An extension of a best approximation theorem.

Carbone, A.

Displaying similar documents to “An extension of a best approximation theorem.”

Extensions of best approximation and coincidence theorems.

Park, Sehie (1997)

International Journal of Mathematics and Mathematical Sciences

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The best approximation and an extension of a fixed point theorem of F. E. Browder.

Sehgal, V.M., Singh, S.P. (1995)

International Journal of Mathematics and Mathematical Sciences

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Best coapproximation in metric spaces.

Narang, T.D. (1992)

Publications de l'Institut Mathématique. Nouvelle Série

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An application of KKM-map principle.

Carbone, A. (1992)

International Journal of Mathematics and Mathematical Sciences

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On almost coincidence points in generalized convex spaces.

Mitrović, Zoran D. (2006)

Fixed Point Theory and Applications [electronic only]

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$M$ -convexity and best approximation.

Chatterjee, Dipak (1980)

Publications de l'Institut Mathématique. Nouvelle Série

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Coincidence theorems for set-valued maps with g-kkm property on generalized convex space

Lai-Jiu Lin, Ching-Jung Ko, Sehie Park (1998)

Discussiones Mathematicae, Differential Inclusions, Control and Optimization

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In this paper, a set-valued mapping with G-KKM property is defined and a generalization of minimax theorem for set-valued maps with G-KKM property on generalized convex space is established. As a consequence of this results we verify the coincidence theorem for set-valued maps with G-KKM property on G-convex space. Finally, we apply our results to the best approximation problem and fixed point problem.

Best approximation and strict convexity of metric spaces

Tulsi Dass Narang (1981)

Archivum Mathematicum

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On best simultaneous approximation.

Naidu, S.V.R. (1992)

Publications de l'Institut Mathématique. Nouvelle Série

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Metrically convex functions in normed spaces

Stanisław Kryński (1993)

Studia Mathematica

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Properties of metrically convex functions in normed spaces (of any dimension) are considered. The main result, Theorem 4.2, gives necessary and sufficient conditions for a function to be metrically convex, expressed in terms of the classical convexity theory.