watermarking

MATLAb的灰色系统的预测数据的简单实现，(MATLAb simple implementation of Grey Prediction)

用自适应梯形公式求解常微分方程初值问题的数值解的MATLAB主程序及使用例子。(MATLAB main solving initial value problems of ordinary differential equations using adaptive trapezoidal numerical solutions and the use of examples.)

The classical filtering and prediction probl em is re-examined using the Bode- Shannon representation of random processes and the “state transition

设计了镜像滤波器opt_filter函数来实现子带分解与合成。取N=256， nbands=16，调用滤波器函数完成子带分解与合成(Mirror filters are designed to achieve opt_filter function subband decomposition and synthesis. Take N = 256, nbands = 16, call the filter function and achieve Synthesis Subband Decomposition)

一个关于认知无线电方面的PDF文档，对学习MIMO和认知无线电的人有帮助。(A cognitive radio about the PDF document to the study of MIMO and cognitive radio people have help.)

Test Ant colony optimization

HCL Test Paper Pattern (HR Interview, Techincal And Aptitude) Aptitude is an online round. There were only 2 rounds for us. 1.Aptitude(2 Apps for IT and CSE) A. General aptitude(60 que in 50 min) B. Technical Aptitude(Data Structures,C,OS)[25 que in 20 min]

digital system processing(generation of complex exponential sequence)

自适应滤波的一种最小均值法因算法简单故应用很广泛值得探究与开发的继续研究(A minimal adaptive filtering algorithm is simple because it means method is widely applied and development should continue to explore )

实验一 双极性矩形随机信号的归一化功率谱密度一 1.1 功率谱密度简介 平稳过程的任何一个非零样本函数的持续时间为无限长，显然都不满足绝对可积和总能量有限的条件。因此，它的傅里叶变换不存在即没有频谱函数。所以我们用功率谱密度来表述其频谱特性。 随机过程的任一实现是一个确定的功率型信号。而对于任意的确定功率信号f(t)，它的功率谱密度为： 式中， 是f(t)的截短函数 对应的频谱函数。f(t)是平稳随机过程 的一个实现。而随机过程某一个实现的功率谱密度不能作为过程的功率谱密度。过程的功率谱密度应该看作是任一实现的功率谱密度的统计平均，即 虽然该式给出了平稳随机过程的功率谱密度，但我们通常都不利用这个式子来计算功率谱。我们知道，确知的非周期功率信号的自相关函数与功率谱密度是一对傅里叶变换。对于平稳随机过程，也有类似的关系，即 和 对于平稳随机过程我们通常先求出其自相关函数再利用上式求出其功率谱密度。 1.2 实验要求  1.了解平稳随机信号功率谱的概念及计算方法  2.仿真不同占空比，等概、非等概双极性矩形随机信号的归一化功率谱密度  3.分析不同信号所包含的频谱分量，有无直流分量和定时分量信息 (A pair of rectangular random experiment polarity signal sample return a nonzero function of any duration power spectral density of a 1.1 power spectral density of a stationary process Introduction of infinite length, apparently not satisfied absolutely integrable and the total energy of the limited conditions. Therefore, it is the Fourier transform of the spectrum that does not function does not exist. Therefore, we use the power spectral density to express their spectral characteristics. Any random process is a realization of a certain type signal power. For arbitrarily determined power signal f (t), its power spectral density is: wherein, is f (t) is a function corresponding to the truncated spectrum function. f (t) is a stationary random process of realization. The random process to achieve a certain power spectral density can not serve as the power spectral density of the process. Power spectral density process should be seen as a statistical average power spectral density of any r)