Sentence examples for systems of multivariate from inspiring English sources

In this paper, we present a hybrid parallel algorithm for solving systems of multivariate constraints by exploiting both the CPU and the GPU multicore architectures.

To date, two general systems of multivariate regressions have been proposed to account for dependencies between pairs of species in a regional species pool.

This system of multivariate variational inequalities has a solution.

The set of solutions of this system of multivariate variational inequalities is closed convex in (K^{N}).

From the above, we claim that the system of multivariate variational inequalities (3.1) is equivalent to the variational inequality (3.2).

The purpose of this paper is to study a kind of system of multivariate variational inequalities and to prove the existence theorem of solutions.

If (A_{1}, A_{2},ldots,A_{N}) are also strictly monotone, this system of multivariate variational inequalities has a unique solution.

When the modification is cast as an additional forcing term on the original structure a system of multivariate polynomials in the parameters of the beam cross-section are revealed.

At Eurocrypt 2012, following similar approaches by Gaudry [9] and Diem [2,3], FPPR method provided V with the structure of a vector space, to reduce the resolution of Semaev's polynomial to a system of multivariate polynomial equations.

We prove some existence theorems for solutions of a certain system of multivariate nonexpansive operator equations and calculate the solutions by using the generalized Mann and Halpern iterative algorithms in uniformly convex and uniformly smooth Banach spaces.

In addition, the system of multivariate variational inequalities (3.12) is equivalent to bigllangle operatorname{grad} f(x), y-x bigrrangle geq0, quadforall y in K^{N}, (3.13) where operatorname{grad} f(x)=biggl(frac{partial f}{partial x_{1}}, frac{partial f}{partial x_{2}},ldots, frac{partial f}{partial x_{N}}biggr).