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asymptotic vector

  • 1 асимптотический вектор

    Русско-английский научно-технический словарь Масловского > асимптотический вектор

  • 2 асимптотический вектор

    Mathematics: asymptotic vector

    Универсальный русско-английский словарь > асимптотический вектор

  • 3 Отсутствие артиклей перед существительными, которые снабжены ссылками

    It follows from Theorem 1 that $x=1$
    Section 2 of this paper gives (contains) a concise presentation of the notation to be used below
    Property 1 is called (known as) the triangle inequality
    This assertion (statement, proposition) has been proved in part 1 (part (a)) of the (our) proof
    Algorithm 1 (с большой буквы) defines elementary permutations and elementary triangle matrices of index 2
    Equation (1) ((the) inequality (1)) can thus be written in the (артикль обязателен) form (2)
    In the language of our notation, algorithm (1) (с маленькой буквы) is a stable way of computing the inner product
    The only place where the algorithm can break down is in statement 3 (in Statement 3)
    We combine Exercises 1 and 2 to construct an algorithm for finding an approximate eigenvector
    This case is illustrated in (но не on) Figure 1
    The asymptotic formula (1) was proved in Example 1
    Corollary 1 can be used to estimate the error in the inverse of a perturbed matrix
    By property 1 (by Theorem 1), this function is positive except at the zero vector
    A less trivial example is given in Appendix 3
    Step 1 in Example 1 and steps 2 and 3 in Example 2
    The idea of a norm will be introduced in Chapter 4
    Now from statements 2 and 3 of (1), we have...
    All the drivers for solving linear systems are listed in Table 1 (are illustrated in Figure 1)
    If Algorithm 1 in four-digit arithmetic is applied to refine $x$, then we obtain...
    Assertion (ii) is nothing but the statement that one natural way of extending these ideas to $R^n$ is to generalize formula (1) to obtain a Euclidean length of a vector
    By property 1, this function is positive except at the zero vector
    We have seen on page 3 that set of matrices is a vector space which is essentially identical with...
    Equation (1) effectively gives an algorithm for using the output of Algorithm 1 to solve...

    Русско-английский словарь по прикладной математике и механике > Отсутствие артиклей перед существительными, которые снабжены ссылками

  • 4 Определенные артикли перед существительными, которые снабжены ссылками

    The differential problem (1) can be reduced to the form (2)
    The asymptotic formula (1) follows from the above lemma
    The differential equation (1) can be solved numerically
    What is needed in the final result is a simple bound on quantities of the form (1)
    The inequality (1) (артикль можно опустить) shows that $a>b$
    The bound (estimate) (2) is not quite as good as the bound (estimate) (1)
    If the norm of $A$ satisfies the restriction (1), then by the estimate (2) this term is less than unity
    Since the spectral radius of $A$ belongs to the region (1), this iterative method converges for any initial guesses
    The array (1) is called the matrix representing the linear transformation of $f$
    It should be noted that the approximate inequality (1) bounds only the absolute error in $x$
    The inequality (1) shows that...
    The second step in our analysis is to substitute the forms (1) and (2) into this equation and simplify it by dropping higher-order terms
    For small $ze$ the approximation (1) is very good indeed
    A matrix of the form (1), in which some eigenvalue appears in more than one block, is called a derogatory matrix
    The relation between limits and norms is suggested by the equivalence (1)
    For this reason the matrix norm (1) is seldom encountered in the literature
    To establish the inequality (1) from the definition (2)
    Our conclusion agrees with the estimate (1)
    The characterization is established in almost the same way as the results of Theorem 1, except that the relations (1) and (2) take place in the eigenvalue-eigenvector relation...
    This vector satisfies the differential equation (1)
    The Euclidean vector norm (2) satisfies the properties (1)
    The bound (1) ensures only that these elements are small compared with the largest element of $A$
    There is some terminology associated with the system (1) and the matrix equation (2)
    A unique solution expressible in the form (1) restricts the dimensions of $A$
    The factorization (1) is called the $LU$-factorization
    It is very uncommon for the condition (1) to be violated
    The relation (1) guarantees that the computed solution gives very small residual
    This conclusion follows from the assumptions (1) and (2)
    The factor (1) introduced in relation (2) is now equal to 2
    The inequalities (1) are still adequate
    We use this result without explicitly referring to the restriction (1)

    Русско-английский словарь по прикладной математике и механике > Определенные артикли перед существительными, которые снабжены ссылками

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