A variational inequality satisfied in a Hilbert space The 2019 Stack Overflow Developer Survey Results Are In Unicorn Meta Zoo #1: Why another podcast? Announcing the arrival of Valued Associate #679: Cesar Manaraprojections in normed linear spacesDistance minimizers in $L^1$ and $L^infty$Maximizing an inner-product over a convex set.On a Variational InequalityComposition of projections has a fixed point in a Hilbert spaceOrthogonal decomposition in Hilbert spacesVariational Inequality only for Real PartInequality with projections in Hilbert SpaceHilbert space $x-P(x)in A^perpRightarrow |x-P(x)|=d(x,A)$Interior solution of a Variational Inequality in Hilbert Space
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A variational inequality satisfied in a Hilbert space
The 2019 Stack Overflow Developer Survey Results Are In
Unicorn Meta Zoo #1: Why another podcast?
Announcing the arrival of Valued Associate #679: Cesar Manaraprojections in normed linear spacesDistance minimizers in $L^1$ and $L^infty$Maximizing an inner-product over a convex set.On a Variational InequalityComposition of projections has a fixed point in a Hilbert spaceOrthogonal decomposition in Hilbert spacesVariational Inequality only for Real PartInequality with projections in Hilbert SpaceHilbert space $x-P(x)in A^perpRightarrow |x-P(x)|=d(x,A)$Interior solution of a Variational Inequality in Hilbert Space
$begingroup$
I'm trying to establish the existance of $u in K subset V$, a closed convex subset of vector space with an inner product, such that for a fixed $q in V$:
$$(u-q,v-u) geq 0 quad forall v in K$$
The proof I'm reading proceeds as follows:
Note that the inequality holds iff $|u-q| leq |v-q|$. Since $K$ is a closed convex subset, there exists a unique element of $K$ that minimizes $|v-q|$, namely $u = P_Kq$ where $P_K$ is the projection of $q$ onto $K$.
This was a bit terse for me. Why does the inequality hold? From what fact does $u = P_Kq$ follow?
real-analysis functional-analysis convex-analysis proof-explanation convex-optimization
$endgroup$
add a comment |
$begingroup$
I'm trying to establish the existance of $u in K subset V$, a closed convex subset of vector space with an inner product, such that for a fixed $q in V$:
$$(u-q,v-u) geq 0 quad forall v in K$$
The proof I'm reading proceeds as follows:
Note that the inequality holds iff $|u-q| leq |v-q|$. Since $K$ is a closed convex subset, there exists a unique element of $K$ that minimizes $|v-q|$, namely $u = P_Kq$ where $P_K$ is the projection of $q$ onto $K$.
This was a bit terse for me. Why does the inequality hold? From what fact does $u = P_Kq$ follow?
real-analysis functional-analysis convex-analysis proof-explanation convex-optimization
$endgroup$
2
$begingroup$
Puh, what is $q$?
$endgroup$
– amsmath
Mar 24 at 18:52
$begingroup$
my bad $q in V$
$endgroup$
– yoshi
Mar 24 at 19:03
$begingroup$
You should note that $V$ has to be complete, otherwise the projection might not exist.
$endgroup$
– gerw
Mar 25 at 7:10
add a comment |
$begingroup$
I'm trying to establish the existance of $u in K subset V$, a closed convex subset of vector space with an inner product, such that for a fixed $q in V$:
$$(u-q,v-u) geq 0 quad forall v in K$$
The proof I'm reading proceeds as follows:
Note that the inequality holds iff $|u-q| leq |v-q|$. Since $K$ is a closed convex subset, there exists a unique element of $K$ that minimizes $|v-q|$, namely $u = P_Kq$ where $P_K$ is the projection of $q$ onto $K$.
This was a bit terse for me. Why does the inequality hold? From what fact does $u = P_Kq$ follow?
real-analysis functional-analysis convex-analysis proof-explanation convex-optimization
$endgroup$
I'm trying to establish the existance of $u in K subset V$, a closed convex subset of vector space with an inner product, such that for a fixed $q in V$:
$$(u-q,v-u) geq 0 quad forall v in K$$
The proof I'm reading proceeds as follows:
Note that the inequality holds iff $|u-q| leq |v-q|$. Since $K$ is a closed convex subset, there exists a unique element of $K$ that minimizes $|v-q|$, namely $u = P_Kq$ where $P_K$ is the projection of $q$ onto $K$.
This was a bit terse for me. Why does the inequality hold? From what fact does $u = P_Kq$ follow?
real-analysis functional-analysis convex-analysis proof-explanation convex-optimization
real-analysis functional-analysis convex-analysis proof-explanation convex-optimization
edited Mar 24 at 19:04
yoshi
asked Mar 24 at 18:50
yoshiyoshi
1,256917
1,256917
2
$begingroup$
Puh, what is $q$?
$endgroup$
– amsmath
Mar 24 at 18:52
$begingroup$
my bad $q in V$
$endgroup$
– yoshi
Mar 24 at 19:03
$begingroup$
You should note that $V$ has to be complete, otherwise the projection might not exist.
$endgroup$
– gerw
Mar 25 at 7:10
add a comment |
2
$begingroup$
Puh, what is $q$?
$endgroup$
– amsmath
Mar 24 at 18:52
$begingroup$
my bad $q in V$
$endgroup$
– yoshi
Mar 24 at 19:03
$begingroup$
You should note that $V$ has to be complete, otherwise the projection might not exist.
$endgroup$
– gerw
Mar 25 at 7:10
2
2
$begingroup$
Puh, what is $q$?
$endgroup$
– amsmath
Mar 24 at 18:52
$begingroup$
Puh, what is $q$?
$endgroup$
– amsmath
Mar 24 at 18:52
$begingroup$
my bad $q in V$
$endgroup$
– yoshi
Mar 24 at 19:03
$begingroup$
my bad $q in V$
$endgroup$
– yoshi
Mar 24 at 19:03
$begingroup$
You should note that $V$ has to be complete, otherwise the projection might not exist.
$endgroup$
– gerw
Mar 25 at 7:10
$begingroup$
You should note that $V$ has to be complete, otherwise the projection might not exist.
$endgroup$
– gerw
Mar 25 at 7:10
add a comment |
3 Answers
3
active
oldest
votes
$begingroup$
There's an error in the first statement of the proof. The variational inequality proves the inequality in norms, but the converse simply doesn't hold. For example, in $BbbR^2$ under the dot product, take $u = (0, 0)$, $v = (0, 3)$, and $q = (1, 1)$. Then
$$|u - q|^2 = 2 le 5 = |v - q|^2,$$
but
$$langle u - q, v - u rangle = (-1, -1) cdot (0, 3) = -3 < 0.$$
I suggest finding another proof of this inequality.
But, as for your second question, if you can show that $|u - q| le |v - q|$ for all $v in K$ (and where $u$ is assumed to be in $K$), then you've found a point $u in K$ that is of minimal distance from $q$. This, by definition, makes $u$ the metric projection of $q$ onto $K$.
EDIT: Actually, I have a proof of this inequality that I wrote up on hand:
Theorem: Suppose $X$ is a real Hilbert space, and $C$ is closed, non-empty, and convex. Let $x in X$ and $z in C$. Then,
$$langle x - z, c - z rangle le 0 quad forall , c in C$$
if and only if $z = p_C(x)$.
Proof: Suppose $z, c in C$, with $z neq c$. Let $f : mathbbR to mathbbR$ be defined by
beginalign*
f(lambda) &= |x - lambda c - (1 - lambda)z|^2 - |x - z|^2 \
&= 2 lambda langle x - z, z - c rangle + lambda^2 |z - c|^2.
endalign*
Note that this is a convex quadratic in $lambda$.
Suppose that $z = p_C(x)$. When $lambda in [0, 1]$, we have $lambda c + (1 - lambda)z in C$, hence $f(lambda) ge 0 = f(0)$. The minimum value of $f$ must be achieved at some $lambda^* le 0$. Thus,
$$0 ge lambda^* = frac-langle x - z, z - c ranglez - c iff langle x - z, c - z rangle le 0.$$
Note that the final inequality also holds for when $c = z = p_C(x)$.
Conversely, suppose $z in C$ such that $langle x - z, c - z rangle le 0$ for all $c in C$. Therefore, when $c neq z$, $lambda^* le 0$. This implies that $f$ is increasing on the interval $[0, 1]$. Hence,
$$|x - c| = f(1) ge f(0) = |x - z|.$$
As this holds for arbitrary $c in C$, we have $z = p_C(x)$.
$endgroup$
1
$begingroup$
What is $K$ in your example?
$endgroup$
– amsmath
Mar 24 at 19:27
$begingroup$
$K$ is the closed, non-empty, convex set onto which we are projecting, as in the question.
$endgroup$
– Theo Bendit
Mar 24 at 19:28
$begingroup$
You should specify it in your example. Otherwise it is incomplete.
$endgroup$
– amsmath
Mar 24 at 19:29
$begingroup$
@amsmath Actually, in my counterexample, there is no such $K$ (I thought you were referring to the second paragraph). My point was that the two inequalities were not equivalent; in particular, if the OP was trying to manipulate one inequality into the other, they were not going to succeed.
$endgroup$
– Theo Bendit
Mar 24 at 20:03
$begingroup$
Of course they are not equivalent. But the points $u$ and $v$ are supposed to be in a closed convex set. However, in your example you can just choose the segment from $u$ to $v$ as $K$. Since one always can do that, your counterexample is actually valid without specifying $K$.
$endgroup$
– amsmath
Mar 24 at 21:02
|
show 3 more comments
$begingroup$
The statement is incorrect. Consider $V = mathbb R^2$ and $K = overlineB_1(0)$, $u=(0,0)$, $v=(epsilon,1-epsilon)$ for some small $epsilon > 0$ and $q = (2,0)$. Then $|u-q|le|v-q|$ and $(u-q,v-u) = -2epsilon < 0$.
$endgroup$
add a comment |
$begingroup$
I think the proof is missing an important detail: What we actually have is that for $u in K$ and $q in V$ the statement
$$ (u - q, v - u ) ge 0 qquad forall v in K$$
is equivalent to
$$ |u - q | le | v - q | qquad forall v in K.$$
The proof is given in the answer by Theo Bendit.
The second statement is just $u = operatornameproj_K(q)$.
$endgroup$
add a comment |
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3 Answers
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active
oldest
votes
3 Answers
3
active
oldest
votes
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votes
active
oldest
votes
$begingroup$
There's an error in the first statement of the proof. The variational inequality proves the inequality in norms, but the converse simply doesn't hold. For example, in $BbbR^2$ under the dot product, take $u = (0, 0)$, $v = (0, 3)$, and $q = (1, 1)$. Then
$$|u - q|^2 = 2 le 5 = |v - q|^2,$$
but
$$langle u - q, v - u rangle = (-1, -1) cdot (0, 3) = -3 < 0.$$
I suggest finding another proof of this inequality.
But, as for your second question, if you can show that $|u - q| le |v - q|$ for all $v in K$ (and where $u$ is assumed to be in $K$), then you've found a point $u in K$ that is of minimal distance from $q$. This, by definition, makes $u$ the metric projection of $q$ onto $K$.
EDIT: Actually, I have a proof of this inequality that I wrote up on hand:
Theorem: Suppose $X$ is a real Hilbert space, and $C$ is closed, non-empty, and convex. Let $x in X$ and $z in C$. Then,
$$langle x - z, c - z rangle le 0 quad forall , c in C$$
if and only if $z = p_C(x)$.
Proof: Suppose $z, c in C$, with $z neq c$. Let $f : mathbbR to mathbbR$ be defined by
beginalign*
f(lambda) &= |x - lambda c - (1 - lambda)z|^2 - |x - z|^2 \
&= 2 lambda langle x - z, z - c rangle + lambda^2 |z - c|^2.
endalign*
Note that this is a convex quadratic in $lambda$.
Suppose that $z = p_C(x)$. When $lambda in [0, 1]$, we have $lambda c + (1 - lambda)z in C$, hence $f(lambda) ge 0 = f(0)$. The minimum value of $f$ must be achieved at some $lambda^* le 0$. Thus,
$$0 ge lambda^* = frac-langle x - z, z - c ranglez - c iff langle x - z, c - z rangle le 0.$$
Note that the final inequality also holds for when $c = z = p_C(x)$.
Conversely, suppose $z in C$ such that $langle x - z, c - z rangle le 0$ for all $c in C$. Therefore, when $c neq z$, $lambda^* le 0$. This implies that $f$ is increasing on the interval $[0, 1]$. Hence,
$$|x - c| = f(1) ge f(0) = |x - z|.$$
As this holds for arbitrary $c in C$, we have $z = p_C(x)$.
$endgroup$
1
$begingroup$
What is $K$ in your example?
$endgroup$
– amsmath
Mar 24 at 19:27
$begingroup$
$K$ is the closed, non-empty, convex set onto which we are projecting, as in the question.
$endgroup$
– Theo Bendit
Mar 24 at 19:28
$begingroup$
You should specify it in your example. Otherwise it is incomplete.
$endgroup$
– amsmath
Mar 24 at 19:29
$begingroup$
@amsmath Actually, in my counterexample, there is no such $K$ (I thought you were referring to the second paragraph). My point was that the two inequalities were not equivalent; in particular, if the OP was trying to manipulate one inequality into the other, they were not going to succeed.
$endgroup$
– Theo Bendit
Mar 24 at 20:03
$begingroup$
Of course they are not equivalent. But the points $u$ and $v$ are supposed to be in a closed convex set. However, in your example you can just choose the segment from $u$ to $v$ as $K$. Since one always can do that, your counterexample is actually valid without specifying $K$.
$endgroup$
– amsmath
Mar 24 at 21:02
|
show 3 more comments
$begingroup$
There's an error in the first statement of the proof. The variational inequality proves the inequality in norms, but the converse simply doesn't hold. For example, in $BbbR^2$ under the dot product, take $u = (0, 0)$, $v = (0, 3)$, and $q = (1, 1)$. Then
$$|u - q|^2 = 2 le 5 = |v - q|^2,$$
but
$$langle u - q, v - u rangle = (-1, -1) cdot (0, 3) = -3 < 0.$$
I suggest finding another proof of this inequality.
But, as for your second question, if you can show that $|u - q| le |v - q|$ for all $v in K$ (and where $u$ is assumed to be in $K$), then you've found a point $u in K$ that is of minimal distance from $q$. This, by definition, makes $u$ the metric projection of $q$ onto $K$.
EDIT: Actually, I have a proof of this inequality that I wrote up on hand:
Theorem: Suppose $X$ is a real Hilbert space, and $C$ is closed, non-empty, and convex. Let $x in X$ and $z in C$. Then,
$$langle x - z, c - z rangle le 0 quad forall , c in C$$
if and only if $z = p_C(x)$.
Proof: Suppose $z, c in C$, with $z neq c$. Let $f : mathbbR to mathbbR$ be defined by
beginalign*
f(lambda) &= |x - lambda c - (1 - lambda)z|^2 - |x - z|^2 \
&= 2 lambda langle x - z, z - c rangle + lambda^2 |z - c|^2.
endalign*
Note that this is a convex quadratic in $lambda$.
Suppose that $z = p_C(x)$. When $lambda in [0, 1]$, we have $lambda c + (1 - lambda)z in C$, hence $f(lambda) ge 0 = f(0)$. The minimum value of $f$ must be achieved at some $lambda^* le 0$. Thus,
$$0 ge lambda^* = frac-langle x - z, z - c ranglez - c iff langle x - z, c - z rangle le 0.$$
Note that the final inequality also holds for when $c = z = p_C(x)$.
Conversely, suppose $z in C$ such that $langle x - z, c - z rangle le 0$ for all $c in C$. Therefore, when $c neq z$, $lambda^* le 0$. This implies that $f$ is increasing on the interval $[0, 1]$. Hence,
$$|x - c| = f(1) ge f(0) = |x - z|.$$
As this holds for arbitrary $c in C$, we have $z = p_C(x)$.
$endgroup$
1
$begingroup$
What is $K$ in your example?
$endgroup$
– amsmath
Mar 24 at 19:27
$begingroup$
$K$ is the closed, non-empty, convex set onto which we are projecting, as in the question.
$endgroup$
– Theo Bendit
Mar 24 at 19:28
$begingroup$
You should specify it in your example. Otherwise it is incomplete.
$endgroup$
– amsmath
Mar 24 at 19:29
$begingroup$
@amsmath Actually, in my counterexample, there is no such $K$ (I thought you were referring to the second paragraph). My point was that the two inequalities were not equivalent; in particular, if the OP was trying to manipulate one inequality into the other, they were not going to succeed.
$endgroup$
– Theo Bendit
Mar 24 at 20:03
$begingroup$
Of course they are not equivalent. But the points $u$ and $v$ are supposed to be in a closed convex set. However, in your example you can just choose the segment from $u$ to $v$ as $K$. Since one always can do that, your counterexample is actually valid without specifying $K$.
$endgroup$
– amsmath
Mar 24 at 21:02
|
show 3 more comments
$begingroup$
There's an error in the first statement of the proof. The variational inequality proves the inequality in norms, but the converse simply doesn't hold. For example, in $BbbR^2$ under the dot product, take $u = (0, 0)$, $v = (0, 3)$, and $q = (1, 1)$. Then
$$|u - q|^2 = 2 le 5 = |v - q|^2,$$
but
$$langle u - q, v - u rangle = (-1, -1) cdot (0, 3) = -3 < 0.$$
I suggest finding another proof of this inequality.
But, as for your second question, if you can show that $|u - q| le |v - q|$ for all $v in K$ (and where $u$ is assumed to be in $K$), then you've found a point $u in K$ that is of minimal distance from $q$. This, by definition, makes $u$ the metric projection of $q$ onto $K$.
EDIT: Actually, I have a proof of this inequality that I wrote up on hand:
Theorem: Suppose $X$ is a real Hilbert space, and $C$ is closed, non-empty, and convex. Let $x in X$ and $z in C$. Then,
$$langle x - z, c - z rangle le 0 quad forall , c in C$$
if and only if $z = p_C(x)$.
Proof: Suppose $z, c in C$, with $z neq c$. Let $f : mathbbR to mathbbR$ be defined by
beginalign*
f(lambda) &= |x - lambda c - (1 - lambda)z|^2 - |x - z|^2 \
&= 2 lambda langle x - z, z - c rangle + lambda^2 |z - c|^2.
endalign*
Note that this is a convex quadratic in $lambda$.
Suppose that $z = p_C(x)$. When $lambda in [0, 1]$, we have $lambda c + (1 - lambda)z in C$, hence $f(lambda) ge 0 = f(0)$. The minimum value of $f$ must be achieved at some $lambda^* le 0$. Thus,
$$0 ge lambda^* = frac-langle x - z, z - c ranglez - c iff langle x - z, c - z rangle le 0.$$
Note that the final inequality also holds for when $c = z = p_C(x)$.
Conversely, suppose $z in C$ such that $langle x - z, c - z rangle le 0$ for all $c in C$. Therefore, when $c neq z$, $lambda^* le 0$. This implies that $f$ is increasing on the interval $[0, 1]$. Hence,
$$|x - c| = f(1) ge f(0) = |x - z|.$$
As this holds for arbitrary $c in C$, we have $z = p_C(x)$.
$endgroup$
There's an error in the first statement of the proof. The variational inequality proves the inequality in norms, but the converse simply doesn't hold. For example, in $BbbR^2$ under the dot product, take $u = (0, 0)$, $v = (0, 3)$, and $q = (1, 1)$. Then
$$|u - q|^2 = 2 le 5 = |v - q|^2,$$
but
$$langle u - q, v - u rangle = (-1, -1) cdot (0, 3) = -3 < 0.$$
I suggest finding another proof of this inequality.
But, as for your second question, if you can show that $|u - q| le |v - q|$ for all $v in K$ (and where $u$ is assumed to be in $K$), then you've found a point $u in K$ that is of minimal distance from $q$. This, by definition, makes $u$ the metric projection of $q$ onto $K$.
EDIT: Actually, I have a proof of this inequality that I wrote up on hand:
Theorem: Suppose $X$ is a real Hilbert space, and $C$ is closed, non-empty, and convex. Let $x in X$ and $z in C$. Then,
$$langle x - z, c - z rangle le 0 quad forall , c in C$$
if and only if $z = p_C(x)$.
Proof: Suppose $z, c in C$, with $z neq c$. Let $f : mathbbR to mathbbR$ be defined by
beginalign*
f(lambda) &= |x - lambda c - (1 - lambda)z|^2 - |x - z|^2 \
&= 2 lambda langle x - z, z - c rangle + lambda^2 |z - c|^2.
endalign*
Note that this is a convex quadratic in $lambda$.
Suppose that $z = p_C(x)$. When $lambda in [0, 1]$, we have $lambda c + (1 - lambda)z in C$, hence $f(lambda) ge 0 = f(0)$. The minimum value of $f$ must be achieved at some $lambda^* le 0$. Thus,
$$0 ge lambda^* = frac-langle x - z, z - c ranglez - c iff langle x - z, c - z rangle le 0.$$
Note that the final inequality also holds for when $c = z = p_C(x)$.
Conversely, suppose $z in C$ such that $langle x - z, c - z rangle le 0$ for all $c in C$. Therefore, when $c neq z$, $lambda^* le 0$. This implies that $f$ is increasing on the interval $[0, 1]$. Hence,
$$|x - c| = f(1) ge f(0) = |x - z|.$$
As this holds for arbitrary $c in C$, we have $z = p_C(x)$.
edited Mar 24 at 19:30
answered Mar 24 at 19:16
Theo BenditTheo Bendit
20.9k12355
20.9k12355
1
$begingroup$
What is $K$ in your example?
$endgroup$
– amsmath
Mar 24 at 19:27
$begingroup$
$K$ is the closed, non-empty, convex set onto which we are projecting, as in the question.
$endgroup$
– Theo Bendit
Mar 24 at 19:28
$begingroup$
You should specify it in your example. Otherwise it is incomplete.
$endgroup$
– amsmath
Mar 24 at 19:29
$begingroup$
@amsmath Actually, in my counterexample, there is no such $K$ (I thought you were referring to the second paragraph). My point was that the two inequalities were not equivalent; in particular, if the OP was trying to manipulate one inequality into the other, they were not going to succeed.
$endgroup$
– Theo Bendit
Mar 24 at 20:03
$begingroup$
Of course they are not equivalent. But the points $u$ and $v$ are supposed to be in a closed convex set. However, in your example you can just choose the segment from $u$ to $v$ as $K$. Since one always can do that, your counterexample is actually valid without specifying $K$.
$endgroup$
– amsmath
Mar 24 at 21:02
|
show 3 more comments
1
$begingroup$
What is $K$ in your example?
$endgroup$
– amsmath
Mar 24 at 19:27
$begingroup$
$K$ is the closed, non-empty, convex set onto which we are projecting, as in the question.
$endgroup$
– Theo Bendit
Mar 24 at 19:28
$begingroup$
You should specify it in your example. Otherwise it is incomplete.
$endgroup$
– amsmath
Mar 24 at 19:29
$begingroup$
@amsmath Actually, in my counterexample, there is no such $K$ (I thought you were referring to the second paragraph). My point was that the two inequalities were not equivalent; in particular, if the OP was trying to manipulate one inequality into the other, they were not going to succeed.
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– Theo Bendit
Mar 24 at 20:03
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Of course they are not equivalent. But the points $u$ and $v$ are supposed to be in a closed convex set. However, in your example you can just choose the segment from $u$ to $v$ as $K$. Since one always can do that, your counterexample is actually valid without specifying $K$.
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– amsmath
Mar 24 at 21:02
1
1
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What is $K$ in your example?
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– amsmath
Mar 24 at 19:27
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What is $K$ in your example?
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– amsmath
Mar 24 at 19:27
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$K$ is the closed, non-empty, convex set onto which we are projecting, as in the question.
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– Theo Bendit
Mar 24 at 19:28
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$K$ is the closed, non-empty, convex set onto which we are projecting, as in the question.
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– Theo Bendit
Mar 24 at 19:28
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You should specify it in your example. Otherwise it is incomplete.
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– amsmath
Mar 24 at 19:29
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You should specify it in your example. Otherwise it is incomplete.
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– amsmath
Mar 24 at 19:29
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@amsmath Actually, in my counterexample, there is no such $K$ (I thought you were referring to the second paragraph). My point was that the two inequalities were not equivalent; in particular, if the OP was trying to manipulate one inequality into the other, they were not going to succeed.
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– Theo Bendit
Mar 24 at 20:03
$begingroup$
@amsmath Actually, in my counterexample, there is no such $K$ (I thought you were referring to the second paragraph). My point was that the two inequalities were not equivalent; in particular, if the OP was trying to manipulate one inequality into the other, they were not going to succeed.
$endgroup$
– Theo Bendit
Mar 24 at 20:03
$begingroup$
Of course they are not equivalent. But the points $u$ and $v$ are supposed to be in a closed convex set. However, in your example you can just choose the segment from $u$ to $v$ as $K$. Since one always can do that, your counterexample is actually valid without specifying $K$.
$endgroup$
– amsmath
Mar 24 at 21:02
$begingroup$
Of course they are not equivalent. But the points $u$ and $v$ are supposed to be in a closed convex set. However, in your example you can just choose the segment from $u$ to $v$ as $K$. Since one always can do that, your counterexample is actually valid without specifying $K$.
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– amsmath
Mar 24 at 21:02
|
show 3 more comments
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The statement is incorrect. Consider $V = mathbb R^2$ and $K = overlineB_1(0)$, $u=(0,0)$, $v=(epsilon,1-epsilon)$ for some small $epsilon > 0$ and $q = (2,0)$. Then $|u-q|le|v-q|$ and $(u-q,v-u) = -2epsilon < 0$.
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add a comment |
$begingroup$
The statement is incorrect. Consider $V = mathbb R^2$ and $K = overlineB_1(0)$, $u=(0,0)$, $v=(epsilon,1-epsilon)$ for some small $epsilon > 0$ and $q = (2,0)$. Then $|u-q|le|v-q|$ and $(u-q,v-u) = -2epsilon < 0$.
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add a comment |
$begingroup$
The statement is incorrect. Consider $V = mathbb R^2$ and $K = overlineB_1(0)$, $u=(0,0)$, $v=(epsilon,1-epsilon)$ for some small $epsilon > 0$ and $q = (2,0)$. Then $|u-q|le|v-q|$ and $(u-q,v-u) = -2epsilon < 0$.
$endgroup$
The statement is incorrect. Consider $V = mathbb R^2$ and $K = overlineB_1(0)$, $u=(0,0)$, $v=(epsilon,1-epsilon)$ for some small $epsilon > 0$ and $q = (2,0)$. Then $|u-q|le|v-q|$ and $(u-q,v-u) = -2epsilon < 0$.
answered Mar 24 at 19:26
amsmathamsmath
3,292421
3,292421
add a comment |
add a comment |
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I think the proof is missing an important detail: What we actually have is that for $u in K$ and $q in V$ the statement
$$ (u - q, v - u ) ge 0 qquad forall v in K$$
is equivalent to
$$ |u - q | le | v - q | qquad forall v in K.$$
The proof is given in the answer by Theo Bendit.
The second statement is just $u = operatornameproj_K(q)$.
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add a comment |
$begingroup$
I think the proof is missing an important detail: What we actually have is that for $u in K$ and $q in V$ the statement
$$ (u - q, v - u ) ge 0 qquad forall v in K$$
is equivalent to
$$ |u - q | le | v - q | qquad forall v in K.$$
The proof is given in the answer by Theo Bendit.
The second statement is just $u = operatornameproj_K(q)$.
$endgroup$
add a comment |
$begingroup$
I think the proof is missing an important detail: What we actually have is that for $u in K$ and $q in V$ the statement
$$ (u - q, v - u ) ge 0 qquad forall v in K$$
is equivalent to
$$ |u - q | le | v - q | qquad forall v in K.$$
The proof is given in the answer by Theo Bendit.
The second statement is just $u = operatornameproj_K(q)$.
$endgroup$
I think the proof is missing an important detail: What we actually have is that for $u in K$ and $q in V$ the statement
$$ (u - q, v - u ) ge 0 qquad forall v in K$$
is equivalent to
$$ |u - q | le | v - q | qquad forall v in K.$$
The proof is given in the answer by Theo Bendit.
The second statement is just $u = operatornameproj_K(q)$.
answered Mar 25 at 7:12
gerwgerw
20.1k11334
20.1k11334
add a comment |
add a comment |
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Puh, what is $q$?
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– amsmath
Mar 24 at 18:52
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my bad $q in V$
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– yoshi
Mar 24 at 19:03
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You should note that $V$ has to be complete, otherwise the projection might not exist.
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– gerw
Mar 25 at 7:10