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Visual-Fortran2002
- 有数值计算中常用的Visual Fortran子过程近200个,内容包括:解线性代数方程组、插值、数值积分、特殊函数、函数逼近、随机数、排序、特征值问题、数据拟合、方程求根和非线性方程组求解、函数的极值和最优化、傅里叶变换谱方法、数据的统计描述、解常微分方程组、两点边值问题的解法和解偏微分方程组,每一个子程序都包括功能、方法、使用说明、子程序和例子五部分。本书的所有子过程都在Visual Fortran 5.0版本上进行过验证,程序都能正确运行。同时配书发行光盘,包括所有子过程、验证过程及所有验
An-Introduction-to-Parallel-and-Vector-Scientific
- In this text, students of applied mathematics, science and engineering are introduced to fundamental ways of thinking about the broad context of parallelism. The authors begin by giving the reader a deeper understanding of the issues through a genera
CALL
- matlab transformed to C++. Eigenvalue
mi
- 幂法求矩阵特征值的c语言实现,求具体矩阵,3阶矩阵-Power method for matrix eigenvalue c language, seeking specific matrix 3 matrix
Pav
- in this package are the programs needed to solve any eigenvalue problem.
-similarity-measurement-
- similarity measurement ,to get the eigenvalue
EigenvalueDecomposition
- 矩阵的EigenvalueDecomposition分解,矩阵分解中一个非常重要的分解原理。-Eigenvalue decomposition of the matrix, the matrix decomposition decomposition of a very important principle.
UNANR_Matlab
- There is a trend to develop blind or semi-blind source extraction algorithms based on second-order statistics, due to its low computation load and fast processing speed. An important and primary work is done by Barros and Cichocki, who propose an
NCS2011---146---autmented-reality
- 目前擴增實境技術相關應用大部分以使用標記為主,但各式應用需求與日俱增,無標記(markerless)擴增實境技術使用上更具彈性,不必受限於標記的使用,因此應用層面更廣。視覺追蹤技術是擴增實境系統重要底層核心技術之一,但使用視覺追蹤技術在實際應用上易受到追蹤物件本身及外觀變化之影響,因此本文提出適用於無標記擴增實境應用之物件追蹤方法,能有效追蹤各式真實物件。首先框選設定追蹤物件;接著擷取物件特徵值,藉由特徵值比對以持續追蹤物件,並利用金字塔L-K光流法以縮短比對運算時間;最後經由2D-3D座標轉換
opencv-doc
- 图像数据操作(内存分配与释放,图像复制、设定和转换) 图像/视频的输入输出(支持文件或摄像头的输入,图像/视频文件的输出) 矩阵/向量数据操作及线性代数运算(矩阵乘积、矩阵方程求解、特征值、奇异值分解) 支持多种动态数据结构(链表、队列、数据集、树、图) 基本图像处理(去噪、边缘检测、角点检测、采样与插值、色彩变换、形态学处理、直方图、图像金字塔结构) 结构分析(连通域/分支、轮廓处理、距离转换、图像矩、模板匹配、霍夫变换、多项式逼近、曲线拟合、椭圆拟合、狄劳尼三角化)
xpyqr
- 匹配追踪和正交匹配追踪,用谱方法计算流体力学一些流动现象的整体稳定性,AHP层次分析法计算判断矩阵的最大特征值。- Matching Pursuit and orthogonal matching pursuit, Spectral methods of computational fluid dynamics flow of some of the overall stability of the phenomenon, Calculate the maximum eigenvalue jud
fun_ge36
- matlab实现了五类灰色关联度模型的计算,包含特征值与特征向量的提取、训练样本以及最后的识别,利用matlab写成的窄带噪声发生。- matlab implements five gray correlation degree computing model, Contains the eigenvalue and eigenvector extraction, the training sample, and the final recognition, Using matlab writt
ne642
- AHP层次分析法计算判断矩阵的最大特征值,matlab实现了五类灰色关联度模型的计算,计算两个矩阵之间的欧氏距离。- Calculate the maximum eigenvalue judgment matrix of AHP, matlab implements five gray correlation degree computing model, Calculation of the Euclidean distance between the two matrices.
0452
- 采用偏最小二乘法,AHP层次分析法计算判断矩阵的最大特征值,时间序列数据分析中的梅林变换工具。- Partial least squares method, Calculate the maximum eigenvalue judgment matrix of AHP, Time series data analysis Mellin transform tool.
ydqmx
- 利用自然梯度算法,计算多重分形非趋势波动分析,AHP层次分析法计算判断矩阵的最大特征值。- Use of natural gradient algorithm, Calculate the multifractal trend fluctuation analysis, Calculate the maximum eigenvalue judgment matrix of AHP.
dxaqg
- 多机电力系统仿真及其潮流计算,各种kalman滤波器的设计,AHP层次分析法计算判断矩阵的最大特征值。- Multi-machine power system simulation and flow calculation, Various kalman filter design, Calculate the maximum eigenvalue judgment matrix of AHP.
2106
- 包含特征值与特征向量的提取、训练样本以及最后的识别,该函数用来计算任意函数的一阶偏导数(数值方法),基于matlab平台实现。- Contains the eigenvalue and eigenvector extraction, the training sample, and the final recognition, This function is used to calculate the arbitrary function of the first order partial
sc428
- 包含收发两个客户端程序,D-S证据理论数据融合,AHP层次分析法计算判断矩阵的最大特征值。- Transceiver contains two client programs, D-S evidence theory data fusion, Calculate the maximum eigenvalue judgment matrix of AHP.
gj862
- 采用加权网络中节点强度和权重都是幂率分布的模型,包括主成分分析、因子分析、贝叶斯分析,包含特征值与特征向量的提取、训练样本以及最后的识别。- Using weighted model nodes in the network strength and weight are power law distribution, Including principal component analysis, factor analysis, Bayesian analysis, Contains the
hangnan-V4.4
- 高斯白噪声的生成程序,包括脚本文件和函数文件形式,AHP层次分析法计算判断矩阵的最大特征值。- Gaussian white noise generator, Including scr ipt files and function files in the form, Calculate the maximum eigenvalue judgment matrix of AHP.