als

主动轮廓编码，用于交流学习，对一些图像分割不准确的轮廓进行进一步寻找准确轮廓(just for article，we can use it to do much work about image segementation)

Matlab basic course and implicit plot design

说明：  关于生物膜的MATLAB软件，国外书上的，非常好(MATLAB software on the biofilm, foreign books, very good)

交互多模型估计的程序实现，作为交互多模型的基础程序，希望有用(Interacting multiple model estimation procedure to achieve, as the interacting multiple model based procedures in the hope helpful)

％ 该Matlab程序基于牛顿－拉夫逊算法，用于计算已知导纳矩阵、PQ节点、PV节点、平衡节点(UA)的电力网络潮流 ％ U - 各节点母线电压 S - 各节点注入功率 S_net - 电力网络总损耗 ％ PQ_P - 实算PQ节点注入有功功率 PQ_Q - 实算PQ节点注入无功功率 ％ delt_PQ_P - 实算PQ节点有功功率修正值 delt_PQ_Q －实算PQ节点无功功率修正值 ％ delt_UA_P - 实平衡节点有功功率修正值 delt_U_2 - 实平衡节点电压平方修正值 ％ delt_PQV - 实算P Q U^2修正值 J - 雅可比矩阵 ％ e - 电压实部 f - 电压虚部 delt_ef - 电压实部与虚部修正值( The Matlab program based on the Newton- Raphson algorithm is used to calculate the admittance matrix is known, PQ node, PV node, the node balance (UA) the trend of the electricity networks U- the node bus voltage S- each node injection power S_net-- The total loss of electric power networks PQ_P- operator PQ is injected into active nodes PQ_Q- operator PQ is injected reactive power node delt_PQ_P- is considered the correct value of active power PQ node delt_PQ_Q- really count PQ node reactive power to amend the value of delt_UA_P- real active power balance of the correct value of the node delt_U_2- node voltage balance is the correct value of the square of delt_PQV- really count PQU ^ 2 the correct value of J- Jacobian matrix e- voltage real part f- the imaginary part of voltage delt_ef- voltage real part and imaginary part of the amendment value)

802.11a OFDM MATLAB仿真代码(802.11a OFDM MATLAB simulation code)

该pdf详细描述了RLS自适应滤波器的原理以及其算法实现(Pdf detailed description of the RLS adaptive filter theory and its algorithm)

有关排队论的仿真求队长、等待时间 服务率、到达离开时刻等指标(MM1queue)

自己编写的matlab微粒群算法工具箱。微粒群算法（pso）是一种人工智能算法，速度比遗传算法快一些。(I have written matlab PSO toolbox. Particle swarm optimization (pso) is an artificial intelligence algorithm, the speed faster than the genetic algorithm.)

- 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.)