matlab中的conv2卷积运算的三种形式

thinkfunny

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matlab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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- p) N0 |6 `5 _9 _. K  X    C = conv2(A, B) peRForms the 2-D convolution of matrices A and B.
    If [ma,na] = size(A), [mb,nb] = size(B), and [mc,nc] = size(C), then
" D; s1 E( J7 |% u, d    mc = max([ma+mb-1,ma,mb]) and nc = max([na+nb-1,na,nb]).

& _: T3 s: {3 s" t  p& \    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
( s8 I& t' c3 L3 G2 c7 g% u    n1 = length(H1), n2 = length(H2), and [mc,nc] = size(C) then
' E* h+ R! D% d2 {1 I- e# I4 u    mc = max([ma+n1-1,ma,n1]) and nc = max([na+n2-1,na,n2]).
" b" @2 K9 h' a7 C, a+ [$ z    conv2(H1, H2, A) is equivalent to conv2(H1(：)*H2(：).', A) up to
    round-off.

# S6 |9 _9 K+ {- _! l    C = conv2(..., SHAPE) returns a subsection of the 2-D
    convolution with size specified by SHAPE:
      'full'  - (default) returns the full 2-D convolution,
      'same'  - returns the central part of the convolution
1 ^: Z; ?1 ?3 k: D1 p6 S                that is the same size as A.
      'valid' - returns only those parts of the convolution
                that are computed without the zero-padded edges.
4 [3 K+ {& A+ |8 r+ \                size(C) = max([ma-max(0,mb-1),na-max(0,nb-1)],0).


9 E4 q& g0 f! ?. P1 Y8 z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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full




same

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# S% H  k0 ~1 d6 k  K  o2 Ovalid
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yin123

三种形式的matlab中的conv2卷积运算