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5th Conference on Novel Optical Systems Design and optimization

作者： Dai, EW Zhou, CH Xi, P Liu, LR Chinese Acad Sci Shanghai Inst Opt & Fine Mech Shanghai 201800 Peoples R China

ISBN: (纸本)0819445355

Over the past years great efforts have been made to find the optimization methods for synthesizing computer-generated holograms, e.g., kinoforms. The simulated annealing (SA) method is widely used in programming to approach the global optimization. But the drawback of the SA is its time consuming. It is not possible to use the SA for some large computational optimization problems. So there is a strong need of the fast and effective algorithm. In this paper we propose a new optimization method, based on the modified Gerchberg-Saxton (G-S) algorithm, for synthesizing the large-scale kinoforms. Both phase and amplitude freedoms are used in this method. This method is especially suitable for the optimization of the large-scale kinoforms. It takes much less computational time than SA and the obtained image quality is also comparable to that of the SA. Another advantage of this method is that the reconstructed image quality is adjustable to meet the different requirements by controlling the noise parameter. The diffractive efficiency or the uniformity of the reconstructed image can be enhanced selectively to satisfy the different needs by the adjustment of the noise parameter. Using this method we have obtained several large-scale kinoforms with fast speed. The pattern of a binary kinoform is transferred into the glass plate by inductive coupled plasma (ICP) technology. Experimental results are also given in this paper to show the effectiveness of our methods.

关键词： computer-generated hologram kinoform optimization algorithm diffractive optics

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Estimation of blur and noise parameters in remote sensing

Estimation of blur and noise parameters in remote sensing

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IEEE International Conference on Acoustics, Speech, and Signal Processing

作者： Jalobeanu, A Blanc-Féraud, L Zerubia, J INRIA Sophia Antipolis UNSA CNRS Joint Res GrpAriana F-06902 Sophia Antipolis France

ISBN: (纸本)0780374029

In this paper we propose a new algorithm to estimate the parameters of the noise related to the sensor and the impulse response of the optical system, from a blurred and noisy satellite or aerial image. The noise is supposed to be white, Gaussian and stationary. The blurring kernel has a parametric form and is modeled in such a way as to take into account the physics of the system (the atmosphere, the optics and the sensor). The observed scene is described by a fractal model, taking into account the scale invariance properties of natural images. The estimation is performed automatically by maximizing a marginalized likelihood, which is achieved by a deterministic algorithm whose complexity is limited to O(N), where N is the number of pixels.

关键词： remote sensing Gaussian noise computational complexity deterministic algorithms image processing optimisation white noise maximum likelihood estimation blur estimation noise parameters estimation remote sensing sensor impulse response optical system blurred satellite image noisy satellite image blurred aerial image noisy aerial image white noise Gaussian noise stationary. noise blurring kernel system physics atmosphere optics fractal model scale invariance properties natural images marginalized maximum likelihood estimation deterministic algorithm complexity optimization algorithm

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Selection of an optimal neural network architecture for computer-aided detection of microcalcifications - Comparison of automated optimization techniques

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MEDICAL PHYSICS 2001年第9期28卷 1937-1948页

作者： Gurcan, MN Sahiner, B Chan, HP Hadjiiski, L Petrick, N Univ Michigan Dept Radiol Ann Arbor MI 48109 USA

Many computer-aided diagnosis (CAD) systems use neural networks (NNs) for either detection or classification of abnormalities. Currently, most NNs are "optimized" by manual search in a very limited parameter space. In this work, we evaluated the use of automated optimization methods for selecting an optimal convolution neural network CNN) architecture. Three automated methods, the steepest descent (SD). the simulated annealing (SA), and the genetic algorithm (GA), were compared. We used as an example the CNN that classifies true and false microcalcifications detected on digitized mammograms by a prescreening algorithm. Four parameters of the CNN architecture were considered for optimization, the numbers of node groups and the filter kernel sizes in the first and second hidden layers, resulting in a search space of 432 possible architectures. The area A. under the receiver operating characteristic (ROC) curve was used to design a cost function. The SA experiments were conducted with four different annealing schedules. Three different parent selection methods were compared for the GA experiments. An available data set was split into two groups with approximately equal number of samples. By using the two groups alternately for training and testing, two different cost surfaces were evaluated. For the first cost surface, the SD method was trapped in a local minimum 91% (392/432) of the time. The SA using the Boltzman schedule selected the best architecture after evaluating, on average, 167 architectures. The GA achieved its best performance with linearly scaled roulette-wheel parent selection;however, it evaluated 391 different architectures, on average, to find the best one. The second cost surface contained no local minimum. For this surface, a simple SD algorithm could quickly find the global minimum, but the SA with the very fast reannealing schedule was still the most efficient. The same SA scheme, however, was trapped in a local minimum on the first cost surface. O

关键词： computer-aided diagnosis mammography microcalcification optimization algorithm convolution neural network

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optimization for aircraft engines with regression and neural-network analysis approximators

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JOURNAL OF PROPULSION AND POWER 2001年第1期17卷 85-92页

作者： Patnaik, SN Guptill, JD Hopkins, DA Lavelle, TM NASA John H Glenn Res Ctr Lewis Field Computat Sci Branch Cleveland OH 44135 USA Ohio Aerosp Inst Brookpark OH 44142 USA NASA John H Glenn Res Ctr Lewis Field Machine Dynam Branch Cleveland OH 44135 USA NASA John H Glenn Res Ctr Lewis Field Prop Syst Anal Off Cleveland OH 44135 USA

The NASA Engine Performance Program (NEPP) can configure and analyze almost any type of gas-turbine engine that can be generated through the interconnection of a set of standard physical components, In addition, the code can optimize engine performance by changing adjustable variables under a set of constraints, For engine-cycle problems at certain operating points, the NEPP code can encounter difficulties: nonconvergence in Powell's optimization algorithm and deficiencies in the Newton-Raphson solver during engine balancing. A project was undertaken to correct the deficiencies, Nonconvergence was avoided through a cascade optimization strategy. Deficiencies associated with engine balancing were eliminated through neural-network and linear-regression methods. An approximation-interspersed cascade strategy was used to optimize engine operation over the Right envelope. Replacement of Powell's algorithm by the cascade strategy improved the optimization segment of the NEPP code. The performance of the linear-regression and neural-network methods as alternate engine analyzers was found to be satisfactory. The paper illustrates the results and insights gained from the improved version of the NEPP code considering two examples: a supersonic mixed-flow turbofan engine and a subsonic waverotor-topped engine.

关键词： Neural Network Methods Overall Pressure Ratio High Pressure Turbine Airbreathing Propulsion optimization algorithm Gas Turbine Engines Subsonic Aircraft Mach Number Sequential Linear Programming Aspect Ratio

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Experimental evaluation of flexible manipulator trajectory optimization

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2001年第4期24卷 834-843页

作者： Pond, B Sharf, I Univ Victoria Dept Mech Engn Victoria BC V8W 3P6 Canada

Experimental results showing the effectiveness of trajectory optimization for reducing vibration excitation in point-to-point maneuvers of flexible manipulators are presented. Joint trajectories are found as the solution to a functional (or global) optimization problem. To reduce vibration, the functional is chosen to be the strain energy of the manipulator integrated over the time interval of the motion. A numerical example is presented to help verify the algorithm. A laboratory-based flexible-link manipulator is then described, and a model of its dynamics is obtained by combining analysis with experimental parameter identification. Through the use of the model, the optimal trajectory is generated and compared, both in simulation and experimentally, to a polynomial trajectory and the globally optimal straight-line trajectory. The experiments agree with the simulation in confirming that joint trajectory optimization can significantly reduce the total strain energy incurred during point-to-point motions.

关键词： Pontryagin's Maximum Principle Flexible Manipulators Stiffness Matrices Motion Planning Space Station Remote Manipulator System optimization algorithm Numerical Simulation Numerical optimization Nonlinear Dynamics Numerical Modeling

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Evolution strategies for film cooling optimization

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AIAA JOURNAL 2001年第3期39卷 537-539页

作者： Müller, SD Walther, JH ETH Zentrum Swiss Fed Inst Technol Inst Computat Sci CH-8092 Zurich Switzerland

Presents a study which implemented an evolutionary algorithm in a realistic automated design cycle of turbine blade film cooling. Description of a blade cooling configuration; Blade cooling optimization; Conclusions.

关键词： Film Cooling Radial Velocity Vortex Breakdown Coolant Angle of Attack Delta Wing Ogive Cylinder Heat Transfer Charge Coupled Device optimization algorithm

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Computational aspects of transfer trajectories to halo orbits

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2001年第4期24卷 796-804页

作者： Kechichian, JA Aerospace Corp Astrodynam Dept El Segundo CA 90245 USA

The method of regularization is applied to the singular differential equations of the restricted circular three-body model in rotating coordinates centered at the L-1 Lagrange libration point of the sun-Earth system. The regularized equations are used through an iterative process to generate converged transfer trajectories from a low circular parking orbit around the Earth to the vicinity of the L-1 point, where a small velocity change inserts the spacecraft into a desired periodic halo orbit. These computation methods, which use backward numerical integration to provide a transfer solution that meets the end or boundary conditions with 1-m accuracy, are based on the use of double precision integrators with built-in interpolators as well as an unconstrained optimization algorithm that minimizes the summed squares of the differences between certain achieved parameters and their desired target values. The existence of optimal values of certain target parameters that lead to the minimization of the velocity change needed to insert into the halo orbit of interest is also shown, as well as the range of its feasible values at least in the case of the perigee location of the departure hyperbola.

关键词： Orbital Elements Earth Perigee Earth Centered Inertial Orbital Maneuvers Numerical Integration optimization algorithm Right Ascension Second Order Differential Equations International Sun Earth Explorer 3

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Numerical aspects of finite element simulations of residual stresses in metal matrix composites

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INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING 2001年第3期50卷 629-644页

作者： Teixeira-Dias, F Menezes, LF Univ Aveiro Dept Mech Engn P-3810193 Aveiro Portugal Univ Coimbra CEMUC Dept Mech Engn P-3030 Coimbra Portugal

When a metal matrix composite (MMC) is cooled down from the fabrication or annealing temperature to room temperature, residual stresses are induced in the composite due to the mismatch of the thermal expansion coefficients of the matrix and reinforcement. A thermomechanical model describing these processes is presented considering that the reinforcement component has a thermo-elastic behaviour and that the matrix material exhibits a thermo-elastoviscoplastic behaviour. The model is implemented with a semi-implicit forward gradient finite element method algorithm and the resulting code is used to perform numerical simulations and calculate thermally induced residual stress fields in MMCs. Several tests are performed on a continuously reinforced MMC and a short cylindrical particle MMC in order to optimize the algorithm and define its governing parameters. Good agreement was obtained with results from other authors. Copyright (C) 2001 John Wiley & Sons, Ltd.

关键词： metal matrix composites residual stresses numerical simulation optimization algorithm material behaviour

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Design of diffractive optical element for true beam smoothing

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OPTICS COMMUNICATIONS 2001年第4-6期189卷 167-173页

作者： Tan, QF Yan, YB Jin, GF Wu, MX Tsing Hua Univ State Key Lab Precis Measurement Technol & Instru Beijing 100084 Peoples R China

Diffractive optical element (DOE) can be used for beam smoothing. The phase of the DOE is generally designed by the optimization algorithm. In optimization, the intensities of the sampling points on the focal plane are optimized to be consistent with the required beam smoothing, but the other points are not consistent with such a requirement. In this paper. a new method with a more restrictive way in the optimization is proposed to design the DOE for realizing a true beam smoothing. The result obtained by this new method is that the intensity of any point on the focal plane is fully filled with the required demand, besides the used sampling points in the optimization. (C) 2001 Published by Elsevier Science B.V.

关键词： diffractive optical element true beam smoothing optimization algorithm

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Stochastic parameter tuning applied to space vehicle flight control design

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2001年第3期24卷 597-604页

作者： Miyazawa, Y Motoda, T Natl Aerosp Lab Guidance & Control Lab Flight Div Tokyo 1828522 Japan

The feasibility of applying the stochastic parameter tuning method to the design of space vehicle flight control systems is studied. Stochastic parameter tuning is a form of optimization by which the probability of the flight control system's total mission achievement is maximized, Mission achievement probability is estimated by applying the Monte Carlo method to the results of a large number of simulated flights, The flight simulation models contain various types of uncertain parameters, the stochastic properties of which are defined a priori. The flight control system requirements are defined based on the results of the flight simulations, and an optimization algorithm called the mean tracking technique is used to tune the feedback/feedforward gains and other adjustable parameters of the flight control laws to maximize the probability of satisfying the requirements. The feasibility of the stochastic parameter tuning method is demonstrated by applying it to the design of the flight control system of a reentry space vehicle, a low speed subscaled model of which was flight tested in 1996, The stochastic parameter tuning method improves the robustness of the flight control system, Although stochastic parameter tuning requires large computational resources, the recent advent of low-cost, high-performance computers means that it has become feasible and practical. Furthermore, distributed computation can allow a large number of flight simulations to be conducted within limited time and cost constraints. An asynchronous parallel computation using distributed low-cost computers is applied to the Monte Carlo flight simulation.

关键词： Control System Design Stochastic optimization Proportional Integral Derivative Space Vehicle Developments optimization algorithm Space Vehicle Flight Control Design Guidance Laws Probability Distribution Functions Landing Performance Attitude Control

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