Приклади вживання Mathbb Англійська мовою та їх переклад на Українською
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Is a vector space over R{\displaystyle\mathbb{R}}.
The real exponential function exp: R→ R{\displaystyle\ exp:\mathbb{R}\to\mathbb{R}} can be characterized in a variety of equivalent ways.
Over the rational field Q{\displaystyle\mathbb{Q}}.
Let f: R n→ R{\displaystyle f:\mathbb{R}^{n}\to\mathbb{R}} be a convex function with domain R n{\displaystyle\mathbb{R}^{n}}.
Is also a vector spaces over R{\displaystyle\mathbb{R}}.
The function k: X× X→ R{\displaystyle k\colon{\mathcal{X}}\times{\mathcal{X}}\to\mathbb{R}} is often referred to as a kernel or a kernel function.
As it is not algebraic over Q{\displaystyle\mathbb{Q}}.
Consider the inner-product space( R 2,⟨⋅,⋅⟩){\displaystyle(\mathbb{R}^{2},\langle\cdot,\cdot\rangle)} with the standard euclidean inner product and standard basis.
Of all continuous functions f from R{\displaystyle\mathbb{R}}.
The group H 1( S 1)= Z{\displaystyle H_{ 1}( S^{1})=\ mathbb{Z}} represents a finitely-generated abelian group, with a single generator representing the one-dimensional hole contained in a circle.[14].
The additive group of rational numbers Q{\displaystyle\mathbb{Q}}.
For a spinless single particle moving in R3{\displaystyle\mathbb{R}^{3}}, the particle's velocity is given.
These concepts can begeneralized for multidimensional cases on R n{\displaystyle\mathbb{R}^{n}}.
Supergeometry is formulated in terms of Z 2{\displaystyle\mathbb{Z}_{2}}-graded modules and sheaves over Z 2{\displaystyle\mathbb{Z}_{2}}-graded commutative algebras(supercommutative algebras).
Times differentiable for every n∈ N{\displaystyle n\in\mathbb{N}}.
Let S{\displaystyle S} be a set of obstacles(either segments, or polygons) in R 2{\displaystyle\mathbb{R}^{2}}. Let p{\displaystyle p} be a point in R 2{\displaystyle\mathbb{R}^{2}} that is not within an obstacle.
The results obtained arealso specified for the Newton kernel in$\mathbb{R}^n$.
In particular, this property distinguishes the real numbers from other ordered fields(e.g.,the rational numbers Q{\displaystyle\mathbb{Q}}) and is critical to the proof of several key properties of functions of the real numbers.
This differentialequation leads to the solution I( u)= k log u{\displaystyle I(u)=k\log u}for any k∈ R{\displaystyle k\in\mathbb{R}}.
The ring C( R){\displaystyle C(\mathbb{R})} of all continuous functions f from R{\displaystyle\mathbb{R}} to R{\displaystyle\mathbb{R}} under pointwise multiplication contains the ideal of all continuous functions f such that f(1)= 0.
Let ε∈ R> 0{\displaystyle\varepsilon\in\mathbb{R}>0} be fixed.
Let μ n{\displaystyle\mu_{n}}, n∈ N{\displaystyle n\in\mathbb{N}} be a sequence of probability measures on a metric space S{\displaystyle S} such that μ n{\displaystyle\mu_{n}} converges weakly to some probability measure μ∞{\displaystyle\mu_{\infty}} on S{\displaystyle S} as n→∞{\displaystyle n\to\infty}.
The same result holds in algebraic geometry for algebraic vectorbundle over P k 1{\displaystyle\mathbb{P}_{k}^{1}} for any field k{\displaystyle k}.
Given certain mild conditions on the shape of the activation function, RBF networks are universalapproximators on a compact subset of R n{\displaystyle\mathbb{R}^{n}}.
In the first instance, configuration space and real space are the same, while in the second, real space is still R 3{\displaystyle\mathbb{R}^{3}}, but configuration space becomes R 3 N{\displaystyle\mathbb{R}^{3N}}.
Let d{\displaystyle d} be a positive integer, D{\displaystyle{\mathcal{D}}} be a collection of datasets, and f:D→ R d{\displaystyle f\colon{\mathcal{D}}\rightarrow \mathbb{R}^{d}} be a function.
Given certain mild conditions on the shape of the activation function, RBF networks are universalapproximators on a compact subset of R n{\displaystyle\mathbb{R}^{n}}.[4] This means that an RBF network with enough hidden neurons can approximate any continuous function on a closed, bounded set with arbitrary precision.
In symbolic logic,"∃"(a backwards letter"E" in a sans-serif font) is used to indicate existential quantification.[2] Thus, if P(a, b, c)is the predicate"a·b= c" and N{\displaystyle\mathbb{N}} is the set of natural numbers, then.
In mathematics, a geometric transformation is any bijection of a set to itself(or to another such set) with some salient geometrical underpinning.[1] More specifically, it is a function whose domain and range are sets of points- most often both R 2{\displaystyle\mathbb{R}^{2}} or both R 3{\displaystyle\mathbb{R}^{3}}- such that the function is injective so that its inverse exists.[2] The study of geometry may be approached via the study of these transformations.[3].
We can say a knot K{\displaystyle K} is an injective and continuous function K:[ 0,1]→ R 3{\displaystyle K\colon[0,1]\to\mathbb{R}^{3}} with K( 0)= K( 1){\displaystyle K(0)=K(1)}.