|
|||||
|
|
| 非均匀采样系统多新息随机梯度辨识性能分析 | |
| 引用本文： | 丁洁,谢莉,丁锋.非均匀采样系统多新息随机梯度辨识性能分析[J].控制与决策,2011,26(9):1338-1342. |
| 作者姓名： | 丁洁 谢莉 丁锋 |
| 作者单位： | 江南大学控制科学与工程研究中心,江苏无锡,214122 |
| 基金项目： | 国家自然科学基金项目(60974043) |
| 摘 要： | 针对一类非均匀采样系统，提出了其输入输出表达的多新息随机梯度辨识方法．该方法将随机梯度算法中的新息项扩展为向量，有效利用了历史新息所包含的信息，从而提高辨识精度和算法的收敛速度，同时又保留了随机梯度算法计算量小的优点．仿真例子通过改变新息长度，验证了所提出辨识算法性能的优越性． |
| 关 键 词： | 非均匀采样 多率系统 随机梯度 多新息辨识 参数估计 |
| 收稿时间： | 2010/4/27 0:00:00 |
| 修稿时间： | 2010/8/4 0:00:00 |
Performance analysis of multi-innovation stochastic gradient identification for non-uniformly sampled systems |
|
| DING Jie,XIE Li,DING Feng.Performance analysis of multi-innovation stochastic gradient identification for non-uniformly sampled systems[J].Control and Decision,2011,26(9):1338-1342. |
|
| Authors: | DING Jie XIE Li DING Feng |
| Affiliation: | DING Jie,XIE Li,DING Feng Control Science and Engineering Research Center,Jiangnan University,Wuxi 214122,China. |
| Abstract: | A state space model is derived for non-uniformly sampled systems.Based on the obtained input/output representation,a multi-innovation stochastic gradient identification algorithm is presented by expanding the scalar innovation to an innovation vector.The proposed algorithm uses both the current innovation and the historical innovations,which improves the stochastic gradient algorithm for the identification accuracy and convergence rate.Simulation example verifies the superiority of the proposed algorithm by... |
| Keywords: | non-uniform sampling multirate systems stochastic gradient multi-innovation identification parameter estimation |
| 本文献已被 CNKI 万方数据 等数据库收录！ | |
| 点击此处可从《控制与决策》浏览原始摘要信息 | |
| 点击此处可从《控制与决策》下载全文 | |