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Numerical_Methods_matlab

于 2010-07-20 发布文件大小:315KB

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matlab实现：高斯消元法，LU分解法，迭代法，奇异值分解，乔累斯基分解法，gauss迭代解线性方程组，jacobi迭代解线性方程组(matlab implementation: Gauss elimination, LU decomposition, iterative methods, singular value decomposition, Cholesky decomposition, gauss iterative solution of linear equations, jacobi iterative solution of linear equations)

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mathews.tar,2457600,1997-08-23

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newton
牛顿法求函数极值。程序以香蕉函数为例。可以运行(Newton' s Method function extremum. Rosenbrock function as an example program. Can run)

2010-10-14 17:02:28下载

积分：1
phasor
Phasor Plot PSCAD using Matlab

2014-10-09 03:42:20下载

积分：1
PV-connected-to-grid
PV WITH THREE PHASE INVERTER

2012-11-07 21:46:17下载

积分：1
newshuangxiangquanqiao
说明：双有源全桥DC-DC变换器双重移相MATLAB仿真(Matlab simulation of double active full bridge double phase shifting)

2020-10-06 10:27:39下载

积分：1
QPSKand16QAM
该程序是关于扩频通信在不同调制方式下的抗噪声性能比较(compare in Qpsk and 16 QAM in DSSS)

2010-05-06 18:23:25下载

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Self_collimation
二维光子晶体自聚焦光束的FDTD模拟程序配PML吸收边界(Two-dimensional photonic crystal since the FDTD simulation program focused beam with PML absorbing boundary)

2012-08-28 14:23:03下载

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project-417-2011
Zero forcing precoding in MU-MIMO

2013-05-11 23:41:22下载

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EMBEDDED-PROGRAM1
PROGRAM IS USED FOR Interface matrix keyboard with 8051.

2014-10-19 21:19:11下载

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WRAN_simul
This is WRAN simulation file. It contations too many m files. You can open these files. Thank you

2013-09-04 13:32:27下载

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fcn_SR_KF
This file compares three different versions of the Kalman filter. The Kalman filter is used for recursive parameter estimation. The Kalman filter can handle noisy measurements. The first implemented filter (fcn_KF) is the Kalman filter with standard update of the covariance matrix P. The covariance matrix reflects the uncertainties of the predictions. To improve the numerical stability Potter developed a square root update (fcn_KF_SRP) of the covariance matrix P. Another version is the square root covariance update via triangularization (fcn_KF_SRT). This file generates a model. Then the three Kalman filters perform an estimation of the model parameter. At the end the results are compared. Sources: Simon, D. (2006): Optimal state estimation Kaminski, P. (1971): Discrete Square Root Filtering: A Survey of Current Techniques Golub, G. (1996): Matrix Computations

2014-02-14 18:30:49下载

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Numerical_Methods_matlab

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