The basic neural network computing

本文在学习探讨VSM算法的同时，对SVM在液压系统故障诊断中的应用进行了论述。以液压设备中常见的克令吊为研究对象，运用支持向量机理论对其进行故障诊断的仿真研究和实验研究，其中包括实验系统数学模型的设计、仿真模型的建立(用SIMUL工NK仿真软件建立仿真模型)、特征参数的提取、数据的采集等。-In this paper, VSM learning algorithm to explore the same time, SVM in the hydraulic system fault diagnosis are discussed. With hydraulic equipment in the common crane as the research object, using support vector machine theory of their fault diagnosis simulation and experimental studies, including a mathematical model experimental system design, simulation model (using SIMUL Engineering Simulation NK Software to build simulation models), the extraction of characteristic parameters, data collection and so on.

浙江大学编的神经网络入门教程，pdf格式。-Zhejiang University, made the neural network Tutorial, pdf format.

c++语言实现基于遗传算法的TSP问题，是学习遗传编程的很好的例子-c++ language implementation of the TSP problem based on genetic algorithms, genetic programming to learn a good example of

用VC++实现的，超级好用的8种神经网络源代码,超好用,超简洁 ，是我多年研究所得，已经全部测试过-With VC++ Realize, and eight kinds of super-to-use neural network source code,超好用, super-simple, is my research for many years, they have all been tested

免疫优化计算、学习与识别,是焦李成著的一本经典书中的源程序,供大家学习!-Immune Optimization calculation, learning and recognition, JIAO Li-cheng book is a classic source book for everyone to learn!

CCE is a multi-instance learning method solving multi-instance problems through adapting multi-instance representation to single-instance algorithms, which is quite different from existing multi-instance learning algorithms which attempt to adapt single-instance algorithms to multi-instance representation

一个运用遗传算法来训练神经网络的程序-use of a genetic algorithm to train the neural network process

这是IBM公司使用的一个生成数据流的源文件代码，对需要生成数据流做实验的朋友很有帮助。-This is IBM" s use of a data stream generated source file code, on the need to generate data flow experiment" s friends helpful.

神经网络模式识别及其实现，第九章。 内含：HOPFIELD和LAM -pattern recognition and neural network to achieve, chap. Intron : LAM and HOPFILED

人工智能中重要的一个问题, 用广度优先搜索的方法解决-AI an important issue, breadth- first search of solutions