yuanzhen

说明：  matlab实用程序，大概100个，写成txt文档(matlab utility, about 100, written in txt file)

资源分配的matlab文件，可以参考一下(resource allocation)

用matlab自编写的简单遗传算法程序(SGA) (using Matlab since the preparation of a simple genetic algorithm (SGA))

matlab程序能够实时接收COM数据并提取有关信息。(matlab program can receive real-time COM data and extract relevant information.)

基于信号匹配原理的三阵元信号方位估计的方法(Based on the principle of signal matched the three array element signal DOA estimation methods)

元胞自动机 nasch 模型！单条道路上模拟 的(a cellular automaton，nasch model on one lane)

用AR模型和SIMIU功率谱模拟脉动风，在叠加平均风，得到风序列(SIMIU power spectrum with AR model and simulate the fluctuating wind , the average wind overlay, get wind sequence)

主成分分析法将图像分为低秩部分和稀疏部分(Principal Component Analysis (PCA) divides images into low rank and sparse parts)

说明：  Matlab模拟退火算法 求解TSP问题(Matlab simulated annealing algorithm for solving TSP problems)

- 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.)