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，然后用由最优于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．
In this paper, the method of minimum entropy deconvolution is proposed to identify the non-mini mum phase system .The system is modelled as the state space model .Least square deconvolutde spectrum 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 quence estimated by the optimal smoother,The heuristic search algorithm is proposed froposed 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.It is shown that the method is effective both fron simulation and from applying it to the real selsmic data.
出处
《控制理论与应用》
EI
CAS
CSCD
北大核心
1994年第3期309-314,共6页
Control Theory & Applications
关键词
反褶积
系统辨识
最小熵
deconvolution
system identification
system identification
signal processing
non-minimum phase system
