This paper concerns the identification problem of scalar errors-in-variables (EIV) systems with general nonlinear output observations and ARMA observation noises. Under independent and identically distributed (i.i.d.) Gaussian inputs with unknown variance, recursive algorithms for estimating the parameters of the EIV systems are presented. For general nonlinear observations, conditions on the system are imposed to guarantee the almost sure convergence of the estimates. A simulation example is included to justify the theoretical results.

中文翻译：

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带有一般非线性输出观测值和ARMA观测噪声的变量误差系统的识别

本文涉及具有一般非线性输出观测值和ARMA观测噪声的标量变量错误（EIV）系统的识别问题。在具有未知方差的独立且均匀分布的（iid）高斯输入下，提出了用于估计EIV系统参数的递归算法。对于一般的非线性观测，会施加系统条件以保证估计值几乎可以肯定地收敛。包括一个仿真例子来证明理论结果是正确的。