non-identifiability that result from the non-ignorable missingness mechanism. The asymptotic properties of the proposed estimator are derived. Finite sample performance is assessed through simulation studies. Finally, for the purpose of illustration we analyze an endometrial cancer dataset and a hip fracture dataset.
Mejias, Jorge F; Payeur, Alexandre; Selin, Erik; Maler, Leonard; Longtin, André
2014-01-01
The control of input-to-output mappings, or gain control, is one of the main strategies used by neural networks for the processing and gating of information. Using a spiking neural network model, we studied the gain control induced by a form of inhibitory feedforward circuitry-also known as "open-loop feedback"-, which has been experimentally observed in a cerebellum-like structure in weakly electric fish. We found, both analytically and numerically, that this network displays three different regimes of gain control: subtractive, divisive, and non-monotonic. Subtractive gain control was obtained when noise is very low in the network. Also, it was possible to change from divisive to non-monotonic gain control by simply modulating the strength of the feedforward inhibition, which may be achieved via long-term synaptic plasticity. The particular case of divisive gain control has been previously observed in vivo in weakly electric fish. These gain control regimes were robust to the presence of temporal delays in the inhibitory feedforward pathway, which were found to linearize the input-to-output mappings (or f-I curves) via a novel variability-increasing mechanism. Our findings highlight the feedforward-induced gain control analyzed here as a highly versatile mechanism of information gating in the brain.
Directory of Open Access Journals (Sweden)
Jorge F Mejias
2014-02-01
Full Text Available The control of input-to-output mappings, or gain control, is one of the main strategies used by neural networks for the processing and gating of information. Using a spiking neural network model, we studied the gain control induced by a form of inhibitory feedforward circuitry — also known as ’open-loop feedback’ —, which has been experimentally observed in a cerebellum-like structure in weakly electric fish. We found, both analytically and numerically, that this network displays three different regimes of gain control: subtractive, divisive, and non-monotonic. Subtractive gain control was obtained when noise is very low in the network. Also, it was possible to change from divisive to non-monotonic gain control by simply modulating the strength of the feedforward inhibition, which may be achieved via long-term synaptic plasticity. The particular case of divisive gain control has been previously observed in vivo in weakly electric fish. These gain control regimes were robust to the presence of temporal delays in the inhibitory feedforward pathway, which were found to linearize the input-to-output mappings (or f-I curves via a novel variability-increasing mechanism. Our findings highlight the feedforward-induced gain control analyzed here as a highly versatile mechanism of information gating in the brain.
Non-monotonic wetting behavior of chitosan films induced by silver nanoparticles
Energy Technology Data Exchange (ETDEWEB)
Praxedes, A.P.P.; Webler, G.D.; Souza, S.T. [Instituto de Física, Universidade Federal de Alagoas, 57072-970 Maceió, AL (Brazil); Ribeiro, A.S. [Instituto de Química e Biotecnologia, Universidade Federal de Alagoas, 57072-970 Maceió, AL (Brazil); Fonseca, E.J.S. [Instituto de Física, Universidade Federal de Alagoas, 57072-970 Maceió, AL (Brazil); Oliveira, I.N. de, E-mail: italo@fis.ufal.br [Instituto de Física, Universidade Federal de Alagoas, 57072-970 Maceió, AL (Brazil)
2016-05-01
Highlights: • The addition of silver nanoparticles modifies the morphology of chitosan films. • Metallic nanoparticles can be used to control wetting properties of chitosan films. • The contact angle shows a non-monotonic dependence on the silver concentration. - Abstract: The present work is devoted to the study of structural and wetting properties of chitosan-based films containing silver nanoparticles. In particular, the effects of silver concentration on the morphology of chitosan films are characterized by different techniques, such as atomic force microscopy (AFM), X-ray diffraction (XRD) and Fourier transform infrared spectroscopy (FTIR). By means of dynamic contact angle measurements, we study the modification on surface properties of chitosan-based films due to the addition of silver nanoparticles. The results are analyzed in the light of molecular-kinetic theory which describes the wetting phenomena in terms of statistical dynamics for the displacement of liquid molecules in a solid substrate. Our results show that the wetting properties of chitosan-based films are high sensitive to the fraction of silver nanoparticles, with the equilibrium contact angle exhibiting a non-monotonic behavior.
Psychophysiological responses to short-term cooling during a simulated monotonous driving task.
Schmidt, Elisabeth; Decke, Ralf; Rasshofer, Ralph; Bullinger, Angelika C
2017-07-01
For drivers on monotonous routes, cognitive fatigue causes discomfort and poses an important risk for traffic safety. Countermeasures against this type of fatigue are required and thermal stimulation is one intervention method. Surprisingly, there are hardly studies available to measure the effect of cooling while driving. Hence, to better understand the effect of short-term cooling on the perceived sleepiness of car drivers, a driving simulator study (n = 34) was conducted in which physiological and vehicular data during cooling and control conditions were compared. The evaluation of the study showed that cooling applied during a monotonous drive increased the alertness of the car driver. The sleepiness rankings were significantly lower for the cooling condition. Furthermore, the significant pupillary and electrodermal responses were physiological indicators for increased sympathetic activation. In addition, during cooling a better driving performance was observed. In conclusion, the study shows generally that cooling has a positive short-term effect on drivers' wakefulness; in detail, a cooling period of 3 min delivers best results. Copyright © 2017 Elsevier Ltd. All rights reserved.
International Nuclear Information System (INIS)
Abgrall, Remi; Mezine, Mohamed
2003-01-01
The aim of this paper is to construct upwind residual distribution schemes for the time accurate solution of hyperbolic conservation laws. To do so, we evaluate a space-time fluctuation based on a space-time approximation of the solution and develop new residual distribution schemes which are extensions of classical steady upwind residual distribution schemes. This method has been applied to the solution of scalar advection equation and to the solution of the compressible Euler equations both in two space dimensions. The first version of the scheme is shown to be, at least in its first order version, unconditionally energy stable and possibly conditionally monotonicity preserving. Using an idea of Csik et al. [Space-time residual distribution schemes for hyperbolic conservation laws, 15th AIAA Computational Fluid Dynamics Conference, Anahein, CA, USA, AIAA 2001-2617, June 2001], we modify the formulation to end up with a scheme that is unconditionally energy stable and unconditionally monotonicity preserving. Several numerical examples are shown to demonstrate the stability and accuracy of the method
Hamid, Nubailah Abd; Ibrahim, Azmi; Adnan, Azlan; Ismail, Muhammad Hussain
2018-05-01
This paper discusses the superelastic behavior of shape memory alloy, NiTi when used as reinforcement in concrete beams. The ability of NiTi to recover and reduce permanent deformations of concrete beams was investigated. Small-scale concrete beams, with NiTi reinforcement were experimentally investigated under monotonic loads. The behaviour of simply supported reinforced concrete (RC) beams hybrid with NiTi rebars and the control beam subject to monotonic loads were experimentally investigated. This paper is to highlight the ability of the SMA bars to recover and reduce permanent deformations of concrete flexural members. The size of the control beam is 125 mm × 270 mm × 1000 mm with 3 numbers of 12 mm diameter bars as main reinforcement for compression and 3 numbers of 12 mm bars as tension or hanger bars while 6 mm diameter at 100 mm c/c used as shear reinforcement bars for control beam respectively. While, the minimal provision of 200mm using the 12.7mm of superelastic Shape Memory Alloys were employed to replace the steel rebar at the critical region of the beam. In conclusion, the contribution of the SMA bar in combination with high-strength steel to the conventional reinforcement showed that the SMA beam has exhibited an improve performance in term of better crack recovery and deformation. Therefore the usage of hybrid NiTi with the steel can substantially diminish the risk of the earthquake and also can reduce the associated cost aftermath.
Touyarou, Peio; Sulmont-Rossé, Claire; Gagnaire, Aude; Issanchou, Sylvie; Brondel, Laurent
2012-04-01
This study aimed to observe the influence of the monotonous consumption of two types of fibre-enriched bread at breakfast on hedonic liking for the bread, subsequent hunger and energy intake. Two groups of unrestrained normal weight participants were given either white sandwich bread (WS) or multigrain sandwich bread (MG) at breakfast (the sensory properties of the WS were more similar to the usual bread eaten by the participants than those of the MG). In each group, two 15-day cross-over conditions were set up. During the experimental condition the usual breakfast of each participant was replaced by an isocaloric portion of plain bread (WS or MG). During the control condition, participants consumed only 10 g of the corresponding bread and completed their breakfast with other foods they wanted. The results showed that bread appreciation did not change over exposure even in the experimental condition. Hunger was lower in the experimental condition than in the control condition. The consumption of WS decreased energy intake while the consumption of MG did not in the experimental condition compared to the corresponding control one. In conclusion, a monotonous breakfast composed solely of a fibre-enriched bread may decrease subsequent hunger and, when similar to a familiar bread, food intake. Copyright Â© 2011. Published by Elsevier Ltd.
Denjoy minimal sets and Birkhoff periodic orbits for non-exact monotone twist maps
Qin, Wen-Xin; Wang, Ya-Nan
2018-06-01
A non-exact monotone twist map φbarF is a composition of an exact monotone twist map φ bar with a generating function H and a vertical translation VF with VF ((x , y)) = (x , y - F). We show in this paper that for each ω ∈ R, there exists a critical value Fd (ω) ≥ 0 depending on H and ω such that for 0 ≤ F ≤Fd (ω), the non-exact twist map φbarF has an invariant Denjoy minimal set with irrational rotation number ω lying on a Lipschitz graph, or Birkhoff (p , q)-periodic orbits for rational ω = p / q. Like the Aubry-Mather theory, we also construct heteroclinic orbits connecting Birkhoff periodic orbits, and show that quasi-periodic orbits in these Denjoy minimal sets can be approximated by periodic orbits. In particular, we demonstrate that at the critical value F =Fd (ω), the Denjoy minimal set is not uniformly hyperbolic and can be approximated by smooth curves.
The behavior of welded joint in steel pipe members under monotonic and cyclic loading
International Nuclear Information System (INIS)
Chang, Kyong-Ho; Jang, Gab-Chul; Shin, Young-Eui; Han, Jung-Guen; Kim, Jong-Min
2006-01-01
Most steel pipe members are joined by welding. The residual stress and weld metal in a welded joint have the influence on the behavior of steel pipes. Therefore, to accurately predict the behavior of steel pipes with a welded joint, the influence of welding residual stress and weld metal on the behavior of steel pipe must be investigated. In this paper, the residual stress of steel pipes with a welded joint was investigated by using a three-dimensional non-steady heat conduction analysis and a three-dimensional thermal elastic-plastic analysis. Based on the results of monotonic and cyclic loading tests, a hysteresis model for weld metal was formulated. The hysteresis model was proposed by the authors and applied to a three-dimensional finite elements analysis. To investigate the influence of a welded joint in steel pipes under monotonic and cyclic loading, three-dimensional finite elements analysis considering the proposed model and residual stress was carried out. The influence of a welded joint on the behavior of steel pipe members was investigated by comparing the analytical result both steel pipe with a welded joint and that without a welded joint
Monotonic and fatigue deformation of Ni--W directionally solidified eutectic
International Nuclear Information System (INIS)
Garmong, G.; Williams, J.C.
1975-01-01
Unlike many eutectic composites, the Ni--W eutectic exhibits extensive ductility by slip. Furthermore, its properties may be greatly varied by proper heat treatments. Results of studies of deformation in both monotonic and fatigue loading are reported. During monotonic deformation the fiber/matrix interface acts as a source of dislocations at low strains and an obstacle to matrix slip at higher strains. Deforming the quenched-plus-aged eutectic causes planar matrix slip, with the result that matrix slip bands create stress concentrations in the fibers at low strains. The aged eutectic reaches generally higher stress levels for comparable strains than does the as-quenched eutectic, and the failure strains decrease with increasing aging times. For the composites tested in fatigue, the aged eutectic has better high-stress fatigue resistance than the as-quenched material, but for low-stress, high-cycle fatigue their cycles to failure are nearly the same. However, both crack initiation and crack propagation are different in the two conditions, so the coincidence in high-cycle fatigue is probably fortuitous. The effect of matrix strength on composite performance is not simple, since changes in strength may be accompanied by alterations in slip modes and failure processes. (17 fig) (auth)
Ecomorphological convergence in planktivorous surgeonfishes
Friedman, S. T.
2016-01-26
© 2016 European Society For Evolutionary Biology. Morphological convergence plays a central role in the study of evolution. Often induced by shared ecological specialization, homoplasy hints at underlying selective pressures and adaptive constraints that deterministically shape the diversification of life. Although midwater zooplanktivory has arisen in adult surgeonfishes (family Acanthuridae) at least four independent times, it represents a clearly specialized state, requiring the capacity to swiftly swim in midwater locating and sucking small prey items. Whereas this diet has commonly been associated with specific functional adaptations in fishes, acanthurids present an interesting case study as all nonplanktivorous species feed by grazing on benthic algae and detritus, requiring a vastly different functional morphology that emphasizes biting behaviours. We examined the feeding morphology in 30 acanthurid species and, combined with a pre-existing phylogenetic tree, compared the fit of evolutionary models across two diet regimes: zooplanktivores and nonzooplanktivorous grazers. Accounting for phylogenetic relationships, the best-fitting model indicates that zooplanktivorous species are converging on a separate adaptive peak from their grazing relatives. Driving this bimodal landscape, zooplanktivorous acanthurids tend to develop a slender body, reduced facial features, smaller teeth and weakened jaw adductor muscles. However, despite these phenotypic changes, model fitting suggests that lineages have not yet reached the adaptive peak associated with plankton feeding even though some transitions appear to be over 10 million years old. These findings demonstrate that the selective demands of pelagic feeding promote repeated - albeit very gradual - ecomorphological convergence within surgeonfishes, while allowing local divergences between closely related species, contributing to the overall diversity of the clade. Journal of Evolutionary Biology
Ecomorphological convergence in planktivorous surgeonfishes.
Friedman, S T; Price, S A; Hoey, A S; Wainwright, P C
2016-05-01
Morphological convergence plays a central role in the study of evolution. Often induced by shared ecological specialization, homoplasy hints at underlying selective pressures and adaptive constraints that deterministically shape the diversification of life. Although midwater zooplanktivory has arisen in adult surgeonfishes (family Acanthuridae) at least four independent times, it represents a clearly specialized state, requiring the capacity to swiftly swim in midwater locating and sucking small prey items. Whereas this diet has commonly been associated with specific functional adaptations in fishes, acanthurids present an interesting case study as all nonplanktivorous species feed by grazing on benthic algae and detritus, requiring a vastly different functional morphology that emphasizes biting behaviours. We examined the feeding morphology in 30 acanthurid species and, combined with a pre-existing phylogenetic tree, compared the fit of evolutionary models across two diet regimes: zooplanktivores and nonzooplanktivorous grazers. Accounting for phylogenetic relationships, the best-fitting model indicates that zooplanktivorous species are converging on a separate adaptive peak from their grazing relatives. Driving this bimodal landscape, zooplanktivorous acanthurids tend to develop a slender body, reduced facial features, smaller teeth and weakened jaw adductor muscles. However, despite these phenotypic changes, model fitting suggests that lineages have not yet reached the adaptive peak associated with plankton feeding even though some transitions appear to be over 10 million years old. These findings demonstrate that the selective demands of pelagic feeding promote repeated - albeit very gradual - ecomorphological convergence within surgeonfishes, while allowing local divergences between closely related species, contributing to the overall diversity of the clade. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European
MM Algorithms for Geometric and Signomial Programming.
Lange, Kenneth; Zhou, Hua
2014-02-01
This paper derives new algorithms for signomial programming, a generalization of geometric programming. The algorithms are based on a generic principle for optimization called the MM algorithm. In this setting, one can apply the geometric-arithmetic mean inequality and a supporting hyperplane inequality to create a surrogate function with parameters separated. Thus, unconstrained signomial programming reduces to a sequence of one-dimensional minimization problems. Simple examples demonstrate that the MM algorithm derived can converge to a boundary point or to one point of a continuum of minimum points. Conditions under which the minimum point is unique or occurs in the interior of parameter space are proved for geometric programming. Convergence to an interior point occurs at a linear rate. Finally, the MM framework easily accommodates equality and inequality constraints of signomial type. For the most important special case, constrained quadratic programming, the MM algorithm involves very simple updates.
Particle swarm genetic algorithm and its application
International Nuclear Information System (INIS)
Liu Chengxiang; Yan Changxiang; Wang Jianjun; Liu Zhenhai
2012-01-01
To solve the problems of slow convergence speed and tendency to fall into the local optimum of the standard particle swarm optimization while dealing with nonlinear constraint optimization problem, a particle swarm genetic algorithm is designed. The proposed algorithm adopts feasibility principle handles constraint conditions and avoids the difficulty of penalty function method in selecting punishment factor, generates initial feasible group randomly, which accelerates particle swarm convergence speed, and introduces genetic algorithm crossover and mutation strategy to avoid particle swarm falls into the local optimum Through the optimization calculation of the typical test functions, the results show that particle swarm genetic algorithm has better optimized performance. The algorithm is applied in nuclear power plant optimization, and the optimization results are significantly. (authors)
Hougardy, Stefan
2016-01-01
Algorithms play an increasingly important role in nearly all fields of mathematics. This book allows readers to develop basic mathematical abilities, in particular those concerning the design and analysis of algorithms as well as their implementation. It presents not only fundamental algorithms like the sieve of Eratosthenes, the Euclidean algorithm, sorting algorithms, algorithms on graphs, and Gaussian elimination, but also discusses elementary data structures, basic graph theory, and numerical questions. In addition, it provides an introduction to programming and demonstrates in detail how to implement algorithms in C++. This textbook is suitable for students who are new to the subject and covers a basic mathematical lecture course, complementing traditional courses on analysis and linear algebra. Both authors have given this "Algorithmic Mathematics" course at the University of Bonn several times in recent years.
Convergence estimates in approximation theory
Gupta, Vijay
2014-01-01
The study of linear positive operators is an area of mathematical studies with significant relevance to studies of computer-aided geometric design, numerical analysis, and differential equations. This book focuses on the convergence of linear positive operators in real and complex domains. The theoretical aspects of these operators have been an active area of research over the past few decades. In this volume, authors Gupta and Agarwal explore new and more efficient methods of applying this research to studies in Optimization and Analysis. The text will be of interest to upper-level students seeking an introduction to the field and to researchers developing innovative approaches.
SCORE DIGITAL TECHNOLOGY: THE CONVERGENCE
Directory of Open Access Journals (Sweden)
Chernyshov Alexander V.
2013-12-01
Full Text Available Explores the role of digital scorewriters in today's culture, education, and music industry and media environment. The main principle of the development of software is not only publishing innovation (relating to the sheet music, and integration into the area of composition, arrangement, education, creative process for works based on digital technology (films, television and radio broadcasting, Internet, audio and video art. Therefore the own convergence of musically-computer technology is a total phenomenon: notation program combined with means MIDI-sequencer, audio and video editor. The article contains the unique interview with the creator of music notation processors.
DEFF Research Database (Denmark)
Henriksen, Lars Skov; Zimmer, Annette; Smith, Steven Rathgeb
. Specifically, we will investigate whether and to what extent social services and health care in these three countries are affected by current changes. With a special focus on nonprofit organizations, we will particularly address the question whether a trend towards convergence of the very different welfare......Due to severe societal, economic and political changes, of which the financial crisis counts prominently, welfare states all over the world are under stress. In our comparative analysis, we will concentrate on specific segments of welfare state activity in Denmark, Germany, and the United States...
Tel, G.
We define the notion of total algorithms for networks of processes. A total algorithm enforces that a "decision" is taken by a subset of the processes, and that participation of all processes is required to reach this decision. Total algorithms are an important building block in the design of
Modeling the convergence accommodation of stereo vision for binocular endoscopy.
Gao, Yuanqian; Li, Jinhua; Li, Jianmin; Wang, Shuxin
2018-02-01
The stereo laparoscope is an important tool for achieving depth perception in robot-assisted minimally invasive surgery (MIS). A dynamic convergence accommodation algorithm is proposed to improve the viewing experience and achieve accurate depth perception. Based on the principle of the human vision system, a positional kinematic model of the binocular view system is established. The imaging plane pair is rectified to ensure that the two rectified virtual optical axes intersect at the fixation target to provide immersive depth perception. Stereo disparity was simulated with the roll and pitch movements of the binocular system. The chessboard test and the endoscopic peg transfer task were performed, and the results demonstrated the improved disparity distribution and robustness of the proposed convergence accommodation method with respect to the position of the fixation target. This method offers a new solution for effective depth perception with the stereo laparoscopes used in robot-assisted MIS. Copyright © 2017 John Wiley & Sons, Ltd.
Global Convergence of Schubert’s Method for Solving Sparse Nonlinear Equations
Directory of Open Access Journals (Sweden)
Huiping Cao
2014-01-01
Full Text Available Schubert’s method is an extension of Broyden’s method for solving sparse nonlinear equations, which can preserve the zero-nonzero structure defined by the sparse Jacobian matrix and can retain many good properties of Broyden’s method. In particular, Schubert’s method has been proved to be locally and q-superlinearly convergent. In this paper, we globalize Schubert’s method by using a nonmonotone line search. Under appropriate conditions, we show that the proposed algorithm converges globally and superlinearly. Some preliminary numerical experiments are presented, which demonstrate that our algorithm is effective for large-scale problems.
Quantum Behaved Particle Swarm Optimization Algorithm Based on Artificial Fish Swarm
Yumin, Dong; Li, Zhao
2014-01-01
Quantum behaved particle swarm algorithm is a new intelligent optimization algorithm; the algorithm has less parameters and is easily implemented. In view of the existing quantum behaved particle swarm optimization algorithm for the premature convergence problem, put forward a quantum particle swarm optimization algorithm based on artificial fish swarm. The new algorithm based on quantum behaved particle swarm algorithm, introducing the swarm and following activities, meanwhile using the a...
Pointwise convergence of Fourier series
Arias de Reyna, Juan
2002-01-01
This book contains a detailed exposition of Carleson-Hunt theorem following the proof of Carleson: to this day this is the only one giving better bounds. It points out the motivation of every step in the proof. Thus the Carleson-Hunt theorem becomes accessible to any analyst.The book also contains the first detailed exposition of the fine results of Hunt, Sjölin, Soria, etc on the convergence of Fourier Series. Its final chapters present original material. With both Fefferman's proof and the recent one of Lacey and Thiele in print, it becomes more important than ever to understand and compare these two related proofs with that of Carleson and Hunt. These alternative proofs do not yield all the results of the Carleson-Hunt proof. The intention of this monograph is to make Carleson's proof accessible to a wider audience, and to explain its consequences for the pointwise convergence of Fourier series for functions in spaces near $äcal Lü^1$, filling a well-known gap in the literature.
RES: Regularized Stochastic BFGS Algorithm
Mokhtari, Aryan; Ribeiro, Alejandro
2014-12-01
RES, a regularized stochastic version of the Broyden-Fletcher-Goldfarb-Shanno (BFGS) quasi-Newton method is proposed to solve convex optimization problems with stochastic objectives. The use of stochastic gradient descent algorithms is widespread, but the number of iterations required to approximate optimal arguments can be prohibitive in high dimensional problems. Application of second order methods, on the other hand, is impracticable because computation of objective function Hessian inverses incurs excessive computational cost. BFGS modifies gradient descent by introducing a Hessian approximation matrix computed from finite gradient differences. RES utilizes stochastic gradients in lieu of deterministic gradients for both, the determination of descent directions and the approximation of the objective function's curvature. Since stochastic gradients can be computed at manageable computational cost RES is realizable and retains the convergence rate advantages of its deterministic counterparts. Convergence results show that lower and upper bounds on the Hessian egeinvalues of the sample functions are sufficient to guarantee convergence to optimal arguments. Numerical experiments showcase reductions in convergence time relative to stochastic gradient descent algorithms and non-regularized stochastic versions of BFGS. An application of RES to the implementation of support vector machines is developed.
SUPER-SAPSO: A New SA-Based PSO Algorithm
Bahrepour, M.; Mahdipour, E.; Cheloi, R.; Yaghoobi, M.
2008-01-01
Swarm Optimisation (PSO) has been received increasing attention due to its simplicity and reasonable convergence speed surpassing genetic algorithm in some circumstances. In order to improve convergence speed or to augment the exploration area within the solution space to find a better optimum
Directory of Open Access Journals (Sweden)
Dalei Jing
2017-07-01
Full Text Available In the present study, a modified Reynolds equation including the electrical double layer (EDL-induced electroviscous effect of lubricant is established to investigate the effect of the EDL on the hydrodynamic lubrication of a 1D slider bearing. The theoretical model is based on the nonlinear Poisson–Boltzmann equation without the use of the Debye–Hückel approximation. Furthermore, the variation in the bulk electrical conductivity of the lubricant under the influence of the EDL is also considered during the theoretical analysis of hydrodynamic lubrication. The results show that the EDL can increase the hydrodynamic load capacity of the lubricant in a 1D slider bearing. More importantly, the hydrodynamic load capacity of the lubricant under the influence of the EDL shows a non-monotonic trend, changing from enhancement to attenuation with a gradual increase in the absolute value of the zeta potential. This non-monotonic hydrodynamic lubrication is dependent on the non-monotonic electroviscous effect of the lubricant generated by the EDL, which is dominated by the non-monotonic electrical field strength and non-monotonic electrical body force on the lubricant. The subject of the paper is the theoretical modeling and the corresponding analysis.
Convergent Validity of the PUTS
Directory of Open Access Journals (Sweden)
Valerie Cathérine Brandt
2016-04-01
Full Text Available Premonitory urges are a cardinal feature in Gilles de la Tourette syndrome. Severity of premonitory urges can be assessed with the Premonitory Urge for Tic Disorders Scale (PUTS. However, convergent validity of the measure has been difficult to assess due to the lack of other urge measures.We investigated the relationship between average real-time urge intensity assessed by an in-house developed real-time urge monitor, measuring urge intensity continuously for 5mins on a visual analogue scale, and general urge intensity assessed by the PUTS in 22 adult Tourette patients (mean age 29.8+/- 10.3; 19 male. Additionally, underlying factors of premonitory urges assessed by the PUTS were investigated in the adult sample using factor analysis and were replicated in 40 children and adolescents diagnosed with Tourette syndrome (mean age 12.05 +/- 2.83 SD, 31 male.Cronbach’s alpha for the PUTS10 was acceptable (α = .79 in the adult sample. Convergent validity between average real-time urge intensity scores (as assessed with the real-time urge monitor and the 10-item version of the PUTS (r = .64 and the 9-item version of the PUTS (r = .66 was good. A factor analysis including the 10 items of the PUTS and average real-time urge intensity scores revealed three factors. One factor included the average real-time urge intensity score and appeared to measure urge intensity, while the other two factors can be assumed to reflect the (sensory quality of urges and subjective control, respectively. The factor structure of the 10 PUTS items alone was replicated in a sample of children and adolescents.The results indicate that convergent validity between the PUTS and the real-time urge assessment monitor is good. Furthermore, the results suggest that the PUTS might assess more than one dimension of urges and it may be worthwhile developing different sub-scales of the PUTS assessing premonitory urges in terms of intensity and quality, as well as subjectively
The serial message-passing schedule for LDPC decoding algorithms
Liu, Mingshan; Liu, Shanshan; Zhou, Yuan; Jiang, Xue
2015-12-01
The conventional message-passing schedule for LDPC decoding algorithms is the so-called flooding schedule. It has the disadvantage that the updated messages cannot be used until next iteration, thus reducing the convergence speed . In this case, the Layered Decoding algorithm (LBP) based on serial message-passing schedule is proposed. In this paper the decoding principle of LBP algorithm is briefly introduced, and then proposed its two improved algorithms, the grouped serial decoding algorithm (Grouped LBP) and the semi-serial decoding algorithm .They can improve LBP algorithm's decoding speed while maintaining a good decoding performance.
Cognitive radio resource allocation based on coupled chaotic genetic algorithm
International Nuclear Information System (INIS)
Zu Yun-Xiao; Zhou Jie; Zeng Chang-Chang
2010-01-01
A coupled chaotic genetic algorithm for cognitive radio resource allocation which is based on genetic algorithm and coupled Logistic map is proposed. A fitness function for cognitive radio resource allocation is provided. Simulations are conducted for cognitive radio resource allocation by using the coupled chaotic genetic algorithm, simple genetic algorithm and dynamic allocation algorithm respectively. The simulation results show that, compared with simple genetic and dynamic allocation algorithm, coupled chaotic genetic algorithm reduces the total transmission power and bit error rate in cognitive radio system, and has faster convergence speed
Madheswaran, C. K.; Ambily, P. S.; Dattatreya, J. K.; Ramesh, G.
2015-06-01
This work describes the experimental investigation on behaviour of reinforced GPC beams subjected to monotonic static loading. The overall dimensions of the GPC beams are 250 mm × 300 mm × 2200 mm. The effective span of beam is 1600 mm. The beams have been designed to be critical in shear as per IS:456 provisions. The specimens were produced from a mix incorporating fly ash and ground granulated blast furnace slag, which was designed for a compressive strength of 40 MPa at 28 days. The reinforced concrete specimens are subjected to curing at ambient temperature under wet burlap. The parameters being investigated include shear span to depth ratio (a/d = 1.5 and 2.0). Experiments are conducted on 12 GPC beams and four OPCC control beams. All the beams are tested using 2000 kN servo-controlled hydraulic actuator. This paper presents the results of experimental studies.
Asymptotic Poisson distribution for the number of system failures of a monotone system
International Nuclear Information System (INIS)
Aven, Terje; Haukis, Harald
1997-01-01
It is well known that for highly available monotone systems, the time to the first system failure is approximately exponentially distributed. Various normalising factors can be used as the parameter of the exponential distribution to ensure the asymptotic exponentiality. More generally, it can be shown that the number of system failures is asymptotic Poisson distributed. In this paper we study the performance of some of the normalising factors by using Monte Carlo simulation. The results show that the exponential/Poisson distribution gives in general very good approximations for highly available components. The asymptotic failure rate of the system gives best results when the process is in steady state, whereas other normalising factors seem preferable when the process is not in steady state. From a computational point of view the asymptotic system failure rate is most attractive
Simple bounds for counting processes with monotone rate of occurrence of failures
International Nuclear Information System (INIS)
Kaminskiy, Mark P.
2007-01-01
The article discusses some aspects of analogy between certain classes of distributions used as models for time to failure of nonrepairable objects, and the counting processes used as models for failure process for repairable objects. The notion of quantiles for the counting processes with strictly increasing cumulative intensity function is introduced. The classes of counting processes with increasing (decreasing) rate of occurrence of failures are considered. For these classes, the useful nonparametric bounds for cumulative intensity function based on one known quantile are obtained. These bounds, which can be used for repairable objects, are similar to the bounds introduced by Barlow and Marshall [Barlow, R. Marshall, A. Bounds for distributions with monotone hazard rate, I and II. Ann Math Stat 1964; 35: 1234-74] for IFRA (DFRA) time to failure distributions applicable to nonrepairable objects
Using exogenous variables in testing for monotonic trends in hydrologic time series
Alley, William M.
1988-01-01
One approach that has been used in performing a nonparametric test for monotonic trend in a hydrologic time series consists of a two-stage analysis. First, a regression equation is estimated for the variable being tested as a function of an exogenous variable. A nonparametric trend test such as the Kendall test is then performed on the residuals from the equation. By analogy to stagewise regression and through Monte Carlo experiments, it is demonstrated that this approach will tend to underestimate the magnitude of the trend and to result in some loss in power as a result of ignoring the interaction between the exogenous variable and time. An alternative approach, referred to as the adjusted variable Kendall test, is demonstrated to generally have increased statistical power and to provide more reliable estimates of the trend slope. In addition, the utility of including an exogenous variable in a trend test is examined under selected conditions.
Monotonicity of the ratio of modified Bessel functions of the first kind with applications.
Yang, Zhen-Hang; Zheng, Shen-Zhou
2018-01-01
Let [Formula: see text] with [Formula: see text] be the modified Bessel functions of the first kind of order v . In this paper, we prove the monotonicity of the function [Formula: see text] on [Formula: see text] for different values of parameter p with [Formula: see text]. As applications, we deduce some new Simpson-Spector-type inequalities for [Formula: see text] and derive a new type of bounds [Formula: see text] ([Formula: see text]) for [Formula: see text]. In particular, we show that the upper bound [Formula: see text] for [Formula: see text] is the minimum over all upper bounds [Formula: see text], where [Formula: see text] and is not comparable with other sharpest upper bounds. We also find such type of upper bounds for [Formula: see text] with [Formula: see text] and for [Formula: see text] with [Formula: see text].
Ergodic averages for monotone functions using upper and lower dominating processes
DEFF Research Database (Denmark)
Møller, Jesper; Mengersen, Kerrie
We show how the mean of a monotone function (defined on a state space equipped with a partial ordering) can be estimated, using ergodic averages calculated from upper and lower dominating processes of a stationary irreducible Markov chain. In particular, we do not need to simulate the stationary...... Markov chain and we eliminate the problem of whether an appropriate burn-in is determined or not. Moreover, when a central limit theorem applies, we show how confidence intervals for the mean can be estimated by bounding the asymptotic variance of the ergodic average based on the equilibrium chain. Our...... methods are studied in detail for three models using Markov chain Monte Carlo methods and we also discuss various types of other models for which our methods apply....
Ergodic averages for monotone functions using upper and lower dominating processes
DEFF Research Database (Denmark)
Møller, Jesper; Mengersen, Kerrie
2007-01-01
We show how the mean of a monotone function (defined on a state space equipped with a partial ordering) can be estimated, using ergodic averages calculated from upper and lower dominating processes of a stationary irreducible Markov chain. In particular, we do not need to simulate the stationary...... Markov chain and we eliminate the problem of whether an appropriate burn-in is determined or not. Moreover, when a central limit theorem applies, we show how confidence intervals for the mean can be estimated by bounding the asymptotic variance of the ergodic average based on the equilibrium chain. Our...... methods are studied in detail for three models using Markov chain Monte Carlo methods and we also discuss various types of other models for which our methods apply....
Using an inductive approach for definition making: Monotonicity and boundedness of sequences
Directory of Open Access Journals (Sweden)
Deonarain Brijlall
2009-09-01
Full Text Available The study investigated fourth–year students’ construction of the definitions of monotonicity and boundedness of sequences, at the Edgewood Campus of the University of KwaZulu –Natal in South Africa. Structured worksheets based on a guided problem solving teaching model were used to help students to construct the twodefinitions. A group of twenty three undergraduateteacher trainees participated in the project. These students specialised in the teaching of mathematics in the Further Education and Training (FET (Grades 10 to 12 school curriculum. This paper, specifically, reports on the investigation of students’ definition constructions based on a learnig theory within the context of advanced mathematical thinking and makes a contribution to an understanding of how these students constructed the two definitions. It was found that despite the intervention of a structured design, these definitions were partially or inadequately conceptualised by some students.
Non-monotonic resonance in a spatially forced Lengyel-Epstein model
Energy Technology Data Exchange (ETDEWEB)
Haim, Lev [Physics Department, Ben-Gurion University of the Negev, Beer-Sheva 84105 (Israel); Department of Oncology, Soroka University Medical Center, Beer-Sheva 84101 (Israel); Hagberg, Aric [Center for Nonlinear Studies, Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545 (United States); Meron, Ehud [Physics Department, Ben-Gurion University of the Negev, Beer-Sheva 84105 (Israel); Department of Solar Energy and Environmental Physics, BIDR, Ben-Gurion University of the Negev, Sede Boqer Campus, Midreshet Ben-Gurion 84990 (Israel)
2015-06-15
We study resonant spatially periodic solutions of the Lengyel-Epstein model modified to describe the chlorine dioxide-iodine-malonic acid reaction under spatially periodic illumination. Using multiple-scale analysis and numerical simulations, we obtain the stability ranges of 2:1 resonant solutions, i.e., solutions with wavenumbers that are exactly half of the forcing wavenumber. We show that the width of resonant wavenumber response is a non-monotonic function of the forcing strength, and diminishes to zero at sufficiently strong forcing. We further show that strong forcing may result in a π/2 phase shift of the resonant solutions, and argue that the nonequilibrium Ising-Bloch front bifurcation can be reversed. We attribute these behaviors to an inherent property of forcing by periodic illumination, namely, the increase of the mean spatial illumination as the forcing amplitude is increased.
Directory of Open Access Journals (Sweden)
Wiwik Budiawan
2016-02-01
Full Text Available Manusia sebagai subyek yang memiliki keterbatasan dalam kerja, sehingga menyebabkan terjadinya kesalahan. Kesalahan manusia yang dilakukan mengakibatkan menurunnya tingkat kewaspadaan masinis dan asisten masinis dalam menjalankan tugas. Tingkat kewaspadaan dipengaruhi oleh 5 faktor yaitu keadaan monoton, kualitas tidur, keadaan psikofisiologi, distraksi dan kelelahan kerja. Metode untuk mengukur 5 faktor yaitu kuisioner mononton, kuisioner Pittsburgh Sleep Quality Index (PSQI, kuisioner General Job Stress dan kuisioner FAS. Sedangkan untuk menguji tingkat kewaspadaan menggunakan Software Psychomotor Vigilance Test (PVT. Responden yang dipilih adalah masinis dan asisten masinis, karena jenis pekerjaan tersebut sangat membutuhkan tingkat kewaspadaan yang tinggi. Hasil pengukuran kemudian dianalisa menggunakan uji regresi linear majemuk. Dalam penelitian ini menghasilkan keadaan monoton, kualitas tidur, keadaan psikofisiologi, distraksi dan kelelahan kerja berpengaruh secara simultan terhadap tingkat kewaspadaan. Hal ini dibuktikan dengan ketika sebelum jam dinas, hasil uji F-hitung keadaan monoton, kualitas tidur, keadaan psikofisiologi adalah sebesar 0,876, sedangkan untuk variabel distraksi dan Kelelahan Kerja (FAS terhadap tingkat kewaspadaan memiliki nilai 2,371. pada saat sesudah bekerja variabel distraksi dan kelelahan kerja (FAS terhadap tingkat kewaspadaan memiliki nilai F-hitung 2,953,dan nilai 0,544 untuk keadaan monoton, kualitas tidur, keadaan psikofisiologi. Faktor yang memiliki pengaruh terbesar terhadap tingkat kewaspadaan sebelum jam dinas yaitu faktor kualitas tidur, sedangkan untuk sesudah jam dinas adalah faktor kelelahan kerja. Abstract Human beings as subjects who have limitations in work, thus causing the error. Human error committed resulted in a decreased level of alertness machinist and assistant machinist in the line of duty. Alert level is influenced by five factors: the state of monotony, quality of sleep
Energy Technology Data Exchange (ETDEWEB)
Zhao Xuejing [Universite de Technologie de Troyes, Institut Charles Delaunay and STMR UMR CNRS 6279, 12 rue Marie Curie, 10010 Troyes (France); School of mathematics and statistics, Lanzhou University, Lanzhou 730000 (China); Fouladirad, Mitra, E-mail: mitra.fouladirad@utt.f [Universite de Technologie de Troyes, Institut Charles Delaunay and STMR UMR CNRS 6279, 12 rue Marie Curie, 10010 Troyes (France); Berenguer, Christophe [Universite de Technologie de Troyes, Institut Charles Delaunay and STMR UMR CNRS 6279, 12 rue Marie Curie, 10010 Troyes (France); Bordes, Laurent [Universite de Pau et des Pays de l' Adour, LMA UMR CNRS 5142, 64013 PAU Cedex (France)
2010-08-15
The aim of this paper is to discuss the problem of modelling and optimising condition-based maintenance policies for a deteriorating system in presence of covariates. The deterioration is modelled by a non-monotone stochastic process. The covariates process is assumed to be a time-homogenous Markov chain with finite state space. A model similar to the proportional hazards model is used to show the influence of covariates on the deterioration. In the framework of the system under consideration, an appropriate inspection/replacement policy which minimises the expected average maintenance cost is derived. The average cost under different conditions of covariates and different maintenance policies is analysed through simulation experiments to compare the policies performances.
International Nuclear Information System (INIS)
Zhao Xuejing; Fouladirad, Mitra; Berenguer, Christophe; Bordes, Laurent
2010-01-01
The aim of this paper is to discuss the problem of modelling and optimising condition-based maintenance policies for a deteriorating system in presence of covariates. The deterioration is modelled by a non-monotone stochastic process. The covariates process is assumed to be a time-homogenous Markov chain with finite state space. A model similar to the proportional hazards model is used to show the influence of covariates on the deterioration. In the framework of the system under consideration, an appropriate inspection/replacement policy which minimises the expected average maintenance cost is derived. The average cost under different conditions of covariates and different maintenance policies is analysed through simulation experiments to compare the policies performances.