Proving Triangle Inequality for L-Normed Vector Space

Mathman23
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Hi

I'm given the following assignment which deals with to looks like an L-normed vectorspace:

Prove that,

|f(y_1) - f(y_2)| \leq || y_1 - y_2||

To prove this do I approach the above as a triangle inequality or as a cauchy-swartz inequality?

Best Regards,

Fred
 
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What do you know about f ? How is the norm defined?
 
Hello and thank You for Your reply,

f is defined as follows:

f: \mathbb{R}^n \rightarrow \mathbb{R} and

y1, y2 \in \mathbb{R}^n

Best Regards,

Fred

benorin said:
What do you know about f ? How is the norm defined?
 
More must be given, (or I am just that tired) since

|f(y_1) - f(y_2)| \leq || y_1 - y_2||

does not, in general (under those conditions), hold for arbitrary f:R^n->R, like, say, put f(y)=2 ||y|| with y2=0 and y1=y gives

|f(y) - f(0)| = 2||y|| \not\leq || y - 0||
 
Hello again,

According to my textbook the first step is to show that

f(y_2) \leq || y_1 - y_2|| + f(y_1)

The is a sub-problem of a problem which deals distance from a point to a set.

f is defined as the distance from a point in \mathbb{R}^n to a subset S of \mathbb{R}^n

and finally I'm suppose to conclude that f is Uniform continuites on <br /> \mathbb{R}^n

Any idears?

Best Regards,

Fred

benorin said:
More must be given, (or I am just that tired) since

|f(y_1) - f(y_2)| \leq || y_1 - y_2||

does not, in general (under those conditions), hold for arbitrary f:R^n->R, like, say, put f(y)=2 ||y|| with y2=0 and y1=y gives

|f(y) - f(0)| = 2||y|| \not\leq || y - 0||
 
Mathman23 said:
Hello again,

According to my textbook the first step is to show that

f(y_2) \leq || y_1 - y_2|| + f(y_1)

The is a sub-problem of a problem which deals distance from a point to a set.

f is defined as the distance from a point in \mathbb{R}^n to a subset S of \mathbb{R}^n

and finally I'm suppose to conclude that f is Uniform continuites on <br /> \mathbb{R}^n

Any idears?

Best Regards,

Fred

Since f is defined as the distance from a point in \mathbb{R}^n to a subset S of \mathbb{R}^n, we should have

f_S(y)=\mbox{inf}\left\{ \|x-y\| : x\in S\right\} for y\in\mathbb{R}^n

I put a subscript of S on f since f depends on S, but consider S fixed and supress the subscript from here on.

f(y_2) \leq || y_1 - y_2|| + f(y_1) is the statement that

\mbox{inf}\left\{ \|x-y_2\| : x\in S\right\} \leq \| y_1 - y_2\| + \mbox{inf}\left\{ \|x-y_1\| : x\in S\right\},

how could you prove that?
 
benorin said:
Since f is defined as the distance from a point in \mathbb{R}^n to a subset S of \mathbb{R}^n, we should have

f_S(y)=\mbox{inf}\left\{ \|x-y\| : x\in S\right\} for y\in\mathbb{R}^n

I put a subscript of S on f since f depends on S, but consider S fixed and supress the subscript from here on.

f(y_2) \leq || y_1 - y_2|| + f(y_1) is the statement that

\mbox{inf}\left\{ \|x-y_2\| : x\in S\right\} \leq \| y_1 - y_2\| + \mbox{inf}\left\{ \|x-y_1\| : x\in S\right\},

how could you prove that?



By showing that normed distance from x to y1 and from x to y2 are equal? Cause they belong to the same subset?

Best Regards
Fred
 
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By the triangle inequality, for all x,y_1,y_2\in\mathbb{R}^n, we have

\|x-y_2\| \leq \| y_1 - y_2\| +\|x-y_1\|,

and since x\in S\mbox{ and }S\subset\mathbb{R}^n, we may restrict x to be in S and inf over x in S to obtain

\mbox{inf}\left\{ \|x-y_2\| : x\in S\right\} \leq \mbox{inf}\left\{\| y_1 - y_2\| + \|x-y_1\| : x\in S\right\} = \| y_1 - y_2\| + \mbox{inf}\left\{ \|x-y_1\| : x\in S\right\}
 
Hello again and thank You for Your answer,

And this shows, that

|f(y_1) - f(y_2)| \leq || y_1 - y_2||

is true?

Best Regards

Fred

benorin said:
By the triangle inequality, for all x,y_1,y_2\in\mathbb{R}^n, we have

\|x-y_2\| \leq \| y_1 - y_2\| +\|x-y_1\|,

and since x\in S\mbox{ and }S\subset\mathbb{R}^n, we may restrict x to be in S and inf over x in S to obtain

\mbox{inf}\left\{ \|x-y_2\| : x\in S\right\} \leq \mbox{inf}\left\{\| y_1 - y_2\| + \|x-y_1\| : x\in S\right\} = \| y_1 - y_2\| + \mbox{inf}\left\{ \|x-y_1\| : x\in S\right\}
 
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  • #10
Swap y1 and y2, see what you get.
 
  • #11
Hello again,


then

|f(y_1) - f(y_2)| \leq || y_1 - y_2||

since

\mbox{inf}\left\{ \|x-y_2\| : x\in S\right\} - \| y_1 - y_2\| \leq \mbox{inf}\left\{\| y_1 - y_2\| + \|x-y_1\| : x\in S\right\} ?

Best Regards

Fred

benorin said:
Swap y1 and y2, see what you get.
 
  • #12
Of this

\mbox{inf}\left\{ \|x-y_2\| : x\in S\right\} \leq \mbox{inf}\left\{\| y_1 - y_2\| + \|x-y_1\| : x\in S\right\} = \| y_1 - y_2\| + \mbox{inf}\left\{ \|x-y_1\| : x\in S\right\}

you need only first and last bits (including the <= sign), namely

\mbox{inf}\left\{ \|x-y_2\| : x\in S\right\} \leq \| y_1 - y_2\| + \mbox{inf}\left\{ \|x-y_1\| : x\in S\right\}

in this, swap y1 and y2, to get

\mbox{inf}\left\{ \|x-y_1\| : x\in S\right\} \leq \| y_2 - y_1\| + \mbox{inf}\left\{ \|x-y_2\| : x\in S\right\}

and since \| y_2 - y_1\| = \| y_1 - y_2\| , we have this pair of inequalities

\boxed{\begin{array}{cc} \mbox{inf}\left\{ \|x-y_2\| : x\in S\right\} \leq \| y_1 - y_2\| + \mbox{inf}\left\{ \|x-y_1\| : x\in S\right\} \\ \mbox{inf}\left\{ \|x-y_1\| : x\in S\right\} \leq \| y_1 - y_2\| + \mbox{inf}\left\{ \|x-y_2\| : x\in S\right\} \end{array} }

thinking of theses as being of the form

A\leq k+B
B\leq k+A

we then have

A-B\leq k and
B-A\leq k

thus |B-A| \leq k i.e. |f(y_1) - f(y_2)| \leq || y_1 - y_2||
 
  • #13
Hello again, and thank You for Your answers,

I need to conclude that the function f is is uniformly continius on \mathbb{R}^n.

In order to show this by proving that definition of uniformly continious functions applies to my specific f function?

Best Regards,

Fred

benorin said:
Of this

\mbox{inf}\left\{ \|x-y_2\| : x\in S\right\} \leq \mbox{inf}\left\{\| y_1 - y_2\| + \|x-y_1\| : x\in S\right\} = \| y_1 - y_2\| + \mbox{inf}\left\{ \|x-y_1\| : x\in S\right\}

you need only first and last bits (including the <= sign), namely

\mbox{inf}\left\{ \|x-y_2\| : x\in S\right\} \leq \| y_1 - y_2\| + \mbox{inf}\left\{ \|x-y_1\| : x\in S\right\}

in this, swap y1 and y2, to get

\mbox{inf}\left\{ \|x-y_1\| : x\in S\right\} \leq \| y_2 - y_1\| + \mbox{inf}\left\{ \|x-y_2\| : x\in S\right\}

and since \| y_2 - y_1\| = \| y_1 - y_2\| , we have this pair of inequalities

\boxed{\begin{array}{cc} \mbox{inf}\left\{ \|x-y_2\| : x\in S\right\} \leq \| y_1 - y_2\| + \mbox{inf}\left\{ \|x-y_1\| : x\in S\right\} \\ \mbox{inf}\left\{ \|x-y_1\| : x\in S\right\} \leq \| y_1 - y_2\| + \mbox{inf}\left\{ \|x-y_2\| : x\in S\right\} \end{array} }

thinking of theses as being of the form

A\leq k+B
B\leq k+A

we then have

A-B\leq k and
B-A\leq k

thus |B-A| \leq k i.e. |f(y_1) - f(y_2)| \leq || y_1 - y_2||
 
  • #14
What is the definition of a uniformly continuous function?
 
  • #15
Definition:uniformly continuous function

S is a subset of \mathbb{R}^n and f: S \rightarrow \mathbb{R} be a real valued function. The function f is said to be uniformly continuous, if there for every epsilon > 0, exists a delta > 0 such that,

|f(x) - f(y) | < epsilon

for all x,y \in S, which statisfies that ||x - y|| < delta

Do I then apply this definition to my given f(x) ? and use it to show how f(x) = 0, if x belongs to Y ?

Best Regards
Fred

benorin said:
What is the definition of a uniformly continuous function?
 
  • #16
Mathman23 said:
Do I then apply this definition to my given f(x) ? and use it to show how f(x) = 0, if x belongs to Y ?
Fred

Yes, if you wish to prove f is a uniformly continuous function do just that: the first bit is done, so just choose delta = epsilon and it is done.

And do U mean x belongs to S? Indeed it is a simple matter that f(x)=0 for every x in S, since (for fixed x) the shortest distance between x and y when y is allowed to be x is 0.
 
  • #17
benorin said:
Yes, if you wish to prove f is a uniformly continuous function do just that: the first bit is done, so just choose delta = epsilon and it is done.

And do U mean x belongs to S? Indeed it is a simple matter that f(x)=0 for every x in S, since (for fixed x) the shortest distance between x and y when y is allowed to be x is 0.

regarding uniform continuity

then according to the definition of uniformly continious functions then
|x - y| = |x| - |y|

From here I'm a bit unsure

Do I do the following y = x + \delta then x \geq 0

|x - (x+ \delta)| = \delta

then |x - (x+ \delta)| &lt; \epsilon

futermore since \delta &gt; 0 according to the definition:

\delta &lt; \epsilon

therefore f is uniformly continious.

Am I on the right path here?

Best Regards
Fred
 
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  • #18
Mathman23 said:
Definition:uniformly continuous function

S is a subset of \mathbb{R}^n and f: S \rightarrow \mathbb{R} be a real valued function. The function f is said to be uniformly continuous, if there for every epsilon > 0, exists a delta > 0 such that,

|f(x) - f(y) | < epsilon

for all x,y \in S, which statisfies that ||x - y|| < delta

Recall that we just proved that

|f(x) - f(y) | \leq \| x-y\| for all x,y\in\mathbb{R}^n

we now wish to show that

\mbox{ For every } \epsilon &gt;0, \mbox{ there exists a } \delta &gt;0\mbox{ such that }\| x-y\| &lt; \delta \Rightarrow |f(x)-f(y)| &lt;\epsilon

So fix \epsilon &gt;0. Choose \delta = \epsilon so that

\| x-y\| &lt; \delta \Rightarrow |f(x)-f(y)| \leq \| x-y\| &lt; \delta =\epsilon

where we have used that bit of which I wrote "Recall that we just proved ..." to get the |f(x)-f(y)| \leq \| x-y\| part of the above line.

--Ben
 
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  • #19
Thank You again,

If have two small final followup questions:

(a) If S is closed set, and if x \notin S, then f(x) > 0

(b) if Y is closed, then

X = {x \in R^n | f(x) = 0}

I know in (a) that since x is not in S, then the metric distance between x,y is larger than zero, but does that explain f(x) > 0??

Any hints on how to solve (b) ?

Best Regards

Fred

benorin said:
Yes, if you wish to prove f is a uniformly continuous function do just that: the first bit is done, so just choose delta = epsilon and it is done.

And do U mean x belongs to S? Indeed it is a simple matter that f(x)=0 for every x in S, since (for fixed x) the shortest distance between x and y when y is allowed to be x is 0.
 
  • #20
"I know in (a) that since x is not in S, then the metric distance between x,y is larger than zero, but does that explain f(x) > 0??"

How do you know this is so? If had, say, S=(0,1) (the segment of the real line strictly between 0 and 1) what than is f(0) ?
 
  • #21
benorin said:
"I know in (a) that since x is not in S, then the metric distance between x,y is larger than zero, but does that explain f(x) > 0??"

How do you know this is so? If had, say, S=(0,1) (the segment of the real line strictly between 0 and 1) what than is f(0) ?

If S = (x=1, y = 0) then f(x) > 0 ??

I'm a bit lost here, any hints?

Sincerely
Fred
 
  • #22
This is a trick question:

benorin said:
How do you know this is so? If had, say, S=(0,1) (the segment of the real line strictly between 0 and 1) what then is f(0) ?

I was trying to ensure you understood why "I know in (a) that since x is not in S, then the metric distance between x,y is larger than zero..."

Understand that if y is the particular point in S whose distance to x is a minimum, then f(x)-||x-y||, that is to say the value of f(x) is that minimum distance between x and y.

A geometric example will help: We're in \mathbb{R}^2. Let S be the unit square [0,1]x[0,1]. Now fix a point x in \mathbb{R}^2, I'll pick x=(2,1/2). Now f[(2,1/2)] can be determined as follows:

first, find the point in S (the unit square) which is closest to (2,1/2) (which is x in our example), and denote this "closest point" by y. So what is y? Well clearly y is on the right-hand edge of the unit square S since were it not, we could easily find a point in S that is closer to (2,1/2). Every point on the right-hand edge of S is of the form (1,t), where 0\leq t\leq 1. The distance d between (1,t) and (2,1/2) is given by the usual distance formula

d=\sqrt{(2-1)^2+(1/2 -t)^2}=\sqrt{1+(1/2 -t)^2}

and we seek the value of t with 0\leq t\leq 1 that minimizes d. We reason that the minimum occurs for t=1/2 and hence determine that y=(1,1/2).

Second, we recall that f(x) is the distance between x and y, i.e. f(x)=||x-y||, and, in this example, the distance is given by the usual formula, so we have

f[(2,1/2)] = ||(2,1/2)-(1,1/2)||=\sqrt{(1-2)^2+(1/2 -1/2)^2}=1.

Which makes sense, if you think about the diagram (you should draw one). End Geometric Example.

Notice that in the above example S was a closed set. In the so-called trick question I posed at the top of this post, S was (0,1) on the real line (which is not a closed set) and I had asked what then is f(0)? We would first determine the point y in (0,1) whose distance to 0 is a minimum, at least we would if there were such a point, but 0 is a limit point of (0,1) so there are infinitely many points in (0,1) infinitely close to 0, but there is always one closer... strictly speaking, there is no point y in (0,1) of minimum distance to 0, but there is an infimum (the inf) of the set of such distances, which is 0 (this is the value of the distance, not the point y at which it occurs), and thus f(0)=0. But notice that 0 (the point) is not in S, and yet we have f(0)=0 and not f(0)>0. Why?


Answer: S is not closed. In the example where S was the unit square in R^2, S was closed. Can you find a point z in R^2 that is not is S such that f(z)=0? Why not?
 
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  • #23
Hi all,

I been thinking regarding:

(a) If S is closed set, and if x \notin S, then f(x) > 0

(b) if Y is closed, then

X = \{x \in R^n | f(x) = 0 \}

I know that according to my textbook the definition of a closed set is a as follows:

A subset F of \mathbb{R}^n is closed if its complement:

\mathbb{R}^n \mathrm{\} F = \{ x \in R^n | x \notin F \} is open.

Do I then need to show that x is an internal point of \mathbb{R}^n


Sincerely

Fred
 
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