使用labview编写的神经网络程序，多输入多数出。

统计模式识别算法包，包括线性分类算法，SVM，PCA，LDA，EM，k-means分类等多种常用的模式识别算法。-Statistical pattern recognition algorithm package, including a linear classification algorithm, SVM, PCA, LDA, EM, k-means classification and many other commonly used pattern recognition algorithms.

Evenly spaces the cities on the perimeter of a wheel and returns a vector of their coordinates 利用AI技术生成一个圆-Evenly spaces the cities on the perimeter of a wheel and returns a vector of their coordinates the use of AI technology to generate a circle

遗忘因子法递推算法用于估计数学模型的参数,精确度较高!-Forgetting factor recursive algorithm method used to estimate the parameters of the mathematical model, high accuracy!

条码技术-barcode technology

利用c语言实现人工智能神经网络的bam算法-Using c language bam neural network artificial intelligence algorithms

本程序是使用一种遗传算法解决m个工件分配给m架机床的效益最优化问题，-this program is to use a genetic algorithm to solve m m allocated to the workpiece-machine efficiency optimization,

实现了一般表达式的合一算法（采用最一般合一求取方法）-achieve a general expression of unity algorithm (to use the most general strike Ecumenical methods)

knn，即k最近邻算法是模式识别中的一种比较简单而经典的分类算法-Knn, or k-nearest neighbor algrithom, is a simple and classical classifier algrithom.

利用竞争学习进行模式分类实例-using competitive learning example for pattern classification

2。《遗传算法――理论、应用与软件实现》，王小平、曹立明编着 西安交通大学出版社 2002年第一版 本书全面系统地介绍了遗传算法的基本理论，重点介绍了遗传算法的经典应用和国内外的新发展。全书共分11章。第1章概述了遗传算法的产生与发展、基本思想、基本操作以及应用情况；第2章介绍了基本遗传算法；第3章论述了遗传算法的数学基础；第4章分析了遗传算法的多种改进方法；第5章初步介绍了进货计算理论体系；第6章介绍了遗传算法应用于数值优化问题；第7章介绍了遗传算法应用于组合优化问题；第8章介绍了遗传算法应用于机器学习；第9章讨论了遗传算法在智能控制中的应用；第10章讨论了遗传算法与人工生命研究的相关问题；第11章介绍了遗传算法在图像处理、模式识别中的应用。-2. "Genetic Algorithm-- theory, application and software," Wang Xiaoping, Li-Ming Cao compile Xi"an Jiaotong University Press in 2002 the first book version of the comprehensive and systematic introduction of the genetic algorithm"s basic On focuses on the classical genetic algorithm use and the new development. The book is divided into 11 chapters. Chapter 1 provides an overview of the genetic algorithm for the selection and development of basic ideas, basic operation and the application; Chapter 2 introduces the basic genetic algorithms; Chapter 3 of the genetic basis of a mathematical algorithm; Chapter 4 Analysis of the genetic algorithm app