提出了随机结构响应密度演化分析的映射降维算法。
A mapping-based dimension-reduction algorithm for probability density evolution analysis of stochastic structural responses is proposed.
本文研究含有线性等式约束的非线性规划问题的降维算法。
In this paper, the descending dimension algorithm for nonlinear programming problems with linear equality constraints are discussed.
本文提出具有线性等式约束多目标规划问题的一个降维算法。
Then we use the descending dimension algorithm to transform the quadratic program problems into solving a system of linear equations.
本文提出具有线性等式约束多目标规划问题的一个降维算法。
Based on the property, a step-by-step degree reduction algorithm was presented.
提出的降维算法，避免了求交的盲目性，提高了速度，而且 不需要过多的附加运算。
The declines dimension algorithm presented in this paper avoids the blindness in begging to hand over, increases speed and omitts the need for excessive affixture calculation.
本文讨论了约束非线性规划问题的降维算法，为非线性规划算法的研究提供了一种新途径。
In this paper, descending algorithms for the constrained nonlinear programming problems are discussed and we offer a new way to research methods of nonlinear programming by that.
模糊粗糙集理论是解决数据集维数问题的有效工具，但基于模糊粗糙集的降维算法还不多。
Fuzzy rough set theory is an effective tool for reduction of data dimension, but there are few dimension reduction algorithms that are based on fuzzy rough set theory so far.
在此基础上，提出了超球投影嵌入支持向量鉴别分析特征降维算法，分层次人脸拒识分类算法。
Then hierachical face recognition with the ability of rejection for non-target and classification for target is proposed.
提出统计不相关的核化图嵌入算法，为求解各种统计不相关的核化降维算法提供了一种统一方法。
An uncorrelated kernel extension of graph embedding which provides a unified method for computing all kinds of uncorrelated kernel dimensionality reduction algorithms is proposed.
最后，根据降秩技术中的交叉谱思想，提出了一种新的对信号子空间维数减少时的处理算法。
Finally, to deal with the situation that the dimension of the signal subspace decreases, a new algorithm is proposed based on the idea of the Cross Spectral Method.
该方法保留了信号的相位信息，并且能够有效地抑制噪声，在降维的同时简化了算法。
This method preserves the signals phase information and inhibits the noise effectively. The calculation dimension is reduced and the algorithm is simplified by using this method.
SVD非常有用的原因是，它能够找到我们矩阵的一个降维表示，他强化了其中较强的关系并且扔掉了噪音（这个算法也常被用来做图像压缩）。
Thereason SVD is useful, is that it finds a reduced dimensional representation ofour matrix that emphasizes the strongest relationships and throws away thenoise.
LPLE算法解决了传统LLE算法在源数据稀疏情况下的不能有效进行降维的问题，这也是其他传统的流形学习算法没有解决的。
LPLE is better than LLE in that it gives the global coordinates of the sparse data and this isn't be resolved by the other conventional algorithm.
实现了基于数据降维的高维数据特征提取算法。
Realizes high, dimension data feature extraction algorithm by using debasing dimension of data.
采用奇异摄动算法使系统降维。
The singular perturbation algorithm is proposed to reduce the system dimension.
非负矩阵分解算法简单，易于实现，并且具有降维、收敛和稀疏等特性。
Moreover, NMF algorithm is simple and easy to implement and it has features such as dimension-lowering and sparse convergence.
为提高计算效率，本方法采用了射线加速技术，包括背面采集、二元空间分区算法和降维处理。
For raising the capacity, this method has used the ray acceleration technology, including that the back gathers and the partition algorithm in binary space and decreasing dimensions.
从简单普适的穷搜(ES)法出发分别建立了降维搜索(RS)算法和AI算法，从而大幅度缩小了搜索空间。
Based on the simple exhaustive search (es) method, a reduced-space search (RS) algorithm and an AI algorithm are developed respectively, which make the search space reduced dramatically.
局部保持投影(LPP)是一种新的数据降维技术，但其本身是一种非监督学习算法，对于分类问题效果不是太好。
Locality Preserving Projections algorithm (LPP) is a new dimensionality reduction technique. But it is an unsupervised learning algorithm. It could not process classification effectively.
局部线性嵌入(LLE)算法是有效的非线性降维方法，时间复杂度低并具有强的流形表达能力。
The Locaally linear Embedding (LLE) algorithm is an effective technique for nonlinear dimensionality reduction of high-dimensional data.
局部线性嵌入(LLE)算法是有效的非线性降维方法，时间复杂度低并具有强的流形表达能力。
The Locaally linear Embedding (LLE) algorithm is an effective technique for nonlinear dimensionality reduction of high-dimensional data.
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