A multi‐resolution multi‐classifier system for speaker verification

This paper describes a Speaker Verification System based on the use of multi resolution classifiers in order to cope with performance degradation due to natural variations of the excitation source and of the vocal tract. The different resolution representations of the speaker are obtained by considering multiple frame lengths in the feature extraction process and from these representations a single Pseudo‐Multi Parallel Branch (P‐MPB) Hidden Markov Model is obtained. In the verification process, different resolution representations of the speech signal are classified by multiple P‐MPB systems: the final decision is obtained by means of different combination techniques. The system based on the Weighted Majority Vote technique considerably outperforms baseline systems: improvements are between 15% and 38%. The execution time of the verification process is also evaluated and it proves to be very acceptable, thus allowing the use of the approach for applications in real time systems.     

The impact of multi‐group multi‐layer network structure on the performance of distributed consensus building strategies

We consider a structural approach to the consensus building problem in multi‐group multi‐layer (MGML) distributed sensor networks (DSNs) common in many natural and engineering applications. From among the possible network structures, we focus on bipartite graph structure as it represents a typical MGML structure and has a wide applicability in the real world. We establish exact conditions for consensus and derive a precise relationship between the consensus value and the degree distribution of nodes in a bipartite MGML DSN. We also demonstrate that for subclasses of connectivity patterns, convergence time and simple characteristics of network topology can be captured by explicit algebra. Direct inference of the convergence behavior of consensus strategies from MGML DSN structure is the main contribution of this paper. The insights gained from our analysis facilitate the design and development of large‐scale DSNs that meet specific performance criteria. Copyright © 2012 John Wiley & Sons, Ltd.     

A dual‐band eight‐antenna multi‐input multi‐output array for 5G metal‐framed smartphones

A dual‐band eight‐antenna array operating in the long‐term evolution (LTE) band 41 (2.496‐2.69 GHz) and 3.5‐GHz band (3.3‐3.7 GHz) for fifth‐generation (5G) metal‐framed smartphone is presented. The proposed dual‐band antenna array is composed of four identical dual‐antenna building blocks (DABBs). Each DABB consists of two identical antenna elements with a neutralization line between them. The antenna array is simulated, fabricated, and measured. The isolations are better than 10.5 dB and 11.0 dB in the low band (LB; LTE band 41) and high band (HB; 3.5‐GHz band). The total efficiencies are 41% to 54% and 46% to 64% in the two operation bands, respectively. In addition, the measured envelope correlation coefficients are less than 0.11 and 0.06, the calculated channel capacities are better than 34.5 and 36.3 bps/Hz in the LB and HB, respectively. Furthermore, four hand‐grip scenarios are investigated, and results show that proposed antenna array can maintain excellent multiple‐input multiple‐output performances in all scenarios.     

A necessary and sufficient condition for the controllability of single‐leader multi‐chain systems

In this work, the controllability of single‐leader multi‐agent systems with chain structures is studied. It is shown that the necessary and sufficient condition for the multi‐chain system to be controllable is that there exist no two chain lengths in the form ? ₁=i + k ₁(2i + 1) and ? ₂=i + k ₂(2i + 1), where i is some natural number and k ₁ and k ₂ some nonnegative integers. Using this condition, the author derives an upper bound based on the length of the longest chain and proves that if the number of chains exceeds this bound, the multi‐chain system must be uncontrollable. In addition, the author investigates an augmented system constructed by connecting some follower nodes of the multi‐chain system and obtains a sufficient condition for the augmented system to be uncontrollable. Finally, the author shows how to select a minimum number of additional leaders to make an uncontrollable multi‐chain system controllable. Numerical examples are provided to illustrate the results. Copyright © 2016 John Wiley & Sons, Ltd.     

Observer‐based leader‐following consensus of uncertain nonlinear multi‐agent systems

In this paper, the leader‐following consensus problem of uncertain high‐order nonlinear multi‐agent systems on directed graph with a fixed topology is studied, where it is assumed that the relative states of a follower and its neighbors are immeasurable and only the relative outputs are available. Nonlinear adaptive observers are firstly proposed for each follower to estimate the states of it and its neighbors, and an observer‐based distributed adaptive control scheme is constructed to guarantee that all followers asymptotically synchronize to a leader with tracking errors being semi‐globally uniform ultimate bounded. On the basis of algebraic graph theory and Lyapunov theory, the closed‐loop system stability analysis is conducted. Finally, numerical simulations are presented to illustrate the effectiveness and potential of the proposed new design techniques. Copyright © 2017 John Wiley & Sons, Ltd.     

Meta‐heuristic multi‐ and many‐objective optimization techniques for solution of machine learning problems

Recently, multi‐ and many‐objective meta‐heuristic algorithms have received considerable attention due to their capability to solve optimization problems that require more than one fitness function. This paper presents a comprehensive study of these techniques applied in the context of machine learning problems. Three different topics are reviewed in this work: (a) feature extraction and selection, (b) hyper‐parameter optimization and model selection in the context of supervised learning, and (c) clustering or unsupervised learning. The survey also highlights future research towards related areas.     

Robust multi‐response surface optimization: a posterior preference approach

This paper discusses the use of multi‐response surface optimization (MRSO) to select the preferred solutions from among various non‐dominated solutions (NDS). Since MSRO often involves conflicting responses, the decision‐maker's (DM) preference information should be included in the model in order to choose the preferred solutions. In some approaches this information is added to the model after the problem is solved. In contrast, this paper proposes a three‐stage method for solving the problem. In the first stage, a robust approach is used to construct a regression model. In the second phase, non‐dominated solutions are generated by the ε‐constraint approach. The robust solutions obtained in the third phase are NDS that are more likely to be Pareto solutions during consecutive iterations. A simulation study is then presented to show the effective performance of the proposed approach. Finally, a numerical example from the literature is brought in to demonstrate the efficiency and applicability of the proposed methodology.     

Output‐feedback adaptive consensus tracking control for a class of high‐order nonlinear multi‐agent systems

In this paper, an output‐feedback adaptive consensus tracking control scheme is proposed for a class of high‐order nonlinear multi‐agent systems. The agents are allowed to have unknown parameters, unknown nonlinearities, and input quantization simultaneously. The desired trajectory to be tracked is available for only a subset of agents, and only the relative outputs and the quantized inputs need to be measured or transmitted as signal exchange among neighbors regardless of the system order. By introducing a kind of high‐gain K‐filters and a smooth function, the effect among agents caused by the unknown nonlinearities is successfully counteracted, and all closed‐loop signals are proved to be globally uniformly bounded. Moreover, it is shown that the tracking errors converge to a residual set that can be made arbitrarily small. Simulation results on robot manipulators are presented to illustrate the effectiveness of the proposed scheme. Copyright © 2017 John Wiley & Sons, Ltd.     

Robust consensus tracking for a class of heterogeneous second‐order nonlinear multi‐agent systems

This paper deals with the robust consensus tracking problem for a class of heterogeneous second‐order nonlinear multi‐agent systems with bounded external disturbances. First, a distributed adaptive control law is proposed based on the relative position and velocity information. It is shown that for any connected undirected communication graph, the proposed control law solves the robust consensus tracking problem. Then, by introducing a novel distributed observer and employing backstepping design techniques, a distributed adaptive control law is constructed based only on the relative position information. Compared with the existing results, the proposed adaptive consensus protocols are in a distributed fashion, and the nonlinear functions are not required to satisfy any globally Lipschitz or Lipschitz‐like condition. Numerical examples are given to verify our proposed protocols. Copyright © 2014 John Wiley & Sons, Ltd.     

A compact multi‐band multi‐input multi‐output antenna for 4G/5G and IoT devices using theory of characteristic modes

A compact four element multi‐band multi‐input multi‐output (MIMO) antenna system for 4G/5G and IoT applications is presented in this paper. The proposed antenna is developed using the theory of characteristic modes helping in systematic design of MIMO antenna system. It consists of four L‐shaped planar inverted‐F antenna (PIFA) elements each operating at 3.5, 12.5, and 17 GHz bands with the bandwidth of 359 MHz, 1 GHz, and more than 3.7 GHz, respectively. The proposed antenna system is suitable for both 4G/5G and internet of things devices as it shows the satisfactory MIMO system performance. Good isolation characteristics are observed by implementing complimentary Metamaterial structure on the ground plane resulting in isolation level lower than ?21 dB between the antenna elements. The proposed antenna is fabricated and experimental results are also presented and discussed.     

Empirical evaluation of a decision support model for adopting software product line engineering

ContextThe software product line engineering (SPLE) community has provided several different approaches for assessing the feasibility of SPLE adoption and selecting transition strategies. These approaches usually include many rules and guidelines which are very often implicit or scattered over different publications. Hence, for the practitioners it is not always easy to select and use these rules to support the decision making process. Even in case the rules are known, the lack of automated support for storing and executing the rules seriously impedes the decision making process.ObjectiveWe aim to evaluate the impact of a decision support system (DSS) on decision-making in SPLE adoption. In alignment with this goal, we provide a decision support model (DSM) and the corresponding DSS.MethodFirst, we apply a systematic literature review (SLR) on the existing primary studies that discuss and present approaches for analyzing the feasibility of SPLE adoption and transition strategies. Second, based on the data extraction and synthesis activities of the SLR, the required questions and rules are derived and implemented in the DSS. Third, for validation of the approach we conduct multiple case studies.ResultsIn the course of the SLR, 31 primary studies were identified from which we could construct 25 aspects, 39 questions and 312 rules. We have developed the DSS tool Transit-PL that embodies these elements.ConclusionsThe multiple case study validation showed that the adoption of the developed DSS tool is justified to support the decision making process in SPLE adoption.     

MRMOGA: a new parallel multi‐objective evolutionary algorithm based on the use of multiple resolutions

In this paper, we introduce MRMOGA (Multiple Resolution Multi‐Objective Genetic Algorithm), a new parallel multi‐objective evolutionary algorithm which is based on an injection island approach. This approach is characterized by adopting an encoding of solutions which uses a different resolution for each island. This approach allows us to divide the decision variable space into well‐defined overlapped regions to achieve an efficient use of multiple processors. Also, this approach guarantees that the processors only generate solutions within their assigned region. In order to assess the performance of our proposed approach, we compare it to a parallel version of an algorithm that is representative of the state‐of‐the‐art in the area, using standard test functions and performance measures reported in the specialized literature. Our results indicate that our proposed approach is a viable alternative to solve multi‐objective optimization problems in parallel, particularly when dealing with large search spaces. Copyright © 2006 John Wiley & Sons, Ltd.     

Design and optimization of multi‐band Wilkinson power divider

In this paper, a general and easy procedure for designing the symmetrical Wilkinson power divider that achieves equal‐power split at N arbitrary frequencies is introduced. Each quarter‐wave branch in the conventional Wilkinson divider is replaced by N sections of transmission lines, and the isolation between the output ports is achieved by using N resistors. The design parameters are the characteristic impedances and lengths of the N transmission line sections, and the N isolation resistors. The even–odd modes of analysis are used to derive the design equations. Closed‐form expressions, which are suitable for CAD purposes, are derived for the dual‐band divider. For N ≥ 3, closed‐form expressions are not available, and therefore, the powerful particle swarm optimization method is used to obtain the design parameters. Examples of the dual‐, triple‐, and quad‐band dividers are presented to validate the proposed design procedure, and the results are compared, wherever possible, with published results using other methods. © 2007 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2008.     

Parallelizing and optimizing large‐scale 3D multi‐phase flow simulations on the Tianhe‐2 supercomputer

The lattice Boltzmann method (LBM) is a widely used computational fluid dynamics method for flow problems with complex geometries and various boundary conditions. Large‐scale LBM simulations with increasing resolution and extending temporal range require massive high‐performance computing (HPC) resources, thus motivating us to port it onto modern many‐core heterogeneous supercomputers like Tianhe‐2. Although many‐core accelerators such as graphics processing unit and Intel MIC have a dramatic advantage of floating‐point performance and power efficiency over CPUs, they also pose a tough challenge to parallelize and optimize computational fluid dynamics codes on large‐scale heterogeneous system. In this paper, we parallelize and optimize the open source 3D multi‐phase LBM code openlbmflow on the Intel Xeon Phi (MIC) accelerated Tianhe‐2 supercomputer using a hybrid and heterogeneous MPI+OpenMP+Offload+single instruction, mulitple data (SIMD) programming model. With cache blocking and SIMD‐friendly data structure transformation, we dramatically improve the SIMD and cache efficiency for the single‐thread performance on both CPU and Phi, achieving a speedup of 7.9X and 8.8X, respectively, compared with the baseline code. To collaborate CPUs and Phi processors efficiently, we propose a load‐balance scheme to distribute workloads among intra‐node two CPUs and three Phi processors and use an asynchronous model to overlap the collaborative computation and communication as far as possible. The collaborative approach with two CPUs and three Phi processors improves the performance by around 3.2X compared with the CPU‐only approach. Scalability tests show that openlbmflow can achieve a parallel efficiency of about 60% on 2048 nodes, with about 400K cores in total. To the best of our knowledge, this is the largest scale CPU‐MIC collaborative LBM simulation for 3D multi‐phase flow problems. Copyright © 2015 John Wiley & Sons, Ltd.     

Robust consensus for uncertain multi‐agent systems with discrete‐time dynamics

This paper investigates robust consensus for multi‐agent systems with discrete‐time dynamics affected by uncertainty. In particular, the paper considers multi‐agent systems with single and double integrators, where the weighted adjacency matrix is a polynomial function of uncertain parameters constrained into a semialgebraic set. Firstly, necessary and sufficient conditions are provided for robust consensus based on the existence of a Lyapunov function polynomially dependent on the uncertainty. In particular, an upper bound on the degree required for achieving necessity is provided. Secondly, a necessary and sufficient condition is provided for robust consensus with single integrator and nonnegative weighted adjacency matrices based on the zeros of a polynomial. Lastly, it is shown how these conditions can be investigated through convex programming by exploiting linear matrix inequalities and sums of squares of polynomials. Some numerical examples illustrate the proposed results. Copyright © 2013 John Wiley & Sons, Ltd.     

On the multi‐input second‐order sliding mode control of nonlinear uncertain systems

This note addresses the multi‐input second‐order sliding mode control design for a class of nonlinear multivariable uncertain dynamics. Among the most important peculiarities of the considered control problem, the considered sliding vector variable has a uniform vector relative degree [2,2, … ,2] with respect to the vector control variable, and only the sign of the sliding vector and of its derivative are available for feedback. Additionally, the symmetric part of the state‐dependent control matrix is supposed to be positive definite. Under some further mild restrictions on the uncertain system's dynamics, a control algorithm that realizes a multi‐input version of the ‘twisting’ second‐order sliding mode control algorithm is suggested. Simple controller tuning conditions are derived by means of a constructive Lyapunov analysis, which demonstrates that the suggested control algorithm guarantees the semiglobal asymptotic convergence to the sliding manifold. Simulation results, which confirm the good performance of the proposed scheme and investigate the actual accuracy obtained under the discrete‐time implementation effects, are given. Copyright © 2011 John Wiley & Sons, Ltd.     

Procedures for estimating desirable initial states of a production line: a comparative study

Two procedures for estimating initial states of a production line that ensure the line has a high probability of meeting the specified production target during a scheduled production shift are presented. The problem of determining desirable initial states is important in low variety, high volume production systems such as those from the automobile industry. One procedure is derived from design of experiments (DOE) theory whereas the other uses a genetic algorithm (GA). In the study it was determined that both procedures are straightforward to implement and produce good solutions to the problem. The results from the procedures are compared and their benefits and disadvantages are discussed.     

Gradient‐free method for distributed multi‐agent optimization via push‐sum algorithms

This paper studies the problem of minimizing the sum of convex functions that all share a common global variable, each function is known by one specific agent in the network. The underlying network topology is modeled as a time‐varying sequence of directed graphs, each of which is endowed with a non‐doubly stochastic matrix. We present a distributed method that employs gradient‐free oracles and push‐sum algorithms for solving this optimization problem. We establish the convergence by showing that the method converges to an approximate solution at the expected rate of , where T is the iteration counter. A numerical example is also given to illustrate the proposed method. Copyright © 2014 John Wiley & Sons, Ltd.     

Distributed consensus and tracking control of second‐order time‐varying nonlinear multi‐agent systems

In this paper, the distributed consensus and tracking protocols are developed for the second‐order time‐varying nonlinear multi‐agent systems under general directed graph. Firstly, the consensus and tracking problems can be converted into a conventional stabilization control problem. Then a state transformation is employed to deal with the time‐varying nonlinearities. By choosing an appropriate time‐varying parameter and coupling strengths, exponential consensus and tracking of second‐order nonlinear multi‐agent systems can be achieved. Finally, a simulation is given to illustrate the effectiveness of the proposed consensus and tracking protocols. Copyright © 2017 John Wiley & Sons, Ltd.     

Portable multi‐gray scale video playing scheme for high‐performance electrowetting displays

Electrowetting display technology is realized by tuning the surface energy of a hydrophobic surface by applying a voltage based on electrowetting mechanism. Electrowetting displays have favorable optical properties combined with reflective paper‐like performance. It has been successfully demonstrated in reflective mode with high switching speed. In this paper, we propose a portable driving scheme that can display 4‐bit gray scale dynamic video using an active matrix electrowetting display. The proposed driving scheme includes an electronic system and a dynamic driving waveform design. High‐performance multi‐gray video playing and quick response were obtained for a Quarter Video Graphics Array electrowetting display cell fabricated by our team.