weighted matrix
英 [ˈweɪtɪd ˈmeɪtrɪks]
美 [ˈweɪtɪd ˈmeɪtrɪks]
网络 加权矩阵
双语例句
- The sensitivity and expansibility of this model were integrated by analysis the weighted conjunction matrix, an application was presented to illustrate the effectivity of the model.
通过对模型的权重邻接阵的分析来整合模型的扩展性和灵敏性，并通过应用验证了该模型的有效性。 - The precise relationship between the singular value decompositions of a weighted extended matrix and its original matrix is derived by using the properties of Kronecker product.
利用Kronecker积的性质得到加权延拓矩阵的奇异值分解与原矩阵（母矩阵）的奇异值分解的定量关系。 - By extending the method of spatial weighted matrix, brings forth the conception of spatial entity association matrix and spatial entity state association matrix, gives the method of their establishment and offers new basic tools for SDM.
通过对空间权重矩阵进行拓展，提出了空间实体关联矩阵和空间状态关联矩阵的概念，并给出了建立方法，为空间数据挖掘提供了新的基础工具。 - When the optimal regulator is designed for the same controlled system, if the weighted matrix Q and R are different and the response performance will be different too.
对于同一种控制对象设计最优调节器时，二次型指标中加权矩阵Q和R的选择不同，系统的动态性能也不一样。 - In the second part, weighted matrix Pad é-type approximation by introducing a set of scalar weights { ω_k} for the generating polynomial v ( z) is presented. Three explicit determinant formulas are given.
第二部分对生成多项式v（z）引入数量权因子{ωk}，构造了加权的矩阵Padé-型逼近，并给出了它的三种行列式公式。 - And then based on the K-nearest-neighbour rule, the weighted matrix of samples is computed. Lastly, weighted hybrid C-means clustering based on the K-nearest-neighbour rule is presented.
然后以K近邻规则为基础，计算出样本集的加权矩阵，最后得到基于K近邻加权的混合C均值聚类算法。 - Then the sparse solution in frequency domain can be obtained through computing the weighted matrix equation.
然后求解这个加权矩阵方程，得到频率域的稀疏解。 - The selection of optimum weighted matrix
最优加权矩阵的选取 - In order to improve the precision of the fusion estimation, this paper presents the optimal information fusion fix-interval smoother based on the multi-sensor optimal information fusion criterion weighted by matrix in the linear minimum variance sense. The algorithm considers the correlation of estimation errors among local subsystems.
为了提高融合估计的精度，采用矩阵加权线性最小方差意义下的最优信息融合准则，对多传感器系统，考虑局部估计误差之间的相关性，给出了最优信息融合固定区间平滑器算法。 - Choice of Weighted Matrix of LQ Problem for Second Order Discrete System
二阶离散系统LQ问题加权阵的选择 - A Method of Weighted Matrix Selection for Hydroturbine Linear Optimal Regulator
水电机组线性最优调节器加权矩阵的确定方法 - In the algorithm the weighted matrix Q, R need not be determined first.
本算法无需首先确定二次型性能指标中的加权阵Q，R。 - The problem of choosing weighted matrix of LQ for second order discrete system in the case of single input is discussed here in the article.
本文针对单输入条件下二阶定常线性离散系统，讨论了线性二次型（LQ）问题中加权阵的选择问题。 - A kind of neural networks learning algorithms for multiple-pattern pairs weighted matrix
多模式对连接权矩阵的一种神经网络学习算法 - A method is proposed for selecting the weighted matrix for the hydroturbine linear optimal regulator.
给出一种适合于水电机组线性最优调节器的加权矩阵的确定方法&基于次时间最优控制的加权矩阵的确定方法。 - Also proved and given are analytic relations between weighted matrix and the multinomial eigenvalue of the System and that between weighted matrix and both open-loop and close-loop systems when close-loop is stable.
证明并给出了当要求闭环系统是渐近稳定时，加权阵与系统开、闭环特征多项式之间以及系统开、闭环极点之间的一组解析关系式。 - A kind of neural networks learning algorithms for multiple-pattern pairs weighted matrix of fuzzy associative memories ( FAMs) and its strict theoretic proofs are presented in this paper.
该文提出多模式对连接权矩阵的一种神经网络学习算法，并给出了严格的理论证明。 - Weighted Matrix Pad é-type Approximation and Its Applications in Control Theory
加权的矩阵Padé-型逼近及其在控制论中应用 - Then under the precondition of choosing specific weighted matrix to ensure the stability of lower-order closed-loop system, and by applying the controller order reduction technique based on frequency-weighted left coprime factorization ( FWLCF), the order of designed controller is reduced, and corresponding simulations are carried out.
进而在选取特定加权矩阵保证降阶闭环系统稳定前提下，应用基于频率加权左互质分解的控制器降阶方法，对所设计的高阶H∞控制器进行降阶。 - Therefore, similar to the algorithm of enhance basis matrix sparseness method, this paper give an algorithm for learning more sparseness information of the weighted matrix, and given the iterative formula.
因此，与增强基矩阵稀疏性方法类似，本文还给出一种增强权矩阵稀疏性的非负矩阵分解算法，并给出了相应的迭代公式。 - For example, local features is not obvious enough, the sparseness of the weighted matrix is not strong, slow convergence speed and so on.
例如，提取的局部特征不够明显，权值矩阵的稀疏性不强，算法的收敛速度慢等，这些都使得非负矩阵分解在人脸识别中的应用不是很完美。 - Based on the principle of the generalized subspace approach ( GSA), the filter matrix could be expressed as the multiplication of projection matrix, coefficient weighted matrix and reconstruction matrix.
根据广义子空间法原理，推出了滤波矩阵的结构可以表示为投影矩阵、系数加权矩阵与重构矩阵的连乘。 - This index evaluation model combining the generating unit, fuzzy degree index selection, evaluation model is simple and effective, and the measures;( 2) According to the theory of fuzzy mathematics to design a weighted matrix evaluation model of automatic.
该指标生成模型结合了评估单位的特点，利用模糊度进行指标筛选，实现了评价模型的简单、有效、因地制宜；（2）根据模糊数学的原理设计一个加权矩阵的自动评估模型。 - By weighted covariance matrix estimating local surface variation, an octree-based subdivision of the box bounding the point cloud is created.
该方法对点云建立包围盒，通过权化的协变矩阵估计局部点云曲面变化，并进行自适应的八叉树细分。 - The selection principle of weighted matrix is discussed in terms of the fundamental of optimal control theory, hence to sum up three procedures using heuristic method to design optimal controller.
根据最优控制理论基本原理，讨论了加权矩阵的选取原则，总结出试探法设计最优控制器的三个步骤。 - The algorithm improves the sparseness degree of the weighted matrix, which makes the distance between the basis matrixes bigger, the number of zero increased, recognition efficiency improved and the information of the original image increased.
该算法提高了权值矩阵的稀疏度，使得权矩阵中数据之间的差异更大，零的数量增多，识别的效率提高，所包含的关于原图像的信息量明显增大。 - The weighted evaluation matrix is determined by using AHP and fuzzy theory to.
运用层次分析法与模糊理论确定评价指标的加权矩阵。 - For this reason, we propose a sample weighted orthogonal subspace projection algorithm, by defining the weighted autocorrelation matrix to estimation background, and then use the orthogonal subspace projection method to detect the targets.
为此，提出了一种加权正交子空间投影算法，通过自定义的加权自相关矩阵估计背景，然后用正交子空间投影法来进行目标探测。 - Firstly introducing the generalized method of moments through classic moments estimation, and describing the fundamental principle of GMM, the choosing of weighted matrix, the distribution of GMM estimator, orthogonality condition and the test of hypothesis in detail.
首先由经典矩估计引出了广义矩方法，并详细介绍了广义矩估计的基本原理，权重矩阵的选择，GMM估计量的分布，正交性条件以及假设检验。 - With respect to the sparsity and discrete of multi-dimensional data, a nuclear fuzzy clustering algorithm under weighted matrix association rules is given with agreement in the original analysis of intrusion detection and other correlation algorithms, from which we can get preprocessing data.
针对多维数据的稀疏性和离散性特点，本文在原有关联算法的基础上，提出了一种矩阵加权关联规则的核模糊聚类算法。