work

matlab实现的卫星轨道模拟，利用卫星轨道根数参量，通过求解开普勒方程求解卫星轨道模型(matlab implementation of satellite orbit simulation, the number of satellite orbit parameters, by solving the Kepler equation model of satellite orbit)

MATLAB 7.0从入门到精通：MATLAB 7.0从入门到精通随书光盘，书籍随书光盘的所有源码(MATLAB 7.0 from the Introduction to Mastery: MATLAB 7.0 from entry to the master CD with the book, books, CD-ROM with all the source books)

拉格朗日乘数法 ， 主要解决求多元函数条件极值的问题。任何一本《高等数学》，《多元微积分》的教材都会介绍(Lagrange multiplier method, mainly to address the requirements of multi-function conditions extremum. A " higher mathematics" , multivariate calculus textbooks will be introduced)

POWER SYSTEMS

说明：  内附有弹道导弹弹道要求及过程，有完整的matlab程序，可以借鉴学习。自己大三时的远程火箭弹道学大作业。(t includes ballistic missile trajectory requirements and process, complete matlab program, which can be used for reference and learning. My junior year of long-range rocket ballistics homework.)

- XCS for Dynamic Environments + Continuous versions of XCS + Test problem: real multiplexer + Experiments: XCS is explored in dynamic environments with different magnitudes of change to the underlying concepts. +Reference papers: H.H. Dam, H.A. Abbass, C.J. Lokan, Evolutionary Online Data Mining – an Investigation in a Dynamic Environment. 2005, accepted for a book chapter in Springer Series on Studies in Computational Intelligence H.H. Dam, H.A. Abbass, C.J. Lokan, Be Real! XCS with Continuous-Valued Inputs. IWLCS 2005, (International Workshop on Learning Classifier Systems). Washington DC, June 2005.(- XCS for Continuous Dynamic Environments Test versions of XCS problem : real multiplexer Experiments : XCS is explored in dynamic environments with di fferent magnitudes of change to the underlying concepts. Reference papers : H. H. Dam, H. A. Abbass, C. J. Lokan. Evolutionary Online Data Mining-an Investiga tion in a Dynamic Environment. 2005. accepted for a book chapter in Springer Series o n Studies in Computational Intelligence H.H. D am, H. A. Abbass, C. J. Lokan. Be Real! XCS with Continuous- Valued Inputs. IW LCS 2005. (International Workshop on Learning Classifi er Systems). Washington DC, June 2005.)

This is WRAN simulation file. It contations too many m files. You can open these files. Thank you

play Canon with piano.

This code is a particle swarm optimization for localization in wireless sensor networks

This code calculated the LDP histogram and is based on B Zhang, Y Gao, S Zhao & J Liu, "Local Derivative Pattern Versus Local Binary Pattern: Face Recognition With High-Order Local Pattern Descriptor," Image Processing, IEEE Transactions on, vol.19, no.2, pp.533,544, Feb. 2010