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Convex Optimization – affine Set



A set $A$ is said to be an affine set if for any two distinct points, the line passing through these points lie in the set $A$.

Note

  • $S$ is an affine set if and only if it contains every affine combination of its points.

  • Empty and singleton sets are both affine and convex set.

    For example, solution of a linear equation is an affine set.

Proof

Let S be the solution of a linear equation.

By definition, $S=left { x in mathbb{R}^n:Ax=b right }$

Let $x_1,x_2 in SRightarrow Ax_1=b$ and $Ax_2=b$

To prove : $Aleft [ theta x_1+left ( 1-theta right )x_2 right ]=b, forall theta inleft ( 0,1 right )$

$Aleft [ theta x_1+left ( 1-theta right )x_2 right ]=theta Ax_1+left ( 1-theta right )Ax_2=theta b+left ( 1-theta right )b=b$

Thus S is an affine set.

Theorem

If $C$ is an affine set and $x_0 in C$, then the set $V= C-x_0=left { x-x_0:x in C right }$ is a subspace of C.

Proof

Let $x_1,x_2 in V$

To show: $alpha x_1+beta x_2 in V$ for some $alpha,beta$

Now, $x_1+x_0 in C$ and $x_2+x_0 in C$ by definition of V

Now, $alpha x_1+beta x_2+x_0=alpha left ( x_1+x_0 right )+beta left ( x_2+x_0 right )+left ( 1-alpha -beta right )x_0$

But $alpha left ( x_1+x_0 right )+beta left ( x_2+x_0 right )+left ( 1-alpha -beta right )x_0 in C$ because C is an affine set.

Therefore, $alpha x_1+beta x_2 in V$

Hence proved.

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