- 更多网络例句与稀疏相关的网络例句 [注：此内容来源于网络，仅供参考]
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The algorithm uses the wavelet decomposition and reconstruction in multi-resolution editing B-spline curves and transforms a zonal matrix or sparse matrix to a row simplified matrix using the properties of the augmented matrix of the system of linear equations,which is a zonal matrix or sparse matrix,by elementary row operation.
该算法利用方程组的增广矩阵为类带状矩阵或者稀疏矩阵这一特点，运用简单的矩阵的行初等变换，将类带状矩阵或者稀疏矩阵化成容易接受的行简化矩阵，解方程组，使小波分解与重构的过程快速准确，使从事相关工作的技术人员更容易理解和接受。
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This thesis consists of two parts. The first one was that boundary value problem was discrete with five point difference method. Three kinds of memory formats were studied, which were full matrix, half band width and row compress sparse. Full matrix memory format and half band width memory format first was contrasted. The results show that half band width has efficiency in space. Then the algebraic system of finite element method was solved by Gauss-Seidel iteration method to popular row compress sparse memory format.
本论文由两部分组成，第1部分针对边值问题，用5点差分格式进行离散，并对离散矩阵这类大型稀疏矩阵，研究了系数矩阵的3种存储格式的优劣，即：满矩阵存储格式、半带宽存储格式和按行压缩稀疏存储格式，首先我们将满矩阵存储方式和半带宽存储格式进行了对比，迭代法的数值实验表明：利用半带宽存储的矩阵在空间运算方面具有高效性；然后针对目前数值实验中流行的按行压缩稀疏存储格式，实现了有限元离散代数系统的迭代法的求解。
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One points at a sequence of one sparse linear algebra system of equation ,utilizing frequent treatment sparse matrix data structure at present that is according to the competent store structure, design the law of conjugation gradient method which solves the equation group of the sparse linear algebra of asking analyses the complexity of calculating.
第一部分针对一类稀疏线性代数方程组，利用目前国际上使用比较频繁的处理稀疏矩阵的按行稀疏存储结构，设计了求解稀疏线性代数方程组的共轭梯度法，并分析计算复杂度。
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For large sparse matrix,it is very important to keep the sparse of matrix in computation.
引言 在实际计算中，我们常常碰到一类大稀疏矩阵，这类矩阵由于它本身的稀疏性，我们除了研究它的计算量外，更重要的是使这类稀疏矩阵在计算中仍然保持其稀疏性。
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Many applied problems in practice can be summed up as the computation of sparse matrix.
很多实际应用问题经常被归结为稀疏矩阵的计算，文中讨论了稀疏矩阵的压缩存储算法，稀疏矩阵中的元素采用三元组表示法作为它的存储结构。
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The "compressed sparse row data format" is adopted to save storage and the "mode multiplication" is used to improve the computation efficiency, so that the finite integration equation is obtained with low storage and high efficiency. To solve the finite integration equation, which is a large-scale sparse algebraic eigenvalue problem under the condition specified, the Krylov subspace iteration method is introduced and the shift-invert Arnoldi method is proposed to exclude the unphysical static electro-magnetic solution and get the needed eigensolution around the specified eigenvalue.
采用"行索引稀疏格式"压缩存贮技术节约内存，采用大型稀疏矩阵的模式乘法，提高矩阵计算效率，高效获得了离散电场分量满足的有限积分方程；针对有限积分特征方程的求解，论文介绍了大型稀疏矩阵Krylov子空间迭代方法，并提出了位移求逆Arnoldi算法，以排除非物理的静态电磁场解，获得指定频率附近的特征值。
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This paper sets forth non zero element dynamic memory trigonometric decomposition method of large scale sparse positive definite normal equation, which is regular, simple and intuitive, and therefore it is ease to realize in the computer.
本文针对具有正定性质的大型稀疏法方程，提出了大型稀疏正定法方程的非零动态存储三角分解法，运用复式链表来动态存储稀疏矩阵。
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The performances of the proposed method are comparable with those of the matching pursuit. And the speed for image sparse decomposition is greatly improved. It will be help to the research of applications based on overcomplete sparse representation.
该算法在保证稀疏分解性能的同时，极大地提高了稀疏分解的速度，为基于超完备图像稀疏表示的实际应用奠定了基础。
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Supported by the National Science Foundation of China, this thesis concentrates on the image sparse representation theories, methods and the image processing applications based on sparse representation. We make deeply study for the applications based on multiscale geometry analysis, theories of overcomplete sparse image representation and its applications, theories of sparse image representation via combined transforms and its applications.
本文在国家自然科学基金项目&联合基图像稀疏表示理论研究及其应用&的资助下，针对图像稀疏表示理论、方法以及基于稀疏表示的图像处理应用问题，重点围绕多尺度几何分析在图像处理中的应用、基于冗余字典的超完备图像稀疏表示理论及应用、组合变换图像稀疏表示理论及应用等内容进行了探索性的研究。
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According to thefunction, the conclusions for L.olgensis and C.lanceolata are asfollows:1CCF＜200,showing growth with constant tree number;2200≤CCF≤300 transition from growth with constant tree number to theself-thinning,in other words,the change of SDI can be described aslinear combination between the growth with constant tree number andthe self-thinning;3CCF＞300,growth in the self-thinning.
建立了CCF与林分密度指数和单位面积林木株数之间的函数关系式，并对长白落叶松和杉木得出：(1)CCF＜200。林分为等株数生长：(2)200≤CCF≤300时。为等株数生长向自然稀疏生长的过渡期，该期间林分密度指数的变化可用等株数生长和自然稀疏生长的线性组合来表达：(3)CCF＞300时，林分为完全的自然稀疏生长
- 更多网络解释与稀疏相关的网络解释 [注：此内容来源于网络，仅供参考]
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sparse Gaussian elimination：稀疏高斯消除法
未经调查地区;资料稀疏地区 sparse data area | 稀疏高斯消除法 sparse Gaussian elimination | 稀疏矩阵 sparse matrix
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open pack ice：稀疏冰稀疏冰
open pack ice 稀疏冰 | open pack ice 稀疏冰稀疏冰 | open phase 缺相
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open pack ice：稀疏冰
open out 展开 | open pack ice 稀疏冰 | open pack ice 稀疏冰稀疏冰
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loose pack ice：稀疏冰
loose oilring 游滑轮注油环 | loose pack ice 稀疏冰 | loose pack ice 稀疏冰稀疏冰
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loose pack ice：稀疏冰稀疏冰
loose pack ice 稀疏冰 | loose pack ice 稀疏冰稀疏冰 | loose propeller blade 可拆卸的螺旋桨叶
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sparse matrix decomposition：稀疏矩阵分解
稀疏波长变换:Sparse wavelength conversion | 稀疏矩阵分解:sparse matrix decomposition | 稀疏分布存储器:sparse distributed memory
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sparse matrix canonical grid method：稀疏矩阵规则网格法
大型稀疏线性方程组:Large sparse linear systems | 稀疏矩阵规则网格法:sparse matrix canonical grid method | 稀疏线性方程组:sparse systems of linear equations
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sparse vegetation：稀疏植被
稀疏脉冲序列 sparse spike train | 稀疏植被 sparse vegetation | 稀少;稀疏 sparsity
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sparse vegetation：稀疏的植物,稀疏植被
sparse vector 稀疏向量 | sparse vegetation 稀疏的植物,稀疏植被 | sparse wood 稀疏林地
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sparsely：稀少地/稀疏地/薄地
sparse /稀疏/疏/稀/ | sparsely /稀少地/稀疏地/薄地/ | sparseness /稀少/稀疏/薄/