搜索资源列表
BP
- 误差反传网络(BP)特点:1)对原始数据的分布型式无要求;2)已知模型的类型应比较全面;3)适用于多目标模式识别;4)外推能力有限;5)定性数据和定量数据混合处理;6)当加入新模型时需要重新训练网络;7)不能用于数据插值。 -1) the distribution pattern of the original data requirements 2) known model types should be more comprehensive 3) suitable for multi
Hopfield
- 循环反馈网络(Hopfield)特点:1)定性数据的模式识别;2)依靠吸引子来作模式识别;3)其功能可由BP网络来实现,但速度较快。 -Loop feedback network (Hopfield) features: 1) the qualitative data of the pattern recognition 2) rely on attractor for pattern recognition 3) its function can be made of BP netwo
ex1
- 贝叶斯方法一篇比较科普的中文介绍可以见pongba的平凡而神奇的贝叶斯方法: http://mindhacks.cn/2008/09/21/the-magical-bayesian-method/,实际实现一个贝叶斯分类器之后再回头看这篇文章,感觉就很不一样。 在模式识别的实际应用中,贝叶斯方法绝非就是post正比于prior*likelihood这个公式这么简单,一般而言我们都会用正态分布拟合likelihood来实现。-pattern identification
RBF
- RBF神经网络源代码,可以用于模式识别分类应用研究中-code for rbf
3333332
- 模式识别中的相关算法的matlab实现,其中包括感知机、最小二乘法以及支持向量机-pattern recognition
kmeans_maxminCluster
- 该代码包含了模式识别中的两个算法,kmeans和最大最小距离聚类,并且里面附有word版的算法结果,清晰明了,代码通过测试,可完美运行-The code contains the pattern recognition of two algorithms, kmeans and maximum and minimum distance clustering, and which with word version of the algorithm result, clarity, the cod
chapter12
- 用SVM算法实现的白酒分类模式识别的源代码,可以嵌入自己开发的应用程序,使用matlab的SVM工具箱实现的-the complementation of pattern classification of SVM algorithm using matlab
faceMFa
- 可以分别介绍MFA,又名边界Fisher分析。对模式识别十分重要的作用,可以帮助新手更好的理解KNN原理,对人脸识别有着很好的演示作用。-Can introduce MFA respectively, also known as boundary Fisher analysis. For pattern recognition is an important role, can help beginners a better understanding of KNN principle, has
SSDRnanjin
- SSDA,又名半监督Fisher分析。对模式识别十分重要的作用,有着其独特的优势,对人脸识别有着很好的演示作用。-SSDA, also known as a semi-supervised Fisher analysis. For pattern recognition is an important role, has its unique advantages, has a very good demonstration effect on face recognition.
fuzzytheory
- 模糊逻辑模式识别,模糊分类,模糊神经网络算法 matlab实例-Fuzzy logic pattern recognition, fuzzy classification, fuzzy neural network algorithm matlab examples
BPregime
- 流型智能分类,模式识别,BP人工神经网络-Intelligent flow classification, pattern recognition, BP artificial neural network
Pattern-Recognise
- c均值法聚类 mfc 模式识别 二维坐标聚类 图形化操作界面 -c mean mfc
bp_neural_network
- 用MATLAB编程BP神经网络程序,要模式识别分类的,-Programming with MATLAB BP neural network program, to pattern recognition and classification of,
main
- 通过KNN和朴素贝叶斯算法 实现 模式识别中的分类-Achieve pattern recognition is classified by KNN and Naive Bayes algorithm
DeepLearnToolbox_CNN_lzbV3.0
- CNN - 主程序 参考文献: [1] Notes on Convolutional Neural Networks. Jake Bouvrie. 2006 [2] Gradient-Based Learning Applied to Document Recognition. Yann LeCun. 1998 [3] https://github.com/rasmusbergpalm/DeepLearnToolbox 作者:陆振波 电子
clusteringAnalysis
- 模式识别中K均值聚类分析算法的matlab实现及注释,其中采用了误差平方和判断。-K-means clustering analysis algorithm in pattern recognition of matlab and annotation, which adopts the error sum of squares of judgment
GMM
- 高斯混合模型,模式识别。matlab源码实现分类-Gaussian mixture model of pattern recognition.The matlab source code to achieve
UCR-Using-an-AIS-Based-on-MD
- 基于流形距离的人工免疫无监督分类与识别算法 关键词:人工免疫系统, 流形, 无监督分类, 聚类, 模式识别-Unsupervised Classiˉcation and Recognition Using an Artiˉcial Immune System Based on Manifold Distance
2012011539_homework2
- 模式识别中基于监督的分类方法。贝叶斯、fisher线性判别-Supervised classification method based on pattern recognition. Bayes, fisher linear discriminant
2012011539_homework3
- 模式识别:神经网络算法使用,PCA和KL变换-Pattern recognition: neural network algorithm, PCA and KL transform