Time Dependent Hurst Exponent in Traffic Time Series

交通时间序列的经验模式分解，岳建海，董科强，本文应用传统的非线性经验模式分解分析交通数据，抽取出交通周期信号。即使嵌入信号波动幅度很小，经验模式分解方法也能够进行高

timeseriesusingRlanguage

Spectrum occupancy information is necessary in a cognitive radio network (CRN) as it helps in modeli

时间序列分析课件，假设以及如何验证在不同假设下如何应用不同的模型

关于时间序列大数据分析的外文书籍。Introductiontotimeseries.pdf（第三版）+DeepTimeSeriesForecastingwithPython.pdf【高清】

Multiscale multifractality of air traffic flow volume time series characterizes the operation and th

Time dependent problems frequently pose challenges in areas of science and engineering dealing with

Introduction to Statistical Time Series

这是关于时间序列与动态模型的电子书，高清，最新版本，经典著作，英文版

Classicalbookforfinancialtimeseries,adoptedbyalotoffirst-tiercolleges.