特征指数 meaning in English
character index
characteristic exponent
Examples
- The variation trajectory of liapunov exponents of car - following fleet and the variation orderliness of average speed , average headway and average space on steady condition were discussed
文章从分析城市快速道路跟车行为入手，利用李雅普诺夫特征指数，定性与定量相结合，讨论了跟驰车队中的混沌特性。 - In chapter five , let { xt , i 1 } be - mixing sequences with identical distributions , which belong to domain of normal attraction with non - generational and stable distribution . with probability one , we have limsup a . s
第五章，设x _ n ， n 1是同分布-混合序列，其分布属于特征指数为( 0 2 )的非退化稳定分布的正则吸引场，证明了依概率1有 - Phase space reconstruction technology and characteristic indices algorithms , which show the wide prospects of engineering application , are presented to in order to distinguish dynamical behavior underlying observed time series from rub - impact rotor
提出了具有工程化前景的相空间重构技术和统计特征指数算法，以评判碰摩转子观测数据所隐含的动力学行为。 - In chapter 3 , firstly , we do some demonstration on the long memory character and the statistical cycle of the return series using the r / s analysis method and the dfa method , and we do some research on the stability of the r / s analysis method , the difference and the contact between the two methods too . secondly we account the characteristic index and the tail index of the fractal distribution , we do some demonstr - ation study on the tail index of our country ’ s return series . lastly we summarize the results of our demonstration
第三章中,首先运用r / s分析法和dfa法对中国股市收益率的长记忆性和统计循环周期进行了实证研究,并且研究了r / s分析法的稳定性以及r / s分析法与dfa法的区别与联系,其次我们论述了分形分布中的特征指数以及尾部指数,对中国股市收益序列的尾部指数进行了实证研究,最后总结了实证研究的结果。 - We try to use the proposed method to understand of information processes in brain . main works of the dissertation are as follows : firstly , introduced the model of wang - smith cnn , and its dynamics characteristics , such as lyapunov exponent ( le ) , bifurcation and dissipative have been analyzed thoroughly . based on this , an improved wang - smith cnn is proposed , whose dynamics characteristics also have been analyzed thoroughly
本文所作的工作主要有：首先，简要介绍wang - smith混沌神经网络模型并深入分析该模型的动力学特性，这主要包括两个方面：一方面是分析只含有一个神经元时系统的lyapunov特征指数、分岔现象以及系统的耗散性；另一方面是分析含有多个神经元时系统的lyapunov特征指数和系统的耗散性。