%?Copyright?and?terms?of?use?（DO?NOT?REMOVE）:
%?The?code?is?made?freely?available?for?non-commercial?uses?only?provided?that?the?copyright?
%?header?in?each?file?not?be?removed?and?suitable?citation（s）?（see?below）?be?made?for?papers?
%?published?based?on?the?code.
%
%?The?code?is?not?optimized?for?speed?and?we?are?not?responsible?for?any?errors?that?might
%?occur?in?the?code.
%
%?The?copyright?of?the?code?is?retained?by?the?authors.??By?downloading/using?this?code?you
%?agree?to?all?the?terms?stated?above.
%
%???[1]?Lin?J.?Keogh?E.?Lonardi?S.?&?Chiu?B.?
%???“A?Symbolic?Representation?of?Time?Series?with?Implications?for?Streaming?Algorithms.“?
%???In?proceedings?of?the?8th?ACM?SIGMOD?Workshop?on?Research?Issues?in?Data?Mining?and?
%???Knowledge?Discovery.?San?Diego?CA.?June?13?2003.?
%
%
%???[2]?Lin?J.?Keogh?E.?Patel?P.?&?Lonardi?S.?
%???“Finding?Motifs?in?Time?Series“.?In?proceedings?of?the?2nd?Workshop?on?Temporal?Data?Mining?
%???at?the?8th?ACM?SIGKDD?International?Conference?on?Knowledge?Discovery?and?Data?Mining.?
%???Edmonton?Alberta?Canada.?July?23-26?2002
%
%?This?function?demonstrates?that?mindist?lower-bounds?the?true?euclidean?distance
%
%?Copyright?（c）?2003?Eamonn?Keogh?Jessica?Lin?Stefano?Lonardi?Pranav?Patel?Li?Wei.??All?rights?reserved.
%
function?mindist_demo

temp?=?sin（0:0.32:20）‘;??????????????????%?make?a?long?sine?wave
time_series_A?=?temp（[1:32]）;???????????%?make?one?test?time?series?from?the?sine?wave
time_series_B?=?temp（[12:43]）;??????????%?make?another?test?time?series?from?the?sine?wave

time_series_A?=?（time_series_A?-?mean（time_series_A））?/?std（time_series_A）;
time_series_B?=?（time_series_B?-?mean（time_series_B））?/?std（time_series_B）;

alphabet_size?=?4;?%?Choose?an?alphabet?size

plot（?[time_series_A??time_series_B]）?%?View?the?test?time?series

%?Now?let?us?create?a?SAX?representation?of?the?time?series
sax_version_of_A?=?timeseries2symbol（time_series_A328?alphabet_size）
sax_version_of_B?=?timeseries2symbol（time_series_B328?alphabet_size）

%?compute?the?euclidean?distance?between?the?time?series
euclidean_distance_A_and_B?=?sqrt（sum（（time_series_A?-?time_series_B）.^2））

%?compute?the?lower?bounding?distance?between?the?time?series
min_dist（sax_version_of_A?sax_version_of_B?alphabet_size4）

?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----
?????文件????????4382??2006-04-21?12:23??SAX\min_dist.m
?????文件????????2344??2006-04-21?12:23??SAX\mindist_demo.m
?????文件????????8454??2003-11-26?12:28??SAX\README.txt
?????文件???????33280??2006-04-22?14:19??SAX\SAX.doc
?????文件????????5432??2015-09-25?09:11??SAX\sax_demo.m
?????文件???????17408??2006-04-21?11:57??SAX\sax_to_20.xls
?????文件????????6082??2006-04-21?12:24??SAX\symbolic_visual.m
?????文件????????8033??2006-04-21?12:17??SAX\timeseries2symbol.m