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  2. Vectorization (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Vectorization_(mathematics)

    In Matlab/GNU Octave a matrix A can be vectorized by A(:). GNU Octave also allows vectorization and half-vectorization with vec(A) and vech(A) respectively. Julia has the vec(A) function as well. In Python NumPy arrays implement the flatten method, [note 1] while in R the desired effect can be achieved via the c() or as.vector() functions.

  3. Video coding format - Wikipedia

    en.wikipedia.org/wiki/Video_coding_format

    A video coding format [a] (or sometimes video compression format) is a content representation format of digital video content, such as in a data file or bitstream. It typically uses a standardized video compression algorithm, most commonly based on discrete cosine transform (DCT) coding and motion compensation .

  4. MATLAB - Wikipedia

    en.wikipedia.org/wiki/MATLAB

    MATLAB (an abbreviation of "MATrix LABoratory" [22]) is a proprietary multi-paradigm programming language and numeric computing environment developed by MathWorks.MATLAB allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages.

  5. Vector quantization - Wikipedia

    en.wikipedia.org/wiki/Vector_quantization

    Vector quantization (VQ) is a classical quantization technique from signal processing that allows the modeling of probability density functions by the distribution of prototype vectors. Developed in the early 1980s by Robert M. Gray , it was originally used for data compression .

  6. Array programming - Wikipedia

    en.wikipedia.org/wiki/Array_programming

    The Nial example of the inner product of two arrays can be implemented using the native matrix multiplication operator. If a is a row vector of size [1 n] and b is a corresponding column vector of size [n 1]. a * b; By contrast, the entrywise product is implemented as: a .* b;

  7. Array (data structure) - Wikipedia

    en.wikipedia.org/wiki/Array_(data_structure)

    For a vector with linear addressing, the element with index i is located at the address B + c · i, where B is a fixed base address and c a fixed constant, sometimes called the address increment or stride. If the valid element indices begin at 0, the constant B is simply the address of the first element of the array.

  8. Transformation matrix - Wikipedia

    en.wikipedia.org/wiki/Transformation_matrix

    If the 4th component of the vector is 0 instead of 1, then only the vector's direction is reflected and its magnitude remains unchanged, as if it were mirrored through a parallel plane that passes through the origin. This is a useful property as it allows the transformation of both positional vectors and normal vectors with the same matrix.

  9. Connected-component labeling - Wikipedia

    en.wikipedia.org/wiki/Connected-component_labeling

    A vector (Index) is updated with all the neighboring pixels of the currently set pixels. Unique pixels are retained and repeated pixels are removed. Set the pixels indicated by Index to mark in the connected-component matrix. Increment the marker for another object in the image.