-
image
说明： 在matlab环境下对图片进行压缩，使用算法为矩阵的奇异值分解(Matlab environment in the picture compression algorithm using singular value decomposition of the matrix)
- 2011-04-15 10:47:24下载
- 积分：1
-
IterSVD_MIMO
MIMO场景下的迭代SVD分解，用于得到最大的singular value(Iterative SVD in MIMO scenerio)
- 2012-04-27 10:17:06下载
- 积分：1
-
k-means
用于图像分割的方法很多，其中基于K均值的图像分割方法较为常用，本程序附有详细注解(Image segmentation method based on K-means, with detailed notes)
- 2014-01-20 12:30:45下载
- 积分：1
-
16-qam
calculating in matlab 16 qam used in digital communication
- 2012-06-17 02:08:58下载
- 积分：1
-
BP
说明： 本代码编译环境为matlab，利用bp神经网络实现了建筑能耗预测，精度高，可扩展性好(This code the compiler environment Matlab, realize the building energy consumption prediction, by using the BP neural network has high precision, good scalability
)
- 2014-10-15 15:34:21下载
- 积分：1
-
superresolution
说明： 超分辨率程序，用matlab开发,可以直接执行(matlab, super resolution)
- 2010-04-12 18:30:32下载
- 积分：1
-
MonteCarlo
蒙特卡洛模拟 随机因素的统计分析 对系统规模没有要求(Monte Carlo simulation of the statistical analysis of random factors in the scale of the system does not require)
- 2009-04-30 16:08:02下载
- 积分：1
-
get_observations
tracking robot by vision sensor
- 2011-11-03 09:13:52下载
- 积分：1
-
otsu
这是本人下载和编译过的关于大津法二值化的matlab代码，效果比较好，可以作为分割的有效辅助(This is, I downloaded and compiled on the Otsu binarization method of matlab code, the effect is better, can be used as an effective auxiliary partition)
- 2007-07-27 10:12:19下载
- 积分：1
-
boxplot_percentwhisk
Normally boxplot plots the whiskers with a maximum length based on the distance between the 25th and 75th percentile. This script uses boxplot but plots the whiskers for a specified percentile and only plots the outliers beyond the new whiskers.
Note that the percentile is defined as the data point just beyond the calculated percentile. For example, if the 98th percentile lies between the 4th and 5th highest data points, then the 4th highest data point will be considered the 98th percentile, the whisker will extend to the 4th highest, and only the 4 highest values will be plotted as outliers.
- 2009-05-25 02:00:22下载
- 积分：1
