chuneng_Charge

已知训练序列的LBG算法的matlab实现，(LBG algorithm matlab realize the known training sequence,)

MMSE-SIC, ML, ZF with Tx= 1 to 10

说明：  数字图象处理,对图象进行二值化处理,得到最简图象(digital image processing, image binarization, the most simple image)

神经网络的 语音识别 初学者可以看看 希望对大家有帮助(Speech recognition neural network can look at beginners)

说明：  机器人matlab编程课本的程序，每一个程序都很好。(The Program of Robot Matlab Programming Textbook)

说明：  6. 在三条径的瑞利信道中，对于OFDM： (1) 请设计一种具体的导引辅助的信道估计方法，用Simulink进行仿真，测量BPSK调制时的误码率性能。画出比特信噪比与信道估计均方误差的关系曲线，画出比特信噪比与误码率的关系曲线。 (6. In the three path Rayleigh channel, for OFDM: (1) Please design a specific guide-assisted channel estimation method, the Simulink simulation, BPSK modulation measuring the bit error rate performance. Draw-bit signal to noise ratio and channel estimation mean square error of the curve, draw-bit signal to noise ratio and bit error rate curve.)

iBatis简单入门教程.简单描述了一个简单demo的书写.(iBatis Tutorial.A brief description of writing a simple demo.)

基于增广矩阵束的L型阵列的二维DOA估计MATLAB程序，简单易懂(Based on augmented matrix l-shaped array beam of 2-d DOA estimation MATLAB procedures, simple and easy to understand)

1、faii.m 求复杂网络矩阵A的对角线元素 2、logistic.m 逻辑斯蒂映射 3、mh_feedback_Lorenz.m & Lorenz.m 洛伦兹方程连续反馈 4、mh_daleytime_feedback.m & Lorenzdt.m 洛伦兹方程延时反馈 5、mh_Henon_map.m 埃农映射 6、mh_ogy_Henon.m OGY方法（参数微扰法）控制埃农映射 7、mh_ogy_logistic.m OGY方法控制逻辑斯蒂映射 8、ode45_Lorenz.m &ode45_Lorenz_ext.m -用Matlab5. 3 求解洛伦兹方程(Faii.m seek the diagonal elements of the complex network of matrix A, logistic.m logic Logistic Map, mh_feedback_Lorenz.m & Lorenz.m Lorentz equation is continuous feedback, mh_daleytime_feedback.m Lorenzdt.m Loren feedback when you hereby Fangcheng Yan mh_Henon_map.m Aye agricultural mapping mh_ogy_Henon.m the OGY method (parameter perturbation method) control angstrom agricultural mapping, the control logic of mh_ogy_logistic.m the OGY method Logistic Map, ode45_Lorenz.m ode45_Lorenz_ext.m- to use Matlab5. 3 solution of the Lorentz equation)

说明：  线性判别分析（LDA）：将高维的样本投影到最佳鉴别矢量空间，来达到抽取分类信息和压缩特种空间维数的效果，投影后保证样本在新的子空间有最大的类间距离和最小的类内距离。(Linear discriminant analysis (LDA): projects high-dimensional samples into the best discriminant vector space to extract classification information and compress the dimension of special space. After projection, it ensures that the samples have the maximum inter class distance and the minimum intra class distance in the new subspace.)