Приклади вживання Linear transformation Англійська мовою та їх переклад на Українською
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Linear transformations.
Triangle area computation and linear transformations.
Linear transformations, ranks and transpose.
Then ϕ B{\displaystyle\phi_{B}} is a linear transformation from V to Fn.
Like any linear transformation of finite-dimensional vector spaces, a rotation can always be represented by a matrix.
Uniqueness of characteristic polynomial of linear transformation in finite fields.
The linear transformation of Rn corresponding to a real n-by-n matrix is orientation preserving if and only if its determinant is positive.
In the basis of addition of vibrations lies a linear transformation of temporal axis and principle of superposition.
The relation of two vector spacescan be expressed by linear map or linear transformation.
But even if you do not touch the linear transformation, then already one such neuron is a fairly powerful classifier.
A Bézier surface willtransform in the same way as its control points under all linear transformations and translations.
A real m-by-n matrix A gives rise to a linear transformation Rn→ Rm mapping each vector x in Rn to the(matrix) product Ax, which is a vector in Rm.
In the MixColumns step, the four bytes of each column of thestate are combined using an invertible linear transformation.
Matrices can conveniently represent linear transformations because matrix multiplication neatly corresponds to the composition of maps, as will be described next.
In the third epoch(1927- 1935),Noether focused on noncommutative algebra, linear transformations, and commutative number fields.
The linear transformations between(possibly) infinite-dimensional vector spaces can be modeled, analogously to the finite-dimensional case, with infinite matrices.
A reflection about a line orplane that does not go through the origin is not a linear transformation; it is an affine transformation. .
If one has a linear transformation T( x){\displaystyle T(x)} in functional form, it is easy to determine the transformation matrix A by transforming each of the vectors of the standard basis by T, then inserting the result into the columns of a matrix.
Implies that the"unsatisfactory" or less than 124 rating points,were not 7,42% but almost(if linear transformation is concerned) 47% of applicants!
One of the main motivations for using matrices to represent linear transformations is that transformations can then be easily composed and inverted.
In the context of quadratic forms, a real quadratic form Q in n variables(or on an n-dimensional real vector space)can by a suitable change of basis(by non-singular linear transformation from x to y) be brought to the diagonal form.
In 1932, he published a classicmonograph 662 pages long titled Linear transformations in Hilbert space and their applications to analysis, a presentation about self-adjoint operators.
The method consists in the computation of informativeindicators that quantify the level of the nonstationarity of the signal and its linear transformation, the coefficients of the inter-spectral correlation.
Bases andtheir associated coordinate representations let one realize vector spaces and linear transformations concretely as column vectors, row vectors, and matrices, hence are useful in calculations.
Matrices andmatrix multiplication reveal their essential features when related to linear transformations, also known as linear maps.
A matrix with the same number of rows and columns,sometimes used to represent a linear transformation from a vector space to itself, such as reflection, rotation, or shearing.
Some transformations that are non-linear on an n-dimensional Euclideanspace Rn can be represented as linear transformations on the n+1-dimensional space Rn+1.
So if all the variables have the same variance σ2, then,since division by n is a linear transformation, this formula immediately implies that the variance of their mean is.
This is a direct result of the linearity of expectation andis useful when applying a linear transformation, such as a whitening transformation, to a vector.