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  2. Sierpiński triangle - Wikipedia

    en.wikipedia.org/wiki/Sierpiński_triangle

    The usage of the word "gasket" to refer to the Sierpiński triangle refers to gaskets such as are found in motors, and which sometimes feature a series of holes of decreasing size, similar to the fractal; this usage was coined by Benoit Mandelbrot, who thought the fractal looked similar to "the part that prevents leaks in motors".

  3. Joint Probabilistic Data Association Filter - Wikipedia

    en.wikipedia.org/wiki/Joint_Probabilistic_Data...

    The joint probabilistic data-association filter (JPDAF) [1] is a statistical approach to the problem of plot association (target-measurement assignment) in a target tracking algorithm.

  4. Kernel regression - Wikipedia

    en.wikipedia.org/wiki/Kernel_regression

    Python: the KernelReg class for mixed data types in the statsmodels.nonparametric sub-package (includes other kernel density related classes), the package kernel_regression as an extension of scikit-learn (inefficient memory-wise, useful only for small datasets) R: the function npreg of the np package can perform kernel regression. [7] [8]

  5. Iterative closest point - Wikipedia

    en.wikipedia.org/wiki/Iterative_Closest_Point

    MeshLab an open source mesh processing tool that includes a GNU General Public License implementation of the ICP algorithm.; CloudCompare an open source point and model processing tool that includes an implementation of the ICP algorithm.

  6. Joint Approximation Diagonalization of Eigen-matrices

    en.wikipedia.org/wiki/Joint_Approximation...

    Joint Approximation Diagonalization of Eigen-matrices (JADE) is an algorithm for independent component analysis that separates observed mixed signals into latent source signals by exploiting fourth order moments. [1] The fourth order moments are a measure of non-Gaussianity, which is used as a proxy for defining independence between the source ...

  7. Error correction code - Wikipedia

    en.wikipedia.org/wiki/Error_correction_code

    A convolutional code that is terminated is also a 'block code' in that it encodes a block of input data, but the block size of a convolutional code is generally arbitrary, while block codes have a fixed size dictated by their algebraic characteristics. Types of termination for convolutional codes include "tail-biting" and "bit-flushing".

  8. Jarque–Bera test - Wikipedia

    en.wikipedia.org/wiki/Jarque–Bera_test

    The null hypothesis is a joint hypothesis of the skewness being zero and the excess kurtosis being zero. Samples from a normal distribution have an expected skewness of 0 and an expected excess kurtosis of 0 (which is the same as a kurtosis of 3). As the definition of JB shows, any deviation from this increases the JB statistic.

  9. Zero-inflated model - Wikipedia

    en.wikipedia.org/wiki/Zero-inflated_model

    As the examples above show, zero-inflated data can arise as a mixture of two distributions. The first distribution generates zeros. The second distribution, which may be a Poisson distribution, a negative binomial distribution or other count distribution, generates counts, some of which may be zeros.