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* The Class QuickSort. * @param <t> the generic type public class QuickSort<t extends Comparable<T>> { * Sort.
Zen in the art of IT: The simple Big-O Notation Post.
Some time ago, I presented a piece on compressing voxel worlds and I just realized that I discussed different types of variable length codes quite a few times, but that I never took the time to present you the basic method of Huffman coding! The problem of finding an optimal variable length code is to find an uniquely decodable binary code (that is, a code using only 0 and 1 for which there exists only one way of decoding a message) that encodes each symbol in a number of bits that is proportional to its probability of occurrence. A first strategy was devised by Robert Fano , Huffman’s teacher at one point. The so-called Shannon-Fano code is a top-down approach to solving the problem but it was shown to be suboptimal. The code proposed by David Huffman solves the problem optimally by taking exactly the opposite approach, that is, building the code bottom-up.
Huffman Codes « Harder, Better, Faster, Stronger
Yes, I realize that after reading the title of this post, 99% of potential readers just kept scrolling. So to the few of you who clicked on it, welcome! Don’t worry, this won’t take long.
Understanding the Fourier transform » #AltDevBlogADay
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