非最小相位线性系统的可辨识性及辨识方法--非平稳输入
Identifiablity and Identification Algorithms for Non-minimum-phase Linear Systems--non-stationary Input Case
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摘要: 非平稳过程在实际中是大量遇到的,该文研究当系统输入是不可量测的非平稳过程时,系 统相位的可辨识性及辨识方法.文中给出了一般性结论并与平稳条件下所得的结果[1]进行 了比较.对零初始条件下的渐近平稳过程这一非平稳特例做了较详细的研究给出了若干有意 义的结果.这些结果比较合理地解决了由系统的幅谱恢复非最小相位系统的相位信息的问 题.Abstract: This paper discusses the identifyability and identification algorithms for the non-minimum-phase linear system with unmeasurable non-stationary input. General results are given and are compared with the conclusions under stationary inputs. If the initial state of the system is zero and the input is one-sided white noise, the input and output of the system are approximately stationary. This is a special case for non-stationary processes. The results obtained for this special case solving are more practical for solving the problem of the unique recovery of the impulse response from amplitude spectrum.
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Key words:
- stochastic systems /
- system identification /
- deconvolution
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