-
PESGM2008-000079
ITs IEEE PESGM08 Paper.
- 2013-12-03 17:34:22下载
- 积分:1
-
mvsb
通信系统中实现残留边带调制,用matlab实现。调制解调过程(Communication systems to achieve VSB modulation, with the realization of matlab. The process of modulation and demodulation)
- 2009-04-12 23:39:50下载
- 积分:1
-
func_ezw_demo_main
basic ezw coding for image compression.
- 2015-03-19 15:38:50下载
- 积分:1
-
hctsa-master
matlab,时间序列分析,分类,数据挖掘,聚类(time series classification)
- 2021-03-29 02:49:10下载
- 积分:1
-
music
空间谱music算法,谱峰搜索,找到信号波达方向(Spatial spectrum MUSIC algorithm, spectrum peak search)
- 2021-04-26 18:28:45下载
- 积分:1
-
matlab7.0-basic-tutorial
matlab7.0基础教程 清华大学出版(matlab7.0 Essentials Tsinghua published)
- 2013-01-27 10:36:43下载
- 积分:1
-
DE-and-NSGA2
这里面是我最近下载的所有的差分进化和NSGA2的代码,还有个很好用的NSGA2和DE的结合。(There is all the difference in the evolution and NSGA2 I recently downloaded the code, there is a good use of a combination of NSGA2 and DE.)
- 2014-11-21 09:33:51下载
- 积分:1
-
心电信号的周期峰值检测算法 LVMck
Matlab源码:关于心电信号的周期峰值检测算法(Matlab source: on the ECG cycle peak detection algorithm)
- 2011-11-05 20:29:35下载
- 积分:1
-
fusefenge
matlab图像肤色分割程序。可以实现从一幅图中分割出人的肤色。(matlab image skin color segmentation. It can be divided people of color from a picture.)
- 2013-05-19 20:08:12下载
- 积分:1
-
gender-classification-experiments
这是用身高体重数据进行性别分类的实验。
用最小错误率贝叶斯分类器决策时,首先通过比较概率大小判断一个体重身高二维向量代表的人是男是女,然后再逐一与已知性别的数据比较,就可以得到错误率的统计。然后改变先验概率,重复上面的过程,观察数据结果的变化。
用最小风险贝叶斯分类器决策时,首先求出用最小错误率贝叶斯分类器得到的条件概率;然后根据人为给定的决策表,根据公式算出条件风险;然后逐一比较条件风险,找出使条件风险最小的决策(也就是分类)。最后用分类得到的结果逐一比较已经知道的原始数据,统计处错误率。
(This is the height and weight data for gender classification experiment.
With the minimum error rate Bayesian classifier decisions , first by comparing the probability of the size and weight to height to determine a person represented by two-dimensional vector is male or female , and then one by one with known gender data comparison, the statistical error rate can be . Then change the prior probability , repeat the above process , the results of the changes observed data .
Bayesian classifier with the minimum risk decision-making , first find the minimum error rate using Bayesian classifier to get the conditional probability then artificially given decision table , according to the formula to calculate conditional risk and then one by one more conditional risk , to find ambassador to the conditions of minimum risk decision making (ie classification) . Finally, the results obtained with the classification by-side comparison of the raw data have been aware of SD error rate .
)
- 2012-02-02 20:40:46下载
- 积分:1