What is the difference between backward slash vs forward slash in MATLAB?
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I have a failry simple question in MATLAB. What s the difference between the backslash operator vs the forward slash operator. For example,
A=[4,12;6,8];
b=[6,12;14,8];
x1 = A/b;
1.1333 -0.2000
0.5333 0.2000
%which is different from:
x2 = A\b;
3.0000 0
-0.5000 1.0000
I am asking because I am trying to convert a simple line of code from MATLAB to c++ which it turns out there's no forward slash in c++ unfortunately.
2 个评论
Torsten
2022-6-19
Of course there is a forward slash in c++. What else should stand for "division" ?
回答(3 个)
John D'Errico
2022-6-20
BOTH of them are linear algebraic solutions. Where matrices are involved, they solve subtly different problems.
A\b solves the linear algebra problem A*X=b.
For these matrices...
A=[4,12;6,8];
b=[6,12;14,8];
X1 = A\b
Did it work?
A*X1
Did it recover the matrix b? Yes.
What does forward slash do? Again, when matrices are involved, it solves a different problem. A/b is equivalent to solving the linear algebra problem X2*b=A.
X2 = A/b
Did it work?
X2*b
Essentially, the two are similar in philosophy. The difference is where the unknown matrix would be in the problem you are implicitly solving.
William Rose
2022-6-20
X=A\B computes X=inv(A)*B.
Y=A/B computes Y=A*inv(B)
A=rand(2,2); B=rand(2,2);
X1=A\B
X2=inv(A)*B
Y1=A/B
Y2=A*inv(B)
When I look at A\B, I try to remember that the A looks like it is "under" the divide sign, which reminds me that A is the denominator in A\B. And it comes first, so inv(A) is before B in the (non-commutative) multiplication.
7 个评论
Stephen23
2022-6-20
编辑:Stephen23
2022-6-20
" Matlab's left divide may not use the equation I gave above - @John D'Errico says it doesn't, and I trust him."
Even better is to read the MLDIVIDE() documentation yourself:
"The equation I gave in my comment (not my original answer) is standard in a statistics class when discussing linear regression."
But almost completely useless when doing numeric computations on numeric data.
In much the same way beginners use the determinent to test if a matrix is singular or not, because that is what they were taught in "statistics class", but in the real world of numeric computing: almost completely useless.
"But A'A is not necessarily invertible (although I have never encoutered a linear regression problem where it's not)."
Whether A'A is invertible is not really the problem here, this still avoids the numeric issue.
"So maybe Matlab has a way to deal with that possibility, by not using inv() when it does left matrix divide."
The MLDIVIDE() documentation explains what algorithms it uses. Read it.
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