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矩阵算法     
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  matrix algorithm
     A MATRIX ALGORITHM ABOUT SET FIRSTVT(P)
     集合FIRSTVT(P)的矩阵算法
短句来源
     Matrix Algorithm of Fuzzy System Structure Analysis
     模糊系统结构分析的矩阵算法
短句来源
     MATRIX ALGORITHM OF INTERIOR-OUTER-SET MODEL
     内集-外集模型的矩阵算法
短句来源
     Rigidity matrix algorithm of elastic beam and its application
     弹性梁刚度矩阵算法及应用
短句来源
     Explicit Matrix Algorithm of Energy Level Efficiencies
     能级效率显式矩阵算法
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  matrix algorithms
     Implementation of Indicating Matrix Algorithms in Analyzing Reticulated Structures
     网壳结构的指示矩阵算法
短句来源
     The experimental data are dealt with two matrix algorithms, and the conclusions from these are compared.
     采用两种矩阵算法对实验数据进行处理,并对结果进行比较和分析。
短句来源
     Based on the analysis of the oil/gas transmission network, the matrix algorithms of shortcut in the chart theory are smartly used to select locations of petroleum gathering/transmission stations, which make the overall transmission distance of the petroleum products shortest and the logistic cost of the ‘down stream’operation of petroleum industry lowest.
     在分析石油天然气运输物流网络的基础上,巧妙地将图论中最短路的矩阵算法应用于石油集输站的选址问题,使成品油的总运输距离最短,从而把石油工业的“下游”作业的物流成本降到最低。
短句来源
  matrix arithmetic
     Matrix Arithmetic of Network Maximal Flux and Minimal Separate Set
     网络最大流与最小割集的矩阵算法
短句来源
     EXERGY LOSS DISTRIBUTION MATRIX ARITHMETIC OF REGENERATIVE SYSTEMS OF COAL-FIRED POWER UNIT
     火电机组回热系统火用损分布的矩阵算法
短句来源
     OPTIMIZED MATRIX ARITHMETIC OF LINE FAULTLOCATION BASED ON FIELD TERMINAL UNIT
     基于现场监控终端的线路故障定位优化矩阵算法
短句来源
     In this paper,application about discernibility matrix arithmetic and HORAFA arithmetic based on the rough set theory is introduced.
     简要介绍了粗糙集理论中区分矩阵算法和HORAFA算法在知识约简中的应用。
短句来源
     Matrix arithmetic of network maximal flux and minimal separate set not only solves these problems,but also solves some other problems by the computer such as minimal fee,distribution and transport.
     网络最大流与最小割集的矩阵算法,不仅能解决许多这类问题,而且能使最小费用流、分配问题和运输问题容易通过计算机来实现。
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  matrix computation
     Guan have introduced matrix computation for information systems.
     Guan等提出了信息系统下的矩阵算法
短句来源
     The concept of equivalent matrix, which expresses equivalent relation, is introduced; the relations between equivalent matrix and equivalent classification are discussed. Proposed algorithm for data cleaning and rule extraction in knowledge system based on matrix computation and its complexity of computation is analyzed.
     本文在等价矩阵概念的基础上,分析了粗糙集知识系统中等价划分与等价矩阵的关系,采用等价矩阵来表示粗糙集的等价关系,提出了一种对数据库知识系统进行数据清洗、从中提取决策规则的矩阵算法,并分析了该算法的计算复杂性。
短句来源
     Matrix Computation for Assignment Reduction and Rule Extraction in Incomplete Information Systems
     不完备信息系统分配约简与规则提取的矩阵算法
短句来源
     MATRIX COMPUTATION FOR DATA CLEANING AND RULE EXTRACTION IN INFORMATION SYSTEM
     信息系统数据清洗、规则提取的矩阵算法
短句来源
     Based on a Rough Attribute Vector Tree (RAVT),two kinds of fast matrix computation algorithms—Recursive Matrix Computation (RMC) method and Parallel Matrix Computation (PMC) method are proposed for data cleaning and rules extraction finished synchronously in rough information system.
     借助于粗糙属性向量树(RAVT)的巧妙构造,提出了两种能同时完成属性约简、数据清洗和规则提取的快速递推矩阵算法(RMC)和分布式并行矩阵算法(PMC).
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  matrix algorithm
A matrix algorithm for computing the stationary state probabilities of the system at arbitrary instants and at instants of arrival and completion of service of primary customers is obtained.
      
The matrix algorithm expansions of the vectors of these forms are calculated.
      
The governing equations were discretized in tridiagonal matrix form and were solved by using the tridiagonal matrix algorithm (TDMA) as well as the alternative direction implicit (ADI) solver.
      
A matrix algorithm for computing the free space distance of TCM signal sequences
      
The matrix algorithm is derived from the Viterbi algorithm, and is an implementation of Viterbi algorithm in the form of matrix.
      
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  matrix algorithms
We use the Euler, Jacobi, Poincaré, and Brun matrix algorithms as well as two new algorithms to evaluate the continued fraction expansions of two vectorsL related to two Davenport cubic formsg1 andg2.
      
Their periods and fundamental domains are found and the expansions of the multiple root vectors of these forms by means of the matrix algorithms due to Euler, Jacobi, Poincaré, Brun, Parusnikov, and Bryuno, are computed.
      
Their periods and fundamental domains are found and the expansions of the multiple root vectors of these forms by means of the matrix algorithms due to Euler, Jacobi, Poincaré, Brun, Parusnikov, and Bryuno, are computed.
      
A recursive approach to cell matrix algorithms is considered and applied to the QR factorization by the rotation method.
      
Parametric and matrix algorithms for calculating heterogeneous states in systems with an incongruently melting binary compound
      
更多          
  matrix arithmetic
Models are designed in a geometry language which supports vector and matrix arithmetic, transformations and instancing of primitive parts.
      
Hierarchical matrices provide a technique for the data-sparse approximation and matrix arithmetic of large, fully populated matrices.
      
This is obtained by trying to perform as much as possible of the matrix arithmetic associated with the solution of the linear equations at each step in advance of that step and in parallel with the integration of earlier steps.
      
The PE, which can be configured as a multiplier-accumulator or an inner product step processor, supports several of the most common systolic algorithms in signal processing and matrix arithmetic.
      
A Sparse Matrix Arithmetic Based on $\Cal H$-Matrices.
      
更多          
  matrix computation
By means of the construction theory of self-adjoint operators and matrix computation, we obtain a sufficient and necessary condition to ensure that the product operator is self-adjoint, which extends the results in the second order case.
      
We present a mathematically rigorous and, at the same time, convenient method for systolic design and derive systolic designs for three matrix computation problems.
      
Different implementations for this method, both dense and sparse, have been developed, using a number of linear algebra software libraries (including sparse linear equation solvers) and optimized sparse matrix computation strategies.
      
Covariance matrix computation of the state variable of a stationary Gaussian process
      
Communication complexity of matrix computation over finite fields
      
更多          
  其他


Let A be any nxn matrix and J, its Jordan canonical form. A nonsingular matrix T which satisfies.T-1AT=J, is called a transformation matrix.In this paper, an algorithm is developed for obtaining the Jordan canonical form J of matrix A and for producing simultaneously a transformation matrix T when all the different eigenvalues of A are known.In [2], a different algorithm, is also proposed. Unfortunately, some mistakes have been found there. The basic idea of [2] is described as follows: suppose that V is the...

Let A be any nxn matrix and J, its Jordan canonical form. A nonsingular matrix T which satisfies.T-1AT=J, is called a transformation matrix.In this paper, an algorithm is developed for obtaining the Jordan canonical form J of matrix A and for producing simultaneously a transformation matrix T when all the different eigenvalues of A are known.In [2], a different algorithm, is also proposed. Unfortunately, some mistakes have been found there. The basic idea of [2] is described as follows: suppose that V is the linear space of n dimensions , is an eigenvalue of A and B = A-I.Denoting V0= { 0 }, W0= V, then one may successively construct spaces Vt and Wi in the way that Wi= V1+1 + Wi+1, Vi+1 Wi+ 1 = { 0 }. Vi+1 = {xWi| Bx Vi} and the process may terminate when dim Vm+1= 0. [2] says that V'm=V1+V2 +defines the subspace of V, which corresponds to the eigenvalue of A, and V can be written as the direct sum of invariant subspaces V= V'm Wm. This is not true. For example, if which satisfies all the above conditions, i.e.,We take W1 = V1+W1=V and V1 W1= {0}. From W1 we can obtain the space V2If we take W2 as the spaces and it satisfies the conditions that W1= V2+W2And V2 W2 = {0}, then dim V3= 0.In fact, V3= {x W2|Bx V2}. Since x W2, x must be of the form aand Bx = On another hand, any vector y V2, must be of the form Thus, if Bx V2, a must be zero, and it follows that dim Vs= 0.V2' = V1 + V2 = is an invariant subapace, but W2 = > is not.The algorithm proposed in this paper gives corrections to the mistakes of [2]. Furthermore it is proved that for any matrix A, the matrix T produced by the computations with our algorithm is indeed a transformation matrix.

本文给出一种计算任意复方阵的Jordan标准形的变换矩阵的算法,并证明按照给出的算法计算结果得到的一个矩阵确是所要求的Jordan标准形的变换矩阵。

In this paper the algorithms for geometric transformation of image data and the decomposition of the image matrix into submatrices are introduced. When the image is digitized in the line scanning mode, the geometric transformation of the two dimensional image matrix can be realized by two one-dimensional geometric transformations, i.e., first carrying out the geometric transformation along the scanning lines and then rotating the image matrix through 90 degrees and carrying out the geometric trans formation...

In this paper the algorithms for geometric transformation of image data and the decomposition of the image matrix into submatrices are introduced. When the image is digitized in the line scanning mode, the geometric transformation of the two dimensional image matrix can be realized by two one-dimensional geometric transformations, i.e., first carrying out the geometric transformation along the scanning lines and then rotating the image matrix through 90 degrees and carrying out the geometric trans formation in the other direction. These algorithms can be implemented in a minicomputer system with an appropriate software and a special-purpose hardwired device, so that it can reduce the computing time effectively and is adaptable in minicomputer digital image processing systems.

本文提出一种实现图像几何形状变换及图像数据分解成子矩阵的算法和装置。由于采用软件和专用解算装置相结合的方法,因此能有效地节省计算机处理时间,并适用于在小型计算机图像处理系统中,实现影像的几何畸变纠正及影像和线划图的投影变换。

A sparse matrix algorithm for the modified nodal approach to network analysis is presented.It takes full advantage of both the diagonally dominant property of the nodal admittance matrix and the symmetric property of sparseness structure. Its storage requirements are small and execution time is less.

本文给出一个适合于改进型节点法的稀疏矩阵算法。该算法既利用了节点导纳矩阵的对角优势,又充分利用了稀疏结构的对称性。具有存贮节省,执行快速的特点。

 
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