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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. Split-step method - Wikipedia

    en.wikipedia.org/wiki/Split-step_method

    The name arises for two reasons. 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.

  4. MacCormack method - Wikipedia

    en.wikipedia.org/wiki/MacCormack_method

    The application of MacCormack method to the above equation proceeds in two steps; a predictor step which is followed by a corrector step. Predictor step: In the predictor step, a "provisional" value of u {\displaystyle u} at time level n + 1 {\displaystyle n+1} (denoted by u i p {\displaystyle u_{i}^{p}} ) is estimated as follows

  5. Proximal gradient method - Wikipedia

    en.wikipedia.org/wiki/Proximal_gradient_method

    Proximal gradient methods starts by a splitting step, in which the functions ,..., are used individually so as to yield an easily implementable algorithm. They are called proximal because each non-differentiable function among f 1 , . . . , f n {\displaystyle f_{1},...,f_{n}} is involved via its proximity operator .

  6. Alternating-direction implicit method - Wikipedia

    en.wikipedia.org/wiki/Alternating-direction...

    In numerical linear algebra, the alternating-direction implicit (ADI) method is an iterative method used to solve Sylvester matrix equations.It is a popular method for solving the large matrix equations that arise in systems theory and control, [1] and can be formulated to construct solutions in a memory-efficient, factored form.

  7. Dormand–Prince method - Wikipedia

    en.wikipedia.org/wiki/Dormand–Prince_method

    Dormand–Prince is the default method in the ode45 solver for MATLAB [4] and GNU Octave [5] and is the default choice for the Simulink's model explorer solver. It is an option in Python's SciPy ODE integration library [6] and in Julia's ODE solvers library. [7]

  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. Conjugate gradient method - Wikipedia

    en.wikipedia.org/wiki/Conjugate_gradient_method

    Conjugate gradient, assuming exact arithmetic, converges in at most n steps, where n is the size of the matrix of the system (here n = 2). In mathematics , the conjugate gradient method is an algorithm for the numerical solution of particular systems of linear equations , namely those whose matrix is positive-semidefinite .