模式识别分类 内有聚类算法.分段线性算法

学习遗传算法的标准入门程序,这是我当初入门的时候用的。-Perfect code to learn genetic algorithm

通过人工智能算法快速实现神经网络识别，具有更加高效和快速的特点-Through artificial neural network algorithm for rapid identification, have a more efficient and rapid characteristics of

模式识别以及重要问题，很好的内容，千万不要错过-Pattern recognition, as well as important issues, very good content, do not miss

此为疾病诊断专家系统，用这种结构建立的知识库可以很方便地实现上面所提到的各种功能。这种结 构的最独特之处就是依靠相同的关键（疾病名或其代码）来实现一种疾病与其症候之 间的相互联系。疾病名与症候分别用二叉树进行排序。排序后可由疾病名而查到与该 疾病名有关的所有详细情况，也可由一种症候而查到哪些疾病有这种症候，以及该症 候可能引起各种疾病的概率。-This is the disease diagnosis expert system, using this structure to establish the knowledge base can easily realize the above mentioned features. The structure of the most unique is that relying on the same key (the disease or its code) to achieve a disease and its symptoms between. Name and symptoms of disease were treated with binary tree sort. Sort by the disease after the name of the disease were found with all the details of which can also be a symptom of the diseases that have found such a symptom, as well as the symptoms may lead to the probability of various diseases.

基于小波神经网络算法的流域日径流预报模型，该例程为结合型小波神经网络的例子-based on wavelet neural network algorithm watershed day runoff forecasting model, the combination of routines for wavelet neural network examples

illustrate Genetic Algorithm with Island model, written in C#.

以上是很好的SVM训练的程序，包括训练和识别-The above is a good SVM training procedures, including training and identification

The software implements particle filtering and Rao Blackwellised particle filtering for conditionally Gaussian Models. The RB algorithm can be interpreted as an efficient stochastic mixture of Kalman filters. The software also includes efficient state-of-the-art resampling routines. These are generic and suitable for any application.-The software implements particle filteri Vi and Rao Blackwellised particle filtering az r conditionally Gaussian Models. The RB algori thm can be interpreted as an efficient stochast ic mixture of Kalman filters. The software also includes efficient state-of-the-art resampl ing routines. These are generic and suitable az r any application.

模式识别――原理、方法及应用-pattern recognition-- principles, methods and applications

This code in this directory implements the binary hopfield network.Source code may be found in HOPNET.CPP. A sample training file is H7x8N4.trn. Sample test pattern files are: H7x8D4.TST, H5x8D7.TST,H5x8D7.TST and H5x8D9.TST, Output of the program goes to both the screen and a file, ARCHIVE.LST.