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  2. PageRank - Wikipedia

    en.wikipedia.org/wiki/PageRank

    The damping factor is subtracted from 1 (and in some variations of the algorithm, the result is divided by the number of documents (N) in the collection) and this term is then added to the product of the damping factor and the sum of the incoming PageRank scores. That is,

  3. Google matrix - Wikipedia

    en.wikipedia.org/wiki/Google_matrix

    The numerical coefficient is known as a damping factor. Usually S is a sparse matrix and for modern directed networks it has only about ten nonzero elements in a line or column, thus only about 10N multiplications are needed to multiply a vector by matrix G. [2] [3]

  4. Damping factor - Wikipedia

    en.wikipedia.org/wiki/Damping_factor

    At around 4 kHz, the real-life difference between an amplifier with a moderate (100) damping factor and one with a low (20) damping factor is about 0.37 dB. However, the amplifier with the low damping factor is acting more like a subtle graphic equaliser than is the amplifier with the moderate damping factor, where the peaks and dips in the ...

  5. Talk:PageRank - Wikipedia

    en.wikipedia.org/wiki/Talk:PageRank

    In "Damping Factor", after the two formulas, it states, "The difference between them is that the PageRank values in the first formula sum to one, while in the second formula each PageRank is multiplied by N and the sum becomes N."

  6. Levenberg–Marquardt algorithm - Wikipedia

    en.wikipedia.org/wiki/Levenberg–Marquardt...

    The (non-negative) damping factor ⁠ ⁠ is adjusted at each iteration. If reduction of ⁠ S {\displaystyle S} ⁠ is rapid, a smaller value can be used, bringing the algorithm closer to the Gauss–Newton algorithm , whereas if an iteration gives insufficient reduction in the residual, ⁠ λ {\displaystyle \lambda } ⁠ can be increased ...

  7. Curve fitting - Wikipedia

    en.wikipedia.org/wiki/Curve_fitting

    Fitting of a noisy curve by an asymmetrical peak model, with an iterative process (Gauss–Newton algorithm with variable damping factor α).Curve fitting [1] [2] is the process of constructing a curve, or mathematical function, that has the best fit to a series of data points, [3] possibly subject to constraints.

  8. Automatic summarization - Wikipedia

    en.wikipedia.org/wiki/Automatic_summarization

    Unlike PageRank, the edges are typically undirected and can be weighted to reflect a degree of similarity. Once the graph is constructed, it is used to form a stochastic matrix, combined with a damping factor (as in the "random surfer model"), and the ranking over vertices is obtained by finding the eigenvector corresponding to eigenvalue 1 (i ...

  9. Logarithmic decrement - Wikipedia

    en.wikipedia.org/wiki/Logarithmic_decrement

    The logarithmic decrement can be obtained e.g. as ln(x 1 /x 3).Logarithmic decrement, , is used to find the damping ratio of an underdamped system in the time domain.. The method of logarithmic decrement becomes less and less precise as the damping ratio increases past about 0.5; it does not apply at all for a damping ratio greater than 1.0 because the system is overdamped.