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Boundary limits of a normalized finite convex generator exist
Statement
Let be convex and satisfy . Then is continuous on , and both extended-real limits exist in ; neither limit is .
Facts & Assumptions
Given: A finite convex function with .
Convex and strictly convex functions on Euclidean convex sets: convexity means for positive and .
The real numbers, The reals form a totally ordered field, The Cauchy-sequence reals have the least-upper-bound property, and Complete ordered field (least-upper-bound property): is the Cauchy-sequence real field with the least-upper-bound property, so every nonempty set of real numbers bounded above has a real supremum and every nonempty set bounded below has a real infimum.
Proof
Fix and let , , , and . For , write . If , convexity at between , at between , at between , and at between gives by rearranging the four two-point inequalities in [F1]. All these endpoint slopes are finite. Thus with , one has for , including .
Fix and set for . If , then is a convex combination of and ; [F1] gives . Rearranging yields . Also is a convex combination of and , so another application of [F1] gives , a finite upper bound. Therefore is either real or ; the infimum property from [F2] gives as (if is finite, approximate it within any ; if , use any real lower target). Since , its limit is if is finite and if . Thus exists and is not .
Given , choose . If , then , and step 1.1 gives . This is continuity at the arbitrary , so is continuous on .
For , put . If , then is a convex combination of and . By [F1] and , this gives . Hence is nondecreasing on and bounded below on by the finite value . By the supremum property in [F2], its limit is the real supremum if it is bounded above, and is otherwise: for finite , values eventually lie between and ; when unbounded, they eventually exceed any prescribed real number. Since and , this quotient tends to if is finite; if , the factor is at least for and the quotient tends to . Thus exists and is not .
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Used by
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Sources
- Yury Polyanskiy and Yihong Wu, Information Theory: From Coding to Learning, Chapter 7, §7.1 (standard reference, not scraped)
- Igal Sason and Sergio Verdú, f-Divergence Inequalities, §II-B, equations (35)–(39) (standard reference, not scraped)