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本文研究系统辨识中小波基展开模型的优化问题。优化准则借用了经典辨识方法中的阶次判定准则。仿真结果表明,与原小波基模型相比,优化小波基模型不仅保留了原模型的辨识精度,而且模型简化,辨识工作量降低。
In this paper, we study the optimization problem of the wavelet base expansion model in system identification. The optimization criterion borrows the criterion of order judgment in the classical identification method. The simulation results show that, compared with the original wavelet base model, the optimized wavelet base model not only retains the recognition accuracy of the original model, but also simplifies the model and reduces the identification workload.