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  2. Transformation matrix - Wikipedia

    en.wikipedia.org/wiki/Transformation_matrix

    If is a linear transformation mapping to and is a column vector with entries, then = for some matrix , called the transformation matrix of . [ citation needed ] Note that A {\displaystyle A} has m {\displaystyle m} rows and n {\displaystyle n} columns, whereas the transformation T {\displaystyle T} is from R n {\displaystyle \mathbb {R} ^{n ...

  3. Projective texture mapping - Wikipedia

    en.wikipedia.org/wiki/Projective_texture_mapping

    Historically, using projective texture mapping involved considering a special form of eye linear texture coordinate generation transform (tcGen for short). This transform was then multiplied by another matrix representing the projector's properties which were stored in texture coordinate transform matrix. The resulting concentrated matrix was ...

  4. Rotation matrix - Wikipedia

    en.wikipedia.org/wiki/Rotation_matrix

    Noting that any identity matrix is a rotation matrix, and that matrix multiplication is associative, we may summarize all these properties by saying that the n × n rotation matrices form a group, which for n > 2 is non-abelian, called a special orthogonal group, and denoted by SO(n), SO(n,R), SO n, or SO n (R), the group of n × n rotation ...

  5. DFT matrix - Wikipedia

    en.wikipedia.org/wiki/DFT_matrix

    In this case, if we make a very large matrix with complex exponentials in the rows (i.e., cosine real parts and sine imaginary parts), and increase the resolution without bound, we approach the kernel of the Fredholm integral equation of the 2nd kind, namely the Fourier operator that defines the continuous Fourier transform. A rectangular ...

  6. Vectorization (mathematics) - Wikipedia

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

    The vectorization is frequently used together with the Kronecker product to express matrix multiplication as a linear transformation on matrices. In particular, vec ⁡ ( A B C ) = ( C T ⊗ A ) vec ⁡ ( B ) {\displaystyle \operatorname {vec} (ABC)=(C^{\mathrm {T} }\otimes A)\operatorname {vec} (B)} for matrices A , B , and C of dimensions k ...

  7. Rotation operator (quantum mechanics) - Wikipedia

    en.wikipedia.org/wiki/Rotation_operator_(quantum...

    From linear algebra one knows that a certain matrix can be represented in another basis through the transformation ′ = where is the basis transformation matrix. If the vectors b {\displaystyle b} respectively c {\displaystyle c} are the z-axis in one basis respectively another, they are perpendicular to the y-axis with a certain angle t ...

  8. List of common coordinate transformations - Wikipedia

    en.wikipedia.org/wiki/List_of_common_coordinate...

    Note: solving for ′ returns the resultant angle in the first quadrant (< <). To find , one must refer to the original Cartesian coordinate, determine the quadrant in which lies (for example, (3,−3) [Cartesian] lies in QIV), then use the following to solve for :

  9. Rotations in 4-dimensional Euclidean space - Wikipedia

    en.wikipedia.org/wiki/Rotations_in_4-dimensional...

    The generating rotation matrix can be classified with respect to the values θ 1 and θ 2 as follows: If θ 1 = 0 and θ 2 ≠ 0 or vice versa, then the formulae generate simple rotations; If θ 1 and θ 2 are nonzero and θ 1 ≠ θ 2, then the formulae generate double rotations; If θ 1 and θ 2 are nonzero and θ 1 = θ 2, then the formulae ...