eCGAmatlab

说明：  应用matlab计算lamb波的频散曲线，计算群速度以及相速度。(Matlab computing applications lamb wave dispersion curves, group velocity and phase velocity calculation.)

fitting magnetization curve

Eigenfunctions of integrable planar billiards are studied — in particular, the number of nodal domains, ν of the eigenfunctions with Dirichlet boundary conditions are considered. The billiards for which the time-independent Schrö dinger equation (Helmholtz equation) is separable admit trivial expressions for the number of domains. Here, we discover that for all separable and nonseparable integrable billiards, ν satisfies certain difference equations. This has been possible because the eigenfunctions can be classified in families labelled by the same value ofm mod kn, given a particular k, for a set of quantum numbers, m, n. Further, we observe that the patterns in a family are similar and the algebraic representation of the geometrical nodal patterns is found. Instances of this representation are explained in detail to understand the beauty of the patterns. This paper therefore presents a mathematical connection

matlab编程实现离散数字信号的有理数插值收取(the matlab programming discrete digital signal rationals interpolation charged)

MIMO OFDM matlab仿真,基于多相结构的信道化接收机，最小二乘回归分析算法。( MIMO OFDM matlab simulation, Channelized receiver based on multi-phase structure, Least-squares regression analysis algorithm.)

本程序是用matlab仿真软件和解析法来计算一维光子晶体带隙的另一个程序(this procedure is used Matlab simulation software and analytical method to calculate one-dimensional photonic bandgap of another program)

使用统计中值法，获取背景图像。简单易懂，希望对大家有帮助。(Using the statistical value method, to obtain the background image. Easy to understand, we hope to help.)

模拟波在功能梯度材料中的传播，解压后为.m文件(Simulate wave propagation in functionally graded materials, after decompression. M file)

说明：  Maximum likelihood Identification system

程序包含的设置包括：列数、样本总个数、建模样本数、预报因子数、预报对象数、学习因子、 动量因子、训练次数、总体误差、隐节点数。(Contains the settings include: the number of rows, the total number of samples, sample size modeling, forecasting factor number, forecasting the number of objects, learning factor, momentum factor, training frequency, the overall error, hidden nodes.)