pegasis

This demo nstrates 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. (This demo nstrates 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. )

Bidirectional extreme learning machine - B-ELM Y. Yang, Y. Wang, and X. Yuan, "Bidirectional extreme learning machine for regression problem and its learning effectiveness," IEEE Transactions on Neural Networks and Learning Systems, Vol. 23, pp. 1498 - 1505, 2012

详细介绍了MATLAB用于图像处理的相关函数命令！方便实用。(MATLAB for detailed information on the correlation function of image processing commands! Convenient and practical.)

This program can be used for LDPC matrix generator.

fcyj mk oujfgyj iuty piutyou oiui9-u9

shortest path algorithms

串联模糊PID，搭建模糊PID框架，并与普通PID对比，演示模糊控制特点(Series fuzzy PID, fuzzy PID frame structures and contrast with the ordinary PID, fuzzy control features demo)

受控对象变化后模型参考自适应仿真模型程序(Changes in the controlled object simulation model)

用不同的算法解决BP网络的问题，十分强大，应有尽有。(use differnt ways to solve the BP network,powerful,convinient)

包含飞行器飞行中的姿态控制，如侧滑角，倾斜角，滚转角，俯仰角，插值与拟合的matlab实现，实现串口的数据采集。( It comprises aircraft flight attitude control, such as slip angle, tilt angle, roll angle, pitch angle, Interpolation and fitting matlab implementation, Achieve serial data acquisition.)