中文说明： 多层感知器是映射到一组适当的输出输入数据集的一个前馈人工神经网络模型。MLP 由每个层完全连接到下一个节点的有向图，多个图层组成。 在这里是完全注释、 平原和明显的代码多层感知器神经网络，把 （使用两个火车和测试数据集） 的输入的数据划分为两个或多个组，或估计所需的输出使用培训 data(regression)。 此网络使用后传播算法来更新其权重和偏置。 在此代码中，变量是数据集与 ModId.mat 培训和测试数据集，并可以与任何其他功能数据集更改。
English Description：
A multilayer perceptron is a feedforward artificial neural network model that maps sets of input data onto a set of appropriate outputs. A MLP consists of multiple layers of nodes in a directed graph, with each layer fully connected to the next one. Here is a fully commented, plain and obvious code for a Multi Layer Perceptron Neural Network to Classify input data (Using two Train and Test Data Sets) into two or more groups or to estimate the desired output using the training data(regression). This Network uses the back propagate algorithm to update its weights and biases. in this code, the ModId.mat variable is the data set with train and test data sets and can be altered with any other feature data sets.