Multi Input Multi Output

a simple code using matlab GUIDE , which is counting the no. of times the button is clicked...

this is the model of an inverted pendulum, whereas the drivetrain is modeled as PT1 system. some of the code desctiption may be in german. to run just open the m-file and click :run

COATAS 信号的三次相位函数的matlab程序，写小论文的时候自己编的(cubic phase function of COATAS)

说明：  次文件夹包含两个程序，可以对振动信号进行包络分析，适合信号处理入门的朋友(do envelope analysis on vibration signal)

一本关于智能天线方面的很好的原版英文资料，对智能天线的学习和设计会有很好的帮助！！！(Smart antenna on one of the good aspects of the original English information on the smart antenna design of the study and there will be a good help! ! !)

一篇介绍matlab实现高效编程的文档，对于每一种方法都有相关的例子(An efficient introduction matlab programming documents, for each method are related to the case)

如何运用MATLAB中的HMM工具包进行模型的建立，求解先验概率和解码(How to use the Hmm toolbox)

图片和SVM计划

：Matlab具有强大的数值计算和分析等能力，而C／C++是目前最为流行的高级程序设计语言，两者互补结合的混合编 程在科学研究和工程实践中具有非常重要的意义。因此，从Matlab调用c，C++代码及c，C++调用m文件两方面，深入地研究 了它们之间混合编程的原理和实现机制，并且给出了具体条件下的混合编程方法和步骤。(: Matlab has powerful numerical calculation and analysis capabilities, while the C/C++ is currently the most popular high-level programming language, which combines a mixture of complementary programming in scientific research and engineering practice of great significance. Therefore, from the Matlab call c, C++ code and c, C++ to call two m files, in-depth study of a hybrid between them and the realization of the principles of programming mechanisms, and under specific conditions are given a mixture of programming methods and procedures.)

最新的支持向量机工具箱，有了它会很方便 1. Find time to write a proper list of things to do! 2. Documentation. 3. Support Vector Regression. 4. Automated model selection. REFERENCES ========== [1] V.N. Vapnik, "The Nature of Statistical Learning Theory", Springer-Verlag, New York, ISBN 0-387-94559-8, 1995. [2] J. C. Platt, "Fast training of support vector machines using sequential minimal optimization", in Advances in Kernel Methods - Support Vector Learning, (Eds) B. Scholkopf, C. Burges, and A. J. Smola, MIT Press, Cambridge, Massachusetts, chapter 12, pp 185-208, 1999. [3] T. Joachims, "Estimating the Generalization Performance of a SVM Efficiently", LS-8 Report 25, Universitat Dortmund, Fachbereich Informatik, 1999. (The newest work tools of svm,it will be very convenient to have it.)