％ Train a two layer neural network with the Levenberg-Marquardt ％ method. ％ ％ If desired, it is possible to use regularization by ％ weight decay. Also pruned (ie. not fully connected) networks can ％ be trained. ％ ％ Given a set of cor

神经网络是单个并行处理元素的集合，我们从生物学神经系统得到启发。在自然界，网 络功能主要由神经节决定，我们可以通过改变连接点的权重来训练神经网络完成特定的功能-A single neural network is a collection of parallel processing elements, we have been inspired by biological nervous system. In nature, the network function of a decisi

用MATLAB实现二层bp神经网络的计算。可以改变阈值和权值以改进算法，并可以将该方法推广到多层网络。-Using MATLAB to achieve the second floor bp neural network computing. Can change the threshold value and weight to improve the algorithm and the method can be extended to the multi-layer network.

Kohonen神经网络算法工作机理为：网络学习过程中，当样本输入网络时，竞争层上的神经元计算输入样本与竞争层神经元权值之间的欧几里德距离，距离最小的神经元为获胜神经元。调整获胜神经元和相邻神经元权值，使获得神经元及周边权值靠近该输入样本。通过反复训练，最终各神经元的连接权值具有一定的分布，该分布把数据之间的相似性组织到代表各类的神经元上，使同类神经元具有相近的权系数，不同类的神经元权系数差别明显。需要注意的是，在学习的过程中，权值修改学习速率和神经元领域均在不断较少，从而使同类神经元逐渐集中。-

This project provides matlab class for implementation of convolutional neural networks. This networks was developed by Yann LeCun and have sucessfully used in many practical applications, such as handwritten digits recognition, face detection, robot