基于Volterra滤波器混沌时间序列多步预测 作者：陆振波，海军工程大学 欢迎同行来信交流与合作，更多文章与程序下载请访问我的个人主页 电子邮件：luzhenbo@sina.com 个人主页：luzhenbo.88uu.com.cn 参考文献： 1、张家树.混沌时间序列的Volterra自适应预测.物理学报.2000.03 2、Scott C.Douglas, Teresa H.-Y. Meng, Normalized Data Nonlineariti

. R. Johnson, Jr., R. K. Martin, J. M. Walsh, A. G. Klein, C. E. Orlicki, and T. Lin, "Blind Channel Shorteners," Proc. The 13th IFAC Symposium on System Identification, Rotterdam, The Netherlands, August 2003.

R. K. Martin, C. R. Johnson, Jr., M. Ding, and B. L. Evans, "Infinite Length Results for Channel Shortening Equalizers," Proc. The IV IEEE Signal Processing Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Rome, Italy, June

function [L,C] = kmeans(X,k) KMEANS Cluster multivariate data using the k-means++ algorithm. [L,C] = kmeans(X,k) produces a 1-by-size(X,2) vector L with one class label per column in X and a size(X,1)-by-k matrix C containing the centers