db4fengjie6

找到了本征模式，运用matlab语言编写的程序，对科技工作者有很有帮助，可以解决maxwell方程(found a pattern of the levy, using the Matlab language procedures, right technology workers are helpful, maxwell equation can be solved)

Applying the Butter command

developing measurements analysing matlab

这是一个matlab图像运算包，多幅图像的数学运算，包括图像的代数运算、图像的逻辑运算、图像的块和邻域操作、图像几何运算等(This is a matlab image computing package, multiple images of mathematics, including algebra images, images of logical operations, the image of the block and neighborhood operations such as geometric operations)

人工神经网络基于matlab开发的线性神经网络的例子开发过程(Artificial neural networks are based on the development of linear neural network matlab examples of the development process)

激励源为高斯脉冲波形的二维 平行板FDTD（时域有限差分）TM波仿真 (Excitation source for the two-dimensional Gaussian pulse waveform parallel plate FDTD (Finite Difference Time Domain) TM wave simulation)

这个程序主要是用来设计实现一个蒙特卡洛的算法 采用matlab设计 可以应用在随机搜索方面(This program is mainly used to design and implement a Monte Carlo algorithm using matlab design can be applied to random search and)

假设在一个ad hoc网络中，移动节点的发射功率PTx总是恒定的。要发送数据的移动节点总是先监听信道，测量接收到的信号功率X，其中X= I + N, I为接收到的干扰，N是噪声。移动节点只有在X＜INThre时，才可以发射。式中，INThre为背景噪声门限。 在仿真中，我们规定每个移动节点的发射功率是常数，PTx = 1W；接收节点接收机的灵敏度Smin = -80 dBm；信号质量 min = 2 dB；系统的背景噪声门限INThre = 1.2e-10。 (Assuming in an ad hoc network, mobile node s transmission power is always constant PTX. To send data to the mobile node always monitor channel, measuring the received signal power X, which X = I+ N, I was received interference, N is the noise. Mobile node only when X <INThre when it is fired. Where, INThre threshold for background noise. In the simulation, we require that each mobile node s transmission power is constant, PTx = 1W receiver node receiver sensitivity Smin =-80 dBm signal quality )

动态时间规整matlab函数、动态时间规整matlab函数 (Dynamic time warping of the matlab function)

针对结构转角信息难以测量的问题，采用转角信息重构技术由随机子空间从振动信号中提取的结构平动位移估算结构转动位移，然后构建改进的单元损伤变量(Since it is difficult to measure the rotational responses of a structure, a technique was adopted to evaluate the approximate modal rotations with the modal displacements, which were extracted from structural vibrational signals with stochastic subspace identification, by static condensation and QR decomposition)