In this paper, the direct Trefftz method is applied to solve the free-vibration problem of a membrane. In the direct Trefftz method, there exists no spurious eigenvalue. However, an ill-posed nature of numerical instability encountered in the direct Trefftz method requires some treatments. The Tikhonov's regularization method and generalized singular-value decomposition method are used to deal ...

In this paper we present a general approach for reducing switching activity on the algorithmic level. We concentrate on iterative algorithms that are suitable for an implementation on parallel processor arrays. The reduction is substantially reached by avoiding operations that hardly contribute to the convergence of the implemented algorithm. Our general approach is exemplified on the implement...

Multidimensional proton nmr spectra of biomolecules dissolved in aqueous solutions are usually contaminated by an intense water artifact. We discuss the application of the generalized eigenvalue decomposition (GEVD) method using a matrix pencil to solve the blind source separation problem of removing the intense solvent peak and related artifacts. 2D NOESY spectra of simple solutes as well as d...

We study the eigenspace with largest eigenvalue of the Laplacian matrix of a simple graph. We find a surprising connection of this space with the theory of modular decomposition of Gallai, whereby eigenvectors can be used to discover modules. In the case of comparability graphs, eigenvectors are used to induce orientations of the graph, and the set of these induced orientations is shown to (rec...

We consider the estimation of the spectral density matrix of a periodically correlated (PC) time series (also known as cyclostationary time series). We use the well known relation between the spectral density matrix of a periodically correlated time series and a stationary vector time series (Gladyshev, 1961). The spectral matrix of the stationary vector time series is estimated using the eigen...

We study the eigenspace with largest eigenvalue of the Laplacian matrix of a simple graph. We find a surprising connection of this space with the theory of modular decomposition of Gallai, whereby eigenvectors can be used to discover modules. In the case of comparability graphs, eigenvectors are used to induce orientations of the graph, and the set of these induced orientations is shown to (rec...

I consider the problem of calculating learning curves (i.e., average generalization performance) of Gaussian processes used for regression. A simple expression for the generalization error in terms of the eigenvalue decomposition of the covariance function is derived, and used as the starting point for several approximation schemes. I identify where these become exact, and compare with existing...

We report on phase-shifted holographic interferogram demodulation by singular-value decomposition. Numerical processing of optically acquired interferograms over several modulation periods was performed in two steps: (1) rendering of off-axis complex-valued holograms by Fresnel transformation of the interferograms; and (2) eigenvalue spectrum assessment of the lag-covariance matrix of hologram ...

A stronger and general sufficient condition for the asymptotic normality of MIMO channel eigenvalues and its capacity is given. Physical interpretation of this condition is discussed. Simple alternative conditions, which do not require eigenvalue decomposition, are proposed. It is demonstrated that some popular correlation matrix models satisfy these conditions. In many cases, the convergence t...