remove-noise-----adaptive-filtering

Matlab source code for simulation of queue in Bank using exponencial distribution.

This program is used for simulation signal mean square error of the Kalman filter

基于MATLAB的PCA和KPCA的实现，有图，有返回的参数，绝对可以运行！(Based on the PCA and KPCA MATLAB to achieve, there are plans to return to the parameters, the absolute can run!)

mimo系统中空时码是其关键技术之一。本程序提出一种新的算法，能有效地提高传输速率(Space-time MIMO system code is one of the key technologies. This procedure presents a new algorithm, can effectively improve the transmission rate)

music算法仿真程序 music算法是多重信号分类算法(MUSIC METHOD)

说明：  对基础信道BPSK的实现与仿真,里面含有对各个结构构成的分别实现(On the basis of the channel realization and simulation of BPSK, which contains the composition of each structure were achieved)

读取图像变换成二进制码流的matlab代码(Read image is converted into a binary stream matlab code)

本程序是计算振动信号各种参数的实验程序。 主要功能是计算均值、标准差、方差、偏斜度、峭度、 峰峰值、方根幅值、平均幅值、峰值、 波形指标、峰值指标、脉冲指标、裕度指标。 ( This program is to calculate the vibration signals of various parameters experimental procedures. The main function is to calculate the mean, standard deviation, variance, skewness, kurtosis, peak-peak amplitude of the square root of the average amplitude of the peak, waveform indices, peak indicators, pulse index, margin targets.)

用matlab绘制的车辆制动曲线，以起亚K9为参考模型，用的时候改下参数即可(Matlab mapping the vehicle braking curve, the Kia K9 as a reference model, when used to change the parameters can be)

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.)