time-frequency

％ 文件名：randlsbget.m ％ 程序员:余波 ％ 编写时间:2007.6.25 ％ 函数功能: 本函数将完成提取隐秘于上的秘密信息 ％ 输入格式举例:result=( scover.jpg ,56, secret.txt ,2001) ％ 参数说明: ％ output是信息隐藏后的图象 ％ len_total是秘密信息的长度 ％ goalfile是提取出的秘密信息文件 ％ key是随机间隔函数的密钥 ％ result是提取的信息 function result=randlsbget(output,len_total,goalfile,key) ste_cover=imread(output) ste_cover=double(ste_cover) ％ 判断嵌入信息量是否过大 [m,n]=size(ste_cover) frr=fopen(goalfile, a ) ％ p作为信息嵌入位计数器将信息序列写回文本文件 p=1 ％ 调用随机间隔函数选取像素点 [row,col]=randinterval(ste_cover,len_toal,key) for i=:len_toal if bitand(ste_cover(row(i),col(i)),1)==1 fwrite(frr,1, bit1 ) result(p,1) else fwrite(frr,0, bit1 ) result(p,1)=0 end if p==len_total break end p=p+1 end fclose(frr) ()

模拟滤波器：数字信号处理及MATLAB实现(Analog Filter: Digital signal processing and MATLAB implementation)

说明：  MATLAB进行有关机器人仿真应用时应用的机器人工具箱，很好用(MATLAB simulation of the application of robot application of robot kit, with good)

说明：  MATLAB7的官方学习手册。全英文的哦。详细的教程，值得一读。(MATLAB7 official study manual. Oh, the whole of English. Detailed tutorial, worth reading.)

A programmable-logic controller (PLC) is a compact computer-based electronic system that uses digital or analog input/output modules to control machines, processes, and other control modules. A PLC is able to receive (input) and transmit (output) various types of electrical and electronic signals and use them to control and monitor practically any kind of mechanical and/or electrical system.

it is a single machine connected ti infinity bus with SVC & TCSC & PSS

飞行仿真模型,Matlab环境中运行，可实现快速仿真，性能分析(Flight simulation model, Matlab environment, run, fast simulation, performance analysis can be achieved)

这是洛伦兹曲线问题用matlab画出一个函数的图像，体现了初值的影响(This is a problem with the Lorenz curve matlab draw a function of the image, reflecting the impact of the initial value)

非常经典的基于模糊信息处理的数据融合方法研究.用MATLAB 实现的。 请大家好好学习(Very classical information processing based on fuzzy data fusion method. Using MATLAB realization. Please study hard)

方差分析中的各种程序代码，包括 单因素方差分析，双因素方差分析，和多因素方差分析。(Analysis of variance in a variety of program code, including single-factor analysis of variance, two-factor analysis of variance, and multivariate analysis of variance.)