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  2. Orthonormal basis - Wikipedia

    en.wikipedia.org/wiki/Orthonormal_basis

    In other words, the space of orthonormal bases is like the orthogonal group, but without a choice of base point: given the space of orthonormal bases, there is no natural choice of orthonormal basis, but once one is given one, there is a one-to-one correspondence between bases and the orthogonal group.

  3. Orthogonal matrix - Wikipedia

    en.wikipedia.org/wiki/Orthogonal_matrix

    For example, it is often desirable to compute an orthonormal basis for a space, or an orthogonal change of bases; both take the form of orthogonal matrices. Having determinant ±1 and all eigenvalues of magnitude 1 is of great benefit for numeric stability.

  4. Gram–Schmidt process - Wikipedia

    en.wikipedia.org/wiki/Gram–Schmidt_process

    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. The number of vectors output by the algorithm will then be the dimension of the space spanned by the original inputs.

  5. 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.

  6. Singular value decomposition - Wikipedia

    en.wikipedia.org/wiki/Singular_value_decomposition

    The geometric content of the SVD theorem can thus be summarized as follows: for every linear map ⁠: ⁠ one can find orthonormal bases of ⁠ ⁠ and ⁠ ⁠ such that ⁠ ⁠ maps the ⁠ ⁠-th basis vector of ⁠ ⁠ to a non-negative multiple of the ⁠ ⁠-th basis vector of ⁠, ⁠ and sends the leftover basis vectors to zero.

  7. Spherical harmonics - Wikipedia

    en.wikipedia.org/wiki/Spherical_harmonics

    The Laplace spherical harmonics : form a complete set of orthonormal functions and thus form an orthonormal basis of the Hilbert space of square-integrable functions (). On the unit sphere S 2 {\displaystyle S^{2}} , any square-integrable function f : S 2 → C {\displaystyle f:S^{2}\to \mathbb {C} } can thus be expanded as a linear combination ...

  8. Orthogonal basis - Wikipedia

    en.wikipedia.org/wiki/Orthogonal_basis

    The concept of orthogonality may be extended to a vector space over any field of characteristic not 2 equipped with a quadratic form ⁠ ⁠.Starting from the observation that, when the characteristic of the underlying field is not 2, the associated symmetric bilinear form , = ((+) ()) allows vectors and to be defined as being orthogonal with respect to when ⁠ (+) () = ⁠.

  9. Orthogonal group - Wikipedia

    en.wikipedia.org/wiki/Orthogonal_group

    In other words, the space of orthonormal bases is like the orthogonal group, but without a choice of base point: given an orthogonal space, there is no natural choice of orthonormal basis, but once one is given one, there is a one-to-one correspondence between bases and the orthogonal group.