ANN

一个双馈电机转子侧控制与网测控制联合调试的模型，使用SVPWM驱动。(A double fed motor rotor side control and network measurement control joint debugging model, using SVPWM drive.)

用MATLAB程序实现演化博弈的均衡求解(Equilibrium solution for evolutionary game)

和积算法应用在ISI信道检测上，首先进行调制，然后利用和积算法进行检测译码，最后看误码率(SP algorithm on the ISI channel detection, first of all be modulated, and integrated algorithm is then used for testing decoding, finally the bit error rate)

说明：  完全自主实现的神经网络代码，对于深刻理解神经网络和BP算法很有帮助。(The neural network code, which is implemented autonomously, is very helpful for us to deeply understand the neural network and BP algorithm.)

This code can capture a frame from a vidoe in matlab.

说明：  一篇讲解关于matlab与vc混合编程的问题。其中的讲解是通过实例来讲的(Matlab with a brief on the problem of mixed programming vc. Which is explained through examples of)

说明：  通过运动尺寸计算，绘制四连杆机构的运动，并动画演示(Size calculated by movement, drawing four Linkages)

This programm is to calculate a two dimentional conduction problem.

Matlab decision tree code

Elman神经网络：Elman网络是 J. L. Elman于1990年首先针对语音处理问题而提出来的, 它是一种典型的局部回归网络( global feed for ward l ocal recurrent)。Elman网络可以看作是一个具有局部记忆单元和局部反馈连接的前向神经网络。Elman网络具有与多层前向网络相似的多层结构。它的主要结构是前馈连接, 包括输入层、 隐含层、 输出层, 其连接权可以进行学习修正 反馈连接由一组“结构 ” 单元构成,用来记忆前一时刻的输出值, 其连接权值是固定的。在这种网络中, 除了普通的隐含层外, 还有一个特别的隐含层,称为关联层 (或联系单元层 ) 该层从隐含层接收反馈信号, 每一个隐含层节点都有一个与之对应的关联层节点连接。关联层的作用是通过联接记忆将上一个时刻的隐层状态连同当前时刻的网络输入一起作为隐层的输入, 相当于状态反馈。隐层的传递函数仍为某种非线性函数, 一般为 Sigmoid函数, 输出层为线性函数, 关联层也为线性函数。(Elman neural network: Elman JL Elman network is first proposed for speech processing problems in 1990. It is a typical local regression network (global feed for ward l ocal recurrent). Elman network can be seen as having a forward neural network of local memory unit and local feedback connections. Elman network has a multi-layer multilayer structure similar to the network. Its main structure is a feedforward connection, comprising an input layer, a hidden layer and output layer, which can be connected right learning correction feedback connected by a set of " structural" units, the output value of the memory for the previous time, which connection weights are fixed. In such a network, in addition to ordinary hidden layer, there is a special hidden layer, called an associative layer (or contact layer unit) this layer receives feedback signals the hidden layer, each hidden layer node has an associated layer node corresponding connection. The role of the associated layer is fo)