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StokesHotine
地球科学：重力场积分(Fortran90)
Stokes/Hotine/V_M垂线偏差积分：数值积分、二维平面FFT、二维球面FFT、一维FFT(Earth Sciences: Gravity Field Points (Fortran90) Stokes/Hotine/V_M deflection of the vertical integration: numerical integration, the two-dimensional plane FFT-dimensional sphere FFT, one-dimensional FFT)
- 2012-10-13 13:14:35下载
- 积分：1
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modified-burgers-model
改进的burgers模型，非常适合学习UMAT的同志们学习，来自廖公云老师的《ABAQUS有限元软件在道路工程中的应用》(Improved burgers model is ideal for learning UMAT comrades learn from Liao Gongyun teacher "ABAQUS finite element software road works)
- 2021-04-05 17:19:03下载
- 积分：1
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matinv
说明： 矩阵求逆，使用fortran语言编写，希望能对有需要的朋友有所帮助(Matrix inversion, written in FORTRAN language, hoping to help friends in need)
- 2020-12-11 17:49:18下载
- 积分：1
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fpa
code for methuristic algorithm flower pollination algorithm
- 2017-05-20 00:21:23下载
- 积分：1
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EmFDTD-v1.2r1
一组很好的FDTD计算二维光子带隙的程序，matlab 7.0以上版本适用(a good group of FDTD calculation of two-dimensional photonic bandgap procedures, Matlab 7.0 and above versions of the application)
- 2007-02-04 02:02:47下载
- 积分：1
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标准方腔流动
用来计算流体力学中非常典型的不可压缩方腔流动。包含MATLAB程序绘制流函数图。(It is used to calculate the incompressible flow of a typical square cavity in fluid mechanics. Contains MATLAB programs to draw stream function diagrams.)
- 2017-09-10 18:32:53下载
- 积分：1
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esmd4matlab_1.0
非极点对称的经验模态分解matlab计算程序(Non - pole symmetry empirical mode decomposition matlab calculation program)
- 2017-09-26 10:23:53下载
- 积分：1
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methods
说明： 常用算法包括第一类整数阶贝塞耳函数，积分刚性方程组的吉尔方法，计算多重积分的高斯方法，快速傅利叶变换，离散随机线性系统的卡尔曼滤波，切比雪夫曲线拟合的c语言算法(failed to translate)
- 2010-04-23 23:54:07下载
- 积分：1
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LU
说明： 数值分析中运用matlab使用LU分解法求线性方程组(Numerical analysis using matlab LU decomposition method for solving linear equations)
- 2012-10-18 23:54:17下载
- 积分：1
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SVD
％ 奇异值分解 (sigular value decomposition,SVD) 是另一种正交矩阵分解法；SVD是最可靠的分解法，
％ 但是它比QR 分解法要花上近十倍的计算时间。[U,S,V]=svd(A)，其中U和V代表二个相互正交矩阵，
％ 而S代表一对角矩阵。 和QR分解法相同者， 原矩阵A不必为正方矩阵。
％ 使用SVD分解法的用途是解最小平方误差法和数据压缩。用svd分解法解线性方程组，在Quke2中就用这个来计算图形信息，性能相当的好。在计算线性方程组时，一些不能分解的矩阵或者严重病态矩阵的线性方程都能很好的得到解( Singular value decomposition (sigular value decomposition, SVD) is another orthogonal matrix decomposition method SVD decomposition is the most reliable method, but it takes more than QR decomposition near ten times the computing time. [U, S, V] = svd (A), in which U and V on behalf of two mutually orthogonal matrix, and the S on behalf of a diagonal matrix. And QR decomposition are the same, the original matrix A is no need for the square matrix. The use of SVD decomposition method are used as a solution of least squares error method and data compression. Using SVD decomposition solution of linear equations, in Quke2 on to use this information to calculate the graphics performance quite good. In the calculation of linear equations, some indecomposable matrix or serious pathological matrix of linear equations can be a very good solution)
- 2020-12-21 10:29:08下载
- 积分：1
