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Plane wave scattering by a dielectric cylinder

FUZZY BASED EXCITATION CONTROL SYSTEM

这是各种计算功率谱的matlab程序，有自相关法，music法，burg法，esprit法等。(This is the calculation of the power spectrum Matlab procedures, since the relevant law, music, burg, esprit law.)

根据matlab GUI等开发环境进行编程的完美日历(MATLAB GUI PROGRAM)

数字图像处理matlab实现，包括如下程序： 1.直方图规定化为高斯双峰函数 2.窗口形状自适应（十字形或矩形）的中值滤波 3.彩色图像目标提取并与背景图像合成 4.插值外推法的彩色图像饱和度调整 5.多种插值方法实现的图像放大和缩小 6.频域变换及分析 7.几何校正 8.插值外推法的黑白图像对比度增强 9.运动模糊矫正(Digital image processing matlab realize, including the following procedures: (1) the bimodal histogram specification as a function of two Gaussian shape adaptive window (cross or rectangular) median filtering three color image with the background object extraction and image synthesis 4. Color image interpolation extrapolation saturation adjustment 5. various interpolation methods to achieve images zoom in and out 6. frequency domain transformation and analysis 7. geometric correction 8. interpolation extrapolation of the black and white image contrast enhancement 9. motion blur correction)

通过matlab的模糊工具箱，编写了倒立摆关于角度、速度的模糊pid控制，实现了对倒立摆的速度，角度的控制。(Through matlab fuzzy toolbox, written on inverted pendulum angle, speed fuzzy pid control, the realization of inverted pendulum speed, angle control.)

this code is developed for weak signal detection in impulsive noise environment.

本程序用于对干涉条纹进行滤波，二值化，骨骼化，最后为求得条纹间距而得到一个像素宽度的图像(This procedure is used to filter the interference fringe, thresholding, skeletonization, and finally to obtain the fringe spacing and width of the image by one pixel)

基于MATLAB的粒子群优化算法程序设计，经典算例。(MATLAB-based particle swarm optimization program design, the classic example.)

BP神经网络：是一种按误差逆传播算法训练的多层前馈网络，是目前应用最广泛的神经网络模型之一。BP网络能学习和存贮大量的输入-输出模式映射关系，而无需事前揭示描述这种映射关系的数学方程。它的学习规则是使用最速下降法，通过反向传播来不断调整网络的权值和阈值，使网络的误差平方和最小。BP神经网络模型拓扑结构包括输入层（input）、隐层(hide layer)和输出层(output layer)。(BP neural network: a Press the front back propagation algorithm to train multilayer feedforward network is one of the most widely used neural network model. BP network can learn and store large amounts of input- output mode mappings without prior reveal mathematical equations that describe this map. It' s learning rule is to use the steepest descent method, through a reverse spread to constantly adjust the network weights and thresholds, so that the minimum squared error of the network. BP neural network topology, including the input layer (input), hidden layer (hide layer) and output layer (output layer).)