- 更多网络例句与时标序列相关的网络例句 [注：此内容来源于网络，仅供参考]
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This paper is expanded into three main parts to study and analyze the stock time series.1 Through the normality tests, All the sample stock-data curves show different phenomenon of Aiguille and Fat-tail, as well as Left-Deviation, which proves that none of the sample series belong to normal distribution, in other words, the linear method can't be applied into the analysis process, so we adopted the R/S method instead.2 The application of R/S method has verified the long-term memory characteristics of the sample series, and Support Vector Regression is combined to enhance the precision of Average circle period.
文中对股票时间序列从以下三个方面进行了研究和分析：1通过正态性检验，发现各样本股票数据均表现出不同程度的尖峰和胖尾以及左偏现象，证明了所有的样本序列全都不属于正态分布，也就是说明它们不能够适用线性方法进行分析，必须采用重标极差分析方法的非线性方法。2应用R/S分析方法验证他们具有长期记忆的特性，并且结合支持向量回归机提高了测定平均循环周期时的精确性。
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Finally, the calculation process of CGR graphic's multi-fractal analysis was studied. the scope of choice of the weight factor and the scale invariance range were discussed, the weight factor can be chosen as ? 15≤q≤50; multi-fractal spectrum and generalized dimension of different sequence were calculated, multi-fractal spectrum and generalized dimension in different scales of different sequences were compared, it was found that multi-fractal spectrum and generalized dimension can show different levels of fractal characteristics of CGR graphics of DNA sequence, which can distinguish more complex structure of sequences.
最后，研究了DNA序列CGR图形的多重分形的计算过程，讨论了权重因子及满足标度不变性的范围选择等问题，得到结论：对CGR图形进行多重分形时权重因子可以选择为-15≤q≤50；计算了不同序列的多重分形谱和广义维数，比较了不同序列不同尺度的多重分形谱和广义维数，发现多重分形谱和广义维数能够表现DNA序列CGR图形的不同层次的分形特征，能够区分更复杂的序列结构。
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Systematic studies were performed on the algorithms of rescaled range analysis on theeven-sampled time series.A new approach based upon the random sub-series was presented.Wefound that the fluctuations of the R/S curve corresponding to the non-trivial algorithm stemsfrom the screening effect.A generalization of the R/S analysis from uniformly-spaced time seriesto uneven-sampled series was proposed.
系统研究几种域重标分析算法在分析等间隔时间序列时的优劣，提出了一种基于随机子序列的新算法，并用屏蔽效应来解释平庸的R/S曲线波动的原因，提出了非等间隔的时间序列的R/S分析方法。
- 更多网络解释与时标序列相关的网络解释 [注：此内容来源于网络，仅供参考]
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volume serial number：卷序号
在引导序列计算到根目录和数据区的绝对位移的过程中使用了该值0x27 2 0x52368BA8 卷序号(Volume Serial Number) 在格式化磁盘时所产生的一个随机序号,它有助于区分磁盘0x2B 11 "NO NAME" 卷标(Volume Label) 本字段只能使用一次,