High-Order Dual-Port Quasi-Absorptive Microstrip Coupled-Line Bandpass Filters

In this article, we present the first demonstration of distributed and symmetrical all-band quasi-absorptive filters that can be designed to arbitrarily high orders. The proposed quasi-absorptive filter consists of a bandpass section (reflective-type coupled-line filter) and absorptive sections (a matched resistor in series with a shorted quarter-wavelength transmission line). Through a detailed analysis, we show that the absorptive sections not only eliminate out-of-band reflections but also determine the passband bandwidth (BW). As such, the bandpass section mainly determines the out-of-band roll-off and the order of the filter can be arbitrarily increased without affecting the filter BW by cascading more bandpass sections. A set of 2.45-GHz one-, two-, and three-pole quasi-absorptive microstrip bandpass filters are designed and measured. The filters show simultaneous input and output absorption across both the passband and the stopband. Measurement results agree very well with the simulation and validate the proposed design concept

Exponential stabilization of a class of stochastic system with Markovian jump parameters and mode-dependent mixed time-delays

Copyright [2010] IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.In this technical note, the globally exponential stabilization problem is investigated for a general class of stochastic systems with both Markovian jumping parameters and mixed time-delays. The mixed mode-dependent time-delays consist of both discrete and distributed delays. We aim to design a memoryless state feedback controller such that the closed-loop system is stochastically exponentially stable in the mean square sense. First, by introducing a new Lyapunov-Krasovskii functional that accounts for the mode-dependent mixed delays, stochastic analysis is conducted in order to derive a criterion for the exponential stabilizability problem. Then, a variation of such a criterion is developed to facilitate the controller design by using the linear matrix inequality (LMI) approach. Finally, it is shown that the desired state feedback controller can be characterized explicitly in terms of the solution to a set of LMIs. Numerical simulation is carried out to demonstrate the effectiveness of the proposed methods.This work was supported in part by the Engineering and Physical Sciences Research Council (EPSRC) of the U.K. under Grant GR/S27658/01, the Royal Society of the U.K., the National 973 Program of China under Grant 2009CB320600, and the Alexander von Humboldt Foundation of Germany. Recommended by Associate Editor G. Chesi

An extended Kalman filtering approach to modeling nonlinear dynamic gene regulatory networks via short gene expression time series

Copyright [2009] IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.In this paper, the extended Kalman filter (EKF) algorithm is applied to model the gene regulatory network from gene time series data. The gene regulatory network is considered as a nonlinear dynamic stochastic model that consists of the gene measurement equation and the gene regulation equation. After specifying the model structure, we apply the EKF algorithm for identifying both the model parameters and the actual value of gene expression levels. It is shown that the EKF algorithm is an online estimation algorithm that can identify a large number of parameters (including parameters of nonlinear functions) through iterative procedure by using a small number of observations. Four real-world gene expression data sets are employed to demonstrate the effectiveness of the EKF algorithm, and the obtained models are evaluated from the viewpoint of bioinformatics

A low-bandgap dimeric porphyrin molecule for 10% efficiency solar cells with small photon energy loss

Dimeric porphyrin molecules have great potential as donor materials for high performance bulk heterojunction organic solar cells (OSCs). Recently reported dimeric porphyrins bridged by ethynylenes showed power conversion efficiencies (PCEs) of more than 8%. In this study, we design and synthesize a new conjugated dimeric D-A porphyrin ZnP2BT-RH, in which the two porphyrin units are linked by an electron accepting benzothiadiazole (BT) unit. The introduction of the BT unit enhances the electron delocalization, resulting in a lower highest occupied molecular orbital (HOMO) energy level and an increased molar extinction coefficient in the near-infrared (NIR) region. The bulk heterojunction solar cells with ZnP2BT-RH as the donor material exhibit a high PCE of up to 10% with a low energy loss (Eloss) of only 0.56 eV. The 10% PCE is the highest for porphyrin-based OSCs with a conventional structure, and this Eloss is also the smallest among those reported for small molecule-based OSCs with a PCE higher than 10% to date

Study of mechanical response in embossing of ceramic green substrate by micro-indentation

Micro-indentation test with a micro flat-end cone indenter was employed to simulate micro embossing process and investigate the thermo-mechanical response of ceramic green substrates. The laminated low temperature co-fired ceramic green tapes were used as the testing material ; the correlations of indentation depth versus applied force and applied stress at the temperatures of 25 degrees C and 75degrees C were studied. The results showed that permanent indentation cavities could be formed at temperatures ranging from 25 degrees C to 75 degrees C, and the depth of cavities created was applied force, temperature and dwell time dependent. Creep occurred and made a larger contribution to the plastic deformation at elevated temperatures and high peak loads. There was instantaneous recovery during the unloading and retarded recovery in the first day after indentation. There was no significant pile-up due to material flow observed under compression at the temperature up to 75 degrees C. The plastic deformation was the main cause for formation of cavity on the ceramic green substrate under compression. The results can be used as a guideline for embossing ceramic green substrates.Comment: Submitted on behalf of EDA Publishing Association (http://irevues.inist.fr/handle/2042/16838

Synchronization of coupled neutral-type neural networks with jumping-mode-dependent discrete and unbounded distributed delays

This is the post-print version of the Article. The official published version can be accessed from the links below - Copyright @ 2013 IEEE.In this paper, the synchronization problem is studied for an array of N identical delayed neutral-type neural networks with Markovian jumping parameters. The coupled networks involve both the mode-dependent discrete-time delays and the mode-dependent unbounded distributed time delays. All the network parameters including the coupling matrix are also dependent on the Markovian jumping mode. By introducing novel Lyapunov-Krasovskii functionals and using some analytical techniques, sufficient conditions are derived to guarantee that the coupled networks are asymptotically synchronized in mean square. The derived sufficient conditions are closely related with the discrete-time delays, the distributed time delays, the mode transition probability, and the coupling structure of the networks. The obtained criteria are given in terms of matrix inequalities that can be efficiently solved by employing the semidefinite program method. Numerical simulations are presented to further demonstrate the effectiveness of the proposed approach.This work was supported in part by the Royal Society of the U.K., the National Natural Science Foundation of China under Grants 61074129, 61174136 and 61134009, and the Natural Science Foundation of Jiangsu Province of China under Grants BK2010313 and BK2011598

Disorder effects on the spin-Hall current in a diffusive Rashba two-dimensional heavy-hole system

We investigate the spin-Hall effect in a two-dimensional heavy-hole system with Rashba spin-orbit coupling using a nonequilibrium Green's function approach. Both the short- and long-range disorder scatterings are considered in the self-consistent Born approximation. We find that, in the case of long-range collisions, the disorder-mediated process leads to an enhancement of the spin-Hall current at high heavy-hole density, whereas for short-range scatterings it gives a vanishing contribution. This result suggests that the recently observed spin-Hall effect in experiment is a result of the sum of the intrinsic and disorder-mediated contributions. We have also calculated the temperature dependence of spin-Hall conductivity, which reveals a decrease with increasing the temperature.Comment: 5 pages, 2 figures, Typos in the values of hole density correcte

Robust synchronization of an array of coupled stochastic discrete-time delayed neural networks

Copyright [2008] IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.This paper is concerned with the robust synchronization problem for an array of coupled stochastic discrete-time neural networks with time-varying delay. The individual neural network is subject to parameter uncertainty, stochastic disturbance, and time-varying delay, where the norm-bounded parameter uncertainties exist in both the state and weight matrices, the stochastic disturbance is in the form of a scalar Wiener process, and the time delay enters into the activation function. For the array of coupled neural networks, the constant coupling and delayed coupling are simultaneously considered. We aim to establish easy-to-verify conditions under which the addressed neural networks are synchronized. By using the Kronecker product as an effective tool, a linear matrix inequality (LMI) approach is developed to derive several sufficient criteria ensuring the coupled delayed neural networks to be globally, robustly, exponentially synchronized in the mean square. The LMI-based conditions obtained are dependent not only on the lower bound but also on the upper bound of the time-varying delay, and can be solved efficiently via the Matlab LMI Toolbox. Two numerical examples are given to demonstrate the usefulness of the proposed synchronization scheme