Consider the typical problem in individual scaling, namely finding a common configuration and weights for each individual from the given interpoint distances or scalar products. Within the STRAIN framework it is shown that the problem of determining weights for a given configuration can be posed as a standard quadratic programming problem. A set of necessary conditions for an optimal configuration to satisfy are given. A closed form expression for the configuration is obtained for the one dimensional case and an approach is given for the two dimensional case.

As an extension of Sylvester’s matrix, a tridiagonal matrix is investigated by determining both left and right eigenvectors. Orthogonality relations between left and right eigenvectors are derived. Two determinants of the matrices constructed by the left and right eigenvectors are evaluated in closed form.

We investigate the shape and strength of the magnetic fabrics (anisotropy of magnetic susceptibility (AMS) data) of various massive granitic plutons from different parts of India, using the eigenvalue method. The study aims to analyse eigenvalues and establish their relationship with various deformational attributes. It involves: (1) calculating eigenvectors and their corresponding eigenvalues from magnetic fabric datasets; (2) finding a link between the geometrical appearance of eigenvectors and the mechanistic issues involved with a specific deformation scenario; and (3) determining shape and strength parameters from the magnetic foliation data distribution.

The statistical analysis for the unimodal magnetic fabric dataset of orthorhombic symmetry class implies that the plane, consisting of intermediate (V2) and minimum (V3) eigenvectors with pole V1, accurately traces the instantaneous stretching axis (ISAmax) of a particular material flow system under a pure shear regime. Moreover, for the distributions of similar symmetry and modality, we infer that the rotational characteristics of eigenvectors with respect to a fixed coordinate cause a distinct shift of such planes (V2–V3) from the ISAmax of a steady-state flow system under simple shear, where a substantial amount of rotational strain is involved. However, our findings also suggest that variation in symmetry and modality of magnetic fabric data distribution of different studied granitoids can directly influence the relative disposition of V2–V3 with respect to the direction of ISAmax. We conclude that eigenvalue analysis of magnetic fabrics is a powerful approach, which can be utilized while studying the salient deformational aspects of any syntectonic massive granitic body.

We construct a simple example, surely known to Harry Kesten, of an R-transient Markov chain on a countable state space S ∪ {δ}, where δ is absorbing. The transition matrix K on S is irreducible and strictly substochastic. We determine the Yaglom limit, that is, the limiting conditional behavior given nonabsorption. Each starting state x ∈ S results in a different Yaglom limit. Each Yaglom limit is an R -1-invariant quasi-stationary distribution, where R is the convergence parameter of K. Yaglom limits that depend on the starting state are related to a nontrivial R -1-Martin boundary.

Let $D$ be a connected bounded domain in ${{\mathbb{R}}^{n}}$ . Let $0\,<\,{{\mu }_{1}}\,\le \,{{\mu }_{2}}\,\le \,\cdots \,\le \,{{\mu }_{k}}\,\le \,\cdots $ be the eigenvalues of the following Dirichlet problem:

$$\left\{ \begin{align}& {{\Delta }^{2}}u(x)\,+\,V(x)u(x)\,=\,\mu \rho (x)u(x),x\in \,D \\& u{{|}_{\partial D}}\,=\,\frac{\partial u}{\partial n}\,{{|}_{\partial D}}\,=\,0, \\ \end{align} \right.$$

where $V(x)$ is a nonnegative potential, and $\rho (x)\,\in \,C(\overset{-}{\mathop{D}}\,)$ is positive. We prove the following inequalities:

$$\begin{align}& {{\mu }_{k+1}}\le \frac{1}{k}\sum\limits_{i=1}^{k}{\mu i+}{{[\frac{8(n+2)}{{{n}^{2}}}{{\left( \frac{\rho \max }{\rho \min } \right)}^{2}}]}^{1/2}}\times \frac{1}{k}{{\sum\limits_{i=1}^{k}{[{{\mu }_{i}}({{\mu }_{k+1}}-{{\mu }_{i}})]}}^{1/2}}, \\& \frac{{{n}^{2}}{{k}^{2}}}{8(n+2)}\le {{\left( \frac{\rho \max }{\rho \min } \right)}^{2}}[\sum\limits_{i=1}^{k}{\frac{\mu _{i}^{1/2}}{{{\mu }_{k+1}}-{{\mu }_{i}}}}]\times \sum\limits_{i=1}^{k}{\mu _{i}^{1/2}}. \\ \end{align}$$

Based on the theory of difference equations, we derive necessary and sufficient conditions for the existence of eigenvalues and inverses of Toeplitz matrices with five different diagonals. In the course of derivations, we are also able to derive computational formulas for the eigenvalues, eigenvectors and inverses of these matrices. A number of explicit formulas are computed for illustration and verification.

We investigate the perturbation of the palindromic eigenvalue problem for the matrix quadratic with A0,A1∈𝒞n×n and (where or H). The perturbation of eigenvalues in the context of general matrix polynomials, palindromic pencils, (semi-Schur) anti-triangular canonical forms and differentiation is discussed.

By means of a symbolic calculus for finding solutions of difference equations, we derive explicit eigenvalues, eigenvectors and inverses for tridiagonal Toeplitz matrices with four perturbed corners.