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assignt
- duda的模式分类作业源代码，第二章上机练习第2题。2类问题的分类器设计。c语言编程。-duda the pattern classification operations source code, the second chapter on the first two aircraft that practice. Two categories of classified design. C programming language.
Fisher1
- 模式识别的经典算法FISHER算法,课程设计的实验作品-the classic pattern recognition algorithm Fisher algorithm, the experimental curriculum design works
ganzhiqi_s200502106
- 模式识别-基于感知函数准则的线性分类器设计，完全自编代码，有详细说明。-pattern recognition-based perceptual function criteria for the classification of linear design, completely writing code is described in detail.
n84-3
- 非线性程序之模式识别与控制系统设计.-nonlinear pattern recognition procedures and control system design.
ISODATA_C++
- 这是一个有关于模式识别中的isodata算法的C++实现。很多课程设计可用到。数据在data.txt里-This is a pattern recognition on the C isodata algorithm to achieve. Many courses available to the design. Data data.txt Lane
Edit Distance算法
- 对模式识别中的字符串模板匹配问题进行的研究，设计了对任意字符串进行匹配和字符串相似度，即列文斯顿距离进行计算的算法-right pattern recognition template matching string for the research and design of the arbitrary strings and string matching similarity, Ken Livingstone distance calculation algorithm
libsvm-3.11
- LIBSVM 是台湾大学林智仁(Lin Chih-Jen)副教授等开发设计的一个简单、易于使 用和快速有效的 SVM 模式识别与回归的软件包， 他不但提供了编译好的可在 Windows 系列系统的执行文件，还提供了源代码，方便改进、修改以及在其它操作系统上应用-LIBSVM is National Taiwan University Lin ( Lin Chih-Jen ) Associate Professor and develop the design of a simple, easy
eyelabel
- 该代码用于眼睛的人工标定，并记录数据只用，是MFC图形化界面设计。用于模式识别，人眼定位，人工智能方面做前期机器学习或训练。-The code used for the artificial eye calibration, and record data only is the graphical interface design MFC. For pattern recognition, the human eye positioning, pre-done in artificial in
Bayes
- 贝叶斯分类实验，设计简单的线性分类器，了解模式识别的基本方法。掌握利用贝叶斯公式进行设计分类器的方法。-Bayesian classification experiment is designed to be simple linear classifier, know the basic methods of pattern recognition. Master the use of Bayesian classifier design formula method.
classify
- 模式识别中，固定增量聚类算法，课程设计项目-Pattern Recognition, fixed incremental clustering algorithm, the curriculum design project
pr
- 关于模式识别的一些文章，离群点的检查，svm的介绍，最优化设计-A number of articles on pattern recognition, inspection of outliers, svm introduction, the most optimal design
Matlab_hanshu
- ：人工神经网络中的BP网络模型在函数逼近、模式识别等领域得到了广泛的应用，但利用神经网络 解决实际问题时，经常涉及到大量的数值计算问题，而运用计算机高级语言编程对神经网络BP模型进行仿真和 辅助设计是件十分麻烦的事情，为了解决这个矛盾，Matlab工具箱中专fq编制了大量有关设计BP网络模型的工 具函数 本文分析了Matlab软件包中人工神经网络工具箱的有关BP网络的工具函数，并给出了部分重要工具函 数的实际应用．-: Artificial Neural Networks in
system
- this is a backpropagation neural network training and testing design for two types of islamic caligraphy pattern recognition as a school project
Neural-Network-Design
- This book gives an introduction to basic neural network architectures and learning rules. Emphasis is placed on the mathematical analysis of these networks, on methods of training them and on their application to practical engineering problems in suc
GeneticAlgorithms
- 求解任务分配和路径选择的改进遗传算法。针对传统的遗传算法编程求解过程中存在的代码复用性不高，灵活性差的情况，在参考麻省理工学院Matthew Wall开发的遗传算法类库GAlib的基础上，提出了基于设计模式的改进遗传算法设计框架，提供了Visual C#代码。该框架通过使用模板方法模式、策略模式和适配器模式大大提高了改进遗传算法在设计实现过程中的可扩展性和灵活性。-Traditional genetic algorithm programming in the process of solvin
Divide-and-conquer-algorithm
- 分治算法是基于多分枝递归的一种算法设计模式。分治算法递归地把一个大问题分解为多个类型相同的子问题，直到这些子问题足够的简单能被直接解决。最后把这些子问题的解结合起来就能得到原始问题的解。-Divide and conquer algorithm is based on a multi-branch recursive algorithm design pattern. Divide and conquer algorithm recursively to a large problem into
ffc-1.4.tar
- Key Features * Neural network design, training, and simulation * Pattern recognition, clustering, and data-fitting tools * Supervised networks including feedforward, radial basis, LVQ, time delay, nonlinear autoregressive (NARX), and laye
Neural-Network-Design-by-Hagan
- 《神经网络设计》本书介绍了神经网络的基本结构和学习规则，重点是对这些神经网络的数学分析，训练方法和神经网络在模式识别、信号处理以及控制系统等工程实践问题中的应用-The book introduces the basic structure of the neural networks and learning rules focus on the mathematical analysis of these neural networks, training methods and neura
Pattern-Recognition2
- 清华模式识别第二次作业，采用dataset2.txt 数据作训练样本，采用身高与体重特征进行性别分类，建立最小错误贝叶斯分类器；2、采用身高体重数据作为特征，以 dataset2.txt 作为训练数据，用 Fisher 线性判别方法设计分类器；3、从多层感知器、SVM、近邻法选择一种方法，进行上述的分类实验；-Tsinghua second operation pattern recognition using dataset2.txt data for training samples, us
mashijuli
- 模式分类之最小马氏距离分类器设计，对给出样本点进行分类处理-Minimum Mahalanobis distance classifier design pattern classification, the sample points are given for classification