Eigenvectors of matric polynomials

ON T H E CHARACTERISTIC ROOTS OF MATRIC POLYNOMIALS* BY N. H. McCOY

Each normal Cn image of a line meets each base 5n_2 in n — 2 points and does not intersect the ruled variety. The images of planes intersect R in (n-\-l)(n — 2)/2 lines. The plane meets each base 5n-2 in a point, the image of which is a line meeting n of the base 5n'_2 and lying on F2. Each base Sn-2 meets R in a manifold of dimensionality n — 3 and of order n — 1. For ^ = 4, the two-dimensiona...

Matric potentials of leaves.

A pressure chamber was used to measure matric potentials of frozen and thawed leaves. Significant matric potentials were demonstrated in sunflower (Helianthus annuus L.), yew (Taxus cuspidata Sieb. and Zucc.), and rhododendron (Rhododendron roseum Rehd.). Matric potentials were particularly negative in rhododendron and were correlated with the amount of cell wall present and with the volume of ...

bioCEED, CEMPE and MatRIC

Algebraic Matric Groups.

where the diagonal elements of DI were denoted by cos qpj + i sin (pi. As is well known, the number of real parameters in R, if (4) is not fulfilled, can be counted as follows: the first column Rji is an n dimensional vector of length 1, giving n1 parameters; the second column Rp is of length 1 and is orthogonal to the first column giving n 2 parameters; the third column of R must be a unit vec...

Recovery of Eigenvectors and Minimal Bases of Matrix Polynomials from Generalized Fiedler Linearizations

A standard way to solve polynomial eigenvalue problems P (λ)x = 0 is to convert the matrix polynomial P (λ) into a matrix pencil that preserves its elementary divisors and, therefore, its eigenvalues. This process is known as linearization and is not unique, since there are infinitely many linearizations with widely varying properties associated with P (λ). This freedom has motivated the recent...