搜索资源列表
Bayesian.Classifier
- 贝叶斯分类实验 模式识别课程实验所用的源程序-Bayesian classifier experimental pattern recognition programs used in the experimental program
c-jun
- 模式识别的聚类方法：C－均值算法，求得不同的分类
Pattern_recognition1
- 张学工老师模式识别第一次作业，用贝叶斯方法和正态分布的监督参数估计对身高体重二维数据进行性别分类-Zhang engineering teacher pattern recognition for the first time operations, using Bayesian methods, and the supervision of normal height and weight of two-dimensional parameter estimation of the gende
Pattern_recognition4
- 张学工老师模式识别第四次作业，分别用C均值方法，分层聚类方法和非监督参数下正态分布函数估计的贝叶斯决策对身高体重二维数据进行分类。-Zhang engineering teacher fourth pattern recognition operations, respectively C-means, hierarchical clustering methods, and non-normal distribution function under the supervision of th
isodata
- 用于将数据进行分类，对学习模式识别的朋友会非常有用-Used for data classification, pattern recognition learning can be very useful friends
OnlineSVR-CPP-Code
- 支持向量机在线学习训练算法C++源码，可以用来做数据分类、模式识别、回归估计、概率密度函数估计等方面。-Support vector machine online learning training algorithm C++ source code, can be used for data classification, pattern recognition, regression estimation, probability density function estimation an
jingqing_v89
- 阐述了负荷预测的应用研究,可以实现模式识别领域的数据的分类及回归，分析了该信号的时域、频域、倒谱，循环谱等。- It describes the application of load forecasting, You can achieve data classification and regression pattern recognition, Analysis of the signal time domain, frequency domain, cepstrum, cyclic s
mangniu
- 可以实现模式识别领域的数据的分类及回归，研究生时的现代信号处理的作业，在matlab R2009b调试通过。- You can achieve data classification and regression pattern recognition, Modern signal processing jobs when the graduate, In matlab R2009b debugging through.
langfing_v36
- 包括AHP，因子分析，回归分析，聚类分析，采用热核构造权重，可以实现模式识别领域的数据的分类及回归。- Including AHP, factor analysis, regression analysis, cluster analysis, Thermonuclear using weighting factors You can achieve data classification and regression pattern recognition.
faohun
- 可以实现模式识别领域的数据的分类及回归，用MATLAB实现的压缩传感，用于时频分析算法。- You can achieve data classification and regression pattern recognition, Using MATLAB compressed sensing, For time-frequency analysis algorithm.
tenglun
- 仿真图是速度、距离、幅度三维图像，D-S证据理论数据融合，可以实现模式识别领域的数据的分类及回归。- FIG simulation speed, distance, amplitude three-dimensional image, D-S evidence theory data fusion, You can achieve data classification and regression pattern recognition.
fieyao
- 可以实现模式识别领域的数据的分类及回归，从先验概率中采样，计算权重，独立成分分析算法降低原始数据噪声。- You can achieve data classification and regression pattern recognition, Sampling a priori probability, calculate the weight, Independent component analysis algorithm reduces the raw data noise.
meifie_V1.3
- 最大信噪比的独立分量分析算法，数据模型归一化，模态振动，可以实现模式识别领域的数据的分类及回归。- SNR largest independent component analysis algorithm, Normalized data model, modal vibration, You can achieve data classification and regression pattern recognition.
noulen_v46
- 进行逐步线性回归，可以实现模式识别领域的数据的分类及回归，相关分析过程的matlab方法。- Stepwise linear regression, You can achieve data classification and regression pattern recognition, Correlation analysis process matlab method.
gangfei
- 与理论分析结果相比，连续相位调制信号(CPM)产生，可以实现模式识别领域的数据的分类及回归。- Compared with the results of theoretical analysis, Continuous phase modulation signal (CPM) to produce, You can achieve data classification and regression pattern recognition.
benlui
- 利用贝叶斯原理估计混合logit模型的参数，gmcalab 快速广义的形态分量分析，可以实现模式识别领域的数据的分类及回归。- Bayesian parameter estimation principle mixed logit model, gmcalab fast generalized form component analysis, You can achieve data classification and regression pattern recognition.
bayes_C++
- 贝叶斯分类器-联合变量_C++，只需更改样本文件名即可测试。(The Bias classifier - the joint variable _C++, can be tested only by changing the name of the sample file.)
bayes_independent variable _C++
- 贝叶斯分类器-独立变量_C++，只需更改样本文件名即可测试。(Bias classifier - independent variable _C++, can be tested only by changing the name of the sample file.)
bayes_independent variable _matlab
- 贝叶斯分类器-独立变量_matlab，只需更改样本文件名即可测试。(Bias classifier - independent variable _matlab, can be tested only by changing the name of the sample file.)
bayes_joint variable _matlab
- 贝叶斯分类器-联合变量_C++，只需更改样本文件名即可测试。(The Bias classifier - the joint variable _C++, can be tested only by changing the name of the sample file.)