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  2. List of software to detect low complexity regions in proteins

    en.wikipedia.org/wiki/List_of_software_to_detect...

    It calculates complexity using reciprocal complexity. no [7] ScanCom 2003 on request Calculates the compositional complexity using the linguistic complexity measure. no [8] CARD 2005 on request Based on the complexity analysis of subsequences delimited by pairs of identical, repeating subsequences. no [9] BIAS: 2006 downloadable / web

  3. Sample entropy - Wikipedia

    en.wikipedia.org/wiki/Sample_entropy

    Like approximate entropy (ApEn), Sample entropy (SampEn) is a measure of complexity. [1] But it does not include self-similar patterns as ApEn does. For a given embedding dimension, tolerance and number of data points, SampEn is the negative natural logarithm of the probability that if two sets of simultaneous data points of length have distance < then two sets of simultaneous data points of ...

  4. Low complexity regions in proteins - Wikipedia

    en.wikipedia.org/wiki/Low_complexity_regions_in...

    Thus, these two codons and their respective amino acids must have been constituents of the earliest oligopeptides, with a length of 10–55 amino acids [41] and very low complexity. Based on several different criteria and sources of data, Higgs and Pudritz [38] suggest G, A, D, E, V, S, P, I, L, T as the early amino acids of the genetic code ...

  5. Smoothed analysis - Wikipedia

    en.wikipedia.org/wiki/Smoothed_analysis

    Thus, a low smoothed complexity means that the hardness of inputs is a "brittle" property. Although worst-case complexity has been widely successful in explaining the practical performance of many algorithms, this style of analysis gives misleading results for a number of problems. Worst-case complexity measures the time it takes to solve any ...

  6. Robust principal component analysis - Wikipedia

    en.wikipedia.org/wiki/Robust_principal_component...

    The 2014 guaranteed algorithm for the robust PCA problem (with the input matrix being = +) is an alternating minimization type algorithm. [12] The computational complexity is (⁡) where the input is the superposition of a low-rank (of rank ) and a sparse matrix of dimension and is the desired accuracy of the recovered solution, i.e., ‖ ^ ‖ where is the true low-rank component and ^ is the ...

  7. Hjorth parameters - Wikipedia

    en.wikipedia.org/wiki/Hjorth_parameters

    Complexity gives an estimate of the bandwidth of the signal, which indicates the similarity of the shape of the signal to a pure sine wave. Since the calculation of the Hjorth parameters is based on variance, the computational cost of this method is sufficiently low, which makes them appropriate for the real-time task.

  8. Low (complexity) - Wikipedia

    en.wikipedia.org/wiki/Low_(complexity)

    Several natural complexity classes are known to be low for themselves. Such a class is sometimes called self-low. [2] Scott Aaronson calls such a class a physical complexity class. [3] Note that being self-low is a stronger condition than being closed under complement. Informally, a class being low for itself means a problem can use other ...

  9. Horner's method - Wikipedia

    en.wikipedia.org/wiki/Horner's_method

    Horner's method is a fast, code-efficient method for multiplication and division of binary numbers on a microcontroller with no hardware multiplier. One of the binary numbers to be multiplied is represented as a trivial polynomial, where (using the above notation) a i = 1 {\displaystyle a_{i}=1} , and x = 2 {\displaystyle x=2} .