共查询到18条相似文献，搜索用时 359 毫秒
1.
线性约束凸规划的一个新原-对偶路径-跟踪内点算法 总被引：1，自引：0，他引：1
In this paper, a primal-dual path-following interior-point algorithm for linearly constrained convex optimization （LCCO） is presented. The algorithm is based on a new technique for finding a class of search directions and the strategy of the central path. At each iteration, only full-Newton steps are used. Finally, the favorable polynomial complexity bound for the algorithm with the small-update method is deserved, namely, O（√nlog n/ε）. 相似文献
2.
Interior-point methods （IPMs） for linear optimization （LO） and semidefinite optimization （SDO） have become a hot area in mathematical programming in the last decades. In this paper, a new kernel function with simple algebraic expression is proposed. Based on this kernel function, a primal-dual interior-point methods （IPMs） for semidefinite optimization （SDO） is designed. And the iteration complexity of the algorithm as O（n^3/4 log n/ε） with large-updates is established. The resulting bound is better than the classical kernel function, with its iteration complexity O（n log n/ε） in large-updates case. 相似文献
3.
A fault diagnosis model is proposed based on fuzzy support vector machine (FSVM) combined with fuzzy clustering (FC).Considering the relationship between the sample point and non-self class,FC algorithm is applied to generate fuzzy memberships.In the algorithm,sample weights based on a distribution density function of data point and genetic algorithm (GA) are introduced to enhance the performance of FC.Then a multi-class FSVM with radial basis function kernel is established according to directed acyclic graph algorithm,the penalty factor and kernel parameter of which are optimized by GA.Finally,the model is executed for multi-class fault diagnosis of rolling element bearings.The results show that the presented model achieves high performances both in identifying fault types and fault degrees.The performance comparisons of the presented model with SVM and distance-based FSVM for noisy case demonstrate the capacity of dealing with noise and generalization. 相似文献
4.
PAN Yong-juan WANG Guo-jin 《浙江大学学报(A卷英文版)》2007,8(8):1199-1209
In computer aided geometric design(CAGD) ,it is often needed to produce a convexity-preserving interpolating curve according to the given planar data points. However,most existing pertinent methods cannot generate convexity-preserving in-terpolating transcendental curves;even constructing convexity-preserving interpolating polynomial curves,it is required to solve a system of equations or recur to a complicated iterative process. The method developed in this paper overcomes the above draw-backs. The basic idea is:first to construct a kind of trigonometric polynomial curves with a shape parameter,and interpolating trigonometric polynomial parametric curves with C2(or G1) continuity can be automatically generated without having to solve any system of equations or do any iterative computation. Then,the convexity of the constructed curves can be guaranteed by the appropriate value of the shape parameter. Performing the method is easy and fast,and the curvature distribution of the resulting interpolating curves is always well-proportioned. Several numerical examples are shown to substantiate that our algorithm is not only correct but also usable. 相似文献
5.
Based on the predictor corrector, we developed a new improved gradient method named the predictor corrector gradient algorithm (PCGM), which is useful for solving linear equations with symmetric positive definite of coefficient matrix.To improve the speed of convergence of traditional gradient method, we let values of original iterative formula be viewed as forecast values.Meanwhile, they are corrected by a new iterative formula through introducing corresponding step parameter.Therefore, a feasible and efficient algorithm is constructed.Numerical experiments indicate that PCGM method not only improve the accuracy and the speed of convergence, but also greatly reduce the number of steps to converge.The simple algorithm is easy to be realized and operated. 相似文献
6.
Based on minimum output energy,an improved blind multiuser detection algorithm is proposed by the use of Hopfield neural network.Compared with traditional algorithms,the proposed algorithm does not need the circuit for constraints.The resources are greatly saved and the complexity is reduced as well.The simulation results show that the performance of the improved algorithm is similar to that of the optimal multiuser detection algorithm which is not suitable for the mobile station.Compared with the traditional gradient blind multiuser detection algorithm,the convergence speed of the improved algorithm is quickened. 相似文献
7.
Non-Rigid Medical Image Registration with Joint Histogram Estimation Based on Mutual Information 总被引：1，自引：0，他引：1
A mutual information-based non-rigid medical image registration algorithm is presented. An approximate function of Hanning windowed sinc is used as kernel function of partial volume (PV) interpolation to estimate the joint histogram, which is the key to calculating the mutual information. And a new method is proposed to compute the gradient of mutual information with respect to the model parameters. The transformation of object is modeled by a free-form deformation (FFD) based on B-splines. The experiments on 3D synthetic and real image data show that the algorithm can converge at the global optimum and restrain the emergency of local extreme. 相似文献
8.
9.
ZHAO Yong-jie 《重庆大学学报(英文版)》2011,10(2):60-67
The paper presents a new solution of inverse displacement analysis of the general six degree-of-freedom serial robot. The inverse displacement analysis of the general serial robot is transformed into a minimization problem and then the optimization method is adopted to solve the nonlinear least squares problem with the analytic form of new Jacobian matrix. In this way, joint variables of the general serial robot can be searched out quickly under the desired precision when positions of the three non-collinear end effector points are given. Compared with the general Newton iterative method, the proposed algorithm can search out the solution when the robot is at the singular configuration and the initial configuration used in the optimization method may also be the singular configuration. So the convergence domain is bigger than that of the general Newton iterative method. Another advantage of the proposed algorithm is that positions of the three non-collinear end effector points are usually much easier to be measured than the orientation of the end effector. The inverse displacement analysis of the general 6R (six-revolute-joint) serial robot is illustrated as an example and the simulation results verify the efficiency of the proposed algorithm. Because the three non-collinear points can be selected at random, the method can be applied to any other types of serial robots. 相似文献
10.
基于两步几何主动轮廓的快速图像分割 总被引：2，自引：0，他引：2
A fast two-stage geometric active contour algorithm for image segmentation is developed. First, the Eikonal equation problem is quickly solved using an improved fast sweeping method, and a criterion of local minimum of area gradient (LMAG) is presented to extract the optimal arrival time. Then, the final time function is passed as an initial state to an area and length minimizing flow model, which adjusts the interface more accurately and prevents it from leaking. For object with complete and salient edge, using the first stage only is able to obtain an ideal result, and this results in a time complexity of O(M), where M is the number of points in each coordinate direction. Both stages are needed for convoluted shapes, but the computation cost can be drastically reduced. Efficiency of the algorithm is verified in segmentation experiments of real images with different feature. 相似文献
11.
A polynomial interior-point algorithm is presented for monotone linear complementarity problem (MLCP) based on:a class of kernel functions with the general barrier term, which are called general kernel functions. Under the mild conditions for the barrier term, the complexity bound of algorithm in terms of such kernel function and its derivatives is obtained. The approach is actually an extension of the existing work which only used the specific kernel functions for the MLCP. 相似文献
12.
1 Introduction Interior-point methods (IPMs) for semidefinite opti-mization (SDO) have been studied intensively,due totheir polynomial complexity and practical efficiency.In the past decade , SDO has become a popular re-search area in mathematical programming when it be-came clear that the algorithm for linear opti mization(LO) can often be extended to the more general SDOcase. Other two factors are also responsible for thisincreasing interest in SDO. Firstly, SDO has a wideapplication… 相似文献
13.
The choice of self-concordant functions is the key to efficient algorithms for linear and quadratic convex optimizations,
which provide a method with polynomial-time iterations to solve linear and quadratic convex optimization problems. The parameters
of a self-concordant barrier function can be used to compute the complexity bound of the proposed algorithm. In this paper,
it is proved that the finite barrier function is a local self-concordant barrier function. By deriving the local values of
parameters of this barrier function, the desired complexity bound of an interior-point algorithm based on this local self-concordant
function for linear optimization problem is obtained. The bound matches the best known bound for small-update methods.
Project supported by the National Natural Science Foundation of China (Grant No.10771133), the Shanghai Leading Academic Discipline
Project (Grant No.S30101), and the Research Foundation for the Doctoral Program of Higher Education (Grant No.200802800010) 相似文献
14.
针对凸二次规划问题,构造了新的核函数.通过构造的核函数来确定搜索方向和逼近度量,接着给出了求解凸二次规划问题的全牛顿步内点算法,最后给出了算法的复杂性界. 相似文献
15.
给出了一个快速算法决定有限域Fq上周期为upn序列的极小多项式.设p,q,u为不同素数,q为模p2的本原根,m为最小正整数使得qm≡1modu和gcd(m,p(p-1))=1.利用一个算法把有限域Fq上周期为upn序列化为几个有限域Fq(ζ)上周期为pn序列,其中ζ为一个u次本原单位根,从而利用肖国正等的算法得到每个周期为pn序列的极小多项式. 相似文献
16.
Mehrotra's recent suggestion of a predictor-corrector variant of primal-dual interior-point method for linear programming is currently the interior-point method of choice for linear programming. In this work the authors give a predictor-corrector interior-point algorithm for monotone variational inequality problems. The algorithm was proved to be equivalent to a level-1 perturbed composite Newton method. Computations in the algorithm do not require the initial iteration to be feasible. Numerical results of experiments are presented. 相似文献
17.
用于线性优化的基于核函数的动态步长原-对偶内点算法 总被引：1，自引：2，他引：1
In this paper, primal-dual interior-point algorithm with dynamic step size is implemented for linear programming （LP） problems. The algorithms are based on a few kernel functions, including both serf-regular functions and non-serf-regular ones. The dynamic step size is compared with fixed step size for the algorithms in inner iteration of Newton step. Numerical tests show that the algorithms with dynaraic step size are more efficient than those with fixed step size. 相似文献
18.
In this paper, primal-dual interior-point algorithm with dynamic step size is implemented for linear programming (LP) problems.
The algorithms are based on a few kernel functions, including both self-regular functions and non-self-regular ones. The dynamic
step size is compared with fixed step size for the algorithms in inner iteration of Newton step. Numerical tests show that
the algorithms with dynamic step size are more efficient than those with fixed step size.
Project supported by Dutch Organization for Scientific Research (Grant No.613.000.010) 相似文献