Why are $(,f_1,…,f_n)$ linearly independent if $|,f_k-e_k|_2<dfrac{1}{sqrt n}$, where $(e_k)$ is an...
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This question already has an answer here:
Prove that $v_1, dots v_n$ is a basis of V.
2 answers
Let $(e_1,...,e_n)$ be an orthonomal basis and $(,f_1,...,f_n)$ vectors such that $|f_k-e_k|_2<dfrac{1}{sqrt n},forall k,$.
I'd like to show that $(,f_1,...,f_n)$ are linearly independent.
I don't know where to start:
I tried to see what happens for $n=2$ but, because $(,f_1,f_2)$ are two different vectors, they are linearly independent, and it does not help to see what happens in higher dimension.
It's easy to see that the $f_i$ are distinct because they are in separated balls.
I also tried to elevate to the square the relation but I found nothing.
linear-algebra orthogonality
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marked as duplicate by Lord Shark the Unknown, mrtaurho, metamorphy, José Carlos Santos
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Jan 30 at 9:18
This question has been asked before and already has an answer. If those answers do not fully address your question, please ask a new question.
add a comment |
$begingroup$
This question already has an answer here:
Prove that $v_1, dots v_n$ is a basis of V.
2 answers
Let $(e_1,...,e_n)$ be an orthonomal basis and $(,f_1,...,f_n)$ vectors such that $|f_k-e_k|_2<dfrac{1}{sqrt n},forall k,$.
I'd like to show that $(,f_1,...,f_n)$ are linearly independent.
I don't know where to start:
I tried to see what happens for $n=2$ but, because $(,f_1,f_2)$ are two different vectors, they are linearly independent, and it does not help to see what happens in higher dimension.
It's easy to see that the $f_i$ are distinct because they are in separated balls.
I also tried to elevate to the square the relation but I found nothing.
linear-algebra orthogonality
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marked as duplicate by Lord Shark the Unknown, mrtaurho, metamorphy, José Carlos Santos
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Jan 30 at 9:18
This question has been asked before and already has an answer. If those answers do not fully address your question, please ask a new question.
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What have you tried? Where did you get stuck? Can you prove it for $n = 2$?
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– Mees de Vries
Jan 24 at 16:30
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I don't know where to start. I can prove it for n=2. See my edit.
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– MiKiDe
Jan 24 at 17:10
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Note that two different vectors need not be linearly independent. One could be a multiple of the other.
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– Mees de Vries
Jan 24 at 17:36
2
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You can see this earlier post: math.stackexchange.com/questions/1452559/….
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– Song
Jan 24 at 18:01
add a comment |
$begingroup$
This question already has an answer here:
Prove that $v_1, dots v_n$ is a basis of V.
2 answers
Let $(e_1,...,e_n)$ be an orthonomal basis and $(,f_1,...,f_n)$ vectors such that $|f_k-e_k|_2<dfrac{1}{sqrt n},forall k,$.
I'd like to show that $(,f_1,...,f_n)$ are linearly independent.
I don't know where to start:
I tried to see what happens for $n=2$ but, because $(,f_1,f_2)$ are two different vectors, they are linearly independent, and it does not help to see what happens in higher dimension.
It's easy to see that the $f_i$ are distinct because they are in separated balls.
I also tried to elevate to the square the relation but I found nothing.
linear-algebra orthogonality
$endgroup$
This question already has an answer here:
Prove that $v_1, dots v_n$ is a basis of V.
2 answers
Let $(e_1,...,e_n)$ be an orthonomal basis and $(,f_1,...,f_n)$ vectors such that $|f_k-e_k|_2<dfrac{1}{sqrt n},forall k,$.
I'd like to show that $(,f_1,...,f_n)$ are linearly independent.
I don't know where to start:
I tried to see what happens for $n=2$ but, because $(,f_1,f_2)$ are two different vectors, they are linearly independent, and it does not help to see what happens in higher dimension.
It's easy to see that the $f_i$ are distinct because they are in separated balls.
I also tried to elevate to the square the relation but I found nothing.
This question already has an answer here:
Prove that $v_1, dots v_n$ is a basis of V.
2 answers
linear-algebra orthogonality
linear-algebra orthogonality
edited Jan 25 at 0:00
Hanno
2,284628
2,284628
asked Jan 24 at 16:13
MiKiDeMiKiDe
52528
52528
marked as duplicate by Lord Shark the Unknown, mrtaurho, metamorphy, José Carlos Santos
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Jan 30 at 9:18
This question has been asked before and already has an answer. If those answers do not fully address your question, please ask a new question.
marked as duplicate by Lord Shark the Unknown, mrtaurho, metamorphy, José Carlos Santos
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Jan 30 at 9:18
This question has been asked before and already has an answer. If those answers do not fully address your question, please ask a new question.
$begingroup$
What have you tried? Where did you get stuck? Can you prove it for $n = 2$?
$endgroup$
– Mees de Vries
Jan 24 at 16:30
$begingroup$
I don't know where to start. I can prove it for n=2. See my edit.
$endgroup$
– MiKiDe
Jan 24 at 17:10
$begingroup$
Note that two different vectors need not be linearly independent. One could be a multiple of the other.
$endgroup$
– Mees de Vries
Jan 24 at 17:36
2
$begingroup$
You can see this earlier post: math.stackexchange.com/questions/1452559/….
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– Song
Jan 24 at 18:01
add a comment |
$begingroup$
What have you tried? Where did you get stuck? Can you prove it for $n = 2$?
$endgroup$
– Mees de Vries
Jan 24 at 16:30
$begingroup$
I don't know where to start. I can prove it for n=2. See my edit.
$endgroup$
– MiKiDe
Jan 24 at 17:10
$begingroup$
Note that two different vectors need not be linearly independent. One could be a multiple of the other.
$endgroup$
– Mees de Vries
Jan 24 at 17:36
2
$begingroup$
You can see this earlier post: math.stackexchange.com/questions/1452559/….
$endgroup$
– Song
Jan 24 at 18:01
$begingroup$
What have you tried? Where did you get stuck? Can you prove it for $n = 2$?
$endgroup$
– Mees de Vries
Jan 24 at 16:30
$begingroup$
What have you tried? Where did you get stuck? Can you prove it for $n = 2$?
$endgroup$
– Mees de Vries
Jan 24 at 16:30
$begingroup$
I don't know where to start. I can prove it for n=2. See my edit.
$endgroup$
– MiKiDe
Jan 24 at 17:10
$begingroup$
I don't know where to start. I can prove it for n=2. See my edit.
$endgroup$
– MiKiDe
Jan 24 at 17:10
$begingroup$
Note that two different vectors need not be linearly independent. One could be a multiple of the other.
$endgroup$
– Mees de Vries
Jan 24 at 17:36
$begingroup$
Note that two different vectors need not be linearly independent. One could be a multiple of the other.
$endgroup$
– Mees de Vries
Jan 24 at 17:36
2
2
$begingroup$
You can see this earlier post: math.stackexchange.com/questions/1452559/….
$endgroup$
– Song
Jan 24 at 18:01
$begingroup$
You can see this earlier post: math.stackexchange.com/questions/1452559/….
$endgroup$
– Song
Jan 24 at 18:01
add a comment |
2 Answers
2
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oldest
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If the $f_k$ are not linearly independent, then they can not span the space, so
$M=$span$({{f_k}})^{perp}neq 0.$ Therefore, there is a non-zero vector $uin M$ such that for each integer $1le kle n, uperp f_k.$
Of course, $u=sum^n_{k=1}langle u,e_krangle e_k, $ so that $|u|^2=sum^n_{k=1}|langle u,e_k-f_krangle |^2. $ Now, apply Cauchy-Schwarz to this last item and then use the hypothesis:
$|u|^2le sum^n_{k=1}|u|^2cdot |e_k-f_k|^2<sum^n_{k=1}|u|^2cdot left ( frac{1}{sqrt n} right )^2=ncdot left ( frac{1}{sqrt n} right )^2cdot |u|^2=|u|^2$, and so we get that $|u|^2<|u|^2$, which is absurd.
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add a comment |
$begingroup$
The condition
$|f_k - e_k|_2 < frac{1}{sqrt n}$ can be written
$$ |(I-T)e_k|_2 < frac{1}{sqrt n}$$
Where $T:Xto X$ is the linear map on $X=operatorname{span}{e_1dots e_n}$ that maps $e_k mapsto f_k$, and $I:Xmapsto X$ is the identity map.
Suppose now $x=sum_i x_i e_i $ is an arbitrary vector in $X$ with $|x|^2_2 = sum_i x_i ^2 = 1$. Then
begin{align} &|(I-T)x|_2
\ le& sum_{i=1}^n | x_i|| (I-T) e_i|_2
\ le &sqrt{sum_i |x_i|^2} sqrt{sum_i | (I-T) e_i|^2_2} \ =& sqrt{sum_i | (I-T) e_i|^2_2}
end{align}
Thus the operator norm $|I-T|_{op} := sup_{x: |x|_2 = 1} |(I-T)x|_2 le sqrt{sum_i | (I-T) e_i|^2_2} < 1 $. By results on Neumann series (see Proof of Neumann Lemma ), $T$ is invertible, and the result follows.
Also, here's a picture showing why a strict inequality is important:
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$begingroup$
the inequality is strict
$endgroup$
– Thinking
Jan 24 at 18:03
$begingroup$
@Thinking oops, yes, and thats important. Thanks
$endgroup$
– Calvin Khor
Jan 24 at 18:03
add a comment |
2 Answers
2
active
oldest
votes
2 Answers
2
active
oldest
votes
active
oldest
votes
active
oldest
votes
$begingroup$
If the $f_k$ are not linearly independent, then they can not span the space, so
$M=$span$({{f_k}})^{perp}neq 0.$ Therefore, there is a non-zero vector $uin M$ such that for each integer $1le kle n, uperp f_k.$
Of course, $u=sum^n_{k=1}langle u,e_krangle e_k, $ so that $|u|^2=sum^n_{k=1}|langle u,e_k-f_krangle |^2. $ Now, apply Cauchy-Schwarz to this last item and then use the hypothesis:
$|u|^2le sum^n_{k=1}|u|^2cdot |e_k-f_k|^2<sum^n_{k=1}|u|^2cdot left ( frac{1}{sqrt n} right )^2=ncdot left ( frac{1}{sqrt n} right )^2cdot |u|^2=|u|^2$, and so we get that $|u|^2<|u|^2$, which is absurd.
$endgroup$
add a comment |
$begingroup$
If the $f_k$ are not linearly independent, then they can not span the space, so
$M=$span$({{f_k}})^{perp}neq 0.$ Therefore, there is a non-zero vector $uin M$ such that for each integer $1le kle n, uperp f_k.$
Of course, $u=sum^n_{k=1}langle u,e_krangle e_k, $ so that $|u|^2=sum^n_{k=1}|langle u,e_k-f_krangle |^2. $ Now, apply Cauchy-Schwarz to this last item and then use the hypothesis:
$|u|^2le sum^n_{k=1}|u|^2cdot |e_k-f_k|^2<sum^n_{k=1}|u|^2cdot left ( frac{1}{sqrt n} right )^2=ncdot left ( frac{1}{sqrt n} right )^2cdot |u|^2=|u|^2$, and so we get that $|u|^2<|u|^2$, which is absurd.
$endgroup$
add a comment |
$begingroup$
If the $f_k$ are not linearly independent, then they can not span the space, so
$M=$span$({{f_k}})^{perp}neq 0.$ Therefore, there is a non-zero vector $uin M$ such that for each integer $1le kle n, uperp f_k.$
Of course, $u=sum^n_{k=1}langle u,e_krangle e_k, $ so that $|u|^2=sum^n_{k=1}|langle u,e_k-f_krangle |^2. $ Now, apply Cauchy-Schwarz to this last item and then use the hypothesis:
$|u|^2le sum^n_{k=1}|u|^2cdot |e_k-f_k|^2<sum^n_{k=1}|u|^2cdot left ( frac{1}{sqrt n} right )^2=ncdot left ( frac{1}{sqrt n} right )^2cdot |u|^2=|u|^2$, and so we get that $|u|^2<|u|^2$, which is absurd.
$endgroup$
If the $f_k$ are not linearly independent, then they can not span the space, so
$M=$span$({{f_k}})^{perp}neq 0.$ Therefore, there is a non-zero vector $uin M$ such that for each integer $1le kle n, uperp f_k.$
Of course, $u=sum^n_{k=1}langle u,e_krangle e_k, $ so that $|u|^2=sum^n_{k=1}|langle u,e_k-f_krangle |^2. $ Now, apply Cauchy-Schwarz to this last item and then use the hypothesis:
$|u|^2le sum^n_{k=1}|u|^2cdot |e_k-f_k|^2<sum^n_{k=1}|u|^2cdot left ( frac{1}{sqrt n} right )^2=ncdot left ( frac{1}{sqrt n} right )^2cdot |u|^2=|u|^2$, and so we get that $|u|^2<|u|^2$, which is absurd.
answered Jan 24 at 17:46
MatematletaMatematleta
11.5k2920
11.5k2920
add a comment |
add a comment |
$begingroup$
The condition
$|f_k - e_k|_2 < frac{1}{sqrt n}$ can be written
$$ |(I-T)e_k|_2 < frac{1}{sqrt n}$$
Where $T:Xto X$ is the linear map on $X=operatorname{span}{e_1dots e_n}$ that maps $e_k mapsto f_k$, and $I:Xmapsto X$ is the identity map.
Suppose now $x=sum_i x_i e_i $ is an arbitrary vector in $X$ with $|x|^2_2 = sum_i x_i ^2 = 1$. Then
begin{align} &|(I-T)x|_2
\ le& sum_{i=1}^n | x_i|| (I-T) e_i|_2
\ le &sqrt{sum_i |x_i|^2} sqrt{sum_i | (I-T) e_i|^2_2} \ =& sqrt{sum_i | (I-T) e_i|^2_2}
end{align}
Thus the operator norm $|I-T|_{op} := sup_{x: |x|_2 = 1} |(I-T)x|_2 le sqrt{sum_i | (I-T) e_i|^2_2} < 1 $. By results on Neumann series (see Proof of Neumann Lemma ), $T$ is invertible, and the result follows.
Also, here's a picture showing why a strict inequality is important:
$endgroup$
$begingroup$
the inequality is strict
$endgroup$
– Thinking
Jan 24 at 18:03
$begingroup$
@Thinking oops, yes, and thats important. Thanks
$endgroup$
– Calvin Khor
Jan 24 at 18:03
add a comment |
$begingroup$
The condition
$|f_k - e_k|_2 < frac{1}{sqrt n}$ can be written
$$ |(I-T)e_k|_2 < frac{1}{sqrt n}$$
Where $T:Xto X$ is the linear map on $X=operatorname{span}{e_1dots e_n}$ that maps $e_k mapsto f_k$, and $I:Xmapsto X$ is the identity map.
Suppose now $x=sum_i x_i e_i $ is an arbitrary vector in $X$ with $|x|^2_2 = sum_i x_i ^2 = 1$. Then
begin{align} &|(I-T)x|_2
\ le& sum_{i=1}^n | x_i|| (I-T) e_i|_2
\ le &sqrt{sum_i |x_i|^2} sqrt{sum_i | (I-T) e_i|^2_2} \ =& sqrt{sum_i | (I-T) e_i|^2_2}
end{align}
Thus the operator norm $|I-T|_{op} := sup_{x: |x|_2 = 1} |(I-T)x|_2 le sqrt{sum_i | (I-T) e_i|^2_2} < 1 $. By results on Neumann series (see Proof of Neumann Lemma ), $T$ is invertible, and the result follows.
Also, here's a picture showing why a strict inequality is important:
$endgroup$
$begingroup$
the inequality is strict
$endgroup$
– Thinking
Jan 24 at 18:03
$begingroup$
@Thinking oops, yes, and thats important. Thanks
$endgroup$
– Calvin Khor
Jan 24 at 18:03
add a comment |
$begingroup$
The condition
$|f_k - e_k|_2 < frac{1}{sqrt n}$ can be written
$$ |(I-T)e_k|_2 < frac{1}{sqrt n}$$
Where $T:Xto X$ is the linear map on $X=operatorname{span}{e_1dots e_n}$ that maps $e_k mapsto f_k$, and $I:Xmapsto X$ is the identity map.
Suppose now $x=sum_i x_i e_i $ is an arbitrary vector in $X$ with $|x|^2_2 = sum_i x_i ^2 = 1$. Then
begin{align} &|(I-T)x|_2
\ le& sum_{i=1}^n | x_i|| (I-T) e_i|_2
\ le &sqrt{sum_i |x_i|^2} sqrt{sum_i | (I-T) e_i|^2_2} \ =& sqrt{sum_i | (I-T) e_i|^2_2}
end{align}
Thus the operator norm $|I-T|_{op} := sup_{x: |x|_2 = 1} |(I-T)x|_2 le sqrt{sum_i | (I-T) e_i|^2_2} < 1 $. By results on Neumann series (see Proof of Neumann Lemma ), $T$ is invertible, and the result follows.
Also, here's a picture showing why a strict inequality is important:
$endgroup$
The condition
$|f_k - e_k|_2 < frac{1}{sqrt n}$ can be written
$$ |(I-T)e_k|_2 < frac{1}{sqrt n}$$
Where $T:Xto X$ is the linear map on $X=operatorname{span}{e_1dots e_n}$ that maps $e_k mapsto f_k$, and $I:Xmapsto X$ is the identity map.
Suppose now $x=sum_i x_i e_i $ is an arbitrary vector in $X$ with $|x|^2_2 = sum_i x_i ^2 = 1$. Then
begin{align} &|(I-T)x|_2
\ le& sum_{i=1}^n | x_i|| (I-T) e_i|_2
\ le &sqrt{sum_i |x_i|^2} sqrt{sum_i | (I-T) e_i|^2_2} \ =& sqrt{sum_i | (I-T) e_i|^2_2}
end{align}
Thus the operator norm $|I-T|_{op} := sup_{x: |x|_2 = 1} |(I-T)x|_2 le sqrt{sum_i | (I-T) e_i|^2_2} < 1 $. By results on Neumann series (see Proof of Neumann Lemma ), $T$ is invertible, and the result follows.
Also, here's a picture showing why a strict inequality is important:
edited Jan 25 at 0:28
answered Jan 24 at 17:52
Calvin KhorCalvin Khor
12.4k21439
12.4k21439
$begingroup$
the inequality is strict
$endgroup$
– Thinking
Jan 24 at 18:03
$begingroup$
@Thinking oops, yes, and thats important. Thanks
$endgroup$
– Calvin Khor
Jan 24 at 18:03
add a comment |
$begingroup$
the inequality is strict
$endgroup$
– Thinking
Jan 24 at 18:03
$begingroup$
@Thinking oops, yes, and thats important. Thanks
$endgroup$
– Calvin Khor
Jan 24 at 18:03
$begingroup$
the inequality is strict
$endgroup$
– Thinking
Jan 24 at 18:03
$begingroup$
the inequality is strict
$endgroup$
– Thinking
Jan 24 at 18:03
$begingroup$
@Thinking oops, yes, and thats important. Thanks
$endgroup$
– Calvin Khor
Jan 24 at 18:03
$begingroup$
@Thinking oops, yes, and thats important. Thanks
$endgroup$
– Calvin Khor
Jan 24 at 18:03
add a comment |
$begingroup$
What have you tried? Where did you get stuck? Can you prove it for $n = 2$?
$endgroup$
– Mees de Vries
Jan 24 at 16:30
$begingroup$
I don't know where to start. I can prove it for n=2. See my edit.
$endgroup$
– MiKiDe
Jan 24 at 17:10
$begingroup$
Note that two different vectors need not be linearly independent. One could be a multiple of the other.
$endgroup$
– Mees de Vries
Jan 24 at 17:36
2
$begingroup$
You can see this earlier post: math.stackexchange.com/questions/1452559/….
$endgroup$
– Song
Jan 24 at 18:01