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基于拟牛顿法的同时扰动随机逼近算法 被引量:4

Simultaneous perturbation stochastic approximation algorithm based on quasi-Newton method
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摘要 基于拟牛顿法原理,结合同时扰动随机逼近算法特性提出了一种搜索方向dk的计算方法,从而提高了同时扰动随机逼近算法的收敛速度和逼近精度.针对典型优化问题分别比较了改进后的同时扰动随机逼近算法、标准同时扰动随机逼近算法及二阶同时扰动随机逼近算法的优化性能,数值分析结果表明:改进后的算法在逼近精度上均优于其他两种算法,收敛速度介于其他两种算法之间. In order to improve convergence speed and approximation precision of simultaneous perturbation stochastic approximation(SPSA),lessons were drawn from Broyden-Fletcher-Goldfarb-Shanno(BFGS)quasi-Newton method,and a computing method of search direction dkbased on SPSA was provided.A typical optimization problem as numerical analysis case was used,and characteristics of the improved SPSA were compared with standard SPSA and the second order SPSA.The results of numerical analysis indicate that the improved SPSA is better than the other two methods at approximation precision aspect,and the performance of convergence speed is between basic SPSA and the second order SPSA.
出处 《华中科技大学学报(自然科学版)》 EI CAS CSCD 北大核心 2014年第9期1-4,共4页 Journal of Huazhong University of Science and Technology(Natural Science Edition)
基金 国家自然科学基金资助项目(61273174 61034006 60874047)
关键词 拟牛顿法 同时扰动随机逼近 搜索方向 收敛速度 逼近精度 quasi-Newton method simultaneous perturbation stochastic approximation search direc-tion convergence speed approximation precision
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参考文献11

  • 1Spall J C.Multivariate stochastic approximation using a simultaneous perturbation gradient approximation[J].IEEE Transaction on Automatic Control,1992,37(3):332-341. 被引量:1
  • 2Steenis R,Rivera D E.Plant-friendly signal generation for system identification using a modified simultaneous perturbation stochastic approximation(SPSA)methodology[J].IEEE Transactions on Control Systems Technology,2011,19(6):1604-1612. 被引量:1
  • 3Lin Zhiqiang,Jia Weimin,Yao Minli,et al.Synthesis of sparse linear arrays using vector mapping and simultaneous perturbation stochastic approximation[J].IEEE Antennas and Wireless Propagation Letters,2012,11:220-223. 被引量:1
  • 4Azim M A,Aung Z,Weidong X,et al.Localization in wireless sensor networks by constrained simultaneous perturbation stochastic approximation technique[C]∥2012 6th International Conference on Signal Processing and Communication Systems.Piscataway:IEEE Press,2012:1-9. 被引量:1
  • 5Zhang F G,Jia W M,Jin W,et al.Beamforming algorithm based on SPSA for mobile satellite receiver[J].Electronics Letters,2012,48(22):1379-1380. 被引量:1
  • 6Wieland J R,Schmeiser B W.Stochastic gradient estimation using a single design point[C]∥Proceedings of the 38th Conference on Winter Simulation.Piscataway:IEEE Press,2006:390-397. 被引量:1
  • 7Spall J C.Accelerated second-order stochastic optimization using only function measurements[C]∥Proceedings of the 36th IEEE Conference on Decision and Control.San Diego:IEEE Press,1997:1417-1424. 被引量:1
  • 8Spall J C.Implementation of the simultaneous perturbation algorithm for stochastic optimization[J].IEEE Transactions on Aerospace and Electronic Systems,1998,34(3):817-823. 被引量:1
  • 9张华军,赵金,王瑞,马坦.基于非线性共轭梯度的同时扰动随机逼近方法[J].华中科技大学学报(自然科学版),2009,37(1):85-87. 被引量:2
  • 10马昌凤.最优化方法及其Matlab程序设计[M].北京:科学出版社,2009.67-69 . 被引量:3

二级参考文献10

  • 1Spall J C. Multivariate stochastic approximation using a simultaneous perturbation gradient approximation [J]. IEEE Transactions on Automatic Control, 1992, 37: 332-341. 被引量:1
  • 2Spall J C. Implementation of the simultaneous perturbation algorithm for stochastic optimization[J]. IEEE Transactions on Aerospace and Electronic Systems, 1998, 34(3): 817-823. 被引量:1
  • 3Spall J C. Accelerated second-order stochastic optimization using only function measurements[C]// Proceedings of the 36th Conference on Decision & Control. San Diego: IEEE Press, 1997, 1 417-1 424. 被引量:1
  • 4Maurin B, Motro R. Investigation of minimal forms with conjugate gradient method[J]. International Journal of Solids and Structures, 2001, 38(14): 2 387-2 399. 被引量:1
  • 5Polak E, Ribiere G. Note sur la convergence de directions conjuguees[J]. Rev Francaise Informat Recherche Operationnelle, 1969, 16: 35-43. 被引量:1
  • 6Ovtchinnikov E E. Jacobi correction equation, line search, and conjugate gradients in hermitian eigenvalue computation Ⅱ: Computing several extreme eigenvalues[J]. SIAM Journal on Numerical Analysis, 2008, 46(5): 2 593-2 619. 被引量:1
  • 7Dai Y H, Yuan Y. A nonlinear conjugate gradient method with a strong global convergence property [J]. SIAMJ Optim, 2000, 10: 177-182. 被引量:1
  • 8Dai Y H, Yuan Y. Nonlinear conjugate gradient methods[M]. Shanghai= Shanghai Science and Technology Press, 2000. 被引量:1
  • 9Dai Y H, Yuan Y. An efficient hybrid conjugate gradient method for unconstrained optimization[J]. Ann Oper Res, 2001, 103: 33-47. 被引量:1
  • 10Wolfe P. Convergence conditions for ascent methods Ⅱ: some corrections [J]. SIAM Rev, 1971, 13: 185-188. 被引量:1

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