89346528ImageEnage

implementation of jpeg compression

tracking robot by vision sensor

数值分析 通过matlab 编程实现。由多元插值等程序组成(matlab numerical simulation )

人工网络的原理及应用讲义。讲得很详细，包括matlab仿真方法(Principles of artificial network and application notes. Very detailed, including the matlab simulation method)

误差系统同步，matlaB程序，混沌系统(Synchronization error system, matlaB procedures, chaotic systems)

Neural Network using a Generalized Linear Model

根据伪随机序列理论，由混合同余法产生均匀分布的随机数，进而根据中心极限定理来产生高斯噪声。 分析所产生的均匀分布和高斯分布随机信号的均值、方差、自相关等数字特征，估计其概率密度函数并进行分析，估计其功率谱密度并进行分析。说明该高斯噪声是否符合白噪声特性。 对该高斯噪声进行FIR低通滤波，估计输出低通型限带白噪声的功率谱、相关时间等，并结合白噪声通过线性系统相关理论来进行分析。 (According to the theory of pseudo-random sequence, a uniformly distributed random numbers by mixed congruential method to generate Gaussian noise, and then according to the central limit theorem. Produce a uniform distribution of the analysis and the mean of the Gaussian distribution random signals, variance, since the digital characteristics of the correlation, the probability density function is estimated and analyzed, it is estimated that its power spectral density, and analyzed. The Gaussian noise is in line with the characteristics of white noise. FIR low pass filter of the Gaussian noise, the estimated output of low-pass type band-limited white noise power spectrum, time, etc., combined with the white noise to be analyzed by linear system theory.)

UTV工具包提供46个Matlab函数，用于计算和修改秩显URV和UTV分解,总称为UTV分解． (UTV Toolkit provides 46 Matlab function, used to calculate and modify the rank significantly URV and UTV decomposition, with a total known as UTV decomposition.)

比较QR分解算法与迫零算法的误码率，支持BPSK调制和QPSK调制，天线数量可以选择(Compare QR decomposition algorithm and zero forcing algorithm BER)

％ 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) ()