On page 36 it is mentioned that in a metric space $X$ the function $$d_E(X)=\operatorname{dist}(x,E)$$ is continuous for any non-empty set $E\subseteq X$.
I thought of this as - "Norm of x that is $||x||$, as the distance of a point $x$ in space $X$ from Origin"
so $||x|| = Inf \{ d_{{0}} (x) : x \in X\}$ is continuous on $X$
so are we basically saying this
$||.|| :X \rightarrow \Bbb{R} $ is a continuous function?
also
2)
I think in the above conversation we were trying to show that the mapping $F(x) \rightarrow ||F(x)||$ is continuous
may be can I call this a continuous transformation?
Oh, sorry, you mean I should have used this link: books.google.com/books?id=BaEgbIoPTygC&pg=PA33 (Anyway you were posting links ending with .co.in - I guess we both simply copied where google redirected us based of language preferences.)
be the space of all real valued continuous functions
on$[0,1]$ .Let $T: X \rightarrow \mathbb{R}$, be alinear functional defined by $T(f) = f(1)$.Let $X_{1} = (X,||.||_{1})$ and $X_{2} = (X,||.||_{\infty})$.Then $T$ is neither continuous on $X_{1}$ nor on $X_{2}$ ?
I think $||f||_{1} = \int_{0}^{1} f dx$ is this correct?
or it has some other definitions?
and is $||f||_{\infty} = sup(f(x),x \in [0,1])$
?
I thought of using this result that if $f$ is continuous on $X$ then there exists some $\alpha$ such that $||T(f)|| \leq \alpha ||f||$
as per here we have to show $||f(1)|| \leq \alpha ||f||$
also what is the norm associated with space $\Bbb{R}$,I think it is modulus?
In both definitions you are missing absolute value, you should have \begin{align*} \|f\|_1 &= \int_0^1 |f(x)| \,dx\\ \|f\|_\infty &= \sup_{x\in[0,1]} |f(x)| \end{align*}
Yes, on $\mathbb R$ you are using absolute value as the norm. (This is the standard norm when you consider $\mathbb R$ as a linear normed space - so you can always assume this one, unless the text specifies explicitly that in some example a different norm on $\mathbb R$ is considered.
You also have equivalent characterization now: A linear function $T\colon X\to\mathbb R$ is continuous if and only if there is an $\alpha$ such that $\|x\|\le1$ implies $|T(x)|\le\alpha$.
BTW where does the problem come from? Is this really what the problem says? Since I suspect that $T$ is continuous w.r.t $\infty$-norm but not w.r.t 1-norm.
We would also like to show that $T$ is not continuous w.r.t. 1-norm.
To this end it suffices to find a sequence $f_n\in C[0,1]$ such that $\|f_n\|=1$ but $|T(f_n)|\to\infty$.
Can you think of an example of a sequence of continuous functions such that $\int_0^1 |f_n(x)|\,dx=1$ but $\lim\limits_{n\to\infty} |f_n(1)|=\infty$. (You can try positive functions so that you do not have to worry about absolute values.)
So if you prefer, replace it with $\int_0^1 |f_n(x)|\,dx \le 1$.
I guess that for examples like this, it's much easier to draw an example than to come up with a function given by an actual formula.
I think that a picture can be enough of an argument for you to see that it indeed is not continuous. But for an assignment you'll probably need to write down a more formal argument, so you might need to try write down an explicit formula for $f_n$ for that.
tail end is on the top (directed upwards parallel to the positive y axis)
and as $n$ increases the top end of the traingle grows in the direction parallel to the positive $y$ axis and thus tending towards infinity as $n$ increases
but in this case how $\int_{0}^{1}|f_{n}| dx \leq 1 $ as $n \rightarrow \infty$
perhaps we could squeeze the base length as $n \rightarrow \infty$ tending the area towards 0
@NV-US Well, if the question is not about functional analysis, then probably this is not the right place... You have main chat room and also several discipline-specific chat rooms.
Let $\Phi$ be a nice Young function (N-function) and $(\Omega,\mathcal{F},P)$ a probability space such that either $P$ is diffuse on a set of non-zero probability or $P$ is purely atomic and there are infinitely many atoms. In other words $(\Omega,\mathcal{F},P)$ is not a finite probability space...
I've heard that the uniform boundedness principle from functional analysis is a quite important result.
The theorem is the following:
Let $X$ be a Banach space and $Y$ a normed vector space. Let $F$ be a collection of continuous linear operators $T:X\to Y$ and suppose that $\sup_{T\in F}\|T(...
A linear operator $T\colon X\to Y$ between linear normed spaces is bounded if there exists a constant $M$ such that $$\|Tx\| \le M\|x\|\tag{*}$$ holds for every $x\in X$. Are there some situations when it is sufficient to verify that this condition is true for elements from some Hamel basis $B$?
...
Ok, so it seems that the feed at least post something in the room. We will see what happens if some of those questions is bumped or if a new question is featured.
@BAYMAX Well, I (and probably most users) will only visit the room from time to time - as opposed to being here all the time. So if they are posted in the form of ticker, they are quite likely to remain unnoticed.
I don't think bounties are that frequent. (If we wanted to add another feed with many items, than the ticker is much better option.)
For example, if we want also another feed with all questions tagged functional-analysis, then adding this as chat messages would result to room drowned with post from feeds.
I wish this does not devolve into me solving your homework for you, but to do that, probably I have to learn how to ask right questions and give reasonable hints.
So the question is basically: Let X be a reflexive linear normed space. If we take any norm on X which generates the same topology, is this norm equivalent to the original one?
Anyway, I am not really sure what is correct answer to this problem. (And not even whether this is the intended formulation.)
What I wrote above is non-sense. Two norms are equivalent iff they generate the same topology.
So I'll have to admit that the question above is rather unclear to me.
If the same question was asked for "vector space X" (not for "norme vector space X"), then the answer would be finite dimensional.
This is quite strange - I have to admit that it's rather unclear to me what the question actually asks.
If you have a norm $\|\cdot\|$ on $X$, then $d(x,y)=\|x-y\|$ is metric on $X$.
And metric gives us a topology.
In fact, whenever we talk about convergence, open set, closed set in a linear normed space, we mean convergence/open/closed w.r.t. this topology (=w.r.t. this metric).