Talk:Discretization

Latest comment: 9 months ago by 2600:1012:A023:7497:B104:8626:7D0C:3983 in topic Discretization and Interpolation

Error in section "Derivation"

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Hello, I am unsure but I think there is an error in the section to calculate the discretization of a continuous system. In the very last step in the process one simplifies   by using  . As far as I can tell this is not correct in general. Assume the system contains an integrator and the matrix   has therefore an eigenvalue at zero. Thus   is not regular and   does not exist. Nevertheless such systems exist and can for sure be discretized. I tried to get through it myself but did not yet succeed. Maybe someone here knows already the solution and is willing to document it here. Please let me know if I can help doing it. --Clupus (talk) 13:35, 20 February 2015 (UTC)Reply

Hello, I think I have provided some information that help "solving" the problem when   is singular. Best. --Sumo Hanoi (talk) 14:45, 2 February 2021 (UTC)Reply

Stray point-list

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Is the point list in the lead meant to be there? It doesn't seem like it is; it just appears completely without explanation or context. If it is meant to be there, we need to make it clear how it fits in. —Kri (talk) 12:47, 1 February 2016 (UTC)Reply

Explanation of difference between "discretization" and "quantization"

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Per WP:Technical, I think it is possibly too technical and laden with linguistics jargon, especially since the article is already quite technical (albeit in a different field). I tried to simplify the phrasing somewhat, but I think adding a sentence more explicitly explaining the difference in connotations might be helpful.

That said, I would need some help understanding the actual difference in connotation between the two terms. Cheers! Scientific29 (talk) 18:54, 13 January 2018 (UTC)Reply

– On the one hand I'd say that you exclusively discretize the continuous time into discrete time. On the other hand, in information theory, you can quantizate any quantity (say a measure of temperature or a voltage) over a finite number of bytes, the space-continuous evolving quantity is represented by a finite set of values ('00','01','10','11' with two bytes). see https://en.wikipedia.org/wiki/Quantization_(signal_processing) — Preceding unsigned comment added by NonLynSys (talkcontribs) 15:51, 22 January 2018 (UTC)Reply

Is Q really the power spectral density of the process noise?

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The units don't seem correct given the rest of the analysis, and the source in the textbook defines the state noise w differently, so I think there might've been an error in translating that source to this page. 128.244.42.15 (talk) 16:43, 9 March 2023 (UTC)Reply

Discretization and Interpolation

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Someone long ago asked in the talk page what would be the "opposite" process of discretization here, and not a single person bothered to provide a response. I want to provide one today: isn't interpolation a form of an inverse process?

Interpolation takes a set of discrete points and constructs a larger set of data, typically a continuous curve, that incorporates those points. Discretization takes a continuous entity and approximates it with a discrete collection of points. Sources that talk about interpolation and discretization together include The Boundary Element Method with Programming and Finite Elements: Theory and Algorithms.

I find it baffling. I do not see one term anywhere on the article for the other. Likewise, unless I go to really catch-all umbrella articles such as numerical analysis or continuous or discrete variable, it is very hard to find an article that contains both terms - relevant pages such as smoothing, curve fitting, or digital signal processing only contain one and not the other. (Same goes for their talk pages.) Therefore, I took the time to add each other in the respective "see also" sections. 2600:1012:A023:7497:B104:8626:7D0C:3983 (talk) 04:44, 20 November 2024 (UTC)Reply