duibidu--yasuo

该书提供了详实的结合，尤为重要的是结合实例(matlab explore)

Matlab數位影音處理 影像方面的處理(Matlab image processing digital audio-visual aspect has been dealt with)

\this file contains the matlab file for radon function with its c file. to run on matlab compile the file using c++ compiler to convert c file into mex file.

说明：   本程序可以绘制p3曲线，直接输入cv、cs、EX,也通过降雨或径流数据计算绘制 [cs,cv,ma] = p3plot(a,kk,b,bb,y1,cs_cv,ma,cs,cv,x0) a=20 横向网格条数 kk=200 纵坐标标注间隔（间隔要是最大值和最小值差的整数倍） b=2000 纵坐标最大值 bb=0 纵坐标最小值 y1=[] 降雨量，横向矩阵输入,如果没有请输入[] cs_cv=[2] 没有，请输入[] ma=[] 年平均降雨量，没有输入[] cs=[] 没有，请输入[] cv=[] 没有，请输入[] x0=0.01 初始概率点，百分数,没有输入[]( this program can draw P3 curve, direct input CV, CS, EX, also by rainfall or runoff data calculation and drawing The [cs, CV, ma] = p3plot (a, KK, B, BB, Y1, cs_cv, Ma, CS, CV, x0) The a=20 of the number of horizontal grid The kk=200 longitudinal coordinate labeling interval (interval if the maximum value and the minimum value of the integer times the difference) The b=2000 of the maximum longitudinal coordinates The bb=0 of the minimum longitudinal coordinates The y1=[] rainfall, transverse matrix input, if not please input [] The cs_cv=[2] no, please enter [] The ma=[] of the average annual rainfall no input []. The cs=[] no, please enter [] The cv=[] no, please enter [] x0=0.01 initial probability, percentage, no input [])

LNBH25/26 SW control guideline. SW driver for STV0910 and STV0913 NIM.

说明：  一种新型的matlab生成随机线条的代码，用于后续处理(A new matlab code for generating random lines for subsequent processing)

说明：  电压对有功灵敏度计算公式，原理为以潮流计算方程为基础，对潮流方程进行线性化，并且交换顺序(The calculation formula of the voltage to the active sensitivity is based on the power flow calculation equation, the power flow equation is linearized, and the exchange sequence)

说明：  神经网络实例集。包括以下几个程序单层线性神经网络实例、感知器神经元解决较复杂输入向量的分类问题、基于感知器神经网络处理复杂的分类问题、数值分析程序matlab-GUI、用BP网络完成函数的逼近源程序、自组织特征映射应用实例(Examples of neural network sets. Procedures include the following examples of single-layer linear neural network, perceptron neuron input vector to solve more complex classification problems, based on the perceptron neural network to deal with complex classification problems, numerical analysis matlab-GUI, using BP network function source approximation, self-organizing feature map application)

QAM and Fading simulation

Simulation of m/m/1 type queuing process