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MATLAB_programming_commands_quick_tutorial_image
MATLAB图像编程命令快捷教程MATLAB programming commands quick tutorial image(MATLAB programming commands quick tutorial image MATLAB programming commands quick tutorial image)
- 2010-08-04 20:24:19下载
- 积分：1
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Channelestimationperformance
hannel estimation performance for Discard Prefix DS-CDMA against the transmitted data vector
- 2010-12-17 02:14:50下载
- 积分：1
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TRANSIENT
TRANSIENT RESPONSE OF THE ELECTRICAL CIRUITS USING MATLAB SIMULATION
- 2013-10-21 13:30:44下载
- 积分：1
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EfPiSoft-1.0_src.tgz
hierarchical Mesh Segmentation based on Fitting Primitives 配套源码(code for hierarchical Mesh Segmentation based on Fitting Primitives)
- 2013-12-07 05:01:48下载
- 积分：1
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CS-Channel-Estimation
信道估计程序，ieee发表的文章对应的原码，本人已经验证，可以使用。(Channel estimation procedures, ieee post corresponding to the original code, I have verified that you can use.)
- 2013-10-25 21:08:24下载
- 积分：1
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MAT
MATLAB函数大全_A-Z，可以看看，很不错的(MATLAB function Daquan _AZ, very good)
- 2015-01-04 17:20:45下载
- 积分：1
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bsplinebezier
B样条和bezier拟合程序，自己输入x,y值，即可进行拟合(B-spline and bezier fitting procedure, enter the x, y values , can be fitted.)
- 2011-12-03 04:11:16下载
- 积分：1
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New-Fuzzy-nNetwork-design-using-Genetic-Algorithm
In this paper a Conventional PD Controller and Fuzzy Neural Controller for trajectory tracking of mobile robot
platform is presented. Using computed torque method is given input- torque on mobile robot wheels. The
locomotion control structure is based on integration of kinematics and dynamics model of mobile robot base.
The proposed Control scheme and Fuzzy Neural Algorithm could be useful for building an autonomous non-destructive testing system based on wheeled mobile robot. Fuzzy Neural Network-Rule base, is optimized using
Genetic Algorithm. Simulations are done using Matlab software.
Key words:Mobile Robot, Conventional, Fuzzy Logic, Neural Network, Genetic Algorithm, trajectory tracking,
- 2013-11-19 14:52:08下载
- 积分：1
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abcde_complexity
Spread Spectrum Watermarking MATLAB
- 2012-01-02 11:21:40下载
- 积分：1
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Modelling_systems_linear_objects_some_systems
STEP:
1.Bringing descriptive model matemaryczny dyiiamike obiektii issue.
2.Present the resulting model in the form of transmittance merging appropriate input and output size.
3. Move the resulting model as rownaii state.
4. By making use of differential equations that describe rowname dyiiamike obiektii modeled. build a model in srodowiskn MATLAB / Simulink.
5.Przy carry out a model built using the experiments indicated by conducting classes and graphs to present position and speed of the system elements.
6. Discuss the correctness of obtained in the course s> wyiiikow stimulations.
- 2010-12-05 00:51:41下载
- 积分：1
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