Tsaicalibrition

基于matlab的ccir传播模型的路径损耗的仿真的程序，此程序可以在matlab上清晰的看见仿真的图形。(Based on the matlab ccir propagation models of path loss of simulation program, the program can clear to see in matlab simulation graphics.)

PI控制的相关模型，以及PI参数设置问题。。。(PI control relevant model, and PI parameter setting problem.)

说明：  检验已有的一组数据的概率分布是否为某种分布(Verify whether the data is a certain distribution)

this is matlab program for showing the result of quasi ostbc

图像去噪算法进行回顾，以崭新 之一。寻找有效的图像去噪方法仍然是一个有效的挑战，在 功能分析和统计数据的交叉(A REVIEW OF IMAGE DENOISING ALGORITHMS, WITH A NEW ONE.The search for efficient image denoising methods still is a valid challenge, at the crossing of functional analysis and statistics)

无功补偿，SVG代表了无功补偿的新方向，可以提高功率因素，克服三相不平衡，消除电压善变和电压波动(Reactive power compensation, SVG represents a new direction of reactive power compensation, can improve power factor, overcome three-phase imbalance, eliminate voltage fickle and voltage fluctuation)

matlab语言常用算法程序集_龚纯，包括很多常用算法的程序 (matlab include the programmes of most popular algorithms)

频率细化技术在超低频/极低频电磁信号检测中的应用(Frequency refinement technique in ELF/low frequency electromagnetic signal detection)

可逆跳跃马尔科夫蒙特卡洛贝叶斯模型选择，主要用于神经网络(Reversible Jump MCMC Bayesian Model Selection This demo demonstrates the use of the reversible jump MCMC algorithm for neural networks. It uses a hierarchical full Bayesian model for neural networks. This model treats the model dimension (number of neurons), model parameters, regularisation parameters and noise parameters as random variables that need to be estimated. The derivations and proof of geometric convergence are presented, in detail, in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Robust Full Bayesian Learning for Neural Networks. Technical report CUED/F-INFENG/TR 343, Cambridge University Department of Engineering, May 1999. After downloading the file, type "tar-xf rjMCMC.tar" to uncompress it. This creates the directory rjMCMC containing the required m files. Go to this directory, load matlab5 and type "rjdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.)

EKF-SLAM Simulator This version of the simulator uses global variables for all large objects, such as the state covariance matrix. While bad programming practice, it is a necessary evil for MatLab efficiency, as MatLab has no facility to avoid gratuitous memory allocation and copying when passing (and modifying) variables between functions. With this concession, effort has been made to keep the code as clean and modular as possible.