bnoise

基于最大信干噪比准则的自适应数字波束形成器程序(Based on the maximum SINR criteria for adaptive digital beamformer program)

扩展卡尔曼的代码,非常有用的，希望多多下载(Extended Kalman code, very useful, and I hope a lot of download)

该内容是关于fdtd的源码,我用过,ok!不错!()

1、《小波图像分解与重构程序存在的问题与解决办法》 我编写程序时尽量实现模块化，方便不同功能程序之间的调用。以上程序实现了一维、二维小波分解与重构的功能，接下来我们就可以此为基础，探讨小波信号压缩和图像融合等技术了。(1, " Wavelet image decomposition and reconstruction process problems and solutions" when I try to modular programming, to facilitate calls between different functional processes. Program achieved more than one-dimensional, two-dimensional Wavelet function, then we can take this as the basis of wavelet signal compression and image fusion with the.)

说明：  Matlab工程应用基础详细讲解了工程上的实际问题(Matlab engineering works on the basis of detailed account of the practical problems)

基于simulink的AGV数字仿真，采用PID控制(AGV digital simulation based on Simulink and PID control)

粒子群算法 粒子群算法 粒子群算法 粒子群算法(Partical Swarm Optimization PSO matlab Partical Swarm Optimization Partical Swarm Optimization Partical Swarm Optimization Partical Swarm Optimization Partical Swarm OptimizationPartical Swarm Optimization)

此为一篇介绍mcmc方法的外文文献 非常适合刚刚接触mcmc方法的初学者(This paper introduces the readers of the Proceedings to an important class of computer based simulation techniques known as Markov chain Monte Carlo (MCMC) methods. General properties characterizing these methods will be discussed, but the main emphasis will be placed on one MCMC method known as the Gibbs sampler. The Gibbs sampler permits one to simulate realizations from complicated stochastic models in high dimensions by making use of the model’s associated full conditional distributions, which will generally have a much simpler and more manageable form. In its most extreme version, the Gibbs sampler reduces the analysis of a complicated multivariate stochastic model to the consideration of that model’s associated univariate full conditional distributions.)

用Matlab编写的对于给定传递系统的阶跃响应和采用修正函数后的阶跃响应(Prepared using Matlab for a given transmission system step response and the adoption of the amendment after the step response function)

极大似然估计是概率论中的重要思想，阅读此文献可以帮助我们了解极大似然估计的含义(Maximum likelihood estimation is important in probability theory thinking, reading this literature can help us understand the meaning of maximum likelihood estimation)