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Convergence of least squares identification algorithms applied to unstable stochastic processes

 

作者: ELI FOGEL,   DANIEL GRAUPE,  

 

期刊: International Journal of Systems Science  （Taylor Available online 1977）
卷期: Volume 8, issue 6  

页码: 612-618

 

ISSN:0020-7721

 

年代: 1977

 

DOI:10.1080/00207727708942067

 

出版商: Taylor & Francis Group

 

数据来源: Taylor

 

摘要:

In this paper we prove the convergence of least squares identification algorithms when applied to unstable signal models. The proof is in terms of the properties of infinite sequences of matrices and of their norms to show that the convergence of least squares identification algorithms applies to unstable deterministic and stochatics processes.

 

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