MP

一个完整的用ITD方法进行环境激励下模态参数识别的程序(this is a program about using ITD mathod to identify modal parameter)

Run the ROI file by issuing the command ROI in the command window and a GUI screen will pop up, the screen may be used for selecting a Region of interest while viewing the full length movie and adjusting the region of interest accordingly, after hitting save the GUI will dismantle the movie to seperate images and will save them in current folder.The GUI panel is self explanatory and as such does not require any further explanations

面包板模型程序，引用通过面包板模型得到几个因素对另一个因素的影响因子(Breadboard model program, cited several factors to get another factor influencing factors breadboard model by)

this file is about beam forming with adaptive file

这是自己整理很久的一片有关于运动目标检测与跟踪算法研究的论文，用matlab实现的。(This is a long-own finishing about moving target detection and tracking algorithm paper, using matlab to achieve.)

宽带信号 DOA估计 TCT算法 此算法可以较好的完成宽带信号的波达角估计 可以解相干信号 属于子空间算法(Wideband signal DOA estimates TCT algorithm this algorithm can better complete the broadband signal can be solution-of-arrival estimation of coherent signals are sub-space algorithm)

The program is about creating spanning tree in matlab environment

matlab中PID控制系统仿真模型，算法简单、稳定性好、可靠性高(PID control system simulation model in matlab, simple algorithm, good stability, high reliability)

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).)

OMP code can be found here