PS2

反馈网络是神经网络的基础 这里提供了神经网络中用到的反馈 这里能充分理解文档的内容就能很好的掌握神经网络的基础。我将各个函数写成了不同的文档 就是便于大家理解。(Feedback network is the basis of the neural network here provides feedback neural network is used here to fully understand the content of the document can very good master the basis of neural network. I will each different function in the form of a document is easy to understand.)

包含十种经典的软件滤波的说明，以及其中8种滤波的例子，都是带的学生写的，并且附带测试报告。(Contains ten kinds of classic filtering software descriptions and examples of which eight kinds of filtering are written with students, and with a test report.)

（1） 分别采集一段浊音和清音语音信号（是你自己说的），采样率为8KHZ，量化精度为16比特线性码； （2） 分析帧长取为30ms（或10ms～50ms）； （3） 根据语音信号倒谱分析和LPC谱分析的编程流程图（图2.1、图2.2）编制浊音语音信号谱分析的matlab程序，上机调试给出相应波形，并根据图形，观察共振峰情况； （4） 将语音信号换为清音语音，运行程序，与浊音语音的运行结果进行比较，并得出结论。 （5） 在LPC谱分析中，改变阶数p （p分别等于4、8、12、40）时，观察对谱包络的影响，并与信号谱（DFT谱）进行比较。 ( voice signal processing)

说明：  使用MATLAB设计滤波器，然后下消除指定位置消除消元(Design the filter with MATLAB, then eliminate the specified position to eliminate the elimination.)

说明：  极坐标潮流程序，附有4节点，33节点，1047节点的数据，已编译通过。(Polar current procedures, with 4 nodes, 33 nodes, 1047 nodes in the data, compiled by.)

matlab ofam 16qam 信道仿真(matlab ofam 16qam )

一个实例搞定MATLAB界面编程 pjimage.m(matlab m_file)

说明：  离散动力学模型预测中国30年以后得艾滋病人数(Discrete kinetic models to predict the 30 years after AIDS was the number of)

Model of SSSC which is used to compensate for the reactive power in transmission line.Model of SSSC which is used to compensate for the reactive power in transmission line.Model of SSSC which is used to compensate for the reactive power in transmission line.Model of SSSC which is used to compensate for the reactive power in transmission line.Model of SSSC which is used to compensate for the reactive power in transmission line.Model of SSSC which is used to compensate for the reactive power in transmission line.

采用Clewlow and Strickland 单要素日现货模型，利用Monte Carlo方法模拟商品现货价格的Matlab程序。(Commodity Model One Factor Spot Model：This code simulates commodity spot prices using the Clewlow and Strickland one factor daily spot model using a Monte Carlo approach. The derived stochastic differential equations (SDEs) are solved using several finite difference schemes.)