时间序列复杂性自动度量:快速的弹簧测试
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苏州大学电子信息学院 苏州 215006

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TP301

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江苏省自然科学基金( BK20141196 )、江苏省研究生创新基金( KYCX18 _ 2509 )项目资助


Automatic measure of time series complexity: rapid spring test
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School of Electronics and Information Engineering, Soochow University, Suzhou 215006, China

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    摘要:

    提出了时间序列复杂性自动度量的弹簧测试的一种提速方法。弹簧测试包括5阈值压缩空间中的弹簧图,以及该弹簧图的自相似性刻画数值CC。针对其速度较慢的问题,应用峰谷值映射简化弹簧图,提速自相似性度量。测试方程使用小波映射混沌、统一方程、Rossler超混沌方程。以分岔图为基本的对比判别几何特征,以基于FFT的谱熵复杂度为自动度量金标准,对比改进前后弹簧自相似性度量CC值的结果,给出各测试例的稳定性分析及计算时间比较。结果表明:改进后的弹簧测试能明显区别周期与混沌,增加了超混沌与混沌的辨识度,时间上提升2-20倍。本工作为周期、混沌、随机三分类识别的自动选参的信号复杂性度量贡献了改良的弹簧测试方法,本质是快速提取三维相图(弹簧图)的非对称非线性统计不变量。

    Abstract:

    A speed-up method of spring test on automatic measure for time series complexity is proposed, including the spring graph in 5-threshold compressed space and the construction creep (CC) rate. For its slow speed, the specific method uses peak and valley values fitting to simplify the spring diagram and to speed up the self-similarity measuring . We select wavelet mapping chaos, unified equation and Rossler hyperchaos equation as test equations. To take the bifurcation diagram as the basic comparison rule of geometric characteristics and to adopt the spectral entropy complexity (SEC) based on FFT as the gold standard. The results of spring self-similarity measure CC before and after the improvement are compared; The calculation time and stability of each test method is given.The results show that the improved method can distinguish between period and chaos and elevate the resolution ratio of hyperchaos and chaos significantly with 2 to 20 times hoisting in terms of time. This work contributes an improved spring test method for the signal complexity measure featured with automatic parameter selection for distinguishing periodic, chaotic and random states. The essence is to extract the asymmetric nonlinear statistical invariants of three-dimensional phase diagram (the spring diagram).

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程杰,李文石.时间序列复杂性自动度量:快速的弹簧测试[J].电子测量技术,2022,45(6):94-98

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  • 在线发布日期: 2024-05-16
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