miscdevice

基于matlab的PID温控模拟，使用了simulink(Matlab-based simulation of PID temperature control, use the simulink)

very excellent 2 degree of freedom two link robot inverse kinematic. its graphically good.

让MIDI技术服务于音乐教学MIDI technical services to music teaching(MIDI technical services to music teaching)

Bayesian Vector Autoregression using Bayesian estimation method

water cycle algorithm for optimization

数据白化处理matlab程序，内有注释，简单易懂，适用于初学者(Data whitening processing matlab program with annotations)

有一个小的错误数据采集财产编辑线225 ： data.ObjectList （ CT表现1 ：电脑断层+ numChildren ， 1 ） = num2cell （儿童） 这一事业的情况，信息渠道，开始形成第二个是不显示的。您可以尝试的坐标(There is a small error in data acquisition and property editing line 225: data.ObjectList (CT performance 1: CT+ numChildren, 1) = num2cell (children) the cause of the situation, information channels, the second is the beginning of the formation do not show of. You can try to coordinate)

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 )

说明：  应用于混沌电路研究，可以对其进行仿真，可观测到混沌现象(applied chaotic circuit, its simulation, observation of Chaos)

说明：  离散信号时域分析的MATLAB实现 熟悉MATLAB编程方法、常用语句和可视化绘图技术(Time domain analysis of discrete signals MATLAB implementation familiar with MATLAB programming, common expressions and visual graphics)