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光谱比较器

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Light output analysis tests character of spectrum radiate of pyrotechnic mixtures and analyses wave band distribute of light by comparing different static blaze spectrograms of the pyrotechnic mixtures. Screen out the better pyrotechnic mixtures according to request of pumping source. Press experiments in airtight erupt container experiment, which simulate the circumstance that pyrotechnic mixtures deflagrate in quartz pipe, realize the press influence to the quartz pipe wall and the disciplinarian of axes press variety. Apply these pyrotechnic mixtures to Nd:YAG lasers as the pumping source and compare pumping efficiency of different pyrotechnic mixtures. Pumping efficiency is an important standard which checkout if these pyrotechnic mixtures are the better pumping source. Sensitivity experiment analysis incarnate security of pyrotechnic mixtures that is the essential parameter in the process of design, manufacture and use.

通过对烟火药的热分析(爆热分析、DTA、TG),了解备选烟火药反应过程中的能量输出特性及反应过程中的物理、化学变化规律;光输出分析实验对烟火药配方光谱辐射特征进行测试,比较其静态火焰光谱图,分析不同烟火药剂光辐射波段分布特征,根据激光泵浦源的辐射要求,进而筛选更符合激光泵浦源药剂要求的烟火药;模拟烟火药在石英管中爆燃环境的密闭爆发器压力分析实验反映了烟火药在石英管中反应时对管壁的压力影响以及管内轴向压力变化规律;将烟火药作为泵浦源应用于Nd:YAG固体激光器,比较不同烟火药的泵浦效率,作为检验烟火药是否适合作为激光泵浦源的重要标准;感度实验分析体现了各种烟火药的安全性,是烟火药设计、制造和使用的必要示性数。

Finally, we conclude that the spectra have essentially different characterizations for N-atom mazer with N being odd and even integers.

通过对入射原子团包含奇数和偶数个原子的腔场光谱的比较,我们得出了以下结论:对于多原子微激射器,含奇数与偶数原子的入射原子团激发的腔场的光谱的特征存在显著差异。

Brightness of aware sort is the classification norm of distance classification. Distance classification compares brightness between aware sort and unknown pixels. Angle of spectral line is the classification norm of degree classification. Degree classification compares angle of spectral line between aware sort and unknown pixels.

距离分类器是以已知地物类别的亮度值作为分类基准,通过比较未知类别像元与已知类别像元亮度值间的距离进行分类;角度分类器是以光谱谱线角为分类基准,通过比较n维波段空间中未知类别像元与已知类别像元光谱角度进行分类。

SABS can be improved by SAFU for Hyperspectral imageries. The proposed SAFU selects the sets of uncorrelated hyperspectral bands for each different class simultaneously while utilizing the inherent separability of different classes in hyperspectral images to reduce dimensionality and further to effectively generate a unique SAFU feature. The experimental results show that the SAFU approach is effective and can be used as an alternative to the existing feature extraction algorithms.

本文提出的SAFU选取不同类别抽取出不同的波段,同时地利用不同类别在高光谱影像中固有的分离性来缩减维度及更进一步地有效产生一个独特的SAFU特徵,最后实验列举了一些分类正确率有不错表现的分类器与PBF分类器进行一些正确率的比较,实验的结果显示SAFU方法是有效且能够被当作目前现有的特徵萃取演算法中的其中一种。

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