sparsity

Sparsity is here defined as the average number of non-zero components in the vector representation of data .

此处，稀疏度指得是每一文本样本所表征的矢量中非零特征项的平均统计数。

This thesis introduces the Sparsity of Matrix and Quantized Energy of AC sub-low frequency coefficients for the Q-DCT matrix .

针对量化后DCT矩阵系数的特点，引入AC次低频系数稀疏度和量化后能量的概念。

It is necessary and possible to lead the concept of sparsity into of labor value .

将稀少性的概念引入劳动价值论既有必要，也有可能

Research of Data Sparsity Problem in Recommendation Systems Based on Collaborative Filtering

基于协同过滤推荐系统的数据稀疏性问题研究

Data sparsity problem is a potential challenge of collaborative filtering .

数据稀缺性问题是协同过滤技术面临的主要挑战。

Based on it , the incompletely sparsity problem is also put forward .

并在此基础上，提出了非完全稀疏性的问题。

Sparsity of source data sets is one major reason causing the poor quality .

数据集的极端稀疏是造成推荐质量低的主要原因之一。

We proposed an object tracking algorithm based on sparsity feature and color feature .

提出结合稀疏性和颜色的方法实现目标追踪的算法。

Sparsity has been successfully used to develop more efficient learning machines .

稀疏性理论已被成功应用于许多机器学习方法中。

Research of Sparsity and Cold Start Problem in Collaborative Filtering

协同过滤系统的稀疏性与冷启动问题研究

A New Algorithm of Solving the Sparsity of Matrix in Collaborative Filtering

一种解决协作过滤中矩阵稀疏性问题的算法

The application of sparsity technology evidently makes the matrix calculation of power system more efficient .

稀疏技术在电力系统中的应用显著提高了电力系统矩阵运算的效率。

Recently , sparsity is introduced into image processing and is widely utilized .

近年来，稀疏概念被引入到图像处理领域，且应用非常广泛。

An Improved DOA Estimation Method Based on Sparsity Constraint

改进的稀疏约束波达方向估计方法

Successive Over Relaxation Iteration Method to Find the Solution of Sparsity Linear Equation System

稀疏线性方程组求解的逐次超松弛迭代法

Sparsity Node Ordering Technology Based on Genetic Algorithms

基于遗传算法的稀疏节点优化编号方法

It discusses the exploitation of sparsity in large LP problems as used in practice .

对高阶线性规划问题实际应用的稀疏技术的开发作了探讨。

As reported in the literature , UWB signals show remarkable sparsity .

已有研究表明，超宽带信号具有很强的稀疏性。

By using sparsity matrix technique and recursion , it can also be used in the larger system .

后者算法结构较前者复杂，程序实现困难，但由于采用了稀疏矩阵技术，并用递推法修正因子表，所以可以应用于规模较大的系统。

In this paper , investigate the nonlinear inverse problem of sparsity constraint regularization .

本文研究了非线性反问题的稀疏约束正则化方法。

Sparsity of the target and the sampling rate on the reconstructed image quality also has been analyzed .

并对目标物体稀疏性和采样率对图像恢复质量的影响进行了分析。

However , recommender systems on vertical e-commerce sites facing the problem of data sparsity .

然而，垂直电子商务网站上个性化推荐却面临着数据稀疏的困扰。

It is necessary and possible to lead the concept of sparsity into the theory of labor value .

将稀少性的概念引入劳动价值论既有必要，也有可能。

An Iterative Approach to DOA Estimation Based on Beam Space Pre processing and Sparsity Constraint

基于波束空间的后验稀疏约束迭代DOA估计方法

It is hard to cluster high-dimensional data using traditional clustering algorithm because of the sparsity of data .

在高维空间中，由于数据的稀疏性，传统的聚类方法难以有效地聚类高维数据。

Sparsity representation model of permuted alias image is obtained by its mathematical model .

首先，根据这类置换混叠图像的数学模型，得到其稀疏表示的模型。

The Bandelet bases could realize best sparsity expression for the geometry regular image .

对于几何正则图像，采用Bandelet基函数可以实现最稀疏表示。

The sparsity of the edges is considered in the regularization model .

为该正则化模型引入了边缘稀疏约束，并研究了求解方法。

The precondition of the CS theory is the sparsity of the signal .

信号的稀疏特性是压缩感知理论应用的前提。

Data set size , dimensionality and sparsity have been identified as aspects that make cluster more difficult .

数据集合的大小，数据的维数和数据的稀疏性都是制约聚类的不同方面。