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- Authors : T. Markandeya Naidu, Dr. D. Bharathi.
- Paper ID : IJERTV3IS10787
- Volume & Issue : Volume 03, Issue 01 (January 2014)
- Published (First Online): 24-01-2014
- ISSN (Online) : 2278-0181
- Publisher Name : IJERT
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Best Simultaneous Approximation in 2-Normed Almost Linear Space
Best Simultaneous Approximation in 2-Normed Almost Linear Space
T. Markandeya Naidu & Dr. D. Bharathi
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Department Of Mathematics, P.V.K.N.Govt.Degree College, Chittoor,Andhra Pradesh, India 2 .Department Of Mathematics, S.V.University, Tirupathi, Andhra Pradesh ,India.
ABSTRACT
In this paper we establish some of the results of best simultaneous approximation in linear 2- normed space in the context of 2- normed almost linear space.
1 .INTRODUCTION
In (1) Gliceria Godini introduced the concept almost linear space which is defined as A non empty set X together with two mappings s: XxX X and m:RxX X Where s(x ,y)=x +y and m(,
x) = x is said to be an almost linear space if it satisfies the following properties.
For every x, y, z X and for every , R
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x +y X ,
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(x + y) +z = x+(y + z) ,
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x +y = y + x ,
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There exists an element 0 X such that x+0=x ,
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1 x = x ,
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(x + y)= x+ y ,
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0 x =0 ,
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( x )=( )x ,ix) ( + )x= x + x for 0,0.
In (1 & 4) Gliceria Godini also introduced the concept normed almost linear space which is defined as an almost linear space X together with ||| . ||| : X R is said to be normed almost linear space if it satisfies the following properties
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||| x |||=0 if and only if x=0, ii) ||| x |||=II ||| x ||| ,
iii) ||| x-z ||||||x-y|||+|||y-z||| for every x,y X and R.
The concept of linear 2-normed space has been initially investigated by S. G hler(17) and has been extensively by Y.J.Cho, C.Diminnie, R.Freese and many other, which is defined as
a linear space X over R with dim>1 together with II .II is called Linear 2- normed space if II . II satisfy the following properties
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II x, y II>0 and II x , y II=0 if and only if x and y are linearly dependent,
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II x , y II = II y , x II,
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II x ,y II = II II x , y II, and
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II x , y+z II = II x , z II + II y ,z II for every x,y,z X and R.
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In (23) T.Markandeya naidu and Dr D.Bharathi introduced a new concept called 2-normed almost linear space and established some of the results of best approximation in 2-nomed almost linear space.In (22) S.Elumalai & R.Vijayaragavan established some of the results of best simultaneous approximation in linear space in the context of linear2-normed space. In this paper we extend some of the results of best simultaneous approximation on linear2- normed space in to 2-normed almost linear space.
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PRELIMINARIES
Definition 2.1. Let X be an almost linear space of dimension> 1 and
||| .|||: X x X R be a real valued function.
If ||| . ||| satisfy the following properties
i) ||| , |||=0 if and only if and are linearly dependent,
ii) ||| , ||| = ||| , |||,
iii) ||| a , ||| = IaI ||| , |||,
iv) ||| , – ||| ||| , – ||| + ||| ,
– ||| for every , , , X and a R.
then (X,|||.|||) is called 2-normed almost linear space.
Definition 2.2. Let X be a 2-normed almost linear space over the real field R and G a non empty subset of . For a bounded sub set A of X let us define
(A) = ||| x , a-g ||| for every x X\ 2.1
and
(A) = 0 G: ||| x , a-0 ||| =
(A) for every x X\. 2.2
(A) is called the chebyshev radius of A with respect to G and an element 0 (A) is called a best simultaneous approximation or chebyshev centre of A with respect to G.
Definition 2.3. When A is a singleton say A={a}, a X\ then (A) is the distance of a to G, denoted by dist(a,G) and defined by dist(a,G)= ||| x,a-g||| for every x
X\
2.3
and (A) is the set of all best approximations of a out of G denoted by
(a) and defined by
(a)={ 0G:|||x,a-0|||=dist(a,G),
for every x X\ }
2.4
It is well known that for any bounded subset A of X we have
(A)= (0())= ( )
(A)= (0())= ( )
Where 0() stands for the convex hull of A and stands for the closure of A.
Definition 2.4. Let X be a 2-normed almost linear spaces and G . We difine
(G) X
in the following way
(G) if for each g
such that the following conditions are hold
i) ||| x, a-g ||| = ||| x, -g ||| for each
2.5
ii) ||| x, a- ||| ||| x, – ||| for every x X\. 2.6
We have (G). If 1 2 then (2)
(1).
Definition 2.5. Let X be a 2-normed almost linear space. The set G is said to be proximinal if (a) is nonempty for each a X\ .
Theorem 3.1 Let ( X, ||| . ||| ) be a
2- normed almost linear space. Let G X and A be a bounded subset of X. Then the function (h,g) defined by sup ||| h, a-g |||,
h X\ , g G, a A is a continuous function on X.
Proof: For any a A and g , G we have
||| h, a-g ||| ||| h, a- ||| +
||| h, g ||| , h X\ . Then
||| h, a-g |||
{ ||| h, a- ||| + ||| h, g ||| }
a best simultaneous approximation g G to any given compact subset A of X.
Proof: Since A is compact there exist a constant t such that
||| a , b ||| t for all a A and b X. Now we define the subset H of G as G G(0,2t) then
inf. ||| b, a-h ||| =
||| b, a-h ||| , b X\ t Since h is compact the continuous function
(h,b) attains its minimum over H for some g
G.
which is the best simultaneous approximation to A.
Theorem 3.3 Let ( X, ||| . ||| ) be a
2- normed almost linear space and let G be a
convex subset of X and A X . If g, G are two best simultaneous approximations to A by elements of G. Then
= g + (1- ) ,0 1 is also best simultaneous approximation to A.
Proof: For x X\ ,
Now if ||| h, g ||| then (h,g) (h, ) +
||| x, a-
|||
By interchanging g and we obtain
= ||| x, a- g + (1- ) |||
(h, ) (h,g) + that implies
| (h,g) – (h, ) |<
=
||| x, (a-g) + (1- ) (a-) |||
That is (h,g) is continuous on X.
||| x, a-g ||| +
Theorem 3.2 Let ( X, ||| . ||| ) be a 2- normed almost linear space. Let G be a finite dimensional subspace of X. Then there exist
||| x, a-g ||| +
(1-) ||| x, a- |||
(1-) ||| x, a- |||
= (, ) + (1-) (, )
= (, )
3.1
(, ) = ||| x, a- |||
||| x, a- + ||| = k 3.4
2
Since A is compact there exist an element 0
such that
2
||| x, a- + |||
2
= ||| x, 0 – + |||
=k 3.5
. 3.3 ||| x, 0- ||| k and ||| x, 0-
||| k .
Then by strict convexity we have
||| x, 0-+0- ||| < 2 k
||| x, g- ||| 3.2
That is ||| x, 0
+ ||| < k
–
2
(, ) = ||| x, a- ||| This proves the result.
Theorem 3.4 Let (X,||| . |||) be a strictly convex 2-normed almost linear space. Let G be a finite dimensional ubspace of X. Then there exists one and only one best simultaneous approximation from the element G by any given compact subset A of X.
Proof : The existence of a best simultaneous approximation follows from the Theorem3.2.
Suppose and ( ) are best simultaneous approximations to A then for x X\ ,
||| x,a-g |||
This contradicts eq.3.5.
Hence the proof.
Theorem 3.5 Let G be a closed and convex subset of a uniformly convex
-
Banach space X.Then for any compact subset A of X there exist unique best approximation to A from the element of G.
Proof:
Let k= ||| x,a-g |||: x X\ and
be any sequence of elements in G Such that
||| x,a- ||| =k.
Also = ||| x,a- ||| ,m1 and x
X\ .
Then k which implies
=
||| x, a- |||
||| x, |||1 for a A 3.6
= ||| x, a- |||
=k 3.3
Now we consider 1 + =
2
+ +
2 +
Then by theorem (3.3),
Let = + .
,
+
+
2
is also
since G is convex, , G.
the best simultaneous approximation. That is
Hence ||| x,a-, |||k and |||
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-
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||| x,a- ||| .
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||| x,a-2 ||| and hence
1 = 2 .
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