| 引用本文: | 王 英,阎平凡.基于状态空间模型的最小熵反褶积[J].控制理论与应用,1994,11(3):309~314.[点击复制] |
| WANG Ying,YAN Pingfan.Minimum Entropy Deconvolution Based on State Space Model[J].Control Theory and Technology,1994,11(3):309~314.[点击复制] |
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| 基于状态空间模型的最小熵反褶积 |
| Minimum Entropy Deconvolution Based on State Space Model |
| 摘要点击 1677 全文点击 391 投稿时间：1992-06-15 修订日期：1993-03-01 |
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| DOI编号 |
| 1994,11(3):309-314 |
| 中文关键词 反褶积 反褶积辨识 信号处理；非最小相位系统 |
| 英文关键词 deconvolution system identification signal processing non-minimun phase system |
| 基金项目 |
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| 中文摘要 |
| 本文提出了基于状态空间模型的最小熵反褶积方法用于辨识非最小相位系统。该方法用状态空间模型对系统建模，首先用最小二乘反褶积估计对应真实系统的最小相位系统，然后用由最优平滑器估计的输入序列构造熵函数搜索具有真实相位的系统，利用主导极点的概念提出了启发式搜索算法，大大减少了搜索时间。仿真及应用于实际数据均表明本文方法是行之有效的。 |
| 英文摘要 |
| In this paper, the method of minimum entropy deconvolution is proposed to identify the non-minimum phase system. The system is modelled as the state space model. Least square deconvolution is used to identify the minimum phase system corresponding to the system of the true phase, that is to estimate the amplitude spectrum of the system. The phase of the system is searched according to the entropy which is the function of the input sequence estimated by the optimal smoother. The heuristic search algorithm is proposed from the idea that a system has the leading poles which dominate the transient response of the system. The searching time is greatly reduced by this algorithm. |