In this paper,we consider a multiple-input single-output(MISO)Hammerstein system whose inputs and output are disturbed by unknown Gaussian white measurement noises.The parameter estimation of such a system is a typica...In this paper,we consider a multiple-input single-output(MISO)Hammerstein system whose inputs and output are disturbed by unknown Gaussian white measurement noises.The parameter estimation of such a system is a typical errors-in-variables(EIV)nonlinear system identification problem.This paper proposes a bias-correction least squares(BCLS)identification methods to compute a consistent estimate of EIV MISO Hammerstein systems from noisy data.To obtain the unbiased parameter estimates of EIV MISO Hammerstein system,the analytical expression of estimated bias for the standard least squares(LS)algorithm is derived first,which is a function about the variances of noises.And then a recursive algorithm is proposed to estimate the unknown term of noises variances from noisy data.Finally,based on bias estimation scheme,the bias caused by the correlation between the input–output signals exciting the true system and the corresponding measurement noise,resulting in unbiased parameter estimates of the EIV MISO Hammerstein system.The performance of the proposed method is demonstrated through a simulation example and a chemical continuously stirred tank reactor(CSTR)system.展开更多
当MISO(Multi Input Single Output)系统存在的加性人工噪声服从一般分布时,系统保密容量讨论难度较大。为推导一般意义多天线系统下的保密容量,引入了信道等效特征的概念。利用信道特征阐明了人工噪声方法的物理概念,并推导出了具有普...当MISO(Multi Input Single Output)系统存在的加性人工噪声服从一般分布时,系统保密容量讨论难度较大。为推导一般意义多天线系统下的保密容量,引入了信道等效特征的概念。利用信道特征阐明了人工噪声方法的物理概念,并推导出了具有普适性的人工噪声方法保密容量上下限,进一步结合熵功率,推导出AWGN信道下的保密容量解析式。理论分析和仿真得出,通过人工噪声可使平均保密容量增大,从而提高MISO系统的安全性。展开更多
基金supported in part by the National Natural Science Foundation of China(62373070 and 52272388)in part by the Chongqing Natural Science Foundation(CSTB2024NSCQ-QCXMX0054,CSTB2022NSCQ-MSX1225 and CSTC2024YCJH-BGZXM0042)in part by the Key Research and Development Project of Anhui Province(202304a05020060).
文摘In this paper,we consider a multiple-input single-output(MISO)Hammerstein system whose inputs and output are disturbed by unknown Gaussian white measurement noises.The parameter estimation of such a system is a typical errors-in-variables(EIV)nonlinear system identification problem.This paper proposes a bias-correction least squares(BCLS)identification methods to compute a consistent estimate of EIV MISO Hammerstein systems from noisy data.To obtain the unbiased parameter estimates of EIV MISO Hammerstein system,the analytical expression of estimated bias for the standard least squares(LS)algorithm is derived first,which is a function about the variances of noises.And then a recursive algorithm is proposed to estimate the unknown term of noises variances from noisy data.Finally,based on bias estimation scheme,the bias caused by the correlation between the input–output signals exciting the true system and the corresponding measurement noise,resulting in unbiased parameter estimates of the EIV MISO Hammerstein system.The performance of the proposed method is demonstrated through a simulation example and a chemical continuously stirred tank reactor(CSTR)system.
文摘当MISO(Multi Input Single Output)系统存在的加性人工噪声服从一般分布时,系统保密容量讨论难度较大。为推导一般意义多天线系统下的保密容量,引入了信道等效特征的概念。利用信道特征阐明了人工噪声方法的物理概念,并推导出了具有普适性的人工噪声方法保密容量上下限,进一步结合熵功率,推导出AWGN信道下的保密容量解析式。理论分析和仿真得出,通过人工噪声可使平均保密容量增大,从而提高MISO系统的安全性。
