低熵相 的英文怎麼說
中文拼音 [dīshāngxiāng]
低熵相
英文
low-entropy phase-
The entropy or number of states of system or subsystem are closely related to interaction of particles and energy level distribution, therefore, to study the temperature dependence of the specific heat may supply some important and useful microscopic information which may play an important role in understanding electronic structure, density of state, phonon spectrum etc. the specific heat measurements at low temperatures also play important roles in the finding of the third law of thermodynamics, the quantum theory of solid and bcs theory for superconducting etc. moreover, specific heat measurements help us to understand the different kinds of phase transitions ( such as : structural phase transition, magnetic phase transition, superconducting phase transition etc. ) and the scaling behavior near the critical point
系統、子系統的熵或微觀狀態數與微觀粒子間的相互作用及能級分佈密切相關，因此研究比熱與溫度的依賴關系能夠提供被測量系統許多極其有用的微觀信息，對理解固體的電子結構、電子態密度、聲子譜等起著十分重要的作用。低溫比熱的測量和研究對熱力學第三定律、固體量子理論和超導bcs等理論的建立起到了積極的推動作用。比熱研究還有助於認識各類相變如結構相變，磁性相變，超導相變等及臨界點附近的標度規律。Through analysis of potential vorticity in equity - entropy surface field, a relatively high potential vorticity center in cyclone top in low - troposphere have discovered, and make cyclone develop in a more deep cyclone circulation by this ; and an anticyclone circulation zone with more severe low potential vorticity in high - troposphere
通過對等熵面的位渦分析，發現了對流層中低層的位渦場，在氣旋上方有一個相對高位渦中心，由此使得氣旋在一個比較深厚的氣旋性環流中發展；而對流層高層則是一個伴有較強位渦低值的反氣旋環流區。Though asm of eufe is 0. 199 j / kg ? k less than that of gdsige, it can be higher than now if more reasonable process is taken, eufe can become magnetic refrigerant materials in practice some day
二者相比， eufe的磁熵變要低0 . 199j kg ? k ，如果改進工藝，制備單相eufe合金，其磁熵變還會有所提高， eufe合金有可能成為一種實用的磁致冷材料。Entropy of an image is to express the smoothness or homogeneity of the image. while computing in a local window, if there exist edges, the local image will not be homogenous, variation of the grayness will be sharp and the entropy obtained will be low. otherwise, the entropy will be high. given the threshold of entropy, it can be determined whether or not exist edges. because entropy operator is sensitive to noise, the effect is bad if it is directly used to detect edges. in view of the deficiency, the paper comes up with an edge detection method in which entropy operator is combined with noise removal. if the entropy computed is higher than the threshold, it will be necessary to determine whether it is caused by noise or by edges. thus edge detection and noise removal can be made at the same time. with this method satisfactory effect has been achieved by experimenting upon image with low ratio of signal to noise
圖像的熵用來刻劃圖像的平滑性或均勻性.在圖像的局部窗口中計算時，如果窗口中存在邊界，則窗口中的圖像不均勻，其灰度變化急劇，計算出的熵小；反之熵大.設定熵的閾值，即可判斷是否存在邊界.由於熵運算元對噪聲很敏感，直接用它進行邊界檢測，效果很差.文中針對這一缺陷，提出將熵運算元與去噪相結合的邊界檢測法，如果計算出的熵大於閾值，要判斷是噪聲的出現所引起，還是邊界的出現所引起，這樣，邊檢測邊界邊去噪聲.用該方法對信噪比較低的圖像進行實驗，得到了滿意的效果Second, a novel algorithm named model predicition ( mp ) is proposed to wipe off spectral correlations of hyperspectral images. mp algorithm finds the linear model of hyperspectral images, in which predictive coefficients are set up that is based on snr. because predictive coefficients include current spectral band, average entropy of the error data is decreased and snr is increased after mp
Mp演算法建立了高光譜圖像的線性模型，推導出了信噪比意義下的最佳預測系數，由於系數中包含了當前譜帶的數據，因此經過mp演算法去相關之後，殘差圖像的平均熵有所降低，同時信噪比提高很多。Various data compression techniques are studied and summarized in this paper, including the traditional and the newly developed techniques, then analyses the features of pipeline leak signals, such as the mechanism of production, entropy and correlation coefficient, are analyzed, and finally a universal and low - complex lossless compression algorithm is proposed and implemented in the pipeline leak detection and location system
本文研究和總結了國內外傳統和最新發展的各種數據壓縮技術，然後分析了管道泄漏信號的特徵，包括管道泄漏信號的產生機理、信息熵和相關系數，提出了一種適合於管道泄漏檢測定位系統的通用、低復雜度的無損壓縮演算法。This algorithm uses approximate entropy index ' s projection pursuit based on real coding genetic optimize algorithm ( rcgoa - pp ) to project the targets information hided in the high - dimensional data into low - dimensional space and then extract small targets with histogram image segmentation method
該演算法用基於近似相對熵的實碼遺傳優化投影尋蹤方法（ rcgoa - pp ） ，有效地將高維數據中隱藏的目標信息集中投影到低維空間中，並用直方圖分割的方法提取出小目標。分享友人