linearpoweramplifiercharacteristic

无心磨削优化，主要用于工程计算，工程优化。(Grinding optimization, is mainly used for engineering calculations, engineering optimization.)

以前使用matlab和vc混合编程都使用的是先将m程序用mcc转化成dll，再在vc中调用 的方法。这种方法对比较复杂的m文件很方便，但是对一些小的程序，如曲线可视化、计算矩阵特征值等，对这些只需要一两行代码的小程序，再使用dll就得不偿失了。经过试验后，发现可以直接在C++程序中调用matlab c/c++ math & graphic library的函数。(before using Matlab and vc mixed programming using the first procedure used mcc m into dl l, then vc call method. This method of complex documents m very easy, but for some minor procedures, such as curve visualization, matrix eigenvalue calculation, and so on, these are just two lines need a small procedure code, reuse dll on the loss outweighs the gain. After testing, can be found directly in the C Programming Calling Matlab c/c math)

稀疏表示分类算法在ORL人脸库上的实验，参考文章： Wright J, Yang A Y, Ganesh A, et al. Robust face recognition via sparse representation[J]. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 2009, 31(2): 210-227. (Sparse representation classification algorithms on ORL face experiments, refer to the article: Wright J, Yang AY, Ganesh A, et al Robust face recognition via sparse representation [J] Pattern Analysis and Machine Intelligence, IEEE Transactions on, 2009, 31 (2):.. 210-227.)

计算输入信号的功率谱密度和估计输入信号带宽并绘图(Evaluation of the single-sided ESD and frequency bandwidth)

matlab版本的OLELM算法（在线极速序列机器学习算法），能进行模型训练和函数拟合。(matlab version OLELM algorithm (line speed serial machine learning algorithms), capable of model training and function fitting.)

Bpsk ber performance of zero forcing in mimo

以高斯函数为载波的PPM调制解调，及于理想误码率曲线相比较的误码率曲线(Gaussian function of PPM modulation and demodulation of the carrier, and the desired BER curves compared to BER curves)

丁丽娟 数值计算方法 课后实验matlab部分上机答案 仅供参考(Dingli Juan numerical methods matlab part of after-school experiment on board the answer is for reference only)

BP神经网络，自适应竞争神经网络对地震进行预测实例(BP neural network, adaptive competitive neural networks to predict the earthquake example)

Face recognition using L1 norm minimization 1.0 :Read the following paper for details of the algorithm - Robust Face Recognition via Sparse Representation by John Wright, Arvind Ganesh, and Yi Ma , Coordinated Science Laboratory, University of Illinois at Urbana-Champaign and Allen Yang, Electrical Engineering and Computer Science, University of California Berkeley.