DSB

此文件为模拟zernike波面拟合图像与原始波面图形的误差的图像。通过模拟真实环境的随机误差，得到误差函数的波面(This file is simulated zernike Wavefront fitting the image with the original wave-front error of graphic images. By simulating the real environment, random error, the wavefront error function to be)

《node入门》是一本较好的入门级教材，本人起初也使用，通俗易懂。希望对大家有所帮助。("Node Getting Started" is a good entry-level textbook, I first use, easy to understand. We want to help.)

人工蜂群算法与粒子群算法结合形成的改进算法，可以通过代码学习了解算法结构(The improved algorithm of artificial swarm algorithm combined with particle swarm algorithm can be used to understand the structure of the algorithm through code learning)

小球撞壁变色的matlab程序，以一图片为背景，小球随机移动，小球撞壁时颜色改变(The ball hit the wall discoloration matlab program)

MATLAB program of v/f control of ac machine

说明：  根据Matlab实现的一个bp算法程序，大家交流(under Matlab bp of an algorithm procedures, exchange)

毕设的题目，LTE移动通信的无线传播信道模型，通过MATLAB仿真了包括多径信道，考虑了多普勒频移以及瑞利信道，考虑了 nQNOiO参数以及 IYsjtyL衰落的多参数信道模型，调试正常。?(Complete set of topics, mobile wireless channel modeling, simulation by MATLAB, including multipath channel, taking into account the Doppler shift and Rayleigh channel, considering the nQNOiO parameter and multi-parameter IYsjtyL fading channel model, debugging normal.)

说明：  首先，建立两个模拟信号的数学模型 有用信号 干扰信号。两个信号的中心频率、信号带宽等参数由学生自己选定，要求两个信号的频谱不重叠 分别画出三个模拟信号的时域波形和频谱图；然后，根据x_a (t)的中心频率和带宽，按照奈奎斯特采样定理选择采样频率fs，分别对信号s_a1 (t)、s_a2 (t)、x_a (t)进行时域采样，得到离散信号s_1 (n)、s_2 (n)、x(n)。利用FFT算法分析离散信号的频谱，分别画出三个离散信号的时域波形和频谱图； 接着，设计数字滤波器H(z)，要求该滤波器对干扰信号s_2 (n)的衰减大于40dB。提出滤波器的设计指标，并设计滤波器，给出滤波器的设计结果，绘制滤波器的幅频特性和相频特性曲线，验证滤波器的设计结果是否达到设计指标要求；此外，选择实现数字滤波器H(z)的结构，画出滤波器结构信号流图；然后，将合成信号x(n)输入数字滤波器H(z)，按照所选择的滤波器结构，设计计算机程序计算滤波器的输出响应y(n)，画出y(n)的时域波形和频谱图；(the synthetic signal x (n) is input into the digital filter H (z). According to the selected filter structure, a computer program is designed to calculate the output response y (n) of the filter, and the time-domain waveform and spectrum diagram of Y (n) are drawn)

function PSNR2 = psnr(I,I_iter) 计算峰值信噪比 I : 原始信号 I_iter : 加噪信号(function PSNR2 = psnr (I, I_iter) calculate the peak signal to noise ratio I: the original signal I_iter: adding noise signal)

核函数主成分分析，用于数据的特征提取，对于训练样本的降维有较好的效果(Kernel principal component analysis, feature extraction for data, which can effectively reduce the dimension of training samples, the better)