Numerical range and orthogonality in normed spaces

Numerical Range and Orthogonality in Normed Spaces

Introducing the concept of the normalized duality mapping on normed linear space and normed algebra, we extend the usual definitions of the numerical range from one operator to two operators. In this note we study the convexity of these types of numerical ranges in normed algebras and linear spaces. We establish some Birkhoff-James orthogonality results in terms of the algebra numerical range V...

Stability of linear predictors and numerical range of shift operators in normed spaces

The zeros of predictor polynomials are shown to belong to the numerical range of a shift operator associated with the particular prediction problem under consideration. The numerical range consists of the classical field of values of the shift operator when the setting is Hilbert space, but a new definition is necessary when the setting is a general normed space. It is shown that a predictor po...

Remotality and proximinality in normed linear spaces

In this paper, we consider the concepts farthest points and nearest points in normed linear spaces, We obtain a necessary and coecient conditions for proximinal, Chebyshev, remotal and uniquely remotal subsets in normed linear spaces. Also, we consider -remotality, -proximinality, coproximinality and co-remotality.

-approximation in normed spaces

Inner Product Spaces and Orthogonality

1 Dot product of R The inner product or dot product of R is a function 〈 , 〉 defined by 〈u,v〉 = a1b1 + a2b2 + · · ·+ anbn for u = [a1, a2, . . . , an] , v = [b1, b2, . . . , bn] ∈ R. The inner product 〈 , 〉 satisfies the following properties: (1) Linearity: 〈au + bv,w〉 = a〈u,w〉+ b〈v,w〉. (2) Symmetric Property: 〈u,v〉 = 〈v,u〉. (3) Positive Definite Property: For any u ∈ V , 〈u,u〉 ≥ 0; and 〈u,u〉 =...