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Model validation tests for multivariable nonlinear models including neural networks

 

作者: S. A. BILLINGS,   Q. M. ZHU,  

 

期刊: International Journal of Control  (Taylor Available online 1995)
卷期: Volume 62, issue 4  

页码: 749-766

 

ISSN:0020-7179

 

年代: 1995

 

DOI:10.1080/00207179508921566

 

出版商: Taylor & Francis Group

 

数据来源: Taylor

 

摘要:

A fast and concise MTMO nonlinear model validity test procedure is derived, based on higher order correlation functions, to form a global-to-local hierarchical validation diagnosis of identified MEMO linear and nonlinear models. The new procedure is applied to four MIMO nonlinear system models including a neural network training example, to demonstrate the effectiveness of the tests.

 

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