I've got the following set of data :
As you can see, I've got two plateau at 1987 and 3757. The problem is I can't find a good algorithm in order to extract them.
I've already tried this algo, without any success.
Any help will be welcomed.
Regards
Related
Problem:
Atmospheric turbulation problem occurs due to foze,temperature variations, looking at to long distances with camera. There is a problem sample below
Example:
What I tried so far:
When I searched, I found this article which suggests to use
Dual Tree Complex Wavelet Transform(DTCWT). I followed through the
article and it seems like a good way to apply. Then I found this
implementation of the article in python code. I have run it and
seen the results but not as expected well.
I have simply took the average of some frames(let say 10), and get a result. I did it because the shaking pixels will be mostly true ones at any time. My results seems not bad after averaging.
What I need:
After searching much I am sure that this solution needs more frame to get one good frame. To do that I need a good image fusion algorithm.
I kindly request that you can suggest me any algorithm or any approaches I can try and go throuh to solve problem.
Note: I am familiar with OpenCV and C++ so priority is on these.
I'm currently trying to build a music generator. In order to improve my deal with patterns in music, I have read this article, which states that "This algorithm (exon-chaining algorithm) can be modified to accommodate the pattern selection problem by replacing the weight of an interval with its duration".(page 9).
However, I'm having trouble understanding the meaning of the exon-chaining problem. I have looked for this problem in many different presentations and articles but still couldn't find satisfying information. I would really appreciate it if someone could explain it to me.
Thanks in advance.
I recently encountered a problem which goes
like this :
A student is given N number of
questions and T time in total. Each question
requires different time to complete and carries
different marks. The problem asks to find the
maximum marks the student can get by
attempting some of the N questions within T
time (Assuming if a question is attempted, it
must be fully completed,no partial attempt of a
question is allowed).
I tried to solve the problem by computing all
possible combinations of questions which takes
<= T seconds to complete but soon found out
its ineffective for large datasets.
How can I optimise my solution? Is there any
alternative solution available?
It looks like a variant of the well known Knapsack Problem
A friend asked me to do a program for him :
The program needed is for resolving a "puzzle game" composed by 10 torches, arranged like a 2x5 (or 5x2) matrix. The goal is to resolve the puzzle by having all torches alight, but here is the difficulty : when you change the state of a torch, adjacent torches have their state changed too (only adjacent, not the ones in diagonals).
So it is like I have a specific matrix which contain binary elements that I need to resolve by turning all elements to True (or "alight"), but elements are linked with adjacent elements like an undirected structured homogeneous graph ("mesh" graph).
Here is some picture to figure how the puzzle works :
Exemple of initial pattern
Puzzle Mechanics
Here is where I need some help/advice/clue :
First, how can I solve this kind of puzzle in a clever way (already done it by trying all possibilities, but when I need more than 5 "step", it takes really too much time to calculate), using maths.
Then, which programming langage should I use ? Which one would fit the best to this kind of processing ? (I want to do an interface where user enter an initial pattern, then the program search the solution and give the step to resolve it by giving coords and eventualy all steps in pictures on the interface. I will surely post it on a forum for my friend and his game mates.)
I'm still searching, but have not found anything that could help me to effectively resolve that kind of puzzle yet.
Thanks a lot for any help and contribution.
PS : sorry for any bad use of english.
You can solved this problem by using BruteForce approach.
There are only 10 torches and you just need to press each torch exactly once. So it will be 2^10 = 1024 combination.
For the programming language you can use: Python, C/C++, Java or C#.
Any programming language can solved this problem.
problem: visiting as many places as possible within the given time and come back to starting point.
I searched the internet and could not find any tutorial or implementation of any algorithm for that problem. Mostly research papers came out.
So, hoping people point out useful sources, then I could pick one and solve my problem.
thanks.
I find out that "Clarke-Wright algorithm" solves VRP and TSP is a special case of VRP.
Maybe that is what I need.
anyone correct me if I am wrong.