The "Eigen cation", H3O+(H2O)3, is the most prevalent protonated water structure in the liquid phase and the most stable gas-phase isomer of the H+(H2O)4 cluster. Nevertheless, its 50 K argon predissociation vibrational spectrum contains unexplainable low frequency peak(s). We have simulated the IR spectra of 10 gas-phase H+(H2O)4 isomers, that include zero to three argon ligands, using dipole ...

The Eigen-FLS approach using an eigenspace-based scheme for fast fuzzy logic system (FLS) establishments has been attempted successfully in speech pattern recognition. However, speech pattern recognition by Eigen-FLS will still encounter a dissatisfactory recognition performance when the collected data for eigen value calculations of the FLS eigenspace is scarce. To tackle this issue, this pape...

Free high-frequency longitudinal vibrations of an inhomogeneous nanosized rod are studied on the basis nonlocal theory elasticity. The upper part spectrum with wavelength comparable to internal characteristic dimension a nanorod is examined. An equations in integral form Helmholtz kernel, incorporating both local and phases, used as constitutive one. original integro-differential equation reduc...

Spectrum sensing is a fundamental component in cognitive radio. New sensing methods are proposed based on the principal component values of the received signal at the secondary users. In particular, two sensing algorithms are suggested, one of the algorithm is based on the ratio of the principal component’s maximum eigen value to principal component’s minimum eigen value called as Maximum Minim...

The anomalies of the temperature dependences of the logarithmic decrement and eigen frequency of the free damped vibrations for Fe-Co-Ni-Ti shape memory alloys were first found in the vicinity of the reverse ay martensitic transformation. It was shown the damping capacity in the alloys investigated is comparable with that for TiNi based alloys.

The Generalized Hebbian Algorithm is shown to be equivalent to Latent Semantic Analysis, and applicable to a range of LSAstyle tasks. GHA is a learning algorithm which converges on an approximation of the eigen decomposition of an unseen frequency matrix given observations presented in sequence. Use of GHA allows very large datasets to be processed.