In optical imaging systems, the aberration is an important factor that impedes realising diffraction-limited imaging. Accurate wavefront sensing and control play important role in modern high-resolution optical imagin...
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In optical imaging systems, the aberration is an important factor that impedes realising diffraction-limited imaging. Accurate wavefront sensing and control play important role in modern high-resolution optical imaging systems nowadays. In this study, a simple model-based phase retrieval algorithm is proposed for accurate efficient wavefront sensing with high dynamic range. In the authors' algorithm, a wavefront is represented by the Zernike polynomials, and the Zernike coefficients are solved by the least-squares-based non-linear optimisation method, i.e. the Lederberg-Marquardt algorithm, with multiple phase-diversity images. The numerical results show that the proposed algorithm is capable of retrieving wavefront with a large dynamic range up to seven wavelength and robust to noise. In comparison, the proposed algorithm is more efficient than the existing model-based technique and more accurate than existing Fourier - transformation-based iterative techniques.
作者：
Hishinuma, KazuhiroIiduka, HideakiMeiji Univ
Grad Sch Sci & Technol Comp Sci Course Tama Ku 1-1-1 Higashimita Kawasaki Kanagawa 2148571 Japan Meiji Univ
Dept Comp Sci Tama Ku 1-1-1 Higashimita Kawasaki Kanagawa 2148571 Japan
Constrained quasiconvex optimization problems appear in many fields, such as economics, engineering, and management science. In particular, fractional programming, which models ratio indicators such as the profit/cost...
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Constrained quasiconvex optimization problems appear in many fields, such as economics, engineering, and management science. In particular, fractional programming, which models ratio indicators such as the profit/cost ratio as fractional objective functions, is an important instance. Subgradient methods and their variants are useful ways for solving these problems efficiently. Many complicated constraint sets onto which it is hard to compute the metric projections in a realistic amount of time appear in these applications. This implies that the existing methods cannot be applied to quasiconvex optimization over a complicated set. Meanwhile, thanks to fixed point theory, we can construct a computable nonexpansive mapping whose fixed point set coincides with a complicated constraint set. This paper proposes an algorithm that uses a computable nonexpansive mapping for solving a constrained quasiconvex optimization problem. We provide convergence analyses for constant diminishing step-size rules. Numerical comparisons between the proposed algorithm and an existing algorithm show that the proposed algorithm runs stably and quickly even when the running time of the existing algorithm exceeds the time limit. (C) 2019 Elsevier B.V. All rights reserved.
A nonlinear programming problem was developed for the separation and classification of Portland cement particles into different fractions through the optimal design of two cyclones classifier in series. The equations ...
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With the development of microgrid, more and more scholars have participated in the optimization research of microgrid power flow. This article mainly summarizes the algorithms for power flow optimization of microgrid,...
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The joint replenishment problem (JRP) is to determine the replenishment cycle times of a group of items over an infinite planning horizon. We investigated the JRP with cycle time constraints under general-integer poli...
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Modelling dependent credit-rating migrations of assets classified into M credit classes and S industries, M x S + 2(MxS) parameters have to be estimated. For a realistic choice of M and S, this number is huge and it g...
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Modelling dependent credit-rating migrations of assets classified into M credit classes and S industries, M x S + 2(MxS) parameters have to be estimated. For a realistic choice of M and S, this number is huge and it greatly exceeds the number of available observations. To avoid brute-force calculations, we suggest sequential and parallel genetic algorithms. Considering a practically important combination of M = 7 and S = 6, the approach is tested on Standard and Poor's data.
This paper deals with soft fault diagnosis of linear analog circuits and concentrates on the circuits including second generation current conveyors. Properties of these circuits are taken into account and an appropria...
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This paper deals with soft fault diagnosis of linear analog circuits and concentrates on the circuits including second generation current conveyors. Properties of these circuits are taken into account and an appropriate realistic conveyor model is put forward. The fault diagnosis includes fault detection, locating faulty elements from among all circuit elements, and estimating their values. The diagnostic method developed in this paper exploits a measurement test in an AC state and uses the nonlinear programming as a mathematical tool. Values of the faulty parameters may belong to wide ranges around their nominal values. For illustration a real-life current conveyor circuit is laboratorily and numerically tested. Proposed method efficiently diagnoses different faults giving correct results in short time. Although the method is dedicated to single fault diagnosis, it can be generalized to double and triple faults either. (1)However, in the case of multiple faults it is less effective. (C) 2019 The Authors. Published by Elsevier GmbH.
We develop theoretical foundations for computer solving configuration theory problems using general-purpose nonlinear programming solvers. The problems related to the existence and isomorphism of combinatorial and geo...
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The health service industry is required to improve its performance and service to the society continuously. Improvements in performance and service can be done by improving health workers' performance, one example...
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ISBN:
(纸本)9781450390385
The health service industry is required to improve its performance and service to the society continuously. Improvements in performance and service can be done by improving health workers' performance, one example of which is improving the performance of medical trainees. Medical trainees are required to be able to serve patients well, timely and on target for 24 hours, hence scheduling is needed. Medical trainees scheduling in this case is to allocate 179 medical trainees divided into 26 groups, followed by scheduling it into 16 units/clinics/hospital departments for 2 years (96 weeks). Each hospital department has criteria for mental workload, physical workload, fatigue level, group capacity and different duration of time. Therefore, there is a need for scheduling that takes the whole thing into account. Scheduling in this case is still conducted by plotting medical trainees manually and has not considered ergonomic factors (the physical workload, mental workload and fatigue level) at each hospital department. Medical trainees scheduling considering ergonomic factors can be adopted to reduce ergonomic risks and achieve better performance of medical trainees. In this paper, the authors propose an integer nonlinear programming which aims to find optimal scheduling to minimize the deviation in mental workload, physical workload and fatigue level that ware experienced by medical trainees in every month. The mental workload, physical workload and fatigue level were evaluated using the NASA TLX method, pulse rate recall questionnaire and Subjective Self Rating Test (SSRT). Optimal scheduling is needed to reduce the fatigue felt by medical trainees during 96 weeks of clinical clerkship. The results revealed the effectiveness of the model because the scheduling in each department was proven to be done in according to the capacity and time vulnerability based on the regulations and could create a balance of physical workload, mental workload and fatigue level of medical tr
In this paper a new method for solving optimal phasor measurement units (PMU) placement problem for full observability in power systems is proposed. A new algorithm is based on forming and solving Groebner bases set o...
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In this paper a new method for solving optimal phasor measurement units (PMU) placement problem for full observability in power systems is proposed. A new algorithm is based on forming and solving Groebner bases set of equations for a defined optimization problem. The technique of Groebner bases is applicable wherever the problem may be presented by the set of polynomials and as such, it can be found in a variety of applied mathematics problems. Groebner bases of the set of polynomials represents the canonical form equivalent to the original set, similar to the way the row echelon form for linear systems represents the triangular form of the linear equations set. The canonical form of the Groebner bases polynomials, along with the utilization of recursive algorithms, allows the solution to be effortlessly obtained. Optimal phasor measurement units placement (OPP) problem can be presented in a linear or nonlinear polynomial form, both of which are used in this paper. The settings of OPP problem have been proposed in this paper with the inclusion of zero injection buses (ZIBs), in normal system states and considering contingency related to PMU outage. The problem formulation is defined according to the application of Groebner bases technique. The proposed model is capable of obtaining the full set of optimal solutions instead of only one or partial solutions. The efficiency of the proposed method is tested on IEEE 14-bus, IEEE 24-bus, IEEE 30-bus, IEEE 118-bus and Polish 2383-bus test system and the results are compared with those of some recently reported methods.
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