有关RBF的参考文献，希望能够给你带来一定的帮助

神经网络用于牌照识别-neural network license for identification

支撑向量机算法的一种改进算法，是基于增量学习的算法-Support Vector Machine Algorithm an improved algorithm is based on the incremental learning algorithm

文中设计了一个3层径向基神经网络(RBFN)用于对企业的5项评价指标进行聚类分析，并与蚁群算法做了比较分析。RBFN由输入层 到隐含层采用传统的K一均值算法，隐含层到输出层通过“模2递减”学习速率的BP学习；蚁群算法根据信息素的分配能够自动调整收索 路径，从而达到数据自动聚类的目的。结果表明，与蚁群算法相比，改进RBFN具有快速收敛、自动识别奇异样本的优点，而蚁群算法 无须教师学习，并能够达到全局最优。-In this paper, we designed a 3-layer RBF neural network (RBFN) for the 5-to-business evaluation indicators cluster analysis and ant colony algorithm has done a comparative analysis. RBFN from input layer to hidden layer using the traditional K-means algorithm, hidden layer to output layer through the Mode 2 decreasing learning rate of BP learning ant colony algorithm based on pheromone can automatically adjust the allocation of land Faso path, thereby to achieve the purpose of automatic data clustering. The results showed that compared with the ant colony algorithm to improve the RBFN has a fast convergence, automatic identification of singular advantage of the sample, while the ant colony algorithm do not need teachers to learn and be able to reach the global optimum.

一个牛人的神经网络支持向量机代码,对于搞模式识别的朋友强烈推荐!-A wonderful program of svm code coming from a superman,and strong recommendation to someone who learn about pattern-recognition .

the matlab code of ginisvm - an svm implementation good at probability regression.-the matlab code of ginisvm- an svm implementation good at probability regression.

著名的神经网络工具箱，功能十分强大，里面包含了数十种神经网络算法的实例。-Well-known neural network toolbox, function very strong, which contains dozens of examples of neural network algorithm.

Mining sequential patterns with constraint (SPADE with constraint)

标准PSO（粒子群）算法，matlab版-standard PSO (PSO) algorithm, Matlab version

--- -一个介绍支持向量机的文档。 认真读一读，会有收获的。-------- introduced a Support Vector Machine documents. Seriously read, there will be rewarding.

在数字信号处理中实现相关的能够人工智能滤波的功能-To artificial intelligence filtering