SPR5layeranglelongrange

This function lets users digitize a published graph that is saved as a image e.g. jpeg

包括了许多CA模型的matlab源程序，对于初学者很有用处。(CA model includes many of the matlab source code, useful for beginners.)

只需要使用Matlab 就可以播放 wave 檔.不需要Media Player或音樂撥放軟體.(Use Matlab to play wave file. This is an example to play 1k tones by using Matlab.)

说明：  解决vrp问题的ALNS的matlab算法(Matlab algorithm of ALNS for VRP Problem)

32*32 pixels picture to 1024*1024 pixels nearest neighbour transformer

Generating bunch of rays parellel to the given axial ray

该MATLAB程序实现了simplex迭代算法，该算法可以在不对目标函数求导情况下进行优化，适合数据量较大的算法优化。(The MATLAB program to achieve a simplex iterative algorithm, which can be optimized in the right objective function derivation, the large amount of data suitable algorithm optimization.)

MATLAB是一种以数值计算和数据图示为主的计算机软件，并包含适应多个学科的专业软件包，以及完善程序开发功能。 本课程设计旨在要求学生熟悉Matlab的功能，掌握Matlab程序设计和GUI设计的方法，培养学生的应用开发能力，为以后的毕业设计奠定一定的基础。(MATLAB is a numerical calculation and data icon-based computer software, and includes a number of disciplines to adapt to the package, as well as improve the development function. This course is designed to require students to know the function of Matlab, master Matlab programming and GUI design methods, and foster the application of student development capacity, for future graduation project to lay a foundation.)

是希尔伯特黄变换的c++源代码，帮助大家一起学习，更进一步的了解希尔伯特黄变换(Is the Hilbert-Huang transform c++ source code to help people learn together, a better understanding of Hilbert Huang Transform)

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.)