https://hackerpaper.kaipfister.de/p/1904.02539/Collected HN comments and submissions linking this paper.enMon, 02 Nov 2026 11:16:22 GMThttps://news.ycombinator.com/item?id=48436672urn:hackerpapers:submission:1904.02539:48436672Sun, 07 Jun 2026 17:01:34 GMT<p>An introduction to functional analysis for science and engineering</p><p></p><p>123 points; 17 discussion replies on HN. <a href="https://hackerpaper.kaipfister.de/p/1904.02539/">Paper and source history</a>. A submission is not an endorsement.</p>math.FAhttps://news.ycombinator.com/item?id=36927167urn:hackerpapers:mention:1904.02539:36927167Sun, 30 Jul 2023 02:23:34 GMT<p>I wish I could upvote this twice. This is the best basic introduction to concepts in functional analysis that I&#x27;ve seen. Another great overview that goes deeper into the math is [1]. Another fantastic application that the website doesn&#x27;t mention is the composition / Koopman operator. In control theory (e.g. autonomous drones, cars, robot arms, etc.), most real-world systems are described by nonlinear dynamics which are very difficult to work with (e.g. safety/stability guarantees, optimizing over forward horizons using NMPC, state estimation, etc.) The Koopman operator however gives a…</p><p><a href="https://hackerpaper.kaipfister.de/p/1904.02539/">Paper and discussion history</a>. A mention is not an endorsement.</p>math.FA