svm_demo

svm_nu 分类源码 用于svm的分类编程同svm_c 相近(svm classification svm_nu source for the classification of programming with similar svm_c)

matlab program to find prime numbers

以块×块的方式获取图像,解决了现有的CS方法中可压缩采样算子所需存储较大的问题(Way to block × block access to images, the CS method to solve the existing sampling operator for compressible large memory requirements and issues)

基于马尔科夫链的连续语音识别的源代码Matlab源码--Speechh Recognition Matlab source code -- (Based on Markov chains, continuous speech recognition source code Matlab source- Speechh Recognition of Matlab the source code-)

随机产生信息码求误码率 信息码长度（帧长64bit） 息码速率为10KHz（100us） 发送带宽20KHz（信息码速率的2倍） 发送信号功率2W 载波频率70MHz 采样频率280MHz（发送数据产生采样率） 20KHz方波 0KHz方波 0KHz方波高低电平采样点数 信息码采样点数 ASK调制的调制度ma=1-2/(2+alpha) 根据2ASK调制度确定alpha值(Random generation of information code for error rate 信息码长度（帧长64bit） Message length (64bit) 息码速率为10KHz（100us） The rate of interest rate is 10KHz (100US) 发送带宽20KHz（信息码速率的2倍） Transmission bandwidth 20KHz (2 times the rate of the information code) 发送信号功率2W Transmit signal power 2W 载波频率70MHz Carrier frequency 70MHz 采样频率280MHz（发送数据产生采样率） Sampling frequency 280MHz (transmit data generated sampling rate) 20KHz方波 20KHz Fang Bo 0KHz方波 0KHz Fang Bo 0KHz方波高低电平采样点数 0KHz square wave height sampling points 信息码采样点数 Information code sampling point ASK调制的调制度ma=1-2/(2+alpha) ASK modulation of the modulation system ma=1-2/ (2+alpha) 根据2ASK调制度确定alpha值 Determine the alpha value according to the 2ASK modulation system )

基于批量最小二乘、迭代最小二乘辨识Volterra Series程序(Based on Least Square, iterative least square identification Volterra Series program)

嵌入同步信号以确定水印的嵌入位置，同时还可以抵抗各种时间轴上的同步攻击(Embedded sync signal to determine the location of the embedded watermark, but also resistant to a variety of simultaneous attacks timeline)

mppt hill climbing with solar cill model

The method works as follows. 1. For a data set with dimensionality, d, compute the variance of data in each dimension (column). 2. Find the column with maximum variance call it cvmax and sort it in any order. 3. Divide the data points of cvmax into K subsets, where K is the desired number of clusters. 4. Find the median of each subset. 5. Use the corresponding data points (vectors) for each median to initialize the cluster centers.

归一化LMS滤波算法的MATLAB仿真程序 (Normalized LMS filtering algorithm MATLAB simulation program)