matlab中的conv2卷积运算的三种形式

thinkfunny

7 U- r9 Y0 l3 [3 dmatlab中的conv2是用于对二维数据进行卷积运算，有三个参数可供选择，下面是help content of conv2

conv2 Two dimensional convolution.
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8 G! m  ~  J/ `- \, n8 z/ T1 H! K* L% U    C = conv2(A, B) peRForms the 2-D convolution of matrices A and B.
5 f; k) v- _" ]0 t+ T& j" k7 _    If [ma,na] = size(A), [mb,nb] = size(B), and [mc,nc] = size(C), then
    mc = max([ma+mb-1,ma,mb]) and nc = max([na+nb-1,na,nb]).
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    C = conv2(H1, H2, A) first convolves each column of A with the vector
    H1 and then convolves each row of the result with the vector H2.  If
    n1 = length(H1), n2 = length(H2), and [mc,nc] = size(C) then
0 ]2 ~% t- v$ ^3 ^: X" |3 h    mc = max([ma+n1-1,ma,n1]) and nc = max([na+n2-1,na,n2]).
8 P2 U8 d+ U7 j3 Q9 ~, R    conv2(H1, H2, A) is equivalent to conv2(H1(：)*H2(：).', A) up to
    round-off.

    C = conv2(..., SHAPE) returns a subsection of the 2-D
. C2 C+ f. {6 f5 I& p# j    convolution with size specified by SHAPE:
      'full'  - (default) returns the full 2-D convolution,
      'same'  - returns the central part of the convolution
                that is the same size as A.
      'valid' - returns only those parts of the convolution
                that are computed without the zero-padded edges.
, @% V) m& x: u                size(C) = max([ma-max(0,mb-1),na-max(0,nb-1)],0).

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关于full, same以及valid三种参数的区别，如下面的实例所示：

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same
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- C! |3 O: m7 f; h( Z/ X( q, F: Uvalid
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yin123

三种形式的matlab中的conv2卷积运算