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  2. Orthogonality (mathematics) - Wikipedia

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

    However, normal may also refer to the magnitude of a vector. In particular, a set is called orthonormal (orthogonal plus normal) if it is an orthogonal set of unit vectors. As a result, use of the term normal to mean "orthogonal" is often avoided. The word "normal" also has a different meaning in probability and statistics.

  3. 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.

  4. Orthogonality - Wikipedia

    en.wikipedia.org/wiki/Orthogonality

    The line segments AB and CD are orthogonal to each other. In mathematics, orthogonality is the generalization of the geometric notion of perpendicularity.Whereas perpendicular is typically followed by to when relating two lines to one another (e.g., "line A is perpendicular to line B"), [1] orthogonal is commonly used without to (e.g., "orthogonal lines A and B").

  5. Normal matrix - Wikipedia

    en.wikipedia.org/wiki/Normal_matrix

    Phrased differently: a matrix is normal if and only if its eigenspaces span C n and are pairwise orthogonal with respect to the standard inner product of C n. The spectral theorem for normal matrices is a special case of the more general Schur decomposition which holds for all square matrices.

  6. Normal operator - Wikipedia

    en.wikipedia.org/wiki/Normal_operator

    Eigenvectors of a normal operator corresponding to different eigenvalues are orthogonal, and a normal operator stabilizes the orthogonal complement of each of its eigenspaces. [3] This implies the usual spectral theorem: every normal operator on a finite-dimensional space is diagonalizable by a unitary operator.

  7. Orthogonal matrix - Wikipedia

    en.wikipedia.org/wiki/Orthogonal_matrix

    Visual understanding of multiplication by the transpose of a matrix. If A is an orthogonal matrix and B is its transpose, the ij-th element of the product AA T will vanish if i≠j, because the i-th row of A is orthogonal to the j-th row of A. An orthogonal matrix is the real specialization of a unitary matrix, and thus always a normal matrix.

  8. 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.

  9. Normal (geometry) - Wikipedia

    en.wikipedia.org/wiki/Normal_(geometry)

    In geometry, a normal is an object (e.g. a line, ray, or vector) that is perpendicular to a given object. For example, the normal line to a plane curve at a given point is the line perpendicular to the tangent line to the curve at the point. A normal vector of length one is called a unit normal vector.