anticipated values - перевод на русский
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anticipated values - перевод на русский

IN MATHEMATICS, THE SQUARE ROOT OF AN EIGENVALUE OF A NONNEGATIVE SELF-ADJOINT OPERATOR
Singular values; Singular Values
  • semi-axes]] of the ellipse.

anticipated values      
ожидаемые величины
anticipated value      

математика

ожидаемое значение

values         
  • The 2017 version of the [[Inglehart–Welzel cultural map of the world]], constructed by sociopolitical scientists [[Ronald Inglehart]] and [[Christian Welzel]] based on the [[World Values Survey]]
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PERSONAL VALUE, BASIS FOR ETHICAL ACTION
Value system; Ethonomics; Value systems; Value (personal and cultural); Protected values; Protected values as deontological rules; Societal values; Personal and cultural value; Value (philosophy); Total absolute value; Philosophic value; Relative value (philosophy); Total philosophic value; Philosophical value; Absolute value (philosophy); Relative value (ethics); Ethic values; Ethic value equality; Ethic value; Philosophic or ethic value; Value duration; Ethic value duration; Value intensity; Personal philosophic value; Personal value system; Personal and cultural values; Absolute value (ethics); Personal or cultural value; Relative ethic value; Total ethic value; Average ethic value; Average ethic value intensity; Ethic value average; Average value intensity; Total whole value; Ethic whole value; Valuation (ethics); Ethic valuing; Absolute ethic value; Absolute and relative ethic value; Value (ethics and philosophy); Ethic valuation; Ethic or philosophic value; Ethic or philosophic good; Ethic good; Negative ethic or philosophic value; Positive and negative value; Human values; Protected Values; Ethical value; Ethical values; Values; Social values; Cultural values; Values (philosophy); Values (ethics); Popular values; Social commitment; Value (ethics); Value (ethics and social psychology)

Определение

family values
¦ plural noun values supposedly characteristic of a traditional family unit, typically those of high moral standards and discipline.

Википедия

Singular value

In mathematics, in particular functional analysis, the singular values, or s-numbers of a compact operator T : X Y {\displaystyle T:X\rightarrow Y} acting between Hilbert spaces X {\displaystyle X} and Y {\displaystyle Y} , are the square roots of the (necessarily non-negative) eigenvalues of the self-adjoint operator T T {\displaystyle T^{*}T} (where T {\displaystyle T^{*}} denotes the adjoint of T {\displaystyle T} ).

The singular values are non-negative real numbers, usually listed in decreasing order (σ1(T), σ2(T), …). The largest singular value σ1(T) is equal to the operator norm of T (see Min-max theorem).

If T acts on Euclidean space R n {\displaystyle \mathbb {R} ^{n}} , there is a simple geometric interpretation for the singular values: Consider the image by T {\displaystyle T} of the unit sphere; this is an ellipsoid, and the lengths of its semi-axes are the singular values of T {\displaystyle T} (the figure provides an example in R 2 {\displaystyle \mathbb {R} ^{2}} ).

The singular values are the absolute values of the eigenvalues of a normal matrix A, because the spectral theorem can be applied to obtain unitary diagonalization of A {\displaystyle A} as A = U Λ U {\displaystyle A=U\Lambda U^{*}} . Therefore, A A = U Λ Λ U = U | Λ | U {\textstyle {\sqrt {A^{*}A}}={\sqrt {U\Lambda ^{*}\Lambda U^{*}}}=U\left|\Lambda \right|U^{*}} .

Most norms on Hilbert space operators studied are defined using s-numbers. For example, the Ky Fan-k-norm is the sum of first k singular values, the trace norm is the sum of all singular values, and the Schatten norm is the pth root of the sum of the pth powers of the singular values. Note that each norm is defined only on a special class of operators, hence s-numbers are useful in classifying different operators.

In the finite-dimensional case, a matrix can always be decomposed in the form U Σ V {\displaystyle \mathbf {U\Sigma V^{*}} } , where U {\displaystyle \mathbf {U} } and V {\displaystyle \mathbf {V^{*}} } are unitary matrices and Σ {\displaystyle \mathbf {\Sigma } } is a rectangular diagonal matrix with the singular values lying on the diagonal. This is the singular value decomposition.

Как переводится anticipated values на Русский язык