A geometric form of the Hahn-Banach extension theorem for L0 linear functions and the Goldstine-Weston theorem in random normed modules

Mathematics – Functional Analysis

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

14 pages

Scientific paper

In this paper, we present a geometric form of the Hahn-Banach extension theorem for $L^{0}-$linear functions and prove that the geometric form is equivalent to the analytic form of the Hahn-Banach extension theorem. Further, we use the geometric form to give a new proof of a known basic strict separation theorem in random locally convex modules. Finally, using the basic strict separation theorem we establish the Goldstine-Weston theorem in random normed modules under the two kinds of topologies----the $(\epsilon,\lambda)-$topology and the locally $L^{0}-$convex topology, and also provide a counterexample showing that the Goldstine-Weston theorem under the locally $L^{0}-$convex topology can only hold for random normed modules with the countable concatenation property.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

A geometric form of the Hahn-Banach extension theorem for L0 linear functions and the Goldstine-Weston theorem in random normed modules does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with A geometric form of the Hahn-Banach extension theorem for L0 linear functions and the Goldstine-Weston theorem in random normed modules, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and A geometric form of the Hahn-Banach extension theorem for L0 linear functions and the Goldstine-Weston theorem in random normed modules will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-707132

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.