# Context Dependent Composition Of Linear Operators

**URL:** <https://discourse.numenta.org/t/context-dependent-composition-of-linear-operators/12510>\
**Category:** Lounge\
**Created:** [July 22, 2026, 11:54pm UTC](https://discourse.numenta.org/t/context-dependent-composition-of-linear-operators/12510 "2026-07-22T23:54:09Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![SeanOConnor](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.numenta.org/seanoconnor/32/3441_2.png) [@SeanOConnor](https://discourse.numenta.org/u/SeanOConnor)\
**Post date:** [July 22, 2026, 11:54pm UTC](https://discourse.numenta.org/t/context-dependent-composition-of-linear-operators/12510/1 "2026-07-22T23:54:09Z")

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I made an effort to express in a comprehensible way some ideas I have about context dependent composition of linear operators:

[https://archive.org/details/context-dependent-composition-of-linear-operators](https://archive.org/details/context-dependent-composition-of-linear-operators)

The funny thing is it is 2026 yet there doesn’t seem to be any literature or papers about that directly related to ML.  
There are some switched matrix for control system type papers and a few things like that:  
[https://liberzon.csl.illinois.edu/teaching/Liberzon-LectureNotes.pdf](https://liberzon.csl.illinois.edu/teaching/Liberzon-LectureNotes.pdf)

That would make even simple switched linear systems interesting for say robotic motion control.