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1111
通过对钢轨和车轮的ansys有限元建模，分析在钢轨的接头处的动力学特性。(Rail and wheel ansys finite element modeling, analysis of the dynamics of the rail joints.)
- 2012-08-16 08:56:38下载
- 积分：1
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RK45andRK54
Runge－Kutta45算法与Runge-Kutta54算法的matlab实现
数值分析课程代码(Runge-Kutta 45 algorithm and Runge-Kutta 54 algorithm matlab implementation
Numerical Analysis Course Code)
- 2021-04-21 16:08:49下载
- 积分：1
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《啊哈！算法》
用简单易懂的图文方式阐释算法的奥秘，快速了解每个算法的使用场景、原理(Explain the mysteries of the algorithm with simple and understandable graphics and text, and quickly understand the scene and principle of each algorithm)
- 2017-10-26 19:20:16下载
- 积分：1
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最速下降法
最优化课程中的最速下降法matlab程序，利用了wolfe搜索和armijo线搜索(Matlab program of steepest descent method in optimization course, using Wolfe search and Armijo line search)
- 2021-03-26 18:19:13下载
- 积分：1
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polynomial_fitting
二元二次多项式曲面拟合法的Matlab实现，含有M文件及数据文件示例(Binary quadratic polynomial surface fitting Matlab, contain the M-file and the data file example)
- 2012-09-18 18:34:41下载
- 积分：1
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MSE_calculation
最小二乘算法，最小均方误差等算法的MSE的计算，MATLAB代码(Least-squares algorithm, such as minimum mean square error MSE calculation algorithm, MATLAB code)
- 2021-01-07 21:28:52下载
- 积分：1
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matlabalgorit
进行干扰源以及声源定位的时延估计技术，以及定位迭代算法相关介绍(Sources of interference and delay estimation techniques for sound source localization, as well as positioning iterative algorithm)
- 2012-10-08 20:50:51下载
- 积分：1
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QR分解
该程序是利用GIvens变换进行矩阵的QR分解(The program uses GIvens transform to solve QR matrix.)
- 2021-03-08 10:59:28下载
- 积分：1
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Inverse
使用C编写的复数矩阵求逆，使用高斯消去法，已经和matlab结果做过对比，无误(Written in C and the complex matrix inverse, using the Gaussian elimination method, has been done and matlab results contrast, correct)
- 2012-07-11 18:23:24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
