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This paper discusses the importance of general orthonormal bases in system identification, highlighting that the accuracy of variance results can be influenced by fixed poles or zeros in model structures. It introduces new variance expressions that improve accuracy and provide insights into the role of orthonormal bases beyond numerical properties, indicating their fundamental importance in estimation. The authors demonstrate that traditional variance approximations can be misleading and propose modificatio

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hao100085

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EN