小波递推最小二乘法的ARMAX模型参数估计

李振强

【期刊名称】《计算机仿真》 【年(卷),期】2012(29)12

【摘 要】For the linear ARMAX model with the noise corrupted output data, a method of parameter estimation was proposed to estimate the parameters of the model with the input - output data in wavelet domain directly. The least squared (LS) method is an important method for parameter estimation in time domain, with the wavelet transform developed, it plays an important role in signal processing. By means of wavelet transform, the signal has both characteristics of time and frequency and becomes a signal in wavelet domain. Then the denoising result is more effective than in time domain and in frequency domain. The parameters of model were estimated by the wavelet least squared method, compared with the least squared method in time domain, the proposed method is more feasible and effective by the simulation.%研究辨识系统优化问题,针对线性时不变ARMAX模型的参数估计,为了提高辨识精度,提出了直接利用小波域的数据,递推估计出模型的参数的方法.首先将时域的输入输出信号采用小波变换,得到了具有时频特征的小波域信号,可进行去噪方面的处理,去噪结果比时域和频域更有效.然后,利用小波递推最小二乘法对ARMAX模型进行参数估计,通过与时域递推最小二乘法的估计参数比较,仿真结果表明提出的方法是有效的. 【总页数】4页(P119-122)

【作 者】李振强

【作者单位】广西工学院,广西柳州545006 【正文语种】中 文 【中图分类】TP391.9 【相关文献】

1.一种小波系数模型在图像噪声参数估计中的应用 [J], 谢杰成;张大力;徐文立 2.基于小波域数据的线性ARMAX模型参数估计 [J], 李振强 3.基于小波域数据的Hammerstein模型参数估计 [J], 李振强 4.基于小波网络的电力负荷非参数估计模型分析 [J], 万星;丁晶;张晓丽

5.渐消记忆递推最小二乘法在呼吸力学参数估计中的应用 [J], 韩厉萍;张立藩;张荣

因版权原因，仅展示原文概要，查看原文内容请购买