mohr

说明：  在matlab中实现信号的模数以及数模转换，并包含简单的界面(achieve the Matlab Signal Module and hundreds of analog conversion, and includes a simple interface)

翻译结果 这功能主要是OFDM系统传输过程，IFFT和FFT变换，加导频，循环前缀，QAM调整，解调出来 (This function is mainly transmitted OFDM system process, IFFT and FFT transform, pilot, cyclic prefix, QAM adjustment, demodulation)

this simulationto make table

无迹卡尔曼滤波UKF是重要的非线性滤波方法。它采用UT变换的方法，不再近似系统的非线性方程，它仍然用高斯随机变量表示状态分布，不过是用特定选择的样本点加以描述，每个点叫一个高斯点，它从系统状态的概率密度函数中取出；然后，按系统的真实模型演化，得到非线性演化后的σ点，使得样本均值和样本方差是真实均值和真实方差的好的近似。 在这个程序中，实现了基于UKF的滤波方法，并且建立了两种仿真环境进行实验。(Unscented Kalman filter UKF is an important nonlinear filtering method. It uses the UT transformation method, no similar system of nonlinear equations, it still says the state with the Gaussian distribution of random variables, but the specific choice is to describe the sample points, each point is called a Gaussian point, it is from probability density function of the system state to remove then, according to the true model of evolution of the system obtained after the nonlinear evolution of σ point, making the sample mean and sample variance is true variance of the mean and the true good approximation. )

最经典的算法，LBG算法，其计算量大，可在进一步改进得到更好的效果(The most classical algorithm, LBG algorithm, the calculation volume can be further improved to get better results)

采用周期图法在matlab中进行功率谱密度计算(Periodogram method using power spectral density calculation in matlab)

这本书刘维的精通matlab于Ｃ和C++混合编程第二版，对进行对matlab优化的有很大的帮助。(The mastery book Liouville matlab in the second edition of the programming the C and C++ mixed on Matlab optimization of great help.)

输入各个字符及对应出现的次数 ； 建立赫夫曼树并对各个字符进行编码 ；然后 对 输入 的 二进制 串进行 译码(Enter the various characters and the corresponding number of emerging establish Huffman tree and the various characters coding then enter strings of binary decoding)

对阈值隐藏图像的提取。已经经过阈值隐藏算法隐藏的二值图像，通过此算法进行信息提取。(Hidden images on the extraction threshold. Hiding algorithm has been hidden threshold binary image information extracted by this algorithm.)

由Matlab编写的实现lv-svm分类的源码程序(Prepared by the Matlab implementation of lv-svm classification of source programs)