ChEst21STBC_OFDM1

matlab信道容量仿真，包括正态，瑞利，nakagami三种信道情况下的信道容量(channel capacity matlab simulation, including normal, Rayleigh, nakagami three kinds of channels in case of channel capacity)

T=[1 0 0 1 0 0 1 0 0 0 1 0 0 1 0 0 1 0 0 0 1 0 0 1 0 0 1] 输入向量的最大值和最小值 threshold=[0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1] net=newff(threshold,[31 3],{ tansig , logsig }, trainlm ) 训练次数为1000，训练目标为0.01，学习速率为0.1 net.trainParam.epochs=1000 net.trainParam.goal=0.01 LP.lr=0.1 net = train(net,P,T) 测试数据，和训练数据不一致 P_test=[0.2101 0.0950 0.1298 0.1359 0.2601 0.1001 0.0753 0.0890 0.0389 0.1451 0.0128 0.1590 0.2452 0.0512 0.1319 0.2593 0.1800 0.0711 0.2801 0.1501 0.1298 0.1001 0.1891 0.2531 0.0875 0.0058 0.1803 0.0992 0.0802 0.1002 (T = [1 0 0 1 0 0 1 0 0 0 1 0 0 1 0 0 1 0 0 0 1 0 0 1 0 0 1] ' of the maximum and minimum input vector threshold = [0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1] net = newff (threshold, [31 3], {' tansig' , ' logsig' }, ' trainlm' ) training times for the 1000 target of 0.01 training, learning rate of 0.1 net.trainParam.epochs = 1000 net. trainParam.goal = 0.01 LP.lr = 0.1 net = train (net, P, T) test data, and training data inconsistencies P_test = [0.2101 0.0950 0.1298 0.1359 0.2601 0.1001 0.0753 0.0890 0.0389 0.1451 0.0128 0.1590 0.2452 0.0512 0.1319 0.2593 0.1800 0.0711 0.2801 0.1501 0.1298 0.1001 0.1891 0.2531 0.0875 0.0058 0.1803 0.0992 0.0802 0.1002 )

用平均值法对图片序列经行背景建模，并保存。(Method of image sequences with the average background modeling by the line and save. （Attached picture) )

qrd_rls_AR_pred.m - use the QR decomposition-based RLS algorithm to predict complex-valued AR process.(qrd_rls_AR_pred.m- use the QR decomposition-based RLS algorithm to predict complex-valued AR process.)

卡尔曼滤波 可以对目标进行跟踪，数据处理 滤波(Kalman filter can track the target, data processing filter)

说明：  it is a very good way to use matlab simulink for analysis of control systems in nature

说明：  matlab 系统仿真 实例第十二章所有例子，可以学习下；(matlab simulation examples of Chapter XII of all the examples, you can learn from the next )

针对电压暂降的问题,按照“DVR系统设计→检测算法研究→控制方法研究→系统建模→结果分析→硬件实现”的思路,利用参数模糊自整定PID控制方法,对三相无串联变压器型DVR进行控制,实现了对系统电压暂降快速、准确的补偿。(Aiming at the problem of sags, a fuzzy PID control strategy is proposed to the transformerless DVR following the idea of “DVR system→detection algorithm→control strategies→system modeling→results analysis→hardware implementing”. )

利用EM算法实现高斯混合模型的优化，完成特征建模(Use of EM Algorithm to to achieve the the the optimization of of the Gaussian mixture model, to complete the Feature Modeling)

basic of matlab program