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Self-learning structural identification algorithm

机译:自学习结构识别算法

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摘要

This paper deals with the identification of the dynamic characteristics of structural system. The relevant neural network characteristics of learning algorithm are discussed in the context of system identification. Because of self-learning nature of neural network the identified dynamic characteristics are strongly affected by the level of noise contained in the teaching signals. Using the Kalman filtering technique, a method to identify the dynamic characteristics of structural system proof against contaminating noise in teaching signals has been developed.
机译:本文涉及识别结构系统的动态特性。在系统识别的背景下讨论了学习算法的相关神经网络特征。由于神经网络的自学性质,所识别的动态特性受教学信号中包含的噪声水平的强烈影响。利用卡尔曼滤波技术,已经开发了一种方法,用于识别结构系统证明的动态特性免受教学信号中的污染噪声的动态特性。

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