这个论证的可逆跳MCMC模拟退火使用翻译..

模式识别工具包，有很多模式识别的算法，可以在matlab中调用-Pattern recognition tool kit, there are many pattern recognition algorithms, you can call matlab

This a GA implementation using binary and real coded variables. Mixed variables can be used. Constraints can also be handled. All constraints must be greater-than-equal-to type (g >= 0) and normalized (see the sample problem in prob1 in objective()).-This a GA implementation using binary and real coded variables. Mixed variables can be used. Constraints can also be handled. All constraints must be greater-than-equal-to type (g gt;= 0) and normalized (see the sample problem in prob1 in objective()).

:一书的配套源程序，结合数据挖掘和机器学习的知识,以java语言实现了具有代表性的各类数据挖掘方法.例如:classifier中的ZeroR.OneR.NaiveBayes.DecisionTable.IBK.C45,还有聚类,数据预处理等-: lt; Lt; Data Mining-- Practical Machine Learning Technology and java achieve gt; Gt; A matching the source, combining data mining and machine learning, the knowledge, java language to a representative of the various types of data mining. For example : the classifier ZeroR . OneR.NaiveBayes.DecisionTable.IBK.C45, clustering, data pretreatment

基于旋量的机器人运动学及动力学分析，是一种新的研究机器人运动学及动力学的方法-Based on spinor analysis of robot kinematics and dynamics

fan_nncC语言神经网络程序包-fan_nncC language neural network package

这是一个神经网络开发包。目录ann下是专门针对神经网络的代码，外部目录是一些公用的代码，与神经网络无关，但是神经网络的代码用到了它们。 ann目录下有一个目录demo，里面存放了一些示例程序，请参照它们进行编程。 ann/prj/vs7下是编译整个库的Visual Stdudio 2003工程文件-This a neural network development kit. Ann directory under specific neural network code, external directory is some common code, has nothing to do with the neural network, but neural networks use of their code. Ann directory is a directory demo, stored inside a sample program, please refer to their program. Ann/prj/vs7 under compiler for the entire 2003 Visual Stdudio engineering documents

CPN算法的matlab实现，CPN人工神经网络-Matlab algorithm of network，The artificial neural network, network

遗传算法与工程设计-Genetic Algorithms and Engineering Design

遗传算法 算法实例MATLAB程序，包括了：选择 变异 交叉 遗传算子-GA

识别数据集,可以用来作为,分类的实验数据.类别:模式识别-Identification of data sets, can be used as, the classification of experimental data. Category: Pattern Recognition