LMD算法 LMDP6Data expansion

  LMD算法利用极值平均、边界局部特征尺度延拓、HDJ极值延拓法、基于ISBM延拓、平行延拓法等对数据拓展，降低端点效应。(The LMD algorithm uses the extreme value average, the boundary local characteristic scale extension, the HDJ extreme value extension method, based on the ISBM extension, the parallel extension method and so on to expand the data, reduces the end effect.)

LMD%2B6种端点拓展方法
...................\boundary_conditions_averextr极值平均.m,1896,2013-05-17
...................\boundary_conditions_charalen边界局部特征尺度延拓.m,1170,2016-10-24
...................\boundary_conditions_HDJ极值延拓法.m,1547,2013-05-17
...................\boundary_conditions_isbm基于ISBM延拓.m,2979,2013-05-17
...................\boundary_conditions_paracon平行延拓法.m,1086,2013-05-17
...................\boundary_conditions_rependp对playfish的程序进行修改.m,1351,2013-05-17
...................\CombinMaxMin.m,465,2016-10-24
...................\extr.m,1820,2016-10-24
...................\lmd.m,1875,2016-10-24
...................\LocalMeanEn.m,394,2016-10-24