搜索资源列表
ConsoleJava
- DotNet版的线性方程的解法,包括:高斯消元法,用于n阶非奇异矩阵;SVD分解法,求最小二乘解.目前还很难找到免费的DotNet版的数值计算程序.这里有源码(J#)和dll文件.-Kind version of the linear equation solution, including : Gaussian Elimination Act, for order n nonsingular matrix; SVD decomposition method, least squares sol
DotMatrix
- DotNet版的线性方程的解法,包括:高斯消元法,用于n阶非奇异矩阵;SVD分解法,求最小二乘解.目前还很难找到免费的DotNet版的数值计算程序.这里有源码(J#)和dll文件.-Kind version of the linear equation solution, including : Gaussian Elimination Act, for order n nonsingular matrix; SVD decomposition method, least squares sol
fanyan
- 用SVD奇异值分解法和阻尼最小二乘算法解决地球物理反问题,程序比较简单易懂
fangzhen1_tls
- 基于SVD分解的总体最小二乘算法,在工程领域有很大的应用
pipeidian_eight
- 计算机视觉中得八点算法,采用SVD分解最小二乘解来求基本矩阵,这是模拟仿真实验程序。-Was 8:00 in computer vision algorithms, using SVD decomposition least-squares solution to seek the fundamental matrix, which is simulation, experimental procedure.
SVD
- 最小二乘估值的SVD分解计算方法,本程序可将最小二乘估值问题转化为超定方程组的问题处理,且可用奇异值分解的方法计算最小二乘问题。-Least Squares Estimates of the SVD decomposition method, the valuation process can be transformed into squares overdetermined equations deal with the problem, and can be calculated sing
用最小二乘法和svd-tls法对arma过程进行功率谱估计并比较结果
- 分别用最小二乘法和svd-tls法对arma过程进行功率谱估计并比较结果。包含实验目的,步骤,程序,结果,分析。-Least square method, respectively, and svd-tls on arma-power spectrum estimation process and the results of the comparison. Contains experimental purposes, steps, procedures, results, analysis.
pronyanalysis
- matlab prony算法 基于svd-tls总体最小二乘-prony analysis matlab code svd-tls
333
- 用QR 法方程组合SVD分解进行最小二乘解方程组,并比较三种方法的稳定性以及准确性-Combined with the QR equation SVD decomposition least squares solution of equations, and compare the stability and accuracy of three methods
SVD_TLS
- 使用自编函数基于奇异值分解总体最小二乘法(svd-tls)实现AR模型谱估计 -The use of self-functions in general based on singular value decomposition least square method (svd-tls) to achieve AR model spectrum estimation
CLAPACK3-Windows
- LAPACK是用Fortran90和规定套路解决系统同步线性方程组,最小二乘解线性方程组,特征值问题,以及奇异值问题。相关的矩阵分解(陆,乔莱斯基,快速反应,分解,舒尔,广义Schur )也提供了,因为有关的计算,如重新安排的舒尔分解和估计条件号码。致密带状矩阵的处理,而不是一般稀疏矩阵。在所有领域,类似的功能是提供真正的和复杂的矩阵,在单,双精度-LAPACK is written in Fortran90 and provides routines for solving systems o
single
- 使用奇异值分解来帮助求解最小二乘问题,特别是在方程系数矩阵不满秩的情况下。-SGELSD computes the minimum-norm solution to a real linear least * squares problem: * minimize 2-norm(| b- A*x |) * using the singular value decomposition (SVD) of A. A is an M-by-N * matrix which
lsandsvd-tls
- 用一般的最小二乘方法和SVD—TLS(总体最小二成)方法估计观测数据的ARMA模型的AR参数。-Least squares method and with the general SVD-TLS (Twenty-general minimum) to estimate the ARMA model of observed data AR parameters.
svd
- 利用奇异值分解法解最小二乘问题或超定方程组-svd algorithm
SVD
- 用matlab仿真,通过不同的方法计算矩阵的SVD分解,并用SVD的方法计算最小二乘问题和进行图像压缩-Matlab simulation, different ways to calculate the matrix SVD decomposition and the SVD method to calculate the least squares problem and the image compression
er
- 基于最小二乘、SVD-TLS的功率谱估计, 比较最小二乘法与SVD-TLS在现代功率谱估计中的差异与优劣。-SVD-TLS power spectrum estimation based on least squares, compare the least squares method with SVD-TLS in modern power spectrum estimation differences and the pros and cons.
OFDM-channel-estimation-methods
- OFDM信道估计的几种方法的仿真,包括最小二乘(LS)法、最小均方误差(MMSE)法、线性最小均方误差(LMMSE)法以及奇异值(SVD)分解法等,毕设资料,非常珍贵-several OFDM channel estimation methods,which contains the least-squares (LS), the minimum mean square error (MMSE), the linear minimum mean square error (LMMSE) and
alglib-2.6.0.delphi
- ALGLIB是一个跨平台的数值分析和数据处理函数库。它支持多种编程语言,如C++,C#,Pascal,VBA等,可以在多个操作系统平台上运行,如:Windows,Linux和Solaris。ALGLIB有以下特点: (1)线性代数(包括矩阵分析); (2)方程求解(线性和非线性); (3)插值; (4)最优化; (5)快速傅里叶变换; (6)数值积分; (7)线性和非线性最小二乘拟合; (8)常微分方程求解; (9)特殊函数; (10)统计(描
SVD
- 奇异值分解方法计算最小二乘问题 SVD方法处理最小二乘问题 主函数(Singular value decomposition method for least squares problems)
svdtls11
- 奇异值分解方法计算SVD方法处理最小二乘问题 对主函数进行分析(The singular value decomposition method calculates the SVD method to deal with the least squares problem and analyzes the main functions)