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Timeline for Impulse signal detection

Current License: CC BY-SA 4.0

23 events
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Oct 14 at 23:07 vote accept Nate River
Oct 15 at 8:55
S Oct 14 at 23:05 history bounty ended Nate River
S Oct 14 at 23:05 history notice removed Nate River
Oct 14 at 23:04 vote accept Nate River
Oct 14 at 23:07
Oct 14 at 21:49 answer added Mateusz Kwaśnicki timeline score: 2
Oct 8 at 5:48 history edited Nate River CC BY-SA 4.0
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Oct 8 at 5:43 history edited Nate River CC BY-SA 4.0
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S Oct 8 at 5:38 history bounty started Nate River
S Oct 8 at 5:38 history notice added Nate River Draw attention
Oct 8 at 5:37 history edited Nate River CC BY-SA 4.0
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Oct 8 at 5:34 history undeleted Nate River
Sep 24 at 18:22 history deleted Nate River via Vote
Sep 24 at 18:21 history edited Nate River CC BY-SA 4.0
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Aug 21 at 14:19 history edited Nate River CC BY-SA 4.0
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Aug 20 at 11:02 comment added mike I think the drift is always < A and is zero as soon as t > 2. The expected value of Y can’t be bigger than 2A, whereas you have it being about proportional to t for large t.
Aug 20 at 1:25 comment added Nate River … sorry typo, it is $$Y_t = A[\delta ([t] - 1)_+ +\max(\{t\}, X) + \max(\{t\}, X + \delta - 1) - X] + \sigma W_t.$$
Aug 20 at 1:19 comment added Nate River Although I don’t think the explicit formula is of much help anyway to answer the problem.
Aug 20 at 1:18 comment added Nate River I believe explicitly we have $$Y_t = A\delta ([t] - 1)_+ + \max(\{t\}, X) + \max(\{t\}, X + \delta - 1) - X + \sigma W_t.$$ Which is messier than I expected! Maybe there is a nicer way to write it.
Aug 20 at 1:00 comment added Nate River @mike I don’t think that holds, perhaps something in the problem set up is not clear?
Aug 19 at 22:01 comment added mike As soon as t > 2 $Y_t = A \delta + \sigma W_t$ so I don’t think you get any information about X after that time.
Aug 19 at 20:59 history edited Nate River CC BY-SA 4.0
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Aug 19 at 20:50 history edited Nate River CC BY-SA 4.0
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Aug 19 at 20:43 history asked Nate River CC BY-SA 4.0