noise

掌握Matlab的流程控制语句，掌握循环结构。 初步学习Matlab的脚本文件、函数文件编写。 初步掌握Matlab脚本文件、函数文件的调试.初步掌握用户参数的交互输入。 (Matlab master process control statements, control loop structure. Matlab script file preliminary study, the function document preparation. Initial grasp of Matlab script file, the file' s debugging function. Initial grasp of the user interactive input parameters.)

Normalization from mid points

this is the full search block matching agorithm algorithm for motion estimation

基于simulink的光伏电池的最大功率的仿真，电导增量法，扰动观察法(Simulation of maximum power of photovoltaic cell based on Simulink, conductance increment method, perturbation method)

BP（Back Propagation）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)。 通过对信息的提取以及记忆，用作分类、聚类、预测等。 (BP (Back Propagation) network is a pre-press error back propagation algorithm Multilayer feedforward network, is one of the most widely used neural network model. BP network can learn and store a large amount of input- output mode mapping without prior reveal mathematical equations that describe the mapping relationship. It s learning rule is to use the steepest descent method, by reverse spread to constantly adjust the network weights and thresholds and the minimum sum of squared error of the network. BP neural network topology comprises an input layer (input), hidden layer (hide layer) and an output layer (output layer). By extracting information and memory, it is used as classification, clustering, prediction.)

说明：  2017-IEEE-Mining Scraper Conveyor

计算机仿真 matlab教程 很好的学习资料 供大家下载(simulink matlab)

matlab中tic与toc函数联合进度条使用例子(tic toc function matlab in combination with the use of examples progress bar)

彩色多普勒成像分析，通过多普勒频谱进行彩色成像(Color Doppler)

一种考虑观测噪声和系统噪声的滤波算法，绘制出了目标轨迹和跟踪效果、x、y轴的滤波方差、位置均方根误差和速度均方根误差。(Consider an observation noise and system noise filtering algorithm, to map out the trajectory of the target and tracking results, x, y-axis variance filtering, position and velocity RMSE root mean square error.)