ARPS-users-guide

wimax-mimo技术的仿真希望大家看看(wimax-mimo simulation technology)

The random walker algorithm was introduced in the paper: Leo Grady and Gareth Funka-Lea, "Multi-Label Image Segmentation for Medical Applications Based on Graph-Theoretic Electrical Potentials", in Proceedings of the 8th ECCV04, Workshop on Computer Vision Approaches to Medical Image Analysis and Mathematical Methods in Biomedical Image Analysis, p. 230-245, May 15th, 2004, Prague, Czech Republic, Springer-Verlag. Available at: http://cns.bu.edu/~lgrady/grady2004multilabel.pdf

MATAL的一个练习包 用于新手的初次尝试(MATAL of a practice package for the novice first attempt)

this program does some digital image processing using matlab. It does some filtering and enhancments to any chosen image

这段代码主要用于工程中的结构有限元设计，依次从代码中很容易求解出结构所划分的节点数，单元数以及荷载等。(This code is mainly used for finite element in structural engineering design, are easily solved by the number of nodes in the structure of the number of units, and load.)

微电网优化调度中采用模糊控制对蓄电池进行控制(Microgrid optimization scheduling using fuzzy control to control the battery)

简介：IFP_FCM,改进型FCM(模糊C均值)聚类算法,由Frank Hoppner与Frank Klawonn于2003年提出,解决了FCM算法对初始值设定较为敏感、训练速度慢、在迭代时容易陷入局部极小的问题。并附带了Box和Jenkins煤气炉数据模型辨识实例。 文件清单： IFP_FCM算法原始论文： Improved fuzzy partitions for fuzzy regression models.pdf 程序清单： IFP_FCM.m - IFP_FCM算法主函数 initifp_fcm.m - initifp_fcm子函数 stepifp_fcm.m - stepifp_fcm子函数 distifp_fcm.m - distifp_fcm子函数 IFP_FCM_T_S_box_test.m - IFP_FCM测试实例：Box和Jenkins煤气炉数据T-S模糊模型辨识 数据文件： box_data.mat - Box和Jenkins煤气炉数据(IFP_FCM, modified FCM (Fuzzy C-Means) clustering algorithm, in 2003, proposed by Frank Hoppner and Frank Klawonn, FCM algorithm to solve the initial value setting is more sensitive, slow training, while iterating easy to fall into local minimum problem. And comes with Box and Jenkins gas furnace model identification data instance.)

this mfile is riten in matlab and is related to mirtoolbox

说明：  高斯白噪声无线通信信道下的误码率仿真，希望对你的学习有用(Gaussian white noise of wireless communication channel under BER simulation, you would like to learn useful)

the code i have uploaded estimate the position of speaker,in environment put a number of microphones that by extended kalman filter estimate the position of speaker