Sentence examples for matrices for which from inspiring English sources

Moreover, we analyze the case of matrices for which freness does not hold: Vandermonde, Hankel, Toeplitz.

The chapter introduces the concept of vectors and matrices, for which there are many applications in engineering and science.

Let (check{U}(j)subset U j)) be the set of matrices for which ({-1} ) is not an eigenvalue.

According to the theory, the eigenvalues λ2 and λ3 of C are the same, and all column matrices for which J1 + J2 + J3 = 0 are corresponding eigenvectors.

We show that the traditional (Faddeev Marchenko) condition is too restrictive to define the class of CMV matrices for which there exists a unique scattering representation.

In fact, in the previous studies, this technique has given eigenvalue problems for non-symmetric matrices for which the problem of the existence of complex eigenvalues arises.

These indicator vectors are modelled on that of the original PEG algorithm [25], indicating sub-matrices for which placement is permitted, thus imposing the form of (20), (24), (26), (27).

These indicator vectors are modelled on the basis of the original PEG algorithm [25], indicating sub-matrices for which placement is permitted, thus imposing the controlled doping root-LDPC form.

In this paper we provide a new upper bound for (2) and give a family of examples of (B^{S} -matrices that are not B^{S} -matriceswhich our bound is a small consthat in contrare to bounot(4) of [1], which can be arbitrarily large.

However, this approach does not always provide a positive semi-definite matrix for which a closed form solution exists.

In this paper, we mainly focus on the case of square nonnegative joint transformation matrix, for which N = P.