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  2. LCP array - Wikipedia

    en.wikipedia.org/wiki/LCP_array

    Likewise, the LCP of A[2] = ab and A[3] = abaab is ab, so H[3] = 2. Augmenting the suffix array with the LCP array allows one to efficiently simulate top-down and bottom-up traversals of the suffix tree , [ 1 ] [ 2 ] speeds up pattern matching on the suffix array [ 3 ] and is a prerequisite for compressed suffix trees.

  3. Min-entropy - Wikipedia

    en.wikipedia.org/wiki/Min-entropy

    The conditional entropy measures the average uncertainty Bob has about Alice's state upon sampling from his own system. The min-entropy can be interpreted as the distance of a state from a maximally entangled state. This concept is useful in quantum cryptography, in the context of privacy amplification (See for example [1]).

  4. Entropy (information theory) - Wikipedia

    en.wikipedia.org/wiki/Entropy_(information_theory)

    The first 128 symbols of the Fibonacci sequence has an entropy of approximately 7 bits/symbol, but the sequence can be expressed using a formula [F(n) = F(n−1) + F(n−2) for n = 3, 4, 5, ..., F(1) =1, F(2) = 1] and this formula has a much lower entropy and applies to any length of the Fibonacci sequence.

  5. TOPSIS - Wikipedia

    en.wikipedia.org/wiki/TOPSIS

    The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is a multi-criteria decision analysis method, which was originally developed by Ching-Lai Hwang and Yoon in 1981 [1] with further developments by Yoon in 1987, [2] and Hwang, Lai and Liu in 1993. [3]

  6. Levenshtein distance - Wikipedia

    en.wikipedia.org/wiki/Levenshtein_distance

    Edit distance matrix for two words using cost of substitution as 1 and cost of deletion or insertion as 0.5. For example, the Levenshtein distance between "kitten" and "sitting" is 3, since the following 3 edits change one into the other, and there is no way to do it with fewer than 3 edits: kitten → sitten (substitution of "s" for "k"),

  7. Rényi entropy - Wikipedia

    en.wikipedia.org/wiki/Rényi_entropy

    In information theory, the Rényi entropy is a quantity that generalizes various notions of entropy, including Hartley entropy, Shannon entropy, collision entropy, and min-entropy. The Rényi entropy is named after Alfréd Rényi , who looked for the most general way to quantify information while preserving additivity for independent events.

  8. Orders of magnitude (entropy) - Wikipedia

    en.wikipedia.org/wiki/Orders_of_magnitude_(entropy)

    Standard entropy of 1 mole of graphite [2] 10 33: ≈ 10 35 J⋅K −1: Entropy of the Sun (given as ≈ 10 42 erg⋅K −1 in Bekenstein (1973)) [3] 10 54: 1.5 × 10 54 J⋅K −1: Entropy of a black hole of one solar mass (given as ≈ 10 60 erg⋅K −1 in Bekenstein (1973)) [3] 10 81: 4.3 × 10 81 J⋅K −1: One estimate of the theoretical ...

  9. Gestalt pattern matching - Wikipedia

    en.wikipedia.org/wiki/Gestalt_Pattern_Matching

    The similarity of two strings and is determined by this formula: twice the number of matching characters divided by the total number of characters of both strings. The matching characters are defined as some longest common substring [3] plus recursively the number of matching characters in the non-matching regions on both sides of the longest common substring: [2] [4]