基于BP神经网络的昼夜节律信号源系统识别

Y. Cisse, Y. Kinouchi, H. Nagashino, M. Akutagawa
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引用次数: 2

摘要

一些生物信号源的动态可以通过测量数据来识别。本文以BP神经网络为例,研究了昼夜节律的调节特性。因此,神经网络的MA模型可以获得这些特征。醒睡时间的变化几乎受前3天数据的抑制。动态的变化可以通过网络的内部表示来评估。这种方法可能对医学诊断有用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
System identification of a circadian signal source using BP neural networks
The dynamics of some biological signal sources may be identified through measured data. The regulating characteristics of the wake-sleep circadian rhythm is identified here as an example by using BP neural networks. As a result, a MA model of neural networks can acquire the characteristics. The change of wake-sleep period is almost controlled suppressively by the data of preceding three days. The change of the dynamics can be evaluated by internal representation of the network. This method may be useful for medical diagnoses.
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