搜索资源列表
开题样本１
- 论文开题报告样本-papers report that opened samples
最近爆发的蠕虫样本WORM_SOBER.AG
- 最近爆发的蠕虫样本WORM_SOBER.AG,有兴趣的朋友可以分析一下-recent outbreak of the worm samples WORM_SOBER.AG, interested friends analysis
可行性报告样本
- 一个可行性报告样本-samples of a feasibility report
基于样本间隔的非参数盲源分离算法程序
- 通过样本间隔估计概率密度函数，代入评价函数，形成非参数盲源分离算法，可以分离超高斯，亚高斯，高斯等的混合信号，分离效果好，速度快！
训练样本
- 好用的训练样本
使用FLD进行但样本识别
- 使用FLD进行但样本识别，解决样本需求问题
训练集负样本
- 从谷歌下载的用于人脸、车牌等训练的负样本集合，总共2000多张各式各样的图片，负样本集合差异明显，非常适合训练。
样本熵的计算
- 样本熵计算，近似熵计算，matlab实现(Sample entropy calculation, approximate entropy calculation)
贝叶斯决策实现线性样本分类
- MATLAB语言编程，用贝叶斯决策算法实现线性样本分类，输入待分类样本，输出样本分类决策面。(MATLAB programming language, using Bayesian decision algorithm to achieve linear sample classification, input samples to be classified, output samples, classification, decision surface.)
使用MATLAB实现样本熵算法
- 使用matlab实现样本熵算法，亲自试过了，非常好用(Using MATLAB sample entropy algorithm, very easy to use)
样本熵
- 求出信号被分解后的样本熵，作为训练和测试样本，为以后的分类与预测做铺垫(The sample entropy is decomposed and used as training and test samples to pave the way for future classification and prediction)
样本序列的均值
- 利用随机数生成器产生一个长度为N的符号序列，求样本序列均值(The random number generator is used to generate a symbol sequence of length N, and the mean of the sample sequence is obtained)
单样本人脸识别
- 利用KNN分类器在FERET人脸库上进行单样本人脸识别(Single sample face recognition on FERET face database using KNN classifier)
手写数字样本
- 关于手写数字的两个样本库，可利用多种语言进行图片的识别处理。(Two sample libraries for handwritten numbers)
车牌样本库
- 用来训练的样本库,只有整车的图片，车牌需要自己识别切割(Image for SVM trainning)
车牌汉字样本
- 车牌识别中汉字训练样本，包含31个省份，每个字符几十到几百个样本。(License plate recognition Chinese character training samples, including 31 provinces, each character tens to hundreds of samples.)
人头训练正负样本数据集
- 用来训练人头识别模型的正负样本数据集，正样本数据已经resize化。(The positive and negative sample data set is used to train the head recognition model, and the positive sample data has been resize.)
样本熵
- 给已知的若干组脑电数据进行样本熵值的计算(Sample entropy calculation for a number of known sets of EEG data.)
多尺度样本熵
- 自编多尺度样本熵程序，实例中用于一段轴承故障数据，简单易懂。MultiscaleSampleEntropy函数中的SampleEntropy也可以单独拎出来计算单个样本熵。(Multi scale sample entropy is used for a section of bearing fault data, which is easy to understand. SampleEntropy in the MultiscaleSampleEntropy function can also
CEEMD-样本熵
- 用ceemd分解信号IMF分量，用峭度相关原则筛选噪声，用样本熵进行特征提取(18/5000 CEEMD was used to decompose the signal and sample entropy was used to extract the feature)