The purpose of this paper is to introduce a new explicit extragradient method for finding minimum-norm solutions of a split feasibility problem in real Hilbert spaces. The advantage of the proposed method is that it u...
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The purpose of this paper is to introduce a new explicit extragradient method for finding minimum-norm solutions of a split feasibility problem in real Hilbert spaces. The advantage of the proposed method is that it uses the less number of iterations to obtain its strong convergence. Numerical experiments illustrate the performances of our new algorithm and provide a comparison with related algorithms.
For p 2, let E be a 2-uniformly smooth and p-uniformly convex real Banach space and let A : E ! E be a Lipschitz and strongly monotone mapping such that A 1(0),;. For given x1 2 E, let f xn g be generated by the algor...
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For p 2, let E be a 2-uniformly smooth and p-uniformly convex real Banach space and let A : E ! E be a Lipschitz and strongly monotone mapping such that A 1(0),;. For given x1 2 E, let f xn g be generated by the algorithm xn +1 = J 1(Jxn Axn), n 1, where J is the normalized duality mapping from E into E and is a positive real number in (0;1) satisfying suitable conditions. Then it is proved that fxn g converges strongly to the unique point x 2 A 1(0). Furthermore, our theorems provide an a ffirmative answer to the Chidume et al. open problem [`Krasnoselskii-type algorithm for zeros of strongly monotone Lipschitz maps in classical Banach spaces', SpringerPlus 4 (2015), 297]. Finally, applications to convex minimization problems are given.
This study hypothesized that oxygen uptake (& x1e40;O-2) measured with a novel protocol of chasing rainbow troutOncorhynchus mykissto exhaustion inside a static respirometer while simultaneously monitoring & x...
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This study hypothesized that oxygen uptake (& x1e40;O-2) measured with a novel protocol of chasing rainbow troutOncorhynchus mykissto exhaustion inside a static respirometer while simultaneously monitoring & x1e40;O-2(& x1e40;O-2chase) would generate the same and repeatable peak value as when peak active & x1e40;O-2(& x1e40;O-2active) is measured in a critical swimming speed protocol. To reliably determine peak & x1e40;O-2chase, and compare to the peak during recovery of & x1e40;O(2)after a conventional chase protocol outside the respirometer (& x1e40;O-2rec), this study applied an iterative algorithm and a minimum sampling window duration (i.e., 1 min based on an analysis of the variance in background and exercise & x1e40;O-2) to account for & x1e40;O(2)dynamics. In support of this hypothesis, peak & x1e40;O-2active(707 +/- 33 mg O(2)h(-1)kg(-1)) and peak & x1e40;O-2chase(663 +/- 43 mg O(2)h(-1)kg(-1)) were similar (P= 0.49) and repeatable (Pearson's and Spearman's correlation test;r >= 0.77;P < 0.05) when measured in the same fish. Therefore, estimates of & x1e40;O(2max)can be independent of whether a fish is exhaustively chased inside a respirometer or swum to fatigue in a swim tunnel, provided & x1e40;O(2)is analysed with an iterative algorithm and a minimum but reliable sampling window. The importance of using this analytical approach was illustrated by peak & x1e40;O(2chase)being 23% higher (P < 0.05) when compared with a conventional sequential interval regression analysis, whereas using the conventional chase protocol (1-min window) outside the respirometer increased this difference to 31% (P < 0.01). Moreover, because peak & x1e40;O(2chase)was 18% higher (P < 0.05) than peak & x1e40;O-2rec, chasing a fish inside a static respirometer may be a better protocol for obtaining maximum & x1e40;O-2.
Fast charging is a promising way for plug-in electric vehicles (PEVs) to get recharged quickly and reduce the impacts of long-lasting charging process on PEV owners' daily life. Decreasing time during charging PEV...
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Fast charging is a promising way for plug-in electric vehicles (PEVs) to get recharged quickly and reduce the impacts of long-lasting charging process on PEV owners' daily life. Decreasing time during charging PEVs also makes the decision of PEV owners choosing where to charge affected more by the time length of driving towards and waiting in charging stations, raising new requirements for charging facilities planning. In this study, a cost minimisation planning method of PEV fast-charging stations taking influences of queuing and driving time into consideration is proposed and solved by the genetic algorithm-based methodology. An iterative algorithm obtaining the equilibrium of the user's decision of place to charge is proposed to consider the impacts of waiting and driving time at different charging stations on PEV owners. The effectiveness of the proposed strategy is then verified through the case analysis based on trajectory data of taxis in Beijing, which shows that the proposed methodology has good performances in computation. Weight of time costs and investment restrictions such as the number of charging stations would also influence the planning result.
In this paper, we introduce the notion of nonlinear equational systems. We consider some important results of equational systems on posets (partially ordered sets) and Banach lattices. Also we see their applications i...
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In this paper, we introduce the notion of nonlinear equational systems. We consider some important results of equational systems on posets (partially ordered sets) and Banach lattices. Also we see their applications in data-flow analysis-a general theory to solve some special types of simultaneous nonlinear equations on complete lattices-and extend the Cournot oligopoly on Banach lattices. At the end, there are some new theoretical suggestions for decision makers, especially computer program designers, to shorten and optimize their calculations.
In this paper, we consider two iterative algorithms for the Sylvester- conjugate matrix equation AV + BW = E (V) over barF + C and AV + B (W) over bar = E (V) over barF + C. When these two matrix equations are consist...
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In this paper, we consider two iterative algorithms for the Sylvester- conjugate matrix equation AV + BW = E (V) over barF + C and AV + B (W) over bar = E (V) over barF + C. When these two matrix equations are consistent, for any initial matrices the solutions can be obtained within finite iterative steps in the absence of round off errors. Some lemmas and theorems are stated and proved where the iterative solutions are obtained. Two numerical examples are given to illustrate the effectiveness of the proposed method. (C) 2013 Elsevier Ltd. All rights reserved.
Analytic algorithms and iterative algorithms are two main computed tomography(CT) image reconstruction ***,total variation(TV) minimization algorithm is a classical iterative *** TV minimization algorithm is an image ...
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Analytic algorithms and iterative algorithms are two main computed tomography(CT) image reconstruction ***,total variation(TV) minimization algorithm is a classical iterative *** TV minimization algorithm is an image reconstruction algorithm based on compressed sensing,which can accurately reconstruct images from sparse data or highly noisy ***,the traditional TV minimization algorithm often incurs over-smoothness at structure's edges if the reconstructed image has an obvious piecewise constant ***,it may lead to block artifacts for grayscale fluctuation ***,this paper proposed an adaptive-weighted high order total variation(AWHOTV) algorithm based on Chambolle-Pock(CP) algorithm *** constructed the second order TV-norm using the second order gradient,adopted anisotropic edge property between neighboring image pixels,adaptively adjusted local image-intensity gradient to keep edge information,and designed CP solving *** evaluate performance of AWHOTV,we utilized simulation and real data to reconstruct images and conduct qualitative and quantitative analysis under ideal data projection and noisy data *** results show that relative to the traditional TV algorithm,AWHOTV can effectively suppress the block artifacts and has good edge protection *** is a better reconstruction algorithm for images with obvious grayscale fluctuation features,which also can be extended to other imaging modalities.
The nonlinear Poisson problems in heat diffusion governed by elliptic type partial differential equations are solved by a modified globally optimal iterative algorithm (MGOIA). The MGOIA is a purely iterative method f...
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The nonlinear Poisson problems in heat diffusion governed by elliptic type partial differential equations are solved by a modified globally optimal iterative algorithm (MGOIA). The MGOIA is a purely iterative method for searching the solution vector x without using the invert of the Jacobian matrix D. Moreover, we reveal the weighting parameter alpha(c) in the best descent vector w = alpha E-c + (DE)-E-T and derive the convergence rate and find a criterion of the parameter gamma. When utilizing alpha(c) and gamma, we can farther accelerate the convergence speed several times. Several numerical experiments are carefully discussed and validated the proposed method.
Precise beam shaping relies on accurate characterisation of deformations in phase and amplitude of a wave as it propagates. We investigate a process where only a priori information about the relative locations of arbi...
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Precise beam shaping relies on accurate characterisation of deformations in phase and amplitude of a wave as it propagates. We investigate a process where only a priori information about the relative locations of arbitrary source regions in time are known. We use the correlations between each region to obtain information about amplitude and phase to piece together a wavefunction representing the wave. We demonstrate that this method can be used to characterise a singularity in an initially unknown wavefunction and remove it using a beam shaping device. In contrast to some other techniques that assume point correlations, we can use any set of simple connected shapes as correlation regions. This leads us to believe that it has some use to beam shaping applications in multimode-fibres or in turbid media where singularities are present in the scattered light.
The procedure of updating an existing but inaccurate model is an essential step toward establishing an effective model. Updating damping and stiffness matrices simultaneously with measured modal data can be mathematic...
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The procedure of updating an existing but inaccurate model is an essential step toward establishing an effective model. Updating damping and stiffness matrices simultaneously with measured modal data can be mathematically formulated as following two problems. Problem 1: Let M (a) aSR (nxn) be the analytical mass matrix, and I >=diag{lambda (1),aEuro broken vertical bar,lambda (p) }aC (pxp) , X=[x (1),aEuro broken vertical bar,x (p) ]aC (nxp) be the measured eigenvalue and eigenvector matrices, where rank(X)=p, p < n and both I > and X are closed under complex conjugation in the sense that , for j=1,aEuro broken vertical bar,l, and lambda (k) aR, x (k) aR (n) for k=2l+1,aEuro broken vertical bar,p. Find real-valued symmetric matrices D and K such that M (a) XI > (2)+DXI >+KX=0. Problem 2: Let D (a) ,K (a) aSR (nxn) be the analytical damping and stiffness matrices. Find such that , where S (E) is the solution set of Problem 1 and ayena <...ayen is the Frobenius norm. In this paper, a gradient based iterative (GI) algorithm is constructed to solve Problems 1 and 2. A sufficient condition for the convergence of the iterative method is derived and the range of the convergence factor is given to guarantee that the iterative solutions consistently converge to the unique minimum Frobenius norm symmetric solution of Problem 2 when a suitable initial symmetric matrix pair is chosen. The algorithm proposed requires less storage capacity than the existing numerical ones and is numerically reliable as only matrix manipulation is required. Two numerical examples show that the introduced iterative algorithm is quite efficient.
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