该过程是基于网络的控制系统。系统由O组成。

Hopfield 网――擅长于联想记忆与解迷路 实现H网联想记忆的关键，是使被记忆的模式样本对应网络能量函数的极小值。 设有M个N维记忆模式，通过对网络N个神经元之间连接权 wij 和N个输出阈值θj的设计，使得: 这M个记忆模式所对应的网络状态正好是网络能量函数的M个极小值。 比较困难，目前还没有一个适应任意形式的记忆模式的有效、通用的设计方法。 H网的算法 1）学习模式――决定权重 想要记忆的模式，用-1和1的2值表示 模式：-1，-1，1，-1，1，1，... 一般表示： 则任意两个神经元j、i间的权重： wij=∑ap(i)ap(j)，p=1…p； P：模式的总数 ap(s)：第p个模式的第s个要素（-1或1） wij：第j个神经元与第i个神经元间的权重 i = j时，wij=0，即各神经元的输出不直接返回自身。 2)想起模式： 神经元输出值的初始化 想起时，一般是未知的输入。设xi(0)为未知模式的第i个要素（-1或1） 将xi(0)作为相对应的神经元的初始值，其中，0意味t=0。 反复部分：对各神经元，计算： xi (t+1) = f (∑wijxj（t）-θi), j=1…n, j≠i n―神经元总数 f（）--Sgn（） θi―神经元i发火阈值 反复进行，直到各个神经元的输出不再变化。-Hopfield network-- good at associative memory solution with the realization of lost H associative memory networks, are key to bringing the memory model samples corresponding network energy function of the minimum. With M-N-dimensional memory model, the network N neurons connect between right wij and N output threshold j design makes : M-mode memory corresponding to the network is a state network energy function is the M-000 minimum. Mor

The purpose of this computer program is to allow the user to construct, train and test differenttypes of artificial neural networks. By implementing the concepts of templates, inheritance andderived classes from C++ object oriented programming, the necessity for declaring multiple largestructures and duplicate attributes is reduced. Utilizing dynamic binding and memory allocationafforded by C++, the user can choose to develop four separate types of neural networks:

以黎曼几何为理论依据，基于S.Amari的修正核函数思想提出了两种新的保角变换，用其对核函数进行数据依赖性改进，进一步提高支持向量机分类器泛化能力。以人工非线性分类问题 为对象进行研究，仿真实验结果表明采用新保角映射可以快速显著地改善分类器泛化性能，而且能大幅度地减少支持向量的数目。-Two novel conformal transformations were proposed based on the Riemannian geometry theory and S.Amari’sidea.And the kernel function was modified by the transformation in a data-dependent way.Our experimental results for theartificial nonlinear data set show that the generalization performance of support vector machines classifier is improvedremarkably and the number of support vectors is decreased greatly.

这是神经网络和遗传算法想结合的c++程序，希望对需要的朋友 有所帮助。-This is a neural network and genetic algorithm would like to combine c++ Procedures, and they hope to help a friend in need.

计算机故障智能诊断系统 用户输入计算机的故障症状 即可由系统得出故障原因和相关的处理方法-Diagnose the system in computer s trouble intelligence Users input the trouble symptom of the computer Can be had cranky reason and relevant treatment methods systematically

该程序是遗传算法的具体实现，通过该程序可以对遗传算法有更深入的了解。-The program is a concrete realization of genetic algorithm, through which the genetic algorithm program can have a deeper understanding.

一个外国人写的字符识别训练源码，VC++源码，有源码、说明及演示可执行程序，对学习和研究模式识别很有帮助。-written by a foreigner Character Recognition training source, VC source, a source that, and the demonstration of the executable, on learning and pattern recognition research helpful.

此程序用于测试神经元的库函数 // 它展示了怎样用这个库所生成的多层BP网络来求解宇称问题-this procedure for testing neuronal function of the library// it tells how to use this library generated by the multi-storey BP network to solve problems Parity

MCRGSA------组播路由问题遗传模拟退火算法 ％M-----------遗传算法进化代数 ％N-----------种群规模，取偶数 ％Pm----------变异概率调节参数 ％K-----------同一温度下状态跳转次数 ％t0----------初始温度 ％alpha-------降温系数 ％beta--------浓度均衡系数 ％ROUTES------备选路径集 ％Num---------到各节点的备选路径数目 ％Cost--------费用邻接矩阵 ％Source------源节点标号 ％End---------目的节点标号组成的向量 ％MBR---------各代最优路径编码-MCRGSA------ Multicast Routing genetic simulated annealing% M----------- genetic algorithm algebra% N----------- population size, even take Pm----------% probability parameter variation%----------- same temperature K Jump under a number of state----------% t0 initial temperature cooling% alpha------- beta coefficient%-------- balanced concentration coefficient% ROUTES------ Alternative Path Set% Enable--------- nodes to the number of alternative paths%-------- Cost adjacent costs Matrix% Source------ source node labeling% End--------- destination node labeling Group Vector%% of the MBR--------- generations optimal path coding

用BP神经网络进行对啤酒质量的识别，各个参数可以自己进行修改。-Using BP neural network to identify the quality of beer, all parameters can be modified.