CSLMS

Compute the OFDM parameters and improve the bit rate

计算声音的旋律，利用了听觉模型和相关函数。(Calculation of the melody of the voice)

说明：  一本matlab的虚拟现实的讲义，书写的还不错！(A virtual reality matlab lecture notes, writing bad!)

仿真程序：首先需要用一个随机发生器产生（0.1）内的均匀随机数，然后再将该序列映射到对应的幅度电平｛Am｝。然后将这个范围再分成4个相等的区间，这些子区间分别对应于4个信号比特的符号00，01，10，11。检测器观察到r=Am+n，并且计算r和4种可能传输的信号幅度之间的距离，它的输出Bm就是相应于最小距离的信号电平。Bm与真正的的传输信号幅度比较，差错计数器用来对检测器产生的差错计数。(Simulation program: first need to use a random generator (0.1) the uniform random number, then the sequence is mapped to the corresponding amplitude level {Am}. Then this range has been divided into four equal intervals, these sub-intervals corresponding to four signal bits of the symbol 00,01,10,11. Detector observed r = Am+ n, and calculate r and 4 possible transmission distance between the signal amplitude, its output corresponding to the minimum distance Bm is the signal level. Bm and the real rate of transmission of the signal comparison, error detection counter is used to generate the error count.)

16QAM的映射图的比较 里面有没有进行信道估计的映射图 和进行了信道估计的映射图(Comparison of 16QAM mapping there are no plans for channel estimation for a map and map channel estimation)

《MATLAB神经网络30个案例分析》中的第13个例子，案例13 SVM神经网络中的参数优化---提升分类器性能。希望对大家有一定的帮助！(The MATLAB neural network analysis of 30 cases of example, 13 cases of 13 SVM parameters optimization of neural network classifier performance- ascension. Hope to have certain help to everybody! )

For use with MATLAB Simulink and Power System Blockset

Here i have attached zip file for noise removal using vector median filter

说明：  主要讨论了QPSK的调制解调原理，分析了它们的调制解调实现过程(Mainly discussed the QPSK modulation and demodulation principle, an analysis of their realization of the process of modulation and demodulation)

本例研究利用Matlab工具箱的BP网络仿真某系统故障的预测,假设3个故障的样本分别为(1 1 0), (0 1 1)(1 0 1), 3个故障分别编码为(1 0), (0 1), (1 1),下面利用BP工具函数设计网络,用自适应学习率算法进行BP的设计、训练和仿真。(cases using the Matlab toolbox BP network simulation of a system fault forecast Assuming three fault samples were (1 1 0), (0 1 1) (1 0 1) three failures were coded as (1 0), (0), (1), below BP network design tool function, Adaptive learning rate BP algorithm design, simulation and training.)