MATLB8823

基本信息--混合编程 VB 出版社: 清华大学出版社 第1版 (2008年5月1日) 丛书名: MATLAB工程应用系列丛书 平装: 297页 正文语种: 中文 开本: 16 ISBN: 7302172315, 9787302172314 条形码: 9787302172314 产品尺寸及重量: 26 x 19 x 2.6 cm 440 g ASIN: B00199KXEO (Basic information- Hybrid Programming VB Publisher: Tsinghua University Press 1 (May 1, 2008) Series Name: MATLAB Application Series Paperback: 297 Body Language: English Folio: 16 ISBN: 7302172315, 9787302172314 bar code: 9787302172314 Product size and weight: 26 x 19 x 2.6 cm 440 g ASIN: B00199KXEO)

改程序包可以进行字旋转链和量子寄存器建模等。(this program package helps modeling spin chains, qubit registers, etc. according to nonrelativistic quantum mechanics and some novel ideas from quantum information theory.)

Matlab alaw mukaw ouptu

matlab 关于光学方面的仿真，几何光学，波动光学等函数(simulation matlab optics, geometrical optics, wave optics, and other functions)

heed protocol in wsn

I have uploaded a code for DCT watermarking..I have embed a basic matrix into original image and calculated the difference.

用于实现weighted k-means算法，可以运行(It is used to perform weighted k-means clustering)

说明：  利用Esprit算法进行TOA估计，可用于无线传感器网络节点定位(TOA estimation by Esprit algorithm for wireless sensor network node localization)

matlab Adaboost代码.本代码主要是用来对AdaBoost分类的仿真，提供了一系列的性能分析代码以及比较详细的注释。(matlab AdaBoost code)

摘　要:提出一种新的基于Pareto多目标进化免疫算法(PMEIA)。算法在每一代进化群体中选取最优非支配抗体保存到记忆细胞文档中 同时引入Parzen窗估计法计算记忆细胞的熵值,根据熵值对记忆细胞文档进行动更新,使算法向着理想Pareto最优边界搜索。此外,算法基于点在目标空间分况进行克隆选择,有利于得到分布较广的Pareto最优边界,且加快了收敛速度。与已有算法相比, PMEIA在收敛性、多样性,以及解的分布性方面都得到很好的提高。(Abstract:This paperproposed a new pareto-based multi-object evolutionary mi mune algorithm(PMEIA). PMEIA selected optmi alnon-dominated antibodieswhichwere then reserved inmemory cellarchive, and introducedParzenwindow to calculate entropy ofmemory cells. Updated thememory cell archive according to entropy ofmemory cells. This guarantees the conver- gence to the true Pareto fron.t Moreover, the performance of clone selection was dependent on distribution in the objective space, whichwas favorable forgetting awidely spreadPareto frontand mi proving convergence speed. Comparedwith the exis- ted algorithms, the obtained solutions ofPMEIA havemuch betterperformance in the convergence, diversity and distribution.)