火范文>英语词典>sparseness翻译和用法

sparseness

网络  稀少; 稀疏; 稀疏性; 稀疏度; 稀疏化

COCA.37869

英英释义

noun

双语例句

  • But traditional collaborative filtering algorithm has the shortcomings of sparseness, expansibility, and synonymy.
    但传统的协同过滤算法存在着稀疏性、扩展性和同义性的问题。
  • The array antenna with low side lobe is designed by employing the Taylor synthesis and density taper sparseness with an overall consideration of the radiation and scattering performance. The side lobe of the array antenna is optimized by random search.
    在综合考虑辐射和散射特性的基础上利用泰勒综合和密度锥削稀疏技术设计了低副瓣电平阵列天线,并采用随机遍历算法对阵列天线副瓣进行了优化。
  • Application of Combined Norm Constrained Sparseness Spike Inverse
    L1-L2范数联合约束稀疏脉冲反演的应用
  • Sparseness Analysis of Radar Echoes and its Application in Ship and Chaff Discrimination
    雷达回波稀疏性分析及其在舰船与箔条云鉴别中的应用
  • A genetic algorithm with adaptive evaluation function is presented to deal with data sparseness problem in automatic semantic tagging.
    针对数据稀疏问题,采用适应度函数较灵活的遗传算法做语义的自动标注;
  • This strategy can reduce the data sparseness and keep the search efficiency meanwhile.
    这种优化策略可以在保证该算法数据查找效率不变的同时,进一步减少数据稀疏,提高空间利用率。
  • This approach make use of the sparseness of speech signals and the independent characteristics of speech signals. Use the fast quasi-newton method, it greatly simplify the Hessian matrix, and it also greatly increases the speed of operation.
    该方法运用语音信号的稀疏性和语音信号之间相互独立的特性,使用快速相对牛顿法,使得在牛顿法中,求海森阵的步骤大为简化,大大提高了运算速度。
  • K-space data has sparseness after transformation, in order to achieve sparse data space, we can use wavelet transform to transform the K-space data, then use the sparse sampling imaging.
    K空间数据具有变换稀疏性,可使用小波变换对K空间数据进行变换,得到具有稀疏性的数据空间,再进行稀疏采样成像。
  • In this paper, an improved algorithm of image feature extracting for independent component analysis was proposed based on basic functions'maximization of sparseness.
    利用基函数稀疏性的极大值特点,本文提出一种改进的基于独立分量分析的图像特征提取算法。
  • But it also has many problems, such as data sparseness problem, the system scalability problem and time factor problem.
    但协同过滤推荐算法还不够成熟,仍然存在一些问题,如数据稀疏性问题、系统的可扩展性问题和时间因素问题等。