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  2. Estimation of signal parameters via rotational invariance ...

    en.wikipedia.org/wiki/Estimation_of_signal...

    Example of separation into subarrays (2D ESPRIT) Estimation of signal parameters via rotational invariant techniques (ESPRIT), is a technique to determine the parameters of a mixture of sinusoids in background noise.

  3. Heterogeneous earliest finish time - Wikipedia

    en.wikipedia.org/wiki/Heterogeneous_Earliest...

    But in complex situations it can easily fail to find the optimal scheduling. HEFT is essentially a greedy algorithm and incapable of making short-term sacrifices for long term benefits. Some improved algorithms based on HEFT look ahead to better estimate the quality of a scheduling decision can be used to trade run-time for scheduling performance.

  4. Ellipsoid method - Wikipedia

    en.wikipedia.org/wiki/Ellipsoid_method

    In mathematical optimization, the ellipsoid method is an iterative method for minimizing convex functions over convex sets.The ellipsoid method generates a sequence of ellipsoids whose volume uniformly decreases at every step, thus enclosing a minimizer of a convex function.

  5. Matching pursuit - Wikipedia

    en.wikipedia.org/wiki/Matching_pursuit

    In the basic version of an algorithm, the large dictionary needs to be searched at each iteration. Improvements include the use of approximate dictionary representations and suboptimal ways of choosing the best match at each iteration (atom extraction). [9] The matching pursuit algorithm is used in MP/SOFT, a method of simulating quantum ...

  6. Multiplicative weight update method - Wikipedia

    en.wikipedia.org/wiki/Multiplicative_Weight...

    Then, there might be a tie. Following the weight update rule in weighted majority algorithm, the predictions made by the algorithm would be randomized. The algorithm calculates the probabilities of experts predicting positive or negatives, and then makes a random decision based on the computed fraction: [further explanation needed] predict

  7. Mathematics of artificial neural networks - Wikipedia

    en.wikipedia.org/wiki/Mathematics_of_artificial...

    Backpropagation training algorithms fall into three categories: steepest descent (with variable learning rate and momentum, resilient backpropagation); quasi-Newton (Broyden–Fletcher–Goldfarb–Shanno, one step secant);

  8. FastICA - Wikipedia

    en.wikipedia.org/wiki/FastICA

    FastICA is an efficient and popular algorithm for independent component analysis invented by Aapo Hyvärinen at Helsinki University of Technology. [1] [2] Like most ICA algorithms, FastICA seeks an orthogonal rotation of prewhitened data, through a fixed-point iteration scheme, that maximizes a measure of non-Gaussianity of the rotated components.

  9. Cox–Zucker machine - Wikipedia

    en.wikipedia.org/wiki/Cox–Zucker_machine

    In arithmetic geometry, the Cox–Zucker machine is an algorithm created by David A. Cox and Steven Zucker.This algorithm determines whether a given set of sections [further explanation needed] provides a basis (up to torsion) for the Mordell–Weil group of an elliptic surface E → S, where S is isomorphic to the projective line.