Performance Analysis of l_0 Norm Constraint Least Mean Square Algorithm

As one of the recently proposed algorithms for sparse system identification, $l_0$ norm constraint Least Mean Square ($l_0$-LMS) algorithm modifies the cost function of the traditional method with a penalty of tap-weight sparsity. The performance of $l_0$-LMS is quite attractive compared with its various precursors. However, there has been no detailed study of its performance. This paper presents all-around and throughout theoretical performance analysis of $l_0$-LMS for white Gaussian input data based on some reasonable assumptions. Expressions for steady-state mean square deviation (MSD) are derived and discussed with respect to algorithm parameters and system sparsity. The parameter selection rule is established for achieving the best performance. Approximated with Taylor series, the instantaneous behavior is also derived. In addition, the relationship between $l_0$-LMS and some previous arts and the sufficient conditions for $l_0$-LMS to accelerate convergence are set up. Finally, all of the theoretical results are compared with simulations and are shown to agree well in a large range of parameter setting.Comment: 31 pages, 8 figure

Mechanism of phonon localized edge modes

The phonon localized edge modes are systematically studied, and two conditions are proposed for the existence of the localized edge modes: (I) coupling between different directions ($x$, $y$ or $z$) in the interaction; (II) different boundary conditions in three directions. The generality of these two conditions is illustrated by different lattice structures: one-dimensional (1D) chain, 2D square lattice, 2D graphene, 3D simple cubic lattice, 3D diamond structure, etc; and with different potentials: valence force field model, Brenner potential, etc.Comment: 5 pages, 8 fig

Graphene-based tortional resonator from molecular dynamics simulation

Molecular dynamics simulations are performed to study graphene-based torsional mechanical resonators. The quality factor is calculated by $Q_{F}=\omega\tau/2\pi$, where the frequency $\omega$ and life time $\tau$ are obtained from the correlation function of the normal mode coordinate. Our simulations reveal the radius-dependence of the quality factor as $Q_{F}=2628/(22R^{-1}+0.004R^{2})$, which yields a maximum value at some proper radius $R$. This maximum point is due to the strong boundary effect in the torsional resonator, as disclosed by the temperature distribution in the resonator. Resulting from the same boundary effect, the quality factor shows a power law temperature-dependence with power factors bellow 1.0. The theoretical results supply some valuable information for the manipulation of the quality factor in future experimental devices based on the torsional mechanical resonator.Comment: (accepted by EPL). New email address for Jin-Wu Jiang after 22/Nov/2011: [email protected]

A theoretical study of thermal conductivity in single-walled boron nitride nanotubes

We perform a theoretical investigation on the thermal conductivity of single-walled boron nitride nanotubes (SWBNT) using the kinetic theory. By fitting to the phonon spectrum of boron nitride sheet, we develop an efficient and stable Tersoff-derived interatomic potential which is suitable for the study of heat transport in sp2 structures. We work out the selection rules for the three-phonon process with the help of the helical quantum numbers $(\kappa, n)$ attributed to the symmetry group (line group) of the SWBNT. Our calculation shows that the thermal conductivity $\kappa_{\rm ph}$ diverges with length as $\kappa_{\rm ph}\propto L^{\beta}$ with exponentially decaying $\beta(T)\propto e^{-T/T_{c}}$, which results from the competition between boundary scattering and three-phonon scattering for flexure modes. We find that the two flexure modes of the SWBNT make dominant contribution to the thermal conductivity, because their zero frequency locates at $\kappa=\pm\alpha$ where $\alpha$ is the rotational angle of the screw symmetry in SWBNT.Comment: accepted by PR

A Robust Zero-point Attraction LMS Algorithm on Near Sparse System Identification

The newly proposed $l_1$ norm constraint zero-point attraction Least Mean Square algorithm (ZA-LMS) demonstrates excellent performance on exact sparse system identification. However, ZA-LMS has less advantage against standard LMS when the system is near sparse. Thus, in this paper, firstly the near sparse system modeling by Generalized Gaussian Distribution is recommended, where the sparsity is defined accordingly. Secondly, two modifications to the ZA-LMS algorithm have been made. The $l_1$ norm penalty is replaced by a partial $l_1$ norm in the cost function, enhancing robustness without increasing the computational complexity. Moreover, the zero-point attraction item is weighted by the magnitude of estimation error which adjusts the zero-point attraction force dynamically. By combining the two improvements, Dynamic Windowing ZA-LMS (DWZA-LMS) algorithm is further proposed, which shows better performance on near sparse system identification. In addition, the mean square performance of DWZA-LMS algorithm is analyzed. Finally, computer simulations demonstrate the effectiveness of the proposed algorithm and verify the result of theoretical analysis.Comment: 20 pages, 11 figure

Why edge effects are important on the intrinsic loss mechanisms of graphene nanoresonators?

Molecular dynamics simulations are performed to investigate edge effects on the quality factor of graphene nanoresonators with different edge configurations and of various sizes. If the periodic boundary condition is applied, very high quality factors ($3\times10^{5}$) are obtained for all kinds of graphene nanoresonators. However, if the free boundary condition is applied, quality factors will be greatly reduced by two effects resulting from free edges: the imaginary edge vibration effect and the artificial effect. Imaginary edge vibrations will flip between a pair of doubly degenerate warping states during the mechanical oscillation of nanoresonators. The flipping process breaks the coherence of the mechanical oscillation of the nanoresonator, which is the dominant mechanism for extremely low quality factors. There is an artificial effect if the mechanical oscillation of the graphene nanoresonator is actuated according to an artificial vibration (non-natural vibration of the system), which slightly reduce the quality factor. The artificial effect can be eliminated by actuating the mechanical oscillation according to a natural vibration of the nanoresonator. Our simulations provide an explanation for the recent experiment, where the measured quality factor is low and varies between identical samples with free edges.Comment: accepted by J. Appl. Phy