Deconvolution and Estimation of Transfer Function Phase and Coefficients for Nongaussian Linear Processes
研究非高斯线性过程，证明其传递函数相位可在宽泛条件下估计，而高斯过程则不能；利用双谱估计相位，并应用于非最小相位传递函数的反卷积问题，附有计算示例。
NonGaussian linear processes are considered. It is shown that the phase of the transfer function can be estimated under broad conditions. This is not true of Gaussian linear processes and in this sense Gaussian linear processes are atypical. The asymptotic behavior of a phase estimate is determined. The phase estimates make use of bispectral estimates. These ideas are applied to a problem of deconvolution which is effective even when the transfer function is not minimum phase. A number of computational illustrations are given.