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  2. Gram–Schmidt process - Wikipedia

    en.wikipedia.org/wiki/Gram–Schmidt_process

    If the Gram–Schmidt process is applied to a linearly dependent sequence, it outputs the 0 vector on the th step, assuming that is a linear combination of , …,. If an orthonormal basis is to be produced, then the algorithm should test for zero vectors in the output and discard them because no multiple of a zero vector can have a length of 1.

  3. QR decomposition - Wikipedia

    en.wikipedia.org/wiki/QR_decomposition

    Householder reflection for QR-decomposition: The goal is to find a linear transformation that changes the vector into a vector of the same length which is collinear to . We could use an orthogonal projection (Gram-Schmidt) but this will be numerically unstable if the vectors x {\displaystyle \mathbf {x} } and e 1 {\displaystyle \mathbf {e} _{1 ...

  4. Orthonormality - Wikipedia

    en.wikipedia.org/wiki/Orthonormality

    A unit vector means that the vector has a length of 1, which is also known as normalized. Orthogonal means that the vectors are all perpendicular to each other. A set of vectors form an orthonormal set if all vectors in the set are mutually orthogonal and all of unit length. An orthonormal set which forms a basis is called an orthonormal basis.

  5. Row- and column-major order - Wikipedia

    en.wikipedia.org/wiki/Row-_and_column-major_order

    Note how the use of A[i][j] with multi-step indexing as in C, as opposed to a neutral notation like A(i,j) as in Fortran, almost inevitably implies row-major order for syntactic reasons, so to speak, because it can be rewritten as (A[i])[j], and the A[i] row part can even be assigned to an intermediate variable that is then indexed in a separate expression.

  6. Array programming - Wikipedia

    en.wikipedia.org/wiki/Array_programming

    In array languages, operations are generalized to apply to both scalars and arrays. Thus, a+b expresses the sum of two scalars if a and b are scalars, or the sum of two arrays if they are arrays. An array language simplifies programming but possibly at a cost known as the abstraction penalty.

  7. NumPy - Wikipedia

    en.wikipedia.org/wiki/NumPy

    In contrast to Python's built-in list data structure, these arrays are homogeneously typed: all elements of a single array must be of the same type. Such arrays can also be views into memory buffers allocated by C / C++ , Python , and Fortran extensions to the CPython interpreter without the need to copy data around, giving a degree of ...

  8. Stride of an array - Wikipedia

    en.wikipedia.org/wiki/Stride_of_an_array

    In computer programming, the stride of an array (also referred to as increment, pitch or step size) is the number of locations in memory between beginnings of successive array elements, measured in bytes or in units of the size of the array's elements. The stride cannot be smaller than the element size but can be larger, indicating extra space ...

  9. Comparison of programming languages (array) - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_programming...

    In addition to support for vectorized arithmetic and relational operations, these languages also vectorize common mathematical functions such as sine. For example, if x is an array, then y = sin (x) will result in an array y whose elements are sine of the corresponding elements of the array x. Vectorized index operations are also supported.