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Does anyone know how to make an algorithm that transforms a binary search tree into an AVL tree, and yes transform it and not make another tree (so it will only be done using rotations) and not with the DSW technique... and in C. The tricky part here is that there is lots of cases since a binary search tree can be unbalanced in various ways and there being 4 types of rotations.
I believe the DSW technique does everything in-place (no memory allocations) if that's what you're looking for.
Otherwise, can you run the fix-up algorithm from AVL continually until the tree has no more changes? That's a technique used in a lot of algorithms that might apply here.
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I have some code in Haskell that is using pattern matching. However, I think that I can use folds and filters. For me this would be more readable, but I want to know it there is any advantage in terms of complexity.
The main reason to use higher-order functions instead of pattern matching and manual recursion is that it makes your code more concise and way easier to read.
Once you get the hang of them, you'll find that reading source code suddenly became way easier as those functions are amongst the most popular in all of Haskell.
It's also considered a good practice, and many people appreciate that you abstract your code.
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which one is best for parsing between Left corner Parsing algorithm and CYK parsing algorithm ? and Why ?
Generally speaking, CYK is a maximum-likelihood parse tree. It never gives you the best performance because of this reason and the fact that it ignores contextual information when assigns the probabilities. You need to modify it to consider more contexts, or integrate it into something else. For example, Left-Corner parser can use a CYK procedure, inside. So the answer to your question is, LC is more powerful than CYK, though it's computationally more expensive. Have a look at Mark Johnson's paper.
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What are applications where search techniques or more specifically planning techniques are used? I am most interested in examples in use.
I know that A* is used for path planning in Robotics, that planning is used in logistics (details would be great) but what other usages are there?
For Search in general Google, etc come to mind with their inverted indices. Again, where else is it used?
For planning examples, including logistics challenges, take a look at this list. Each use case comes with multiple datasets and a problem definition.
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I am wondering how you would code an image vectorization program, al la vectormagic.com? Where would you even begin and would it be possible to create in any web based programming languages?
Behind vectorization programs are complex algorithms (for basic outline look on quite nice paper depixelizing pixel art by guys at Microsoft).
Anyway, it's possible to write almost in any language, that can process images, but those complex algorithms are pretty system resources expensive. So web based languages are quite inappropriate for that type of task.
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What are the effects of multiplication of two different sound? An neither of them are constant, like two different songs, or one track of instrumental and one of vocals.
A simple Google search came up with this:
http://crca.ucsd.edu/~msp/techniques/v0.11/book-html/node77.html
Did you search for it at all?
But basically what happens is you end up creating an envelope where the second acts as a "coefficient" of sorts.
You also end up with a reduction of sound levels (since a decimal times a decimal is less both of them), so you'll need to amplify the signal a bit to retain volume.
The page I linked gives a lot more explanation and has a lot of the algebra needed to write up a code to implement it. Look there if you have any more questions.