Notes, We Review Useful Concepts in Convexity and Normed Spaces
Mastermath, Spring 2019 Lecturers: D. Dadush, J. Briet Geometric Functional Analysis Lecture 0 Scribe: D. Dadush Review of Convexity and Normed Spaces In these notes, we review useful concepts in convexity and normed spaces. As a warning, many of the statements made here will not be proved. For detailed proofs, one is recommended to look up reference books in functional and convex analysis. The intent here is for these notes to serve as a reference for the basic language for the course. The reader may thus skim the material upon first reading, and then reread more carefully later during the course if the relevant concepts remain unclear. 1 Basic Convexity In this section, we will focus on convexity theorems in a finite dimensional real vector space, which will identify with Rn or subspaces theoreof. For vectors x, y 2 Rn, we define the standard T n n inner product hx, yi := x y = ∑i=1 xiyi. For two sets A, B ⊆ R and scalars c, d 2 R, we define the Minkowski sum cA + dB = fca + db : a 2 A, b 2 Bg. A convex set K ⊆ Rn is a set for which the line segment between any two points is in the set, or formally for which 8x, y 2 K, l 2 [0, 1], lx + (1 − l)y 2 K. A useful equivalent definition is that a non-empty set K is convex if 8a, b ≥ 0, aK + bK = (a + b)K. If K = −K, K is said to be symmetric. If K is compact with non-empty interior, then K is a convex body.
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