16QAM

Multiple Coherehence simulate using matlab

有关FastICA算法的matlab实现(FastICA about matlab)

使用MATLAB编程“支持向量机聚类”与 “支持向量机回归”(Support vector machine clustering and support vector machine regression)

使用MATLAB程序编写的MP4视频转换程序，支持iBEwcP格式和viLAedU格式的转换，解码时音视频数据的获取就是建立在此之上的,学习MP4的最佳程序 (Using MATLAB programming MP4 video conversion program that supportsiBEwcP format and formatviLAedU conversion, access is built on top of this, the best learning program MP4 audio and video data decoding )

基于MUSIC算法的doa估计算法的改进,比原来的算法更有效,大家可以下载看一下了,欢迎讨论.(MUSIC algorithm based on the doa estimation algorithm improvements than the original algorithm more effective, We can look at the downloaded welcome discussion.)

omp 算法 你可以通过这个算法完成图像恢复，效果好，恢复时间短，误码率低，解决凸优化算法复杂度高的缺点(omp algorithm you can accomplish by this algorithm for image restoration, good effect, shorter recovery time, error rate, to solve the shortcomings of convex optimization algorithm with high complexity)

说明：  永磁同步电机模型电流预测控制，单矢量运行，用S函数实现(Permanent magnet synchronous motor model current predictive control, single vector operation, using s function to achieve)

these matlab files are different modulation techniques in communication

A. Fusion at the Feature Extraction Level The data obtained from each sensor is used to compute a feature vector. As the features extracted from one biometric trait are independent of those extracted from the other, it is reasonable to concatenate the two vectors into a single new vector. The primary benefit of feature level fusion is the detection of correlated feature values generated by different feature extraction algorithms and, in the process, identifying a salient set of features that can improve recognition accuracy [14]. The new vector has a higher dimension and represents the identity of the person in a different hyperspace. Eliciting this feature set typically requires the use of dimensionality reduction/selection methods and, therefore, feature level fusion assumes the availability of a large number of training data.

用数值方法实现2FSK信号的相关型解调。采用的两个2FSK波形信号为：si(t)=cos(2πfit)，i=1,2,0≤t≤Tb。这里f1=1000/Tb, f2=f1+1/Tb。(Digital modulation.)