fortran

This a camera calibration toolbox for generic lenses. The toolbox can be used to calibrate conventional, wide-angle and fish-eye lens cameras. The calibration is based on viewing a planar calibration object. The intrinsic and extrinsic camera parameters are estimated from control point correspondences between the calibration plane and calibration images. This toolbox is a result of research that has been carried out in the Laboratory of Computational Engineering at Helsinki University of Technology and in the Machine Vision Group at University of Oulu.

现在通信系统中信号通过衰落信号引起的多普勒扩展程序(Now the signal communication system caused by the decline of the Doppler signal extender)

说明：  基于matlab程序，对普通PID控制和模糊自适应PID控制进行仿真(Based on MATLAB program, the general PID control and fuzzy adaptive PID control are simulated)

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. )

日期转换的程序。可将字符型日期转换为数值型。增加了一种常用日期编码格式。建议将其作为mex使用，速度有显著提高。(Date conversion process. Date can be converted to a numeric character. Added a common date code format. Recommend its use as a mex, the speed has improved significantly.)

关于qpsk调制的代码，详细描述和仿真了qpsk的调制过程和AWGN信道(About qpsk modulation code, a detailed description and simulation of the qpsk modulation process and the AWGN channel)

说明：  基于TS模糊模型的二级倒立摆系统仿真研究(Based on TS Fuzzy Model of Double Inverted Pendulum System Simulation)

SVM神经网络的回归预测分析---上证开盘指数预测,matlab的经典算法(SVM neural network regression analysis--- Shanghai opening index prediction, matlab classical algorithm)

很好的一个一维条码检测识别源码，作为参考很有用(Very good detection and recognition of a one-dimensional bar code source, as a useful reference)

基于遗传算法的PID控制算法（MATLAB）(Based on Genetic Algorithm PID control algorithm (MATLAB))