-
matlab1
应用MATLAB对图像进行频率域的平滑和锐化处理的简单例子(Application of MATLAB in frequency domain image smoothing and sharpening the handle of a simple example)
- 2008-05-22 12:56:37下载
- 积分：1
-
LBE
Lattice Boltzmann LBE模型在二维多孔介质流体渗流中的应用，基于geometry: D2Q9, model: BGK(Simple, yet simplistic, Lattice Boltzmann (LB) MATLAB implementation. D2H9, BGK, omega = 1, laminar flow in a 2D channel used as benchmark. Requires Image Processing Toolbox.
)
- 2009-04-26 16:07:25下载
- 积分：1
-
Optimizem
黑箱优化算法，挺不错的，希望大家喜欢(Black-box optimization algorithm, very good, and I hope everyone likes)
- 2008-05-15 16:57:10下载
- 积分：1
-
aeroblk6dofbody
航空飞行器6自由度动力学模型，用于飞行力学和飞机控制仿真(Aviation aircraft 6 DOF dynamics model for flight mechanics and aircraft control simulation)
- 2013-07-18 15:42:46下载
- 积分：1
-
Implementation_of_an_IEEE802.11a_synchronizer
802.11同步算法的matlab仿真与FPGA实现，非常适合工程应用(802.11 synchronization algorithm matlab simulation and FPGA realize, very suitable for engineering applications)
- 2008-08-06 11:37:35下载
- 积分：1
-
An-artificial-immune-algorithm
An artificial immune algorithm based on Matlab
- 2011-04-24 21:04:18下载
- 积分：1
-
relay-protection-in-MATLAB
7.1 简单数字滤波器的MATLAB辅助设计和分析方法 7.2 微机继电保护算法的MATLAB辅助设计和分析方法 7.3 输电线路距离保护的建模与仿真 7.4 Simulink在变压器微机继电保护中的应用举例 7.5 输电线路故障行波仿真举例
(7.1 Simple digital filter MATLAB-aided design and analysis methods 7.2 microcomputer relay protection algorithm MATLAB-aided design and analysis methods 7.3 Transmission Line Distance Protection 7.4 Simulink modeling and simulation of the transformer relay protection Application Examples 7.5 Transmission Line Examples traveling wave fault simulation)
- 2013-08-22 11:51:20下载
- 积分：1
-
gui2
abou gui in different methods like data mining and in other areas
- 2014-11-02 23:27:51下载
- 积分：1
-
tvreg
TV-based image restoration and Chan-Vese segmentation. Usable MATLAB or C/C++
- 2014-11-18 07:25:05下载
- 积分：1
-
fit_ML_normal
fit_ML_normal - Maximum Likelihood fit of the normal distribution of i.i.d. samples!.
Given the samples of a normal distribution, the PDF parameter is found
fits data to the probability of the form:
p(r) = sqrt(1/2/pi/sig^2)*exp(-((r-u)^2)/(2*sig^2))
with parameters: u,sig^2
format: result = fit_ML_normal( x,hAx )
input: x - vector, samples with normal distribution to be parameterized
hAx - handle of an axis, on which the fitted distribution is plotted
if h is given empty, a figure is created.
output: result - structure with the fields
sig^2,u - fitted parameters
CRB_sig2,CRB_u - Cram?r-Rao Bound for the estimator value
RMS - RMS error of the estimation
type - ML
- 2011-02-09 19:09:33下载
- 积分：1
