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UWB，超宽带信号分析必用的子函数，第6部分！(UWB, ultra-wideband signal analysis will be used for Functions, Part 6!)

自适应滤波算法的应用，自适应信号对消的一种例子(The application of adaptive filtering algorithms, adaptive signal cancellation of a case)

Introduction to matlab with simple examples to deal with some mathematical problems

L-M(Levenberg—Marquardt)是一种非线性最优化里面最常用的方法之一，改方法能快速而准确的逼近收敛值。本文简述了改方法的操作原理和具体运用，如可以方便的用于有约束与无约束最优化的求解。本文件里面有源码和测试码以及对该方法的具体介绍PDF文件。欢迎下载。(L- M (Levenberg- Marquardt) is a kind of nonlinear optimization inside one of the most commonly used method, change method can fast and accurate approximation convergence value.This paper briefly describes the operating principle of change method and concrete application, such as easy to solve constrained and unconstrained optimization.This document there are source code and test code as well as to the PDF file the detailed introduction of the method.Welcome to download.)

this a 3d fdtd code using matlab and it can be used as a reference for other structures. Dear sir, i need the VIP access please let me have it.

研究有限矩形区域内，粒子运动到区域边界时会与区域边界发生不同作用（弹性碰撞和吸收两种可能的情况）下的布朗运动。(Finite rectangular region of the particle motion to the regional boundaries will occur with the different roles of the regional boundary (elastic collision and absorption of two possible scenarios), the Brownian motion.)

when SNR is high , 1st sample estimator provides good estimate of A. it has no noise effect . so we don’t need averaging effect to reduce noise when SNR is high. However variance is still low in sample mean estimator which shows that in reality ,sample mean is good estimator than 1st sample estimator. So, for high SNR, we do not need to reduce the effect of noise by averaging. or we can say that for high SNR let say >1000 , 1st sample estimator got reduced noise. But as for as variance is concerned , the sample mean has low variance for high SNR as well.

this code implemented for ICA algorithm and can be use for face recognition

对于抛物方程的具有差分形式的高精度线性迭代法(linear itearnating method)

一种改进的基于模拟退火的粒子群算法(SimPSO)。将模拟退火算法的思想引入粒子群算法中,并对更新公式进行优化(An improved particle swarm optimization algorithm based on simulated annealing (SimPSO). The simulated annealing algorithm is introduced into the particle swarm optimization algorithm, and the updating formula is optimized.)