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
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conv2 Two dimensional convolution.

* W& _) w( y! H' ^    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
    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
9 y  R: ?6 h$ q( X( ?& K) \    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
; O0 |+ D1 P: G8 r    mc = max([ma+n1-1,ma,n1]) and nc = max([na+n2-1,na,n2]).
2 D' _) r" z' j; P    conv2(H1, H2, A) is equivalent to conv2(H1(：)*H2(：).', A) up to
* u4 E  f( N! {& W    round-off.
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    C = conv2(..., SHAPE) returns a subsection of the 2-D
5 v$ d8 Q- r5 L% @2 J: f    convolution with size specified by SHAPE:
4 s& v4 }$ o! y      '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.
* B. U6 c! K. e3 u" C- M                size(C) = max([ma-max(0,mb-1),na-max(0,nb-1)],0).


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


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" v2 u( u8 C* X2 Msame
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' s8 K7 C; N% nvalid

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yin123

三种形式的matlab中的conv2卷积运算