稀疏性的英文

• openness

• "稀疏"英文翻译    few and scattered; few and f ...
• "性"英文翻译    nature; character; dispositi ...
• "【医学】稀疏性天花。" 英文翻译 :    discrete smallpox
• "稀疏" 英文翻译 :    few and scattered; few and far between; thin; sparse 稀疏散乱 scattering; 稀疏的晨星 a few scattered morning stars; 稀疏的枪声 scattered shots; sporadic firing; 稀疏的头发 thin hair; sparse hair; 树木稀疏。 the trees are sparse
• "超稀疏" 英文翻译 :    supersparsity
• "使稀疏" 英文翻译 :    rarefy; thin
• "疏部，稀疏" 英文翻译 :    rarefaction
• "稀少；稀疏" 英文翻译 :    sparsity
• "稀疏, 疏松" 英文翻译 :    raritas
• "稀疏冰" 英文翻译 :    loose ice; loose pack ice; open ice; open pack ice; scarf n. sailing ice; scattered ice
• "稀疏波" 英文翻译 :    expansion wave; rarefaction wave; rarefactional wave
• "稀疏的" 英文翻译 :    loose; rarefied; remote; sparse stand; thin stand
• "稀疏地" 英文翻译 :    sparsely
• "稀疏化" 英文翻译 :    rarefaction
• "稀疏毛" 英文翻译 :    open wool
• "稀疏区" 英文翻译 :    rarefied area
• "稀疏图" 英文翻译 :    spares graph; sparse graph
• "稀疏翼" 英文翻译 :    rarefaction fan
• "稀疏酌" 英文翻译 :    rarefaction
• "稀疏冰稀疏冰" 英文翻译 :    loose ice; loose pack ice; open ice; open pack ice
• "稀疏痘, 稀疏天花" 英文翻译 :    variola discreta
• "稀疏冰稀疏漂冰" 英文翻译 :    scattered ice
• "半稀疏草毛" 英文翻译 :    semi-sparse pubescence
• "骨质稀疏" 英文翻译 :    osteoporosis
• "交通稀疏" 英文翻译 :    light traffic

• It can find that the data is high dimension and sparse . we bring forward hsmbk and hssca algorithms to code with the problem
  针对实验数据的高维性、稀疏性等特征，我们提出了hsmbk和hssca两个聚类算法。
• But with the system scale enlarging , its efficiency gradually declines and some problems such as sparsity , scalability and early rater will appear
  但随着系统规模的扩大，它的效能会逐渐降低，暴露出矩阵稀疏性、扩展性和早期级别等问题。
• To conclude a sparse solution , we present an improved algorithm for least squares support vector machines , and prove its effect by an experiment
  对原有的最小二乘支持向量机在稀疏性上进行了改进，并通过实验，对改进后的最小二乘支持向量机的分类效果进行了验证。
• Second , a new wavelet - based denoising method without free parameters is proposed which is based on the sparseness and decorrelation properties of the discrete wavelet transform
  首先提出了一种基于相关邻域模型的sar图像rcs重构方法。其次，利用离散小波变换的稀疏性和减相关性进行sar图像滤波。
• A model - based recommendation algorithm was proposed , which uses multi - level association rules ( mar ) to alleviate those problems about data sparseness and scalability of the recent recommendation algorithm
  摘要提出一种基于多层关联规则( mar )的推荐算法，着重解决目前推荐算法的稀疏性问题和可扩展性问题。
• Abstract a model - based recommendation algorithm was proposed , which uses multi - level association rules ( mar ) to alleviate those problems about data sparseness and scalability of the recent recommendation algorithm
  摘要提出一种基于多层关联规则( mar )的推荐算法，着重解决目前推荐算法的稀疏性问题和可扩展性问题。
• The connection matrix of a network is usually large and sparse . in this article , the auther brought forward a method to reduce the connection matrix order , which was help for saving operation time and space when it is stored in computer
  通过引进矩阵算子并借助于矩阵的分块运算，针对网络联络矩阵的稀疏性，提出一种含表决系统的网络联络矩阵的降阶方法，节约了算法的运行时间和存储空间。
• Sad is able to differentiate models in form of subroutines , fully exploit the sparsity of the models and need few additional operations . it is concluded that sad is very suitable for the process models that have relatively simple computational structure and consist mainly of polynomials
  符号自动微分具有可对子程序形式的函数求导、可以充分利用模型的稀疏性、无需辅助操作的优点，非常适合针对结构相对简单、计算式以多项式为主的过程系统模型求导。
• This paper applies generalized multipler method to translate convex quadratic programs with equal constraints and non - negative constraints into simple convex quadratic programs with non - negative constraints . the new algorithm is gotten by solving the simple quadratic program . it avoids the computation of inverse matrix and exploits sparsity structure in the matrix of the quadratic form . the results of numerical experiments show the effectiveness of the algorithm on large scale problems
  根据广义乘子法的思想，将具有等式约束和非负约束的凸二次规划问题转化为只有非负约束的简单凸二次规划，通过解简单凸二次规划来得到解等式约束和非负约束的凸二次规划新算法，新算法不用求逆矩阵，这样可充分保持矩阵的稀疏性，用来解大规模稀疏问题.数值结果表明：在微机486 / 33上就能解较大规模的凸二次规划
• In the first and second section of chapter 1 we introduce the model of dimension reduction problem , put forward the concepts of dimension - reduction function and embedding function , and make a classification for the dimension reduction problem ; in section 1 . 3 we discuss " the curse of dimension " and the sparsity of high - dimensional space ; in section 1 . 4 we discuss " intrinsic dimension " and its estimation based on the model of dimension reduction
  第一章首先提出了降维的模型和定义，讨论了相关的问题；第三节讨论“维数祸根”现象和高维空间的稀疏性，通过实例分析其对高维空间的数据分布特性具体影响；第四节讨论了本征维数及其估计的基本问题。