SHT

说明：  3关节机械臂模型 基于simulink的 自己输入simin(simulink model)

自己编的程序，实现快速傅里叶变化，结果和matlab自带的fft2一样。(Own series of programs, fast Fourier transform, results and matlab native fft2 the same.)

说明：  求解动态有限元方程，板式轨道过渡段动力响应分析源程序(Dynamic finite element equations to solve, slab track Dynamic Response Analysis of the transition source)

说明：  电力有源滤波器仿真电路图子电路图之三，算法是经典的dq0算法(APF circuit simulation circuit-ter, the algorithm is the classic dq0 Algorithm)

例3：分析占空比为ta的矩形脉冲频谱 T=1 时间窗大小 ta=0.5 占空比 N=256 t=linspace(-T,T,N) ts=2*T/N fs=1/ts (x=zeros(1,N) x(N/2-round(N/2*ta):N/2+round(N/2*ta))=ones(1,2*round(N/2*ta)+1) y=fft(x,N) figure plot(t,x) title([ 时域信号图 占空比为 ,num2str(ta)]) axis([-T T-0.2 1.2]) xlabel( t /s ) figure subplot(211) f=linspace(-fs/2,fs/2,N) plot(f,abs(fftshift(y))/N) title([ 矩形脉冲双边谱 脉冲时间t=[- ,num2str(ta*T), , ,num2str(ta*T), ] ]) xlabel( f /Hz ) )

使用RGB模型来进行人脸检测，识别的结果还可以，可以作为其他检测方法的对比(use RGB model for face detection and recognition of the results can also can serve as a contrast detection method)

一种新的无味粒子滤波matlab程序, 用于目标跟踪(a new unscented pf )

说明：  FAST ICA算法，用于多个信号盲分离，可以参考一下，挺不错的(Fast ICA algorithm, used for blind separation of multiple signals, can refer to, very good)

说明：  该程序是盲源分离算法中时域—频域分离算法，该算法应用范围广泛。(The procedure is blind source separation algorithm in time domain- the frequency domain separation algorithm, which a wide range of applications.)

1.CAmodelfusion.m 主要功能： （1）完成两个传感器各自对基于CA模型的目标状态的Kalman估计； （2）实现传感器的局部状态估计的SCC和CI融合算法的实现； （3）画出局部估计和两种融合估计的位置、速度、加速度的误差； （4）画出局部估计和两种融合估计的协方差椭圆。 2.CVmodelfusion.m 主要功能： 功能与CAmodelfusion.m基本相似，差异在于实现基于CV模型的估计和估计融合。 3.CovInter.m 主要功能： 寻找CI融合算法的融合估计的协方差阵的行列式最小的权值。 4.f_plot_ellipse_m.m 主要功能： 绘制四种估计的协方差椭圆 (1.CAmodelfusion.m main functions: (1) completion of two sensors each target state based on CA model of Kalman estimation (2) the realization of the sensor partial state estimation algorithm SCC and CI integration and (3) Draw Local estimated position and two fusion estimation, velocity and acceleration errors (4) Draw two fusion of local estimates and estimated covariance ellipse. 2.CVmodelfusion.m Main Features: a CAmodelfusion.m similar, the difference is that the estimated CV-based estimation and model integration. 3.CovInter.m main functions: Find fusion algorithm fusion CI estimated covariance matrix of the determinant minimum weight. 4.f_plot_ellipse_m.m main functions: Draw four kinds estimate covariance ellipse)