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Device management in large networks is of growing importance to network administrators and security analysts alike. The composition of devices on a network can help forecast future traffic demand as well as identify devices that may pose a security risk. However, the sheer number and diversity of devices that comprise most modern networks have vastly increased the management complexity. Motivated by a need for an encryption-invariant device management strategy, we use affiliation graphs to develop a methodology that reveals key insights into the devices acting on a network using only the source and destination IP addresses. Through an empirical analysis of the devices on a university campus network, we provide an example methodology to infer a device’s characteristics (e.g., operating system) through the services it communicates with via the Internet.

We propose an H-/L∞ fault detection observer for linear parameter varying systems with unknown disturbance and actuator fault. The fault detection observer is designed to enhance the fault sensitivity of residual and attenuate the effect of disturbance on residual such that timely and robust fault detection is achieved. The observer design method is carried out in the finite frequency domain and the design conditions are expressed as a set of linear matrix inequalities. By using L∞ performance index to measure the effect of disturbance on residual, the fault detection observer exhibits a peak-to-peak disturbance attenuation performance, which can provide a dynamic threshold for residual evaluation in fault detection. Numerical simulations are conducted to verify the effectiveness of the proposed method.

Summary This paper is concerned with the reliable H∞ static output control of linear time-varying delay systems with sensor faults. Time-varying delay is tackled by the input–output transformation and the resulting closed-loop system lies in the framework of scaled small gain. Some techniques are developed to separate the coupling among the Lyapunov matrix, input matrix, control gain matrix, and output matrix. Based on a relaxed Lyapunov–Krasovskii functional, sufficient conditions for the desired static output controller design with the required H∞ performance level are proposed by means of linear matrix inequalities. The effectiveness of the proposed method is validated by two examples. Copyright © 2016 John Wiley & Sons, Ltd.

In this paper, a controller is designed for a group of cooperative robots to achieve the stable displacements. Communication network among the robots is assumed unavailable and each robot can only measure the displacements relative to their neighbours. The controller will enable the robots to move to a predefined formation or a special formation under a suitable protocol which we will design. We will discuss the effect of different sizes of the multi-vehicle system and conduct simulations to verify the effectiveness of the proposed controller and the formation protocols.

Many assignment problems cannot be solved to optimality in real-time. The existing literature tends to focus on the development of handcrafted heuristics that exploit the structure of a particular assignment problem. We instead seek a general-purpose approach that can automatically learn such heuristics. In this work, we present a deep learning approach that is designed to automatically learn heuristics for a large class of assignment problems. We demonstrate the effectiveness of our approach on the weapon-target assignment (WTA) problem, which is nonlinear and NP-complete. We take non-trivial WTA problem instances and show that our approach reliably finds near-optimal solutions in milliseconds.

In this paper, the predictive and optimal control problem of energy consumption is investigated for hybrid vehicle systems. In order to make the energy usage more efficient (minimizing the energy demand), observations of drivers' behavior are taken into consideration in analysis and predictive control design. Realworld driving experiments are conducted to illustrate the effective and accuracy of the proposed new design techniques.

As the reliance on the Internet and its constituent applications increase, so too does the value in exploiting these networking systems. Methods to detect and mitigate these threats can no longer rely on singular facets of information, they must be able to adapt to new threats by learning from a diverse range of information. For its ability to learn complex inferences from large data sources, deep learning has become one of the most publicised techniques of machine learning in recent years. This chapter aims to investigate a deep learning technique typically used for image classification, the convolutional neural network (CNN), and how its methodology can be adapted to detect and classify malicious network traffic.

Complex nonlinearity and strong coupling in the pitch-yaw-roll of a rotorcraft make it difficult for the attitude control of unmanned aerial vehicles, especially in the presence of wind disturbances and plant uncertainties. To confront these problems, this paper presents a control scheme of two sequential steps, structural parameter determination and robust controller design, in order to achieve the desired attitude regulation performance and disturbance attenuation capability. For the structural parameter design, key structural parameters are specified such that the open-loop transfer functions, from torque inputs to angular velocities, exhibit positive-real properties in particular frequency ranges to incorporate robustness into the controller design. Then, a dual-loop structured controller is designed using dynamic inversion approaches and singular perturbation techniques. The controlled inner loop provides adequate decoupling such that the outer loop may control each Euler angle independently, and proportional-derivative control is used in each outer loop to achieve a desired attitude tracking performance. The effectiveness of the control scheme is verified via an attitude tracking example.

Summary In this paper, a protocol and a control law are designed for a single robot so that a team of such robots can interact and cooperate to reach the displacements from an eligible reference formation. Each robot is equipped with displacement sensors of limited sensing ranges. Communication channels are assumed to be unavailable to the team, and each robot works in stealth mode. The team is scalable such that new robots can be recruited, and existing robots can be dismissed. In order for the team size to be scalable, the extended formation based on relative displacement is established as the reference formation. Thus, using the extended formation as a reference, the control law and the protocol could be flexible. As potential conflicts deflect the robot team from the desired formation, the control law is designed to expose the conflicts to the involved neighboring robots such that the protocol can resolve them. A numerical example is given to illustrate how an extended formation is designed, and a simulation example is conducted to demonstrate the performance and merits of the proposed techniques. Copyright © 2016 John Wiley & Sons, Ltd.

Y-junctions are often adopted to design diplexers since their characteristics can conveniently satisfy the constraints for optimum performance of diplexer design. In order to decrease the size of the Y-junction diplexer, the two branches of the junction can be bent to yield parallel outputs. However, this parallel configuration can degrade the characteristic of the Y-junction. In this letter, two improved novel configurations of Y-junction diplexers are introduced, analyzed with an efficient mode-matching based approach and optimized for best performance. For illustration, the method is applied to two diplexers in substrate-integrated waveguide technology realized using band-pass post filters. For each diplexer, the fractional bandwidths of operation for the up and down channels are 2.70% and 2.44% at 7.4 GHz and 8.2 GHz respectively. The viability of the design approach is validated by full-wave finite-element simulations using Ansys HFSS and measurements on the two fabricated diplexers. © 2016 Wiley Periodicals, Inc. Microwave Opt Technol Lett 58:1384–1388, 2016

In situations where robots need to keep electromagnetic silent in a formation, communication channels become unavailable. Moreover, as passive displacement sensors are used, limited sensing ranges are inevitable due to power insufficiency and limited noise reduction. To address the formation control problem for a scalable team of robots subject to the above restrictions, a flexible strategy is necessary. In this paper, under the assumption that the data transmission among the robots is not available, a novel controller and a protocol are designed that do not rely on communication. As the controller only drives the robots to a partially desired formation, a distributed coordination protocol is proposed to resolve the imperfections. It is shown that the effectiveness of the controller and the protocol rely on the formation connectivity, and a condition is given on the sensing range. Simulations are conducted to illustrate the feasibility and advantages of the new design scheme developed.

In this note, a robust constrained control scheme is proposed for multi-input and multi-output (MIMO) cascade nonlinear systems with unknown external disturbance and input saturation. To efficiently observe unknown external disturbance, a novel sliding mode disturbance observer (SMDO) with finite time convergence performance is presented. A robust constrained control scheme is developed for MIMO nonlinear systems based on backstepping control techniques and the disturbance estimate of the SMDO. With the first-order sliding mode differentiator introduced to compute the derivatives of virtual control laws, the computational burden in backstepping control is reduced for a MIMO cascade nonlinear system. Numerical simulation results are presented to show the effectiveness of the proposed robust constrained control scheme.

This letter presents a novel concept of band-pass filter realized with metal posts in folded substrate-integrated waveguide (FSIW) technology, together with an efficient specific design procedure. As a first step, it is shown that a particular dimension of the middle vane in the FSIW yields an equivalence to a dielectric-loaded unfolded rectangular waveguide. This equivalence is investigated by comparing the modal dispersion characteristics in both folded and unfolded structures. A direct comparison of the posts placed in the FSIW and in the equivalent unfolded waveguide then further confirms their similar characteristics. As a result, the classical mode-matching method (MMM), straightforwardly applied in the equivalent unfolded structure, can be used to efficiently design a post filter in FSIW technology. For illustration, the method is applied to realize a $5^{th}$ -order Chebyshev band-pass post FSIW filter with a center frequency of 7GHz and a fractional bandwidth of 5.71%. The viability and efficiency of the design approach is successfully validated by finite-element simulations and measurements.

In this article, we investigate the performances of different learning approaches for decentralised non-cooperative multi-agent system applied to defend a high-value target from multiple aerial threats for an air defence application. We focus mainly on reinforcement learning (RL) techniques for protection against known fully observable threats with high mobility. We implement two well-known algorithms from two different approaches, including the regret matching (online learning) and the Q-learning with artificial neural networks (offline learning), and compare them to understand their efficiency. Numerical experiments are provided to illustrate the performances of the different learning algorithms under various approaching directions of the threat as well as under collision avoidance with both static and moving obstacles. Finally, discussions for further improvements of these RL techniques are also provided.

As the sophistication of cyber malicious attacks increase, so too must the techniques used to detect and classify such malicious traffic in these networks. Deep learning has been deployed in many application domains as it is able to learn patterns from large feature sets. Given that the implementation of deep learning for network traffic classification is only just starting to emerge, the question of how best to utilise and represent network data to such a classifier still remains. This paper addresses this question by devising and evaluating three different ways of representing data to a deep neural network in the context of malicious traffic classification. We show that although deep learning does not show significant improvement over other machine learning techniques using metadata features, its use on payload data highlights the potential for deep learning to be incorporated into novel deep packet inspection techniques. Furthermore, we show that useful predictions of malicious classes can still be made when the input is limited to just the first 50 bytes of a packet’s payload.

The histogram probabilistic multi-hypothesis tracking (H-PMHT) algorithm is a multi-target track-before-detect method that has been demonstrated to be scalable and efficient and shows good performance on video imagery. However, its application has been limited to intensity-only imagery. In practice, colour and information, such as texture, are often available and can be very helpful when targets are close together. This study compares two alternative methods that incorporate colour information in the H-PMHT: an existing method referred to as spectral H-PMHT and a new approach that treats the colour information as attribute data. The methods are compared with intensity-only H-PMHT on simulations and benchmark data from the VS-PETS03 archive.

In order to improve the utilization efficiency of resources, more and more countries have required manufacturing firms to remanufacture or reuse used products through legislation. For many firms, the profit from reusing used products may be less than the profit from producing new products, so how to make decisions under such legislation constraint is a major concern by these firms. In this paper, we study the optimal acquisition, inventory and production decision problem for such firms under a two-period setting, where firms have two different production ways: (i) production with new raw materials, and (ii) production with used products. The return quantity of used products at the second period depends on the demand of the first period and the acquisition effort. The problem is formulated as a stochastic dynamic programming model. We give the optimal production rule and the optimal inventory decision at the second period, and prove the existence of an optimal policy with a simple structure at the first period. Moreover, based on our theoretical analysis, we calculate the optimal decisions under different parameter settings, and discuss how the firm does react when facing with specific market and production conditions.

The problem of H ∞ fault-tolerant control for networked control systems (NCSs) with actuator failures is addressed in this study. The authors consider the network-induced delays, including sensor-to-controller delay and controller-to-actuator delay, to have both an upper bound and a non-zero lower bound. By using a sampled-data approach, a new model is formulated based on the updating instants of the ZOH. They derive the criteria which ensure that the sample-data NCS is stable with H ∞ norm γ. The authors design the H ∞ fault-tolerant controller that guarantees the closed-loop NCS stability with H ∞ norm γ, when all control components are operational, as well as when some actuators fail to operate. Simulation examples are given to show the effectiveness and less conservative needs of the proposed method.

In this study, a theoretical framework for reconfigurable flight control is developed and applied to near space vehicle (NSV) attitude dynamics. First, NSV reentry mode is described. Second, an adaptive neural network observer is proposed, which ensures asymptotic convergence of the state observer error to zero under control effector damage and uncertainty. Next, a reconfigurable command-filter backstepping controller is designed based on the adaptive neural network observer. The authors focus is on the accommodation of the control effector damage, uncertainty and resulting disturbances. It is shown that the presented new control design results in asymptotic convergence of the attitude tracking error to zero. Finally, simulation results are given to demonstrate the effectiveness and potential of the proposed fault tolerant control scheme.

This paper considers a decentralized supply chain including one retailer and one manufacturer, where the manufacturer’s production yield and the retailer’s demand are both stochastic. At the beginning of the selling season, the retailer places an order and purchases an option contract with the manufacturer. After the selling season, the excess demand is partially backordered, and the retailer exercises his option order and then place an instant order for the backorders. The optimal ordering policy for the retailer and the corresponding production decision for the manufacturer are studied. Numerical examples are carried out to show the impact of the model parameters on the optimal policies.

Notice of Violation of IEEE Publication Principles "Decentralized Event-triggering Passive Control of Networked T-S Fuzzy Systems" by Huijiao Wang, Peng Shi, and Cheng-Chew Lim Submitted to the IEEE Transactions on Fuzzy Systems--August 2014 After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE’s Publication Principles. This paper contains substantial duplication of original text from the paper cited below. The original text was copied without attribution (including appropriate references to the original author(s) and/or paper title) and without permission. Due to the nature of this violation, reasonable effort should be made to remove all past references to this paper, and future references should be made to the following article: Decentralized Event-triggered Dissipative Control of Linear Systems via Dynamic Output Feedback" by Xian-Ming Zhang and Qing-Long Han Submitted to IEEE Transactions on Automatic Control on 7 August "Event-triggered Mixed H-infinity and Passive Control of Linear Systems via Dynamic Output Feedback" by Xian-Ming Zhang and Qing-Long Han in the Proceedings of the 39th Annual Conference of the IEEE Industrial Electronics Society (IECON), November 2013, pp. 5080-5085. In this paper, the problem of decentralized eventtriggering passive control is investigated for networked T-S fuzzy systems based on dynamic output feedback control. A mixed H1 and passivity control criterion for the closed-loop T-S fuzzy system is established. A new co-design method is developed for the decentralized event-triggered scheme and the dynamic output feedback controller. The method ensures that the resulting closedloop T-S fuzzy system is asymptotically stable with a prescribed mixed H1 and passive performance. A mass-spring-damper mechanical system is employed to illustrate the effectiveness of the proposed new design techniques.

This paper studies the coordination issue of a supply chain consisting of one retailer and two suppliers, a main supplier and a backup supplier. The main supplier’s yield is subject to disruption and the retailer faces a random demand. We determine the retailer’s optimal ordering policy and the main supplier’s production quantity that maximize expected profit of the centralized supply chain. We also analyze the decentralized scenario, and a combination of overproduction risk sharing and buy-back contracts with a side payment from/to the backup supplier is provided to coordinate the supply chain. Numerical examples are given to gain some qualitative insights.

This paper investigates the adaptively adjusted event-triggering mechanism-based fault detection for a discrete-time networked control system (NCS). The fault occurrence detection progress, the fault occurrence probability, and an adaptively adjusted event-triggering parameter are taken into account to construct a novel event-triggering mechanism. The event-triggered sensor and the event-triggered control station are used simultaneously to establish new network-based closed-loop models for the NCS subject to an actuator fault, and the sensor-to-control station and the control station-to-actuator network-induced delays. Based on the established models, the event-triggered simultaneous design of a fault detection filter and a controller is presented. A new algorithm for handling the adaptively adjusted event-triggering parameter is proposed. We analyse the performance of the simultaneous design of a fault detection filter and a controller to verify its effectiveness.

Formation control of a robot team is studied under the lack of communication channels. The robots are only equipped with displacement sensors of limited ranges. The robots are equally important and can access the objective formation in an arbitrary shape. In this paper, we present a protocol that has been designed to map the displacements from the sensors to those from the objective formation. With the available local mappings, each robot is driven by its controller to a partially desired local formation. The undesired conflicts among such local formations will trigger the protocol to produce re-mappings. Probability is used to avoid any infinite mapping loops.

This paper presents a novel Y-junction in folded substrate-integrated waveguide technology. The structure is analyzed with finite-element method using Ansys HFSS, and the simulation results show that the reflection coefficients of the 120° branch ports for the folded substrate-integrated waveguide Y-junction can satisfy the constraints for optimum performance of diplexers. In comparison with an unfolded substrate-integrated waveguide Y-junction, the characteristics of the presented structure can meet the constraints in a wider frequency band, which means that the flexibility for the selection of the up and down channel bands is increased.

Insertion loss is a crucial specification to judge the quality of a substrate integrated waveguide (SIW) band-pass filter. In this paper, six Chebyshev band-pass post filters in SIW technology are firstly designed with a lossless mode-matching code. The considered filters are designed with various orders for a center frequency of 10.5 GHz and a fractional bandwidth of 9.52%. These filters are then simulated with a full-wave electromagnetic solver in order to investigate the various contributions of ohmic and dielectric losses affecting the performance. In particular, the influence on the insertion loss of the variations of the metal cladding and vias conductivity, the dielectric loss tangent and the thickness of the substrate is quantitatively analyzed. For validation, one prototype filter is fabricated to compare the simulations to experimental results.

Shielded microstrip lines are widely used in microwave and millimeter wave systems to connect devices while protecting circuits from environmental contaminants, preventing electromagnetic interference, and enhancing the mechanical strength. To avoid the influence of the metallic enclosures on the fundamental mode, the choice of dimensions for the housing is an important issue. In this paper, the influence of those dimensions on the fundamental mode is investigated rigorously using the mode matching technique. In addition, the relationships between the cutoff frequency of the second-order mode and those geometrical variables of the cross-section of the shielded transmission line are presented. With these relationships, a reasonable geometry can be efficiently determined, which is important to prevent performance degradation through higher-order mode excitations, e.g. in waveguide transitions. The analysis results are verified with finite-element simulations obtained with HFSS.

Genetic evolutionary algorithms are effective and optimal test generation methods. However, the methods to select the algorithm parameters are often ad hoc, relying on empirical data. We used a Markov-based method to model the genetic evolutionary test generation process, parameterise the process characteristics, and derive analytical solutions for selecting the optimisation parameters. The method eliminates preliminary test generation calibration and experimentation effort needed to select these parameters, which are used in current practice.

The interrupt mechanism in a system-on-chip (SoC) joins the SoCs hardware and software behaviors. We model interrupts as logical rather than physical events and accordingly provides guidelines to compose software components including interrupt-service-routines. As a benefit, classical indeterministic behaviors (due to the parallelism) in the software domain, such as preemption and nesting, can be constructed as early as raw hardware components are being integrated. In effect, while the interrupt mechanism itself is under rigorous stress, it is simultaneously driving the exercise of the entire SoC. This effect can be observed through software profiling at the hardware integration stage.

Medium access control (MAC) protocols making use of multipacket reception (MPR) capability achieve better throughput than conventional MAC protocols. When a wireless network operates with MPR capable nodes and non-MPR nodes, the MAC protocols must not only utilise the MPR capability to maximise throughput, but must also enable the co-existence with these two types of nodes. We propose a new MPR MAC protocol to achieve the co-existence requirement by adopting a request-to-send (RTS)/clear-to-send (CTS) mechanism in IEEE 802.11 MAC standards. This MPR MAC protocol also improves throughput by allowing additional data transmissions to use the MPR capability fully. We analyse the system throughput of the co-existence of different link characteristics of nodes, and optimise its throughput by adjusting contention window sizes with respect to certain throughput requirements of the nodes. Copyright © 2010 John Wiley & Sons, Ltd.

The Dual-nu Support Vector Machine (SVM) is an effective method in pattern recognition and target detection. It improves on the Dual-C SVM, and offers competitive performance in detection and computation with traditional classifiers. We show that the regularisation parameters Dual-nu and Dual-C can be set such that the same SVM solution is obtained. We present the process of determining the related parameters of one form from the solution of a trained SVM of the other form, and test the relationship with a digit recognition problem. The link between the Dual-nu and Dual-C parameters allows users to use Dual-nu for ease of training, and to switch between the two forms readily.

The verification of system-on-chip is challenging due to its high level of integration. Multiple components in a system can behave concurrently and compete for resources. Hence, for simulation-based verification, we need a methodology that allows one to automatically generate test cases for testing concurrent and resource-competing behaviors. We introduce the use of a transfer-resource graph (TRG) as the model for test generation. From a high abstraction level, TRG is able to model the parallelism between heterogeneous interaction forms in a system. We show how TRG is used in generating test cases of resource competitions and how these test cases are structured in event-driven test programs. For coverage, TRG can be converted to a Petri net, allowing one to measure the completeness of concurrency in simulation.

The Histogram-Probabilistic Multi-Hypothesis Tracker (H-PMHT) is an efficient multi-target tracking approach to the Track-Before-Detect (TkBD) problem. However, it cannot adequately deal with fluctuating targets and this can degrade track management performance. By assuming an alternative measurement model based on a Poisson distribution, the H-PMHT algorithm can be re-derived to incorporate a time-correlated estimate of the component mixing terms, allowing for an improved measure for track quality.

This paper analyzes the characteristics of two cylindrical posts placed in the cross section of a rectangular waveguide based on the mode matching technique. Three methods to approximate the posts are introduced: equal width method, arithmetic sequence thickness method and equal sector method. The scattering parameter convergence of these approximation methods is investigated. Meanwhile, through comparing the difference of the scattering parameters and the accurate values, the rate of convergence for each method is also explored, according to which, the most efficient approximation method is recommended. The calculated results of a symmetric two-post structure are compared with full-wave simulations using ANSYS HFSS.

We present a hand and face segmentation methodology using color and motion cues for the content-based representation of sign language video sequences. The methodology consists of three stages: skin-color segmentation; change detection; face and hand segmentation mask generation. In skin-color segmentation, a universal color-model is derived and image pixels are classified as skin or nonskin based on their Mahalanobis distance. We derive a segmentation threshold for the classifier. The aim of change detection is to localize moving objects in a video sequences. The change detection technique is based on the F test and block-based motion estimation. Finally, the results from skin-color segmentation and change detection are analyzed to segment the face and hands. The performance of the algorithm is illustrated by simulations carried out on standard test sequences.

This paper presents a perturbation method to obtain a sensitivity measure of trained solution from a set of input patterns using support vector machine learning. Applying to classify images of binary classes, the sensitivity measure adds ability to extract content of interest of images for two classes in image classification.

Published version of an article in the journal: Mathematical Problems in Engineering. Also available from the publisher at: http://10.1155/2014/837050 This work addresses the problem of tracking mobile robots in indoor wireless sensor networks (WSNs). Our approach is based on a localization scheme with RSSI (received signal strength indication) which is used widely in WSN. The developed tracking system is designed for continuous estimation of the robot's trajectory. A WSN, which is composed of many very simple and cheap wireless sensor nodes, is deployed at a specific region of interest. The wireless sensor nodes collect RSSI information sent by mobile robots. A range-based data fusion scheme is used to estimate the robot's trajectory. Moreover, a Kalman filter is designed to improve tracking accuracy. Experiments are provided to assess the performance of the proposed scheme. © 2014 Liping Zhang et al.

This paper studies the problem of robust H ∞ controller design for a class of uncertain Markov jump systems with time-varying transition probabilities, which follows nonhomogeneous jump processes. The time varying transition probability matrix is described as a polytope set. By Lyapunov function approach, under the designed controller, a sufficient condition is presented to ensure that the resulting closed-loop system is stochastically stable and that a prescribed H ∞ performance index is satisfied. Finally, an application of a DC motor device is addressed to demonstrate the effectiveness of developed techniques.

Error table compensation can be used to improve the spurious free dynamic range performance of high speed A/D converters. This paper gives details of an error table compensator system that uses a VLSI chip incorporating a transversal filter programmed as a wideband differentiator, additional on-chip circuits including delays and an adder, and a lookup table that is stored in external memory. The cascadable 10GOPS transversal filter differentiator chip has been designed and fabricated and can operate in 32-tap symmetric, 32-tap anti-symmetric or 16-tap non-symmetric modes. It has programmable tap weights and uses 16-bit signed arithmetic with radix-16 multipliers and 4–2 compressors to reduce the transistor count. The chip was fabricated in a 0.35-μm CMOS process, measures 3.1×4.4 mm and contains 310,000 transistors. The chip is pipelined and has a maximum clock rate of 200 MHz. It is shown that the error table compensation system is capable of providing between 7 and 13 dB improvement in the dynamic range of typical high-speed A/D converters.

This chapter focuses on the energy efficiency and reliability issues when applying the novel compressive sensing technique in wireless visual sensor networks. An explanation is given for why compressive sensing is useful for visual sensor networks. The relationships between sparsity control and compression ratio, the effect of block-based sampling on reconstruction quality, complexity consideration of reconstruction process for real-time applications, and compensation for packets missing in network flows are discussed. We analyse the effectiveness of using the 2-dimensional Haar wavelet transform for sparsity control, the difference between compressive sampling in spatial and frequency domains, and the computation of the prime-dual optimisation method and the log barrier algorithm for reconstruction. The effectiveness of the approach on recovered image quality is evaluated using Euclidean distance and variance analysis.

This paper presents a sequencer that accelerates matrix algorithms arising naturally in many multimedia and signal processing applications. The accelerator has been designed to carry out data management tasks common to these algorithms. A novel event-based parameter update mechanism allows production of continuously varying patterns to access triangular, banded and other irregular matrix structures. It has been verified that the accelerator significantly reduces the workload of the attached CPU for a wide range of algorithms. The accelerator has been implemented on a Virtex-5 FPGA platform where it required 1856 slices and achieved a post place-and-route speed of 64 MHz.

We propose a weight-based clustering routing protocol for wireless sensor networks. A new cluster head selection algorithm is developed in the proposed protocol. This algorithm aims at selecting better cluster heads in the network in order to minimise the energy dissipation of intra-cluster and inter-cluster data transmission. The load balance of the cluster heads is also considered when selecting cluster heads. The performance of the proposed protocol is evaluated and compared with two existing clustering-based protocols. Simulation results show that the proposed protocol achieves better energy efficiency and longer network lifetime.

Radio Frequency Identification (RFID) is a technology to store and retrieve information remotely using electromagnetic waves. RFID is poised to drastically change the way industries collect and manage information. Research in this area has been growing in the past few years given the wide range of applications that can benefit from such a technology. In this paper we introduce the Cognitive RFID Integrated System Platform (CRISP), a framework for development and implementation of RFID communication protocols. The framework enables advanced research in the area of RFID wireless communication protocols and algorithms. As such, CRISP provides a flexible, scalable, configurable and high performance RFID research tool. In the following sections the CRISP hardware implementation and software architecture are discussed in detail. Radio configurations and applications are presented. Future research made possible by this flexible platform is also discussed.

We propose a position-based, energy-efficient, and centralised clustering protocol for wireless sensor networks. The protocol aims at prolonging the network lifetime by evenly distributing energy load among sensor nodes in the network. A new cluster head selection algorithm is developed in the proposed protocol. In addition, the protocol uses a novel multi-hop routing approach for inter-cluster communication between cluster heads and the base station. The performance of the proposed protocol is evaluated and compared with three existing clustering-based protocols. Simulation results show that the proposed protocol achieves better energy efficiency and longer network lifetime.

Channel outage represents channel fading and interference. Since each user may experience different fading and interference (i.e., channel outage) over distinct channels, throughput may vary depending on channel selection of users. In this paper, we propose two types of multichannel outage-aware medium access control (MAC) protocols to improve throughput: 1) frequency-domain backoff MAC protocols with outage-aware refined channel sets using distributed channel selection, and 2) time-domain backoff MAC protocols with a lowest-outage increasing heuristic using centralised channel allocation to find optimal user sets. Simulation results show the impacts of the proposed MAC protocols on throughput under multichannel outage environments with respect to various user numbers.

In simulation-based system-on-chip (SoC) verification, in addition to the testbench (TB) - the basic facility for stimulation and observation, software native to the SoC also plays a part in interacting with the SoC. This software is referred to as the test-program (TP). However, the relationship between the TB, the TP and the SoC is not always intuitive and can cause conceptual confusion. This paper discusses this confusion and shows how to address it by positioning the TB and the TP naturally in the verification framework.

A digital signal processor (DSP) system-on-chip (SoC) can be designed using a variety of architectures and techniques. This often presents different verification challenges compared to conventional SoC or processor designs. Verification of such designs should take into account the goals and applications of the DSP, and how they are eventually used. This paper proposes an application based verification methodology and demonstrates this technique on a real-life DSP SoC design. Our technique employs a library of specially devised application functions as test building blocks, followed by a genetic evolutionary test generator to compose these application functions into effective test programs.

Downlink beamforming is well studied in wireless communications over the last decade, including some optimization issues. In this paper, we study the multiuser downlink beamforming when the channel state information (CSI) is provided to the transmitter with limited feedback. With limited feedback, the CSI becomes imperfect. Joint beamforming and power allocation are addressed with limited feedback. We also show that the multiuser beamforming becomes interference-limited even though the number of active users is less than the number of transmit antennas due to limited feedback. From this, we can see that there is capacity loss and the performance is limited by the residual interference due to imperfect CSI.