1 >> aa=randn(1000,1)/10;
 2 >> aa(100)=aa(100)+3;
 3 >> aa(301)=aa(301)+5;
 4 >> aa(501)=aa(501)+7;
 5 >> aa(701)=aa(701)-14;
 6 >> plot(aa);
 7 >> hist(aa,100);
 8 >> a=mean(aa)
 9
10 a =
11
12    -0.0023
13
14 >> c=std(aa)
15
16 c =
17
18     0.5318
19
20 >> num=find(aa>(a+3*c)|aa<(a-3*c))
21
22 num =
23
24    100
25    301
26    501
27    701
28
29 >> std(aa)
30
31 ans =
32
33     0.5318
34
35 >> for i = 1:1000
36 if((aa(i)>(a+3*c)|aa(i)<(a-3*c)))
37 aa(i)=0;
38 else continue;
39 end
40 end
41 >> len=length(aa);
42 >> std(aa)
43
44 ans =
45
46     0.0996
47
48 >> plot(aa);
49
50 >> mean(aa)
51
52 ans =
53
54    -0.0033
55
56 >> hist(aa,100);

 1 >> A=[1,2,3;4,5,6;3,5,7;1,2,3]
 2
 3 A =
 4
 5      1     2     3
 6      4     5     6
 7      3     5     7
 8      1     2     3
 9
10 >> unique(A,'rows','stable')
11
12 ans =
13
14      1     2     3
15      4     5     6
16      3     5     7

% trim.c 文件
function data=trim(data,outval)
%去除坏数据 包括NaN、Inf和异常大小数据if nargin<2outval=4;
end
outliers = (isnan(data)|abs(data)==inf);
[n,m]=size(data);
if m>1,data(any(outliers'),:)=[];
elsedata(find(outliers'),:)=[];
end
[n,m]=size(data);
mu=mean(data);
sigma=std(data);
outliers=(abs(data-ones(n,1)*mu)>outval*ones(n,1)*sigma);
if m>1,data(any(outliers'),:)=[];
elsedata(find(outliers'),:)=[];
end

>> clear all;
>> c=[nan;ones(100,1);inf;100] %含有nan inf和一个不正常大的数100c =NaN1111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111Inf100>> mean(c),trimmean(c,5)ans =NaNans =1>> c=trim(c)c =1111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111>>