this paper is devoted to the spectral theory (more precisely, tothe variational theory of the spectrum) of guided waves in anelastic half cylinder.  we use variational methods to investigateseveral aspects of propagating waves, including localization (seefigure 1), existence criteria and the formulas to find them. weapproach the problem using two complementary methods: thevariational methods fo...

this paper is devoted to the spectral theory (more precisely, tothe variational theory of the spectrum) of guided waves in anelastic half cylinder.  we use variational methods to investigateseveral aspects of propagating waves, including localization (seefigure 1), existence criteria and the formulas to find them. weapproach the problem using two complementary methods: thevariational methods fo...

A reduction of the transmission eigenvalue problem for multiplicative sign-definite perturbations of elliptic operators with constant coefficients to an eigenvalue problem for a non-selfadjoint compact operator is given. Sufficient conditions for the existence of transmission eigenvalues and completeness of generalized eigenstates for the transmission eigenvalue problem are derived. In the trac...

A new, efficient, and stable algorithm for computing all the eigenvalues and eigenvectors of the problem Ax = λBx, where A is symmetric indefinite and B is symmetric positive definite, is proposed.

This paper introduces Stochastic Definite Clause Grammars, a stochastic variant of the wellknown Definite Clause Grammars. The grammar formalism supports parameter learning from annotated or unannotated corpora and provides a mechanism for parse selection by means of statistical inference. Unlike probabilistic contextfree grammars, it is a context-sensitive grammar formalism and it has the abil...

Kernel methods are widely used in statistical learning techniques. We recently introduced a general kernel framework based on weighted transducers or rational relations, rational kernels, to extend kernel methods to the analysis of variable-length sequences or more generally weighted automata. These kernels are efficient to compute and have been successfully used in applications such as spoken-...

Proper selection of material in manufacturing firms is a vital role of designer depending upon the different era of application. The material selection problem is very complex and challenging task today. Erroneous cull of material frequently leads to astronomically immense cost involution, and finally drives towards unfortunate component or product breakdown. Thus, the designer necessitates dis...

In this paper, we solve unconstrained optimization problem using a free line search steepest descent method. First, we propose a double parameter scaled quasi Newton formula for calculating an approximation of the Hessian matrix. The approximation obtained from this formula is a positive definite matrix that is satisfied in the standard secant relation. We also show that the largest eigen value...

In this paper we will present an adaptive wavelet scheme to solvethe generalized Stokes problem. Using divergence free wavelets, theproblem is transformed into an equivalent matrix vector system, thatleads to a positive definite system of reduced size for thevelocity. This system is solved iteratively, where the applicationof the infinite stiffness matrix, that is sufficiently compressible,is r...

Abstract Asymmetry in the synaptic interactions between neurons plays a crucial role determining memory storage and retrieval properties of recurrent neural networks. In this work, we analyze problem storing random memories network connected by matrix with definite degree asymmetry. We study corresponding satisfiability clustering transitions space solutions constraint satisfaction associated f...