Multiwavelength elastic lidar is often used to probe the aerosol profiles of the atmosphere. Normally, the atmosphere is considered homogeneous and an a-priori aerosol ratio is given for each wavelength channel which ...
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ISBN:
(纸本)0819451231
Multiwavelength elastic lidar is often used to probe the aerosol profiles of the atmosphere. Normally, the atmosphere is considered homogeneous and an a-priori aerosol ratio is given for each wavelength channel which is then processed independently. However, it is clear that the multiwavelength retrieved backscatter profiles should contain information that can be used to estimate particle size distribution which may provide a new estimate to range dependant aerosol ratio profiles which can be repeated until convergence. In this paper, we illustrate the basic idea of using multiwavelength data using a two wavelength lidar to obtain local information on the lidar ratio which can be used to improve lidar profiling in inhomogeneous atmospheres and show that a key feature of any scheme is the monotonic dependance between the optical data ratio and the distribution parameter. In addition. we extend the approach to a prototypical Nd:YAG three wavelength (355, 532, 1064 nm) lidar arrangement and show that while an iterative lidar procedure can be used to extract range dependant profiles, imprecision in the inversion procedure as well as error propagation of the lidar back integration can hamper convergence.
This paper deals with the mixed H-2/D-stability control problem. In this paper, we give an iterative algorithm for finding a sub-optimal controller of this problem. The proposed algorithm produces a controller which s...
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ISBN:
(纸本)4907764227
This paper deals with the mixed H-2/D-stability control problem. In this paper, we give an iterative algorithm for finding a sub-optimal controller of this problem. The proposed algorithm produces a controller which satisfies a necessary condition to be globally optimal controller of the mixed H-2/D-stability control problem. Numerical examples show the effectiveness of our algorithm.
The purpose of this paper is to introduce and study a new class of generalized strongly mixed implicit quasi-variational inequalities in Hilbert spaces, which includes the known class of generalized mixed implicit qua...
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The purpose of this paper is to introduce and study a new class of generalized strongly mixed implicit quasi-variational inequalities in Hilbert spaces, which includes the known class of generalized mixed implicit quasi-variational inequalities as a special *** applying the auxiliary variational principle technique, the existence of solutions for this class of quasi-variational inequalities is proved. Moreover, a new iterative algorithm for computing approximate solutions is constructed and the convergence criteria for this iterative algorithm are also established.
An Improved iterative Reprojection Reconstruction (IIRR) from a view of integral equation for incomplete image reconstruction is presented. IIRR is convergence under L2 norm. The convergent velocity and the error of t...
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An Improved iterative Reprojection Reconstruction (IIRR) from a view of integral equation for incomplete image reconstruction is presented. IIRR is convergence under L2 norm. The convergent velocity and the error of the reconstructed image depend on the relaxed parameter, the detected data and some prior information on image. The reconstructed image can be expressed in term of a series of image reconstructed by the detected data. Numerical simulation also shows that IIRR is effective to image reconstruction.
Identification of the channel matrix is of main concern in wireless MIMO (Multiple Input Multiple Output) systems. Here, we present an SVO-based approach for blind identification of the main independent parallel chann...
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Identification of the channel matrix is of main concern in wireless MIMO (Multiple Input Multiple Output) systems. Here, we present an SVO-based approach for blind identification of the main independent parallel channels. The right and left singular vectors are estimated directly (no channel matrix estimation is necessary) and continuously updated during normal transmission. The approach is related to the iterative Power Method (8), as well as the time reversal approach ([4]).
作者：
Youn, BDChoi, KKUniv Iowa
Ctr Comp Aided Design Coll Engn Iowa City IA 52241 USA Univ Iowa
Dept Mech Engn Coll Engn Iowa City IA 52241 USA
During the past decade, numerous endeavors have been made to develop effective reliability-based design optimization (RBDO) methods. Because the evaluation of probabilistic constraints defined in the RBDO formulation ...
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During the past decade, numerous endeavors have been made to develop effective reliability-based design optimization (RBDO) methods. Because the evaluation of probabilistic constraints defined in the RBDO formulation is the most difficult part to deal with, a number of different probabilistic design approaches have been proposed to evaluate probabilistic constraints in RBDO In the first approach, statistical moments are approximated to evaluate the probabilistic constraint. Thus, this is referred to as the approximate moment approach (AMA). The second approach, called the reliability index approach (RIA), describes the probabilistic constraint as a reliability index. Last, the performance measure approach (PMA) was proposed by converting the probability measure to a performance measure. A guide for selecting an appropriate method in RBDO is provided by comparing probabilistic design approaches for RBDO from the perspective of various numerical considerations. It has been found in the literature that PMA is more efficient and stable than RIA in the RBDO process. It is found that PMA is accurate enough and stable at an allowable efficiency, whereas AMA has some difficulties in RBDO process such as a second-order design sensitivity required for design optimization, an inaccuracy to measure a probability of failure, and numerical instability due to its inaccuracy. Consequently, PMA has several major advantages over AMA, in terms of numerical accuracy, simplicity, and stability. Some numerical examples are shown to demonstrate several numerical observations on the three different RBDO approaches.
The authors describe a technique for selectively sharpening only edges that were blurred due to various causes without making interference factors such as random noise more conspicuous. The selective sharpening techni...
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The authors describe a technique for selectively sharpening only edges that were blurred due to various causes without making interference factors such as random noise more conspicuous. The selective sharpening technique described in this paper is implemented as an iterative updating nonlinear algorithm obtained by discretizing a type of nonlinear reaction-diffusion time-evolution equations. The update terms of this algorithm consist of a quadratic nonlinear smoothing term, reaction term, and overshooting term. By performing quantitative evaluation experiments, the authors showed that the proposed technique has significantly better selective sharpness enhancement capabilities than existing sharpness enhancement techniques such as the peaking method. in addition, the authors introduced a processing parameter adaptive control method in the proposed technique and applied it to the suppression of breathing distortions in video sequences. Breathing distortions, which are video sequence distortions that often appear in old films, are time-varying blurring distortions that occur due to temporal variations of the focus. (C) 2004 Wiley Periodicals, Inc.
An iterative adaptive pole placement algorithm is presented. The stability and the convergence of the algorithm are respectively established. Since one-step iterative formulation in computing controller's paramete...
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An iterative adaptive pole placement algorithm is presented. The stability and the convergence of the algorithm are respectively established. Since one-step iterative formulation in computing controller's parameters is used, the on-line computation cost is greatly reduced with respected to the traditional algorithm. The algorithm with the feed-forward can follow arbitrarily bounded output. The algorithm is also extended to multivariate case. Simulation examples show the efficiency and robustness of the algorithm.
A proximal iterative algorithm for the mulitivalue operator equation 0 ∈ T(x) is presented, where T is a maximal monotone operator. It is an improvement of the proximal point algorithm as well know. The convergence o...
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A proximal iterative algorithm for the mulitivalue operator equation 0 ∈ T(x) is presented, where T is a maximal monotone operator. It is an improvement of the proximal point algorithm as well know. The convergence of the algorithm is discussed and all example is given.
In this paper a globally convergent Lagrange and barrier function iterative algorithm is proposed for approximating a solution of the traveling salesman problem. The algorithm employs an entropy-type barrier function ...
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In this paper a globally convergent Lagrange and barrier function iterative algorithm is proposed for approximating a solution of the traveling salesman problem. The algorithm employs an entropy-type barrier function to deal with nonnegativity constraints and Lagrange multipliers to handle linear equality constraints, and attempts to produce a solution of high quality by generating a minimum point of a barrier problem for a sequence of descending values of the barrier parameter. For any given value of the barrier parameter, the algorithm searches for a minimum point of the barrier problem in a feasible descent direction, which has a desired property that the nonnegativity constraints are always satisfied automatically if the step length is a number between zero and one. At each iteration the feasible descent direction is found by updating Lagrange multipliers with a globally convergent iterative procedure. For any given value of the barrier parameter, the algorithm converges to a stationary point of the barrier problem without any condition on the objective function. Theoretical and numerical results show that the algorithm seems more effective and efficient than the softassign algorithm. (C) 2001 Elsevier Science Ltd. All rights reserved.
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