spectral analysis of operators

spectral analysis of operators的基本解释

-

算子的谱分析

与spectral analysis of operators相关的网络例句 [注：此内容来源于网络，仅供参考]

For an abitrary set X, appropriate order relations on WCL (the set of all weak closure operators), WIN (the set of all weak interior operators), WOU (the set of all weak exterior operators), WB (the set of all weak boundary operators), WD (the set of all weak derived operators), WD*(the set of all weak difference derived operators), WR (the set of all weak remote neighborhood system operators) and WN (the set of all weak neighborhood system operators) can be defined respectively, which make WCL, WIN, WOU, WB, WD, WD*, WR and WN to be complete lattices that are ismorphic to CS(X,CS is the set of all closure systems on X.

证明了可以在WCL(X上的弱闭包算子的全体)、 WIN(X上的弱内部算子的全体)、 WOU (X上的弱外部算子的全体)、 WB (X上的弱边界算子的全体)、WD、 WD*(X上的弱差导算子的全体)、 WR(X上的弱远域系算子的全体)和WN(X上的弱邻域系算子的全体)上定义适当的序关系，使它们成为与CS(X，〖JX-*5[JX*5]同构的完备格其中CS(X是给定集合X上的闭包系统的全体。

The influences of the shock thickness and Alfven waves on the particle acceleration by diffusive shock waves are numerically studied through solving one-dimensional diffusive equation including the second-order Fermi effect. It is shown that the spectral index of the energetic particles strongly depends on the shock thickness. For example, the spectral index increases from 2.1 to 3.7 in the low energy range of 3-10 MeV and from 2.5 to 5.0 in the high energy range of 20-60 MeV as the thickness increases. The spectral index decreases from 4.3 to 3.1 as the particle injection energy increases. The spectral index decreases from 4.0 to 1.8 at the quasi-steady stage with the enhancement of the compression ratio from 2 to 4. The results indicate that under the influence of Alfven waves, the energetic particle spectrum at lower energy becomes flat and the spectral index decreases from 2.5 to 0.6 in the low energy range of 3-10 MeV and from 11.6 to 5.0 in the high energy range of 20-60 MeV. At the same time, the rollover energy reaches 19.6 MeV. The spectral index decreases from 5.8 to 2.9 as the energy density of Alfven waves increase. All these results are basically consistent with the theoretical models, as well as the observations of typical energetic particle events.

通过数值求解包含二阶费米加速的一维扩散方程，探讨在准平行激波条件下激波厚度和级联阿尔芬波对粒子加速的影响，研究粒子分布函数的演化与激波厚度和阿尔芬波强度的内禀关系，计算结果表明：(1)考虑激波厚度时，谱指数明显依赖于激波厚度，随着厚度从0.32增大到2.56，低能端(3-10MeV)谱指数逐渐从2.1增加到3.7，高能端(20-60MeV)谱指数从2.4增大到5.0，能谱逐渐变软；当初始注入粒子动量增大1.3倍，质子能谱指数从4.3减小到3.1，且与零厚度激波加速的谱指数差值缩小；厚度不变时，随着压缩比从2增加到4，准稳态分布时低能端(3-10MeV)粒子能谱指数逐渐从4.0减小到1.8谱变硬；(2)在级联阿尔芬波的影响下，随着时间的增大，粒子在低能处(3-10MeV)的谱指数从2.5减小到0.6高能端(20-60MeV)谱指数从11.6减小到5.0，能谱变硬，拐点能量值从7.5MeV增大到为19.6MeV；随着波的能量密度增大，谱指数从5.8减小到2.9，这表明阿尔芬波强度越大，加速效率越高，通过与激波厚度解析结果和高能粒子事件的观测能谱比较发现两者是一致的，说明数值模拟结果是可靠的。

The following results are made from this research: Assessing data quality and band combination of different bands in line with geo-target features in desertification areas, and determining basic bands for desertification monitoring. And understanding and studying the spectral features and variation rules of geo-targets in the experimental area, raising that it is the basis of geo-targets information collection with imaging spectrometer data to understand spectral features and variation rules of geo-targets, realizing that in a great extent spectral-integrated-form-based classification method can remove the phenomenon of "different spectrum with same objects" resulted from reflection ratio curve translation because of the angle change among sensor, targets and observation direction, and the average and variance images can be introduced to solve the problem of two kinds of geo-target with similar spectral forms and much different values of whole reflectionratio. It is suggested that "red edge" range bands of vegetation, which has close relationship with vegetation cover and biomass, is the main characteristic bands and important basis for careful vegetation classification and quantitative retrieval, and pixel-based derivative spectral analysis is very useful for removing the effects of soil background values and quantitatively retrieving vegetation biomass and cover. The remote sense quantitative retrieval model is developed for main appraisable factors of desertification monitoring assessment with imaging spectrometer data and then the applicability of model is analyzed.

研究结果如下：首先针对荒漠化地区的地物特征，对高光谱数据不同波段的数据质量、波段组合进行了评价，提出了适用于荒漠化监测的基本波段选择集；初步了解和掌握了研究地区的地物光谱特性及变异规律，进一步明确了掌握地物光谱特征和变异规律是用成像光谱仪数据提取地物信息的基础；发现了基于光谱整体形状的分类方法在很大程度上能够消除由于传感器、地物目标观测方向之间的角度变化引起的反射率曲线整体平移的"同物异谱"现象，对于谱形相似而整体反射率的值相差较大的两类地物，通过引入均值和方差图像参与分类得到解决；研究还表明在植被"红边"范围内的波段是进行荒漠化监测的主要特征波段，这些波段与植被生物量和盖度都有密切的关系，是开展精细植被分类研究和植被定量反演的重要基础；像元的导数光谱分析可以消除土壤背景的影响，是进行植被生物量和盖度定量反演的有力工具；建立了荒漠化监测主要评价因子的定量反演模型，并分析了模型的适用性。

与spectral analysis of operators相关的网络解释 [注：此内容来源于网络，仅供参考]

spectral analysis of operators：算子的谱分析

specificity 特性 | spectral analysis of operators 算子的谱分析 | spectral decomposition 谱表示