sanjiao-Z

kalman滤波实验，目标轨迹跟踪，很好用的例子，供大家学习用(kalman filtering experiments, the target trajectory tracking, with a good example for all to learn)

两个简单程序，一个是在空域和频域分别实现了两个矩阵的卷积。另一个程序主要是为了查看几个模板的空域及频域响应形式，方便理解(Two simple procedures, one is in the spatial and frequency domain is realized for the convolution of two matrices. Another program is mainly to see the airspace of several templates and frequency domain response form, to facilitate understanding)

This is the second tutorial of a series of image processing tutorials

用matlab构造滤波器,非常有用。用matlab构造等波纹滤波器(Matlab filter structure with very useful)

位置指令为幅值为1.0的阶跃信号，r（k）=1.0。网络结构为1-4-1，高斯函数的参数值取Cj=[-2 -1 1 2]T ，B=[0.5 0.5 0.5 0.5]T 。 网络权值学习参数为η=0.30，α=0.05 。PID控制各参数的初RBF网络控制，被控对象为G（s）= 取采样时间为1ms，采用Z变换进行离散化，离散化后的被控对象为 y(k)=-den(2)*y（k-1）-den(3)*y(k-2)+num(2)*u(k-1)+num(3)*u(k-2) 始值为，kp=20， kd=0.3， ki=0.1。 (Position command for the step signal amplitude of 1.0, r (k) = 1.0. The network structure is 1-4-1, the Gaussian function parameters taken Cj = [-2-1 1 2] T, B = [0.5 0.5 0.5 0.5] T. Weight learning parameter η = 0.30, α = 0.05. PID control parameters at the beginning of each RBF network control, the controlled object is G (s) = take the sampling time is 1ms, using the Z transform discrete, discretized controlled object is y (k) =-den (2)* y (k-1)-den (3)* y (k-2)+num (2)* u (k-1)+num (3)* u (k-2) initial value, kp = 20, kd = 0.3, ki = 0.1.)

matlab demo code .. .. .. ..

语谱图程序，用于语音信号分析。实现获取基音周期，区分清音、浊音等功能(Spectrum language program for speech signal analysis. Achieve access to the pitch period, the distinction between voiceless, voiced etc.)

在目标识别中利用结构化支持向量机加快评估过程而不降低精度(Using ranking SVM to accelerate the uation process of Object Recognition without decreasing accuracy)

在Matlab中用高斯—拉盖尔公式及高斯—埃尔米特公式求函数的近似积分。(How to use IntGaussLager and IntGaussHermite formula expressions caltulate approximate integration of functional in Matlab.)

此程序为基于LMS的自适应均衡器的仿真，取得信号为4QAM信号(This program for the simulation of the LMS-based adaptive equalizer to obtain the signal for 4QAM signal)