Lattice dynamical wavelet neural networks implemented using particle swarm optimization for spatio-temporal system identification

In this brief, by combining an efficient wavelet representation with a coupled map lattice model, a new family of adaptive wavelet neural networks, called lattice dynamical wavelet neural networks (LDWNNs), is introduced for spatio-temporal system identification. A new orthogonal projection pursuit (OPP) method, coupled with a particle swarm optimization (PSO) algorithm, is proposed for augmenting the proposed network. A novel two-stage hybrid training scheme is developed for constructing a parsimonious network model. In the first stage, by applying the OPP algorithm, significant wavelet neurons are adaptively and successively recruited into the network, where adjustable parameters of the associated wavelet neurons are optimized using a particle swarm optimizer. The resultant network model, obtained in the first stage, however, may be redundant. In the second stage, an orthogonal least squares algorithm is then applied to refine and improve the initially trained network by removing redundant wavelet neurons from the network. An example for a real spatio-temporal system identification problem is presented to demonstrate the performance of the proposed new modeling framework

On determination of the geometric cosmological constant from the OPERA experiment of superluminal neutrinos

The recent OPERA experiment of superluminal neutrinos has deep consequences in cosmology. In cosmology a fundamental constant is the cosmological constant. From observations one can estimate the effective cosmological constant $\Lambda_{eff}$ which is the sum of the quantum zero point energy $\Lambda_{dark energy}$ and the geometric cosmological constant $\Lambda$. The OPERA experiment can be applied to determine the geometric cosmological constant $\Lambda$. It is the first time to distinguish the contributions of $\Lambda$ and $\Lambda_{dark energy}$ from each other by experiment. The determination is based on an explanation of the OPERA experiment in the framework of Special Relativity with de Sitter space-time symmetry.Comment: 7 pages, no figure

Resonance-assisted parametric electron pump

We report a theoretical analysis of parametric quantum pumping of electric current which is aided by quantum resonance. The electron pump is realized by cyclic deformations of the barrier heights of a double-barrier quantum well. The pumped current is found to have large values near a resonant level, it has a rather sensitive dependence on such control parameters as the deformation strength, phase difference, and the well width, and it has a power-law temperature dependence.published_or_final_versio

Ultra-Orthogonal Forward Regression Algorithms for the Identification of Non-Linear Dynamic Systems

A new ultra-least squares (ULS) criterion is introduced for system identification. Unlike the standard least squares criterion which is based on the Euclidean norm of the residuals, the new ULS criterion is derived from the Sobolev space norm. The new criterion measures not only the discrepancy between the observed signals and the model prediction but also the discrepancy between the associated weak derivatives of the observed and the model signals. The new ULS criterion possesses a clear physical interpretation and is easy to implement. Based on this, a new Ultra-Orthogonal Forward Regression (UOFR) algorithm is introduced for nonlinear system identification, which includes converting a least squares regression problem into the associated ultra-least squares problem and solving the ultra-least squares problem using the orthogonal forward regression method. Numerical simulations show that the new UOFR algorithm can significantly improve the performance of the classic OFR algorithm

Identification of continuous-time models for nonlinear dynamic systems from discrete data

A new iOFR-MF (iterative orthogonal forward regression--modulating function) algorithm is proposed to identify continuous-time models from noisy data by combining the MF method and the iOFR algorithm. In the new method, a set of candidate terms, which describe different dynamic relationships among the system states or between the input and output, are first constructed. These terms are then modulated using the MF method to generate the data matrix. The iOFR algorithm is next applied to build the relationships between these modulated terms, which include detecting the model structure and estimating the associated parameters. The relationships between the original variables are finally recovered from the model of the modulated terms. Both nonlinear state-space models and a class of higher order nonlinear input–output models are considered. The new direct method is compared with the traditional finite difference method and results show that the new method performs much better than the finite difference method. The new method works well even when the measurements are severely corrupted by noise. The selection of appropriate MFs is also discussed

Strong decays of heavy baryons in Bethe-Salpeter formalism

In this paper we study the properties of diquarks (composed of $u$ and/or $d$ quarks) in the Bethe-Salpeter formalism under the covariant instantaneous approximation. We calculate their BS wave functions and study their effective interaction with the pion. Using the effective coupling constant among the diquarks and the pion, in the heavy quark limit $m_Q\to\infty$, we calculate the decay widths of $\Sigma_Q^{(*)}$ ($Q=c,b$) in the BS formalism under the covariant instantaneous approximation and then give predictions of the decay widths $\Gamma(\Sigma_b^{(*)}\to\Lambda_b+\pi)$.Comment: 41 pages, 1 figure, LaTex2e, typos correcte

Spin-valve effect in a carbon atomic wire

We report a theoretical investigation of the spin-valve effect in an atomic scale system, a carbon chain, generated by the presence of a magnetic field in the device leads. We found that there exists a cutoff energy beyond which the conductance of the device vanishes. This cutoff energy can be critically controlled by the relative orientation of the magnetic fields applied to the leads, so that an atomic scale spin valve can be achieved that switches off electric current when magnetic fields of left and right leads are anti-parallel. The physical origin of this transport behavior is found to be related to the wave-function overlap between the leads and the device scattering region.published_or_final_versio

Carbon nanotube parametric electron pump: A molecular device

We have analyzed the device properties of a single-wall metallic carbon nanotube operated as a parametric electron pump. It is found that a dc current can be pumped out from this molecular device by a cyclic variation of two gate voltages near the nanotube, in the absence of any bias voltage. Due to the particular electronic properties of the nanotube, the pumped current is found to show a remarkable parity effect near the resonant levels, with a rather sensitive dependence on the control parameters of the device such as deformation strength, the amplitude and the phase difference of the gate voltage.published_or_final_versio