Stochastic Realization of Nonminimum Phase Systems

研究具有有理传递函数的线性时不变非最小相位系统的随机实现问题。该问题包括估计自回归移动平均模型的参数，或等效的极点和零点。该研究的新颖之处在于考虑了非最小相位模型，即。其中基础离散系统的零点位于单位圆外。针对非最小相位系统的随机实现问题，提出了两种方法，并期望它们能够仅从输出数据中重建振幅和相位信息。随机实现问题的解决将为参数谱和多谱估计提供一种方法，这在声纳和地震数据处理、语音编码、自适应控制和构建通信系统均衡器等应用中具有重要意义。+

The aim of this research is to solve the stochastic realization problem for linear time-invariant non-minimum phase systems which possess rational transfer functions. This problem consists of estimating the parameters, or equivalently the poles and zeros, of an autoregressive moving average model. The novelty of the research lies in the consideration of non-minimum phase models, ie. those in which the zeros of the underlying discrete system lie outside the unit circle. Two approaches to the stochastic realization problem for non-minimum phase systems are proposed, and it is expected that they will allow the reconstruction of both amplitude and phase information from output data only. Solution of the stochastic realization problem will provide a method for parametric spectral and polyspectral estimation which is important in such applications as estimating the source signature in sonar and seismic data processing, speech coding, adaptive control and constructing equalizers for communication systems. +