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首页> 外文期刊>IEEE Transactions on Signal Processing >Bias-remedy least mean square equation error algorithm for IIR parameter recursive estimation
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Bias-remedy least mean square equation error algorithm for IIR parameter recursive estimation

机译:IIR参数递归估计的偏差补救最小均方方程误差算法

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In the area of infinite impulse response (IIR) system identification and adaptive filtering the equation error algorithms used for recursive estimation of the plant parameters are well known for their good convergence properties. However, these algorithms give biased parameter estimates in the presence of measurement noise. A new algorithm is proposed on the basis of the least mean square equation error (LMSEE) algorithm, which manages to remedy the bias while retaining the parameter stability. The so-called bias-remedy least mean square equation error (BRLE) algorithm has a simple form. The compatibility of the concept of bias remedy with the stability requirement for the convergence procedure is supported by a practically meaningful theorem. The behavior of the BRLE has been examined extensively in a series of computer simulations.
机译:在无限脉冲响应(IIR)系统识别和自适应滤波领域,用于递归估计工厂参数的方程式误差算法具有良好的收敛性,因此众所周知。但是,这些算法在存在测量噪声的情况下给出有偏差的参数估计。在最小均方方程误差(LMSEE)算法的基础上提出了一种新的算法,该算法可以在保持参数稳定性的同时,对偏差进行补救。所谓的偏倚补救最小均方方程误差(BRLE)算法具有一种简单的形式。偏倚补救的概念与收敛过程的稳定性要求的相容性得到了实用上有意义的定理的支持。 BRLE的行为已在一系列计算机模拟中进行了广泛检查。

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