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  2. Prediction by partial matching - Wikipedia

    en.wikipedia.org/wiki/Prediction_by_partial_matching

    Prediction by partial matching (PPM) is an adaptive statistical data compression technique based on context modeling and prediction. PPM models use a set of previous symbols in the uncompressed symbol stream to predict the next symbol in the stream. PPM algorithms can also be used to cluster data into predicted groupings in cluster analysis.

  3. Euler–Maruyama method - Wikipedia

    en.wikipedia.org/wiki/Euler–Maruyama_method

    In Itô calculus, the Euler–Maruyama method (also simply called the Euler method) is a method for the approximate numerical solution of a stochastic differential equation (SDE). It is an extension of the Euler method for ordinary differential equations to stochastic differential equations named after Leonhard Euler and Gisiro Maruyama. The ...

  4. List of numerical-analysis software - Wikipedia

    en.wikipedia.org/wiki/List_of_numerical-analysis...

    Shogun, an open-source large-scale machine-learning toolbox that provides several SVM implementations (like libSVM, SVMlight) under a common framework and interfaces to Octave, MATLAB, Python, R; Waffles is a free-software collection of command-line tools designed for scripting machine-learning operations in automated experiments and processes.

  5. Split-step method - Wikipedia

    en.wikipedia.org/wiki/Split-step_method

    First, the method relies on computing the solution in small steps, and treating the linear and the nonlinear steps separately (see below). Second, it is necessary to Fourier transform back and forth because the linear step is made in the frequency domain while the nonlinear step is made in the time domain .

  6. Quadratically constrained quadratic program - Wikipedia

    en.wikipedia.org/wiki/Quadratically_constrained...

    Popular solver with an API for several programming languages. Free for academics. MOSEK: A solver for large scale optimization with API for several languages (C++, java, .net, Matlab and python) TOMLAB: Supports global optimization, integer programming, all types of least squares, linear, quadratic and unconstrained programming for MATLAB.

  7. Interior-point method - Wikipedia

    en.wikipedia.org/wiki/Interior-point_method

    An interior point method was discovered by Soviet mathematician I. I. Dikin in 1967. [1] The method was reinvented in the U.S. in the mid-1980s. In 1984, Narendra Karmarkar developed a method for linear programming called Karmarkar's algorithm, [2] which runs in provably polynomial time (() operations on L-bit numbers, where n is the number of variables and constants), and is also very ...

  8. 5 Items From the 1970s That Are Worth a Lot of Money - AOL

    www.aol.com/5-items-1970s-worth-lot-170007423.html

    Here are some examples of what just basic vintage games could make you if you sell them. Space Invaders (Atari 2600, 1978): $75 to $1,450. Pong (original Atari Pong C-100, 1972): $100 to $150.

  9. Helmert transformation - Wikipedia

    en.wikipedia.org/wiki/Helmert_transformation

    μ – scale factor, which is unitless; if it is given in ppm, it must be divided by 1,000,000 and added to 1. R – rotation matrix. Consists of three axes (small [clarification needed] rotations around each of the three coordinate axes) r x, r y, r z. The rotation matrix is an orthogonal matrix. The angles are given in either degrees or radians.