LMS

用Maple和MATLAB解决科学计算问题（第三版）.pdf(Using Maple and MATLAB to solve problems in scientific computing (third edition). Pdf)

边缘检测和轮廓跟踪程序,在matlab环境下进行的编程(edge detection and tracking procedures outline of the Matlab environment for programming)

OFDM系统仿真,仿真利用ui界面，实现了BPSK、QPSK、16QAM三种调制方式(OFDM system simulation with ui interface to achieve the BPSK, QPSK, 16QAM three kinds of modulation)

MPPT connected to Buck

自己编写锁模激光程序，有些不完善的地方请见谅(Local mode-locked laser to write your own program, please forgive me some imperfect)

Radar cross section for maritime targets

说明：  12脉动换流器MATLAB-simulink仿真(rectifierSimulation of UHVDC lcc-hvdc, 12-pulse converter by MATLAB-simulink)

此代码是实数编码遗传算法的Matlab例程。用了精英保留策略选择和轮盘赌选择法，叉操作采用中间重组方式。(This code is a real-coded genetic algorithm Matlab routines. Retention policies with the elite selection and roulette wheel selection method, fork operation mode using the middle of restructuring.)

全数字调制解调器设计的matlab程序 有CIC FIR等滤波器(digital modem design Matlab CIC procedures such as FIR filters)

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)