vault backup: 2024-10-02 10:31:54
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1 Daily Notes/2024/10 October/2024-10-02.md
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1 Daily Notes/2024/10 October/2024-10-02.md
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---
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date: 2024-10-02
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tags:
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---
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# Yesterday | Tomorrow
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<< [[2024-10-01]] | [[2024-10-03 ]] >>
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# This Week's Weekly Note
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[[ Weekly Note 2024-09-25]]
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# Tasks for today
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## Due
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```dataview
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task
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where
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due <= date(this.date)
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and due
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and !completed
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and status != "-"
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sort due asc
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group by file.folder
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```
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## Scheduled
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```dataview
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task
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where
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scheduled
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and scheduled <= date(this.date)
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and !completed
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and status != "-"
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sort due asc
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group by file.folder
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```
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## Completed
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```dataview
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task
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where
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completed
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and completion = date(this.date)
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sort due asc
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group by file.folder
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```
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# Calendar Tasks
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1 Daily Notes/2024/9 September/2024-10-02.md
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1 Daily Notes/2024/9 September/2024-10-02.md
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---
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date: <% tp.file.title %>
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tags:
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---
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# Yesterday | Tomorrow
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<< [[<%*if (tp.date.weekday("YYYY-MM-DD", 1, tp.file.title, "YYYY-MM-DD") == tp.file.title) { tR += tp.date.now("YYYY-MM-DD", -3, tp.file.title, "YYYY-MM-DD"); } else { tR += tp.date.now("YYYY-MM-DD", -1, tp.file.title, "YYYY-MM-DD");} %>]] | [[<%*if (tp.date.weekday("YYYY-MM-DD", 5, tp.file.title, "YYYY-MM-DD") == tp.file.title) { tR += tp.date.now("YYYY-MM-DD", +3, tp.file.title, "YYYY-MM-DD"); } else { tR += tp.date.now("YYYY-MM-DD", +1, tp.file.title, "YYYY-MM-DD");} %> ]] >>
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# This Week's Weekly Note
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[[ Weekly Note <%*if (tp.date.weekday("YYYY-MM-DD", 3, tp.file.title, "YYYY-MM-DD") >= tp.file.title) {tR += tp.date.weekday("YYYY-MM-DD", -4, tp.file.title, "YYYY-MM-DD"); } else {tR += tp.date.weekday("YYYY-MM-DD", 3, tp.file.title, "YYYY-MM-DD"); } %>]]
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# Tasks for today
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## Due
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```dataview
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task
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where
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due <= date(this.date)
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and due
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and !completed
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and status != "-"
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sort due asc
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group by file.folder
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```
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## Scheduled
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```dataview
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task
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where
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scheduled
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and scheduled <= date(this.date)
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and !completed
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and status != "-"
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sort due asc
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group by file.folder
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```
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## Completed
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```dataview
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task
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where
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completed
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and completion = date(this.date)
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sort due asc
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group by file.folder
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```
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# Calendar Tasks
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- Goals and Outcomes [startTime:: 10:00] [endTime:: 11:30]
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@ -89,4 +89,4 @@ If this research is successful, this diffusion model will accomplish three main
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**Outcome 3:** Generate time and frequency domain responses based on training data of example systems. The diffusion model is like any other machine learning model: it requires training data. For this diffusion model, we will create training data of physically realizable plants dynamics. This training data will teach the diffusion model to create realistic time and frequency responses as novel samples.
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Perturbing a nominal plant to establish robustness is not a new technique. Robust control can find the set of plants with which a controller remains performant. Finding this set is a well understood problem, and can be straightforward. An engineer can use this set of plants to say how robust a nominal controller is to perturbation, and make guarantees about
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Perturbing a nominal plant to establish robustness is not a new technique. Robust control can find the set of plants with which a controller remains performant. Finding this set is a well understood problem, and can be straightforward. An engineer can use this set of plants to guarantee how robust a nominal controller is to perturbation. But, engineer cannot use this set to make guarantees about a implemented controller. Implementation of control laws requires lowering the abstraction level from the model of a controller used in robust control and must be verified for robustness independently.
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