SPECTRAL DENSITY ESTIMATION FROM NONLINEARLY OBSERVED DATA
研究了已知瞬时非线性函数下，基于输出观测数据估计输入平稳高斯过程谱密度的方法，证明了估计量的均方相合性，并给出了偏差和协方差的渐近表达式及渐近正态性。
Abstract. The estimation of the spectral density function of a stationary Gaussian process at the input of an instantaneous nonlinearity is considered when the nonlinearity is known and a finite set of observations of the output process is given. A class of spectral estimates is considered and their quadratic‐mean consistency is established; precise asymptotic expressions for their bias and covariance are derived and their asymptotic normality is obtained.