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1, At least, therefore, for such groups, the portfolio matrices and their separable SBUs are potentially relevant concepts.

2, Orthogonal matrices; diagonalization of symmetric real matrices.

3, Triangular matrices, in particular, are usually quite tractable.

4, Matrix Analysis: Toeplitz Matrices and Fast Algorithms.

5, Scalar formulas do carry over for these matrices.

6, Estimate for the spectral radius of iterative matrices.

7, Shared memory multi - threaded parallel computing code matrices.

8, A default convention is used for output matrices based upon the names of the input matrices.

9, The rank of matrix which two matrices act right semi - tensor product is given.

10, We introduce some important matrices and their applications in quantum computation and quantum information, including density matrix, unitary matrix, etc.

11, An expression of the generalized eigenvector of adjoint matrices for nonsingular matrix A is derived.

12, Some of the math is quite sophisticated, using differential equations, linear algebra, and covariance matrices.

13, The run-time application of syntactic information uses the transition matrices and the lexicon to rank the words in the lattice.

14, Fig 4.11 outlines the way in which the bigram and matrices are used in conjunction.

15, The text is punctuated throughout by numerical examples,[http://sentencedict.com/matrices.html] most usually based on matrices of small order.

16, The use of longer transitions requires a larger training corpus, increased storage for the transition matrices and is computationally more demanding.

17, Punctuation marks are classified as separate syntactic categories and grammars and transition matrices based around this assumption.

18, The merits of microwave digestion techniques for a wide range of matrices are stressed.

19, The book is divided into two distinct parts, one describing analysis of aqueous samples and the other analysis of solid matrices.

20, A simple solution is to subdivide the 900-pixel matrix into nine 10-by-10 matrices.

21, In this paper we will discuss symmetric bilinear forms and quadratic forms over valuation rings, and establish the congruent standard forms of symmetric matrices over valuation rings.

22, A method of zero-knowledge identity verification is discussed here, and the specified. scheme is put forward based on the encryption properties of the ergodic matrices over the finite field.

23, In this paper, a fast algorithm for image interpolation based on the tensor product of matrices is presented, which transforms the vector interpolation model to matrix form.

24, In the meantime, the calculation of weights of judgement matrices in numerical information are also given.

25, Some new necessary and sufficient conditions for the complex square matrix to be a generalized dominant matrices are given in the paper.

26, This paper proposes an orthonormalization method which can get the same theoretical orthonormal results with the traditional Gram-Schmidt orthogonalization process for skinny (long) matrices.

27, Secondly, one construction of Cartesian authentication code from norm form of one class of nilpotent matrices over finite field is presented and its size parameters are computed.

28, Secondly, we discuss the problem of decomposing a nonnegative matrix into a product of fully indecomposable nonnegative matrices in chapter 2.

29, Their tutorial also includes the slightly more advanced topics of 3-dimensional matrices and error reporting.

30, Some striking examples of this are the group of invertible linear maps or matrices, and the ring of linear maps of a vector space.