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Chapter_5
Chapter 5 Matlab codes from AEMM book
- 2010-12-09 11:37:01下载
- 积分:1
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pca2D
用matlab实现了2dpca算法,基于ORL人脸数据库,识别率较高(Matlab achieved with 2dpca algorithm, based on the ORL face database, the higher recognition rate)
- 2008-06-23 14:11:54下载
- 积分:1
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MobileRadioChannels
介绍了如何用Matlab模拟和仿真移动环境中的各种信道(Describes how to use MATLAB simulation and emulation mobile environment in a variety of channels)
- 2013-04-17 22:28:22下载
- 积分:1
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BP-network
matlab 基于PID控制器的BP神经网络系统的仿真(matlab PID controller based on BP neural network system simulation)
- 2011-01-07 17:24:20下载
- 积分:1
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duoyuanxianxinghuigui
实现多元线性回归分析功能,并引用激光测月的事例进行了检验。(Multiple linear regression analysis function, and quoted the examples of the laser measured monthly inspection.)
- 2012-11-18 22:03:32下载
- 积分:1
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1
说明: bp神经网络对字母的识别,在matlab里运行,并且附带程序和运行后的图像,(The bp neural network recognition of letters, running in the matlab, and the supplementary program and after the operation of the image,)
- 2015-04-07 21:29:01下载
- 积分:1
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histeq
直方图均衡化是指将一幅图像的像素值均匀地分布在图像的各个区间上,从而是图像的视觉效果得到改善。(Histogram equalization is an image pixel values evenly distributed in various intervals in the image, which is to improve the image of the visual effects.)
- 2011-02-13 13:06:36下载
- 积分:1
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SKULL-EDGE-DETECTION
用于提取人脑颅骨的内外边界,能将头皮与脑组织全部舍去,主要用于颅骨修复领域。(Used to extract the boundaries of the human skull, mainly for skull repair area.)
- 2011-10-08 19:36:20下载
- 积分:1
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U16-_Lec3
This is my power electronic lecture note on diode rectification.
- 2014-01-18 07:50:40下载
- 积分:1
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IterativeClosestPointMethod
ICP fit points in data to the points in model. Fit with respect to minimize the sum of square errors with the closest model points and data points.
Ordinary usage:
[R, T] = icp(model,data)
INPUT:
model - matrix with model points,
data - matrix with data points,
OUTPUT:
R - rotation matrix and
T - translation vector accordingly
so
newdata = R*data + T .
newdata are transformed data points to fit model
see help icp for more information
(ICP fit points in data to the points in model. Fit with respect to minimize the sum of square errors with the closest model points and data points.
Ordinary usage:
[R, T] = icp(model,data)
INPUT:
model- matrix with model points,
data- matrix with data points,
OUTPUT:
R- rotation matrix and
T- translation vector accordingly
so
newdata = R*data+ T .
newdata are transformed data points to fit model
see help icp for more information
)
- 2007-09-09 16:06:34下载
- 积分:1