PSNRandSNR

Anova analysis for vibration

线性调频（LFM）脉冲压缩雷达仿真，里面有雷达信号的处理过程，包括原理(Linear FM (LFM) pulse compression radar simulation)

matlab实现的小球运动的源程序，不错的matlab GUI 例程(Matlab achieve a small ball of the source, a good GUI Matlab routines)

D-S证据理论数据融合，粒子图像分割及匹配均为自行编制的子例程，仿真图是速度、距离、幅度三维图像，加入重复控制，合成孔径雷达（SAR)目标成像仿真，从先验概率中采样，计算权重。( D-S evidence theory data fusion, Particle image segmentation and matching subroutines themselves are prepared, FIG simulation speed, distance, amplitude three-dimensional image, Join repetitive control, Synthetic Aperture Radar (SAR) imaging simulation target, Sampling a priori probability, calculate the weight.)

说明：  This is to simulate SBS in matlab

关于Arduino书,程序，要点，起步等级(A book about Arduino)

假设一个接收到的信号为：x(t)=s(t)+n(t), 其中s(t)=A*cos(wt+a), 已知信号的频率w=1KHz， 而信号的幅度和相位未知，n(t)是一个服从N(0,1)分布的白噪声。为了利用计算机对信号进行处理， 将信号按10KHz的频率进行采样。 通过对x(t)进行LMS自适应信号处理，从接收信号中滤出有用信号s(t). 在未知信号频率的情况下，通过对x(t)进行LMS自适应信号处理，从接收信号中滤出有用信号s(t). (Assuming a received signal: x (t) = s (t)+ n (t), one of s (t) = A* cos (wt+ a), the known frequency signal w = 1KHz, And the signal amplitude and phase of the unknown, n (t) is a subject to N (0,1) the distribution of white noise. The use of computers in order to deal with the signal, The signal by sampling frequency of 10KHz. Of x (t) for LMS adaptive signal processing, filtering from the received signal in the useful signal s (t). Frequency signals in unknown circumstances, the adoption of x (t) for LMS adaptive signal processing, filtering from the received signal in the useful signal s (t).)

关于统计软件sas函数的用法和详细说明，供初学者参考(On the use of statistical software sas functions and detailed instructions for beginners reference)

最小二乘支持向量机代码，最小二乘支持向量机很好地解决了普通支持向量机耗时的问题，很适合用于及时诊断故障(fuzzy least square vector machine)

通过设计一个二阶加权系数自适应横向FIR滤波器，对一个加随机噪声的正弦信号实现滤波。 具体设计方案为： 1，生成标准正弦信号S 2，生成等长的随机信号N 3，生成加随机噪声的正弦信号X 4，X通过参数可调数字滤波器，输出Y 5，Y与参考信号作差得到误差E 6，E通过自适应算法调整权值W 7，用LMS算法处理噪声干扰的信号，最终实现滤波器功能(A two order weighted coefficient adaptive transverse FIR filter is designed to filter a sinusoidal signal with random noise. The specific design scheme is as follows: 1, generating a standard sinusoidal signal S 2, generating an equal length random signal N 3, generating a sinusoidal signal X with random noise 4, X can adjust the digital filter by parameter and output Y 5, the difference between the Y and the reference signal is E 6, E adjusts the weight W through the adaptive algorithm 7, the LMS algorithm is used to deal with the noise interference signal, and the filter function is finally realized.)