# Monotonic smoothing of noisy data

**URL:** <https://discourse.julialang.org/t/monotonic-smoothing-of-noisy-data/93184>\
**Category:** Signal and Image Processing\
**Tags:** algorithm, convex-optimization, smoothing, splines\
**Created:** [January 18, 2023, 11:02pm UTC](https://discourse.julialang.org/t/monotonic-smoothing-of-noisy-data/93184 "2023-01-18T23:02:28Z")\
**Posts on this page:** 1\
**Showing post:** 25

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**Author:** ![RoyiAvital](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/royiavital/32/571_2.png) [@RoyiAvital](https://discourse.julialang.org/u/RoyiAvital)\
**Post date:** [May 17, 2025, 3:19pm UTC](https://discourse.julialang.org/t/monotonic-smoothing-of-noisy-data/93184/25 "2025-05-17T15:19:48Z")

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Similar ideas to what is described here are achieved by [P Splines](https://psplines.bitbucket.io) and [Shape Constrained Additive Models](https://link.springer.com/article/10.1007/s11222-013-9448-7).

Originally shared by @slwu89 at [How to embed expert knowledge /constraints in ML training? - #7 by slwu89](https://discourse.julialang.org/t/how-to-embed-expert-knowledge-constraints-in-ml-training/129025/7).

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