ROBUST IDENTIFICATION OF A NON-MINIMUM PHASE SYSTEM - BLIND ADJUSTMENT OF A LINEAR EQUALIZER IN DATA COMMUNICATIONS
ROBUST IDENTIFICATION OF A NON-MINIMUM PHASE SYSTEM - BLIND ADJUSTMENT OF A LINEAR EQUALIZER IN DATA COMMUNICATIONS
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DOI：
10.1109/tac.1980.1102343
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发表时间：
1980-01-01
影响因子：
6.8
通讯作者：
RUGET, G
中科院分区：
文献类型：
--
作者：
BENVENISTE, A;GOURSAT, M;RUGET, G
考虑一个未知的线性时不变无控制系统，由一个已知分布的白色噪声驱动。我们感兴趣的是这个系统的识别，只观察输出。这个问题在主要假设下是众所周知的：系统是最小的（或最大的！）阶段，其中非常流行的最小二乘法给出了一个自回归形式的系统识别。然而，我们感兴趣的情况下，系统是非最小的（也不是最大的！）相位，即，我们希望识别系统的增益和相位。文献中只给出了一个否定的结果：在高斯驱动噪声的情况下，系统的相位是不可能的（因此，二阶统计量与我们的问题无关）。对于一个大类的其他输入分布，我们提出了一个识别过程，并给出了一些数值结果，我们的研究的一个具体的情况下起源：盲调整的横向均衡器没有任何启动期间之前的数据传输。
Consider an unknown linear time-invariant system without control, driven by a white noise with known distribution. We are interested in the identification of this system, observing only the output. This problem is well known under the major assumption: the system is minimum (or maximum!) phase, in which the very popular least squares method gives an identification of the system in an autoregressive form. However, we are Interested in the case where the system is nonminimum (nor maximum!) phase, i.e., we want identification of both gain and phase of the system. The literature gives only a negative result: the idenfication of the phase of the system is impossible in the case of a Gaussian driving noise (hence, second-order statistics are irrelevant to our problem). For a large class of other input distributions, we present an identification procedure, and give some numerical results for a concrete case origin of our study: the blind adjustment of a transversal equalizer without any startup period prior to data transmission.