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Some Inequalities in Valued Inner Product Space S International Journal of Pure and Applied Mathematics Volume 86 No. 6 2013, 983-992 ISSN: 1311-8080 (printed version); ISSN: 1314-3395 (on-line version) url: http://www.ijpam.eu AP doi: http://dx.doi.org/10.12732/ijpam.v86i6.11 ijpam.eu SOME INEQUALITIES IN VALUED INNER PRODUCT SPACE S. Vijayabalaji1, J. Parthiban2 1Department of Mathematics University College of Engineering (A Constituent College of Anna University, Chennai) Pantruti, 607 106. Tamilnadu, INDIA 2Department of Mathematics Kurinji College of Engineering and Technology Tiruchirappalli Dist, 621 307, Tamilnadu, INDIA Abstract: Algebraic Number theory involves using techniques from Algebra and finite group theory to gain deeper understanding of number fields. Mo- tivated by the theory of valued n-inner product over a valued field that was introduced by us; the main objective of this paper is to derive some interest- ing inequalities on valued n-inner product space combined with the theory of equations. AMS Subject Classification: 26D15, 39B62 Key Words: valued inner product, arithmetic mean of vectors 1. Introduction Functional analysis is a branch of mathematical analysis, the core of which is formed by the study of linear spaces endowed with some kind of limit-related structure (e.g. inner product)[10]. The concept of 2-inner product spaces was first introduced by Diminnie, Gahler and White [4, 5]. A systematic presentation of the recent results related to the theory of 2- inner product spaces as well as an extensive list of the related references can c 2013 Academic Publications, Ltd. Received: May 9, 2013 url: www.acadpubl.eu 984 S. Vijayabalaji, J. Parthiban be found in the book [2]. Misiak [9] generalize the 2-inner product into n 2. ≥ Recent results about n-inner product space can be viewed in [3]. In Mathematics, the theory of equations comprises a major part of tradi- tional algebra. An inequality is a relation that holds between two values when they are different [6, 7]. There are many inequalities between means. Now we are trying to discuss some new ones based upon valued inner product space. 2. Preliminaries Definition 2.1. (see [10]) Let X be a real linear space over R. A real valued function ( , ) on X X satisfying the following properties: • • × (1) (x, x) 0. ≥ (2) (x, y) = (y, x) (3) (αx+βy, z) = α(x, z)+β(y, z), for any α, β R( set of real numbers) is ∈ called an inner product on X and the pair (X, ( , )) is called an inner product • • space. Example 2.2. (see [10]) (u, v) = u1v1 + u2v2, where u = (u1, u2) and 2 v = (v1, v2) in R . Theorem 2.3. (Cauchy-Schwarz inequality, see [10]) For any vectors u, v ∈ X, (u, v) u v . | | ≤ k k k k Theorem 2.4. (Triangle inequality, see [10]) For any vectors u, v X, ∈ u + v u + v . k k ≤ k k k k Definition 2.5. (see [11]) A valuation [ ] on a field K is a function with • values in R 0 satisfying the following axioms: ≥ (1) [x] > 0. (2) [x]=0 if and only if x = 0. (3) [xy] = [x][y] . (4) [x] 1 implies [1 + x] C for some constant C 1. If (4) is satisfied ≤ ≤ ≥ for C = 2,then [ ] satisfies the triangle inequality, • (4a)[x + y] [x] + [y] forallx, y K. ≤ ∈ SOME INEQUALITIES IN VALUED INNER PRODUCT SPACE 985 Example 2.6. (see [12]) The real valuation on the rational Q is the absolute value on the real numbers, defined by [x] = x, ifx 0 and x, ifx < 0. ≥ − 3. Valued Inner Product Space Definition 3.1. Let X be a real linear space over R. A real valued function [ , ] on X X satisfying the following properties: • • × (1) [x, x] 0. ≥ (2) [x, y] = [y, x] (3) [αx + βy, z] = [α][x, z] + [β][y, z], for any α, β R( set of real numbers) ∈ is called an valued inner product on X and the pair [(X, [ , ]) is called an • • valued inner product space. Theorem 3.2. (Arithmetic Mean of Inner Product of Vectors as First Kind) Let (X, [ , ]) be a valued inner product space. Then for any non zero • • vectors in X whose elements are greater than or equal to 1, then [u , u ] + [v , v ] [u , v ] + [u , v ] 1 2 1 2 1 1 2 2 , 2 ≥ 2 if u < v and u < v or u > v and u > v . k 1k k 2k k 2k k 1k k 1k k 2k k 2k k 1k Proof. We have [u1, u2] + [v1, v2] [u1, v1] + [u2, v2] 2 − 2 1 1 ( u u + v v ) ( u v + u v ) (by 2.3) ≤ 2 k 1k k 2k k 1k k 2k − 2 k 1k k 1k k 2k k 2k 1 = u ( u v ) v ( u v ) 2 {k 1k k 2k − k 1k − k 2k k 2k − k 1k } 1 = ( u v )( u v ) 0. 2 { k 1k − k 2k k 2k − k 1k } ≥ Therefore [u1,u2]+[v1,v2] [u1,v1]+[u2,v2] , if u < v and u < v or 2 ≥ 2 k 1k k 2k k 2k k 1k u > v and u > v . k 1k k 2k k 2k k 1k Theorem 3.3. (Arithmetic Mean of Inner Product of Vectors as Second Kind) Let (X, [ , ]) be a valued inner product space. Then for any non zero • • vectors in X whose elements are greater than or equal to 1, then [u , v ] + [u , v ] [u , u ] + [v , v ] 1 1 2 2 1 2 1 2 , 2 ≥ 2 986 S. Vijayabalaji, J. Parthiban if u < v and v < u or u > v and v > u . k 1k k 2k k 1k k 2k k 1k k 2k k 1k k 2k Proof. [u1, v1] + [u2, v2] [u1, u2] + [v1, v2] 2 − 2 1 1 ( u v + u v ) ( u u + v v ) (by 2.3) ≤ 2 k 1k k 1k k 2k k 2k − 2 k 1k k 2k k 1k k 2k 1 = u ( v u ) v ( v u ) 2 {k 1k k 1k − k 2k − k 2k k 1k − k 2k } 1 = ( u v )( v u ) 0. 2 { k 1k − k 2k k 1k − k 2k } ≥ Therefore [u1,v1]+[u2,v2] [u1,u2]+[v1,v2] ,if u < v and v < u or 2 ≥ 2 k 1k k 2k k 1k k 2k u > v and v > u . k 1k k 2k k 1k k 2k Example 3.4. Let (X, [ , ]) be a valued inner product space. • • u1 = (1, 2); u2 = (3, 4).[u1, u2] = 1(3) + 2(4) = 11, v1 = (5, 6); v2 = (7, 8).[v1, v2] = 5(7) + 6(8) = 83, [u , u ] + [v , v ] 94 1 2 1 2 = = 47, 2 2 u1 = (1, 2); v1 = (5, 6).[u1, v1] = 1(5) + 2(6) = 17, u2 = (3, 4); v2 = (7, 8).[u2, v2] = 3(7) + 4(8) = 53, [u , u ] + [v , v ] 70 1 2 1 2 = = 35. 2 2 Therefore [u1,u2]+[v1,v2] [u1,v1]+[u2,v2] . 2 ≥ 2 Since u = √12 + 22 = √5; u = √32 + 42 = √25 and v = √52 + 62 = k 1k k 2k k 1k √61; v = √72 + 82 = √113, because u < v and u < v . k 2k k 1k k 2k k 2k k 1k Example 3.5. Let (X, [ , ]) be a valued inner product space. • • u1 = (1, 2); u2 = (5, 6).[u1, u2] = 1(5) + 2(6) = 17, v1 = (3, 4); v2 = (7, 8).[v1, v2] = 3(7) + 4(8) = 53, [u , u ] + [v , v ] 70 1 2 1 2 = = 35, 2 2 u1 = (1, 2); v1 = (3, 4).[u1, v1] = 1(3) + 2(4) = 11, u2 = (5, 6); v2 = (7, 8).[u2, v2] = 5(7) + 6(8) = 83, SOME INEQUALITIES IN VALUED INNER PRODUCT SPACE 987 [u , u ] + [v , v ] 94 1 2 1 2 = = 47. 2 2 [u1,v1]+[u2,v2] [u1,u2]+[v1,v2] Therefore 2 2 . 2 ≥2 2 2 Since u1 = √1 + 2 = √5; u2 = √5 + 6 = √61, and v1 = 2 2 k k 2 2 k k k k √3 + 4 = √25; v2 = √7 + 8 = √113 because u1 < v2 and v1 < u . k k k k k k k k k 2k Theorem 3.6. Cauchy-Schwarz inequality can be derived from the Arith- metic mean of inner products as first kind. Proof. Arithmetic Mean of Inner Product of Vectors as First Kind [u , v ] + [u , v ] [u , u ] + [v , v ] 1 1 2 2 1 2 1 2 , 2 ≤ 2 if u < v and u < v or u > v and u > v . k 1k k 2k k 2k k 1k k 1k k 2k k 2k k 1k We have Geometric mean Arithmetic mean. ≤ [u , v ][u , v ] [u , u ][v , v ] p 1 1 2 2 ≤ p 1 2 1 2 Squaring and put u1 = u2 and v1 = v2. Then [u , v ][u , v ] [u , u ][v , v ]. 1 1 1 1 ≤ 1 1 1 1 Then [u , v ]2 u 2 v 2 . 1 1 ≤ k 1k k 1k Taking positive square root, we get [u , v ] u v . | 1 1 | ≤ k 1k k 1k Theorem 3.7. Cauchy-Schwarz inequality can be derived from the Arith- metic mean of inner products as second kind. Proof. Arithmetic mean of Inner Product of Vectors as Second kind: [u , u ] + [v , v ] [u , v ] + [u , v ] 1 2 1 2 1 1 2 2 , 2 ≤ 2 if u < v and v < u or u > v and v > u . k 1k k 2k k 1k k 2k k 1k k 2k k 1k k 2k We have Geometric mean Arithmetic mean.
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