Learning-based compressed sensing for infrared image super resolution

This paper presents an infrared image super-resolution method based on compressed sensing (CS). First, the reconstruction model under the CS framework is established and a Toeplitz matrix is selected as the sensing matrix. Compared with traditional learning-based methods, the proposed method uses a set of sub-dictionaries instead of two coupled dictionaries to recover high resolution (HR) images. And Toeplitz sensing matrix allows the proposed method time-efficient. Second, all training samples are divided into several feature spaces by using the proposed adaptive k-means classification method, which is more accurate than the standard k-means method. On the basis of this approach, a complex nonlinear mapping from the HR space to low resolution (LR) space can be converted into several compact linear mappings. Finally, the relationships between HR and LR image patches can be obtained by multi-sub-dictionaries and HR infrared images are reconstructed by the input LR images and multi-sub-dictionaries. The experimental results show that the proposed method is quantitatively and qualitatively more effective than other state-of-the-art methods.     

Nonlinear FCS-MPC strategy of NPC/H-5 L inverter based on satisfactory optimization algorithm

In the design of the cost function in the nonlinear finite control set model predictive control (FCS-MPC) system, the traditional method based on weighting factors demonstrates some limitations, such as the weighting factors adjusting and heavy predictive calculation due to the increased number of voltage vectors applied in controlling multilevel converters. This paper proposes a simplified FCS-MPC method based on common mode voltage satisfactory optimization, which could considerably reduce the predictive calculation by the optimized switch combination and simplify the cost function design. Moreover, satisfactory optimization is adopted to achieve the accuracy control of common-mode voltage amplitude without adjusting process of weighting factors. The simulation and experimental results verify the feasibility of this control strategy.     

Extraordinary acoustic transmission,symmetry, blaschke products and resonators

The phenomenon of extraordinary acoustic transmission ( eat) in a resonator, which has recently been investigated experimentally, is studied theoretically. It is shown that the combination of a single propagating mode and a symmetry orthogonal to the direction of propagation for a resonator leads to eat. This is accomplished by decomposing the problem using symmetry, the Blaschke product and the properties of functions of a single complex variable which have modulus one on the real axis. The conditions of a resonator requires that the solution has singularities in the analytic extension to complex frequencies (resonances) and it is precisely near these resonances that we observe eat. The condition of a Blaschke product requires that there is a zero at the complex conjugate of the singularity and eat occurs when the solution on the real axis passes between these complex conjugate pairs of poles and zeros. A detailed numerical study of the problem is conducted and we show that once the single mode of propagation or the symmetry is broken then eat (at least perfect transmission) no longer holds generally.     

Structural,magnetic and optical properties of vanadium doped zinc oxide: Systematic first-principles investigations

The electronic structural, magnetic and optical properties of pure and V-doped ZnO are investigated by first-principles calculations based on the density functional theory. With the introduction of V atoms, the spin-splitting near the Fermi level leads to a net magnetic moment of the system. A significant possibility of room temperature ferromagnetism (RTFM) originated from the Ruderman–Kittel–Kassuya–Yosida (RKKY) exchange is predicted. Oxygen vacancy is positive to enhance the ferromagnetism while zinc vacancy is negative. With respect to the optical properties, the presence of V atoms was found to have an obvious influence on the transmittivity, especially in the low energy region. A slight V-doping can keep a high optical transmission and smoothly modulate the optical bandgap.     

Convergence and permanence of a delayed Nicholson’s Blowflies model with feedback control

In this paper, we study a generalized Nicholson??s Blowflies model with feedback control and multiple time-varying delays. Under proper conditions, we employ a novel proof to establish some criteria to guarantee the global exponential convergence and permanence of this model. Moreover, we give two examples to illustrate our main results.     

Localization of diffusion sources in complex networks with sparse observations

Locating sources in a large network is of paramount importance to reduce the spreading of disruptive behavior. Based on the backward diffusion-based method and integer programming, we propose an efficient approach to locate sources in complex networks with limited observers. The results on model networks and empirical networks demonstrate that, for a certain fraction of observers, the accuracy of our method for source localization will improve as the increase of network size. Besides, compared with the previous method (the maximum–minimum method), the performance of our method is much better with a small fraction of observers, especially in heterogeneous networks. Furthermore, our method is more robust against noise environments and strategies of choosing observers.     

A mathematical model for the admission process in intensive care units

A mathematical model is given for the admission process in Intensive Care Units (ICUs). It is shown that the model exhibits bistability for certain values of its parameters. In particular, it is observed that in a two-dimensional parameter space, two saddle-node bifurcation curves terminate at a single point of the cusp bifurcation, creating an enclosed region in which the model has one unstable and two stable states. It is shown that in the presence of bistability, variations in the value of parameters may lead to undesired outcomes in the admission process as the value of state variables abruptly changes. Using numerical simulations, it is also discussed how such outcomes can be avoided by appropriately adjusting the parameter values.     

A new epidemic model of computer viruses

This paper addresses the epidemiological modeling of computer viruses. By incorporating the effect of removable storage media, considering the possibility of connecting infected computers to the Internet, and removing the conservative restriction on the total number of computers connected to the Internet, a new epidemic model is proposed. Unlike most previous models, the proposed model has no virus-free equilibrium and has a unique endemic equilibrium. With the aid of the theory of asymptotically autonomous systems as well as the generalized Poincare–Bendixson theorem, the endemic equilibrium is shown to be globally asymptotically stable. By analyzing the influence of different system parameters on the steady number of infected computers, a collection of policies is recommended to prohibit the virus prevalence.     

Objective Bayesian analysis of the Frechet stress–strength model

Several reference priors and a general form of matching priors are derived for a stress–strength system, and it is concluded that none of the reference priors is a matching prior. The study shows that the matching prior performs better than Jeffreys prior and reference priors in meeting the target coverage probabilities.     

Global exponential stability for quaternion-valued recurrent neural networks with time-varying delays

Nonlinear Dynamics - In this paper, we employ a novel method for solving the problem of the global exponential stability of quaternion-valued recurrent neural networks (QVNNs) with time-varying...