Robust Kalman filter for linear discrete-time system with gaussian sum noises

This paper considers the filtering problem for discrete-time linear systems where the distributions of the process and observation noises are of gaussian sum distributions. Since the gaussian sum noise can be considered to be a sample from one of the gaussian distributions forming the gaussian sum, we define the distribution selection parameters that specify sample noises from the gaussian sum distribution. By using the maximum a posteriori (MAP) estimates of the selection parameters, a robust state estimation algorithm combined with the Kalman filter is developed. Simulation studies are also included to show the effectiveness of the present algorithm.     

3D television: Developing a multi‐modal multi‐viewer TV system of the future

Abstract— Under the European Union funded Advanced Three‐dimensional Television System Technologies (ATTEST) project, De Montfort University (DMU) is developing a 3D display system targeted specifically at domestic television applications. This system uses a modified transmissive LCD panel together with novel backlighting and optics to project multiple viewing regions, or exit pupils, into the viewing space. These exit pupils are located in space using a head tracker. The display accommodates multiple viewers simultaneously and imposes no physical constraints, such as special eyewear. Viewers may move freely over a “typical” room‐sized area. The design of the backlighting facilitates many other display regimes beyond the “standard” 3DTV mode in which each viewer sees the same image pair.     

A compact band‐pass filter using multi‐element resonators

A compact, band‐pass filter utilizing multi‐element resonators, structured from sections of distributed transmission lines, is presented. A band‐pass filter design procedure is established that emphasizes CAD techniques to characterize the individual resonators and to determine the resonator coupling values required for a specified pass‐band response. Detailed band‐pass filter design examples are illustrated and simulation results are employed to validate the design procedure. © 2003 Wiley Periodicals, Inc. Int J RF and Microwave CAE 13, 447–458, 2003.     

Robust outdoor visual localization using a three‐dimensional‐edge map

Visual localization systems that are practical for autonomous vehicles in outdoor industrial applications must perform reliably in a wide range of conditions. Changing outdoor conditions cause difficulty by drastically altering the information available in the camera images. To confront the problem, we have developed a visual localization system that uses a surveyed three‐dimensional (3D)‐edge map of permanent structures in the environment. The map has the invariant properties necessary to achieve long‐term robust operation. Previous 3D‐edge map localization systems usually maintain a single pose hypothesis, making it difficult to initialize without an accurate prior pose estimate and also making them susceptible to misalignment with unmapped edges detected in the camera image. A multihypothesis particle filter is employed here to perform the initialization procedure with significant uncertainty in the vehicle's initial pose. A novel observation function for the particle filter is developed and evaluated against two existing functions. The new function is shown to further improve the abilities of the particle filter to converge given a very coarse estimate of the vehicle's initial pose. An intelligent exposure control algorithm is also developed that improves the quality of the pertinent information in the image. Results gathered over an entire sunny day and also during rainy weather illustrate that the localization system can operate in a wide range of outdoor conditions. The conclusion is that an invariant map, a robust multihypothesis localization algorithm, and an intelligent exposure control algorithm all combine to enable reliable visual localization through challenging outdoor conditions. © 2009 Wiley Periodicals, Inc.     

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.     

Adaptive haptic rendering for time‐varying haptic and video frame rates in multi‐modal interactions

In multi‐modal interactions including haptics, problems such as input sensor noise, temporal mismatch between graphics and haptics, and non‐constant refresh rates may cause non‐smooth force/torque display. This paper proposes temporal smoothing technique for haptic interaction using a sensing glove in multi‐modal applications. The proposed technique employs two processes: (1) a noise reduction method is applied to reduce jitter noise at the sensors in the sensing glove and (2) an adaptive force extrapolation is applied for time‐varying haptic and video frame rates. To demonstrate the performance of the proposed method, we developed a test platform to assess a simple box model and relatively complex models such as gamephone, portable media player (PMP). It was subsequently demonstrated that the proposed method can support smooth haptic interactions in multi‐modal applications where a haptic device and a sensing glove are used. Copyright © 2009 John Wiley & Sons, Ltd.     

Multi‐targets localization and elliptical circumnavigation by multi‐agents using bearing‐only measurements in two‐dimensional space

In order to enable the multi‐agents to elliptically circumnavigate the multi‐targets in more complex environment, we propose a geometric center estimator and an elliptical circumnavigation controller in two‐dimensional space by only employing bearing measurements without knowing the target's position and velocity. The stability of the algorithm is proved for both stationary targets and dynamic targets. Finally, a series of numerical simulations is presented to verify the correctness of the algorithm both in ideal networks and in networks with communication delays.     

Distributed stereo vision‐based 6D localization and mapping for multi‐robot teams

Joint simultaneous localization and mapping (SLAM) constitutes the basis for cooperative action in multi‐robot teams. We designed a stereo vision‐based 6D SLAM system combining local and global methods to benefit from their particular advantages: (1) Decoupled local reference filters on each robot for real‐time, long‐term stable state estimation required for stabilization, control and fast obstacle avoidance; (2) Online graph optimization with a novel graph topology and intra‐ as well as inter‐robot loop closures through an improved submap matching method to provide global multi‐robot pose and map estimates; (3) Distribution of the processing of high‐frequency and high‐bandwidth measurements enabling the exchange of aggregated and thus compacted map data. As a result, we gain robustness with respect to communication losses between robots. We evaluated our improved map matcher on simulated and real‐world datasets and present our full system in five real‐world multi‐robot experiments in areas of up 3,000 m² (bounding box), including visual robot detections and submap matches as loop‐closure constraints. Further, we demonstrate its application to autonomous multi‐robot exploration in a challenging rough‐terrain environment at a Moon‐analogue site located on a volcano.     

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.     

Novel sliding mode control for multi‐input–multi‐output discrete‐time system with disturbance

This paper investigates sliding mode control for multi‐input–multi‐output discrete‐time system with disturbances. First of all, a novel nonlinear sliding surface, named as hyperbolic hybrid switching sliding surface, is proposed. Two different types of hyperbolic functions are introduced into the proposed sliding surface. Due to the changing of values of the hyperbolic functions, sliding surface switching occurs during the control process, which ensures that both settling time and overshoot can be decreased. The sliding mode controller is obtained based on a novel nonlinear reaching law. The nonlinear reaching law contains several parameters, and by properly designing these parameters, we can decrease the bounds of the sliding variables to small values. The stability analysis of the sliding motion is carried out from singular system viewpoint. Finally, simulation examples and comparison examples are presented to illustrate that the system performance is improved obviously by proposed novel sliding mode control, and the system is robust to the disturbances.     

MIMO雷达最大似然参数估计

多输入多输出(MIMO)雷达使用多个天线同时发射多个独立探测信号,并使用多个天线接收目标回波信号.本文考虑了发射空域分集、相干接收MIMO雷达模型及其最大似然(ML)参数估计方法.基于最大似然准则,本文推导了两种渐近最大似然算法.仿真实验的结果表明,在均匀噪声模型中,其中一种渐近算法与基于延迟求和波束形成的最大似然算法性能接近,而另一种渐近算法性能略差,但具有较低的计算复杂度.而在非均匀噪声模型中,本文所提出的两种渐近最大似然算法的性能均优于基于延迟求和波束形成的最大似然算法.     

Depth‐map generation for multi‐view autostereoscopic 3‐D displays based on the SIFT algorithm constrained by boundary

Abstract— A depth‐map estimation method, which converts two‐dimensional images into three‐dimensional (3‐D) images for multi‐view autostereoscopic 3‐D displays, is presented. The proposed method utilizes the Scale Invariant Feature Transform (SIFT) matching algorithm to create the sparse depth map. The image boundaries are labeled by using the Sobel operator. A dense depth map is obtained by using the Zero‐Mean Normalized Cross‐Correlation (ZNCC) propagation matching method, which is constrained by the labeled boundaries. Finally, by using depth rendering, the parallax images are generated and synthesized into a stereoscopic image for multi‐view autostereoscopic 3‐D displays. Experimental results show that this scheme achieves good performances on both parallax image generation and multi‐view autostereoscopic 3‐D displays.     

Online anomaly detection for multi‐source VMware using a distributed streaming framework

Anomaly detection refers to the identification of patterns in a dataset that do not conform to expected patterns. Such non‐conformant patterns typically correspond to samples of interest and are assigned to different labels in different domains, such as outliers, anomalies, exceptions, and malware. A daunting challenge is to detect anomalies in rapid voluminous streams of data. This paper presents a novel, generic real‐time distributed anomaly detection framework for multi‐source stream data. As a case study, we investigate anomaly detection for a multi‐source VMware‐based cloud data center, which maintains a large number of virtual machines (VMs). This framework continuously monitors VMware performance stream data related to CPU statistics (e.g., load and usage). It collects data simultaneously from all of the VMs connected to the network and notifies the resource manager to reschedule its CPU resources dynamically when it identifies any abnormal behavior from its collected data. A semi‐supervised clustering technique is used to build a model from benign training data only. During testing, if a data instance deviates significantly from the model, then it is flagged as an anomaly. Effective anomaly detection in this case demands a distributed framework with high throughput and low latency. Distributed streaming frameworks like Apache Storm, Apache Spark, S4, and others are designed for a lower data processing time and a higher throughput than standard centralized frameworks. We have experimentally compared the average processing latency of a tuple during clustering and prediction in both Spark and Storm and demonstrated that Spark processes a tuple much quicker than storm on average. Copyright © 2016 John Wiley & Sons, Ltd.     

Resource brokering using a multi‐site resource allocation strategy for computational grids

Grid computing employs heterogeneous resources which may be installed on different platforms, hardware/software, computer architectures, and perhaps using different computer languages to solve large‐scale computational problems. As many more Grids are being developed worldwide, the number of multi‐institutional collaborations is growing rapidly. However, to realize Grid computing's full potential, it is expected that Grid participants must be able to share one another's resources. This paper presents a resource broker that employs the multi‐site resource allocation (MSRA) strategy and the dynamic domain‐based network information model that we propose to allocate Grid resources to submitted jobs, where the Grid resources may be dispersed at different sites, and owned and governed by different organizations or institutes. The jobs and resources may also belong to different clusters/sites. Resource statuses collected by the Ganglia, and network bandwidths gathered by the Network Weather Service, are both considered in the proposed scheduling approach. A dynamic domain‐based model for network information measurement is also proposed to choose the most appropriate resources that meet the jobs' execution requirements. Experimental results show that MSRA outperformed the other tested strategies. Copyright © 2010 John Wiley & Sons, Ltd.     

Adaptive finite‐time neural backstepping control for multi‐input and multi‐output state‐constrained nonlinear systems using tangent‐type nonlinear mapping

This article focuses on the problem of adaptive finite‐time neural backstepping control for multi‐input and multi‐output nonlinear systems with time‐varying full‐state constraints and uncertainties. A tan‐type nonlinear mapping function is first proposed to convert the strict‐feedback system into a new pure‐feedback one without constraints. Neural networks are utilized to cope with unknown functions. To improve learning performance, a composite adaptive law is designed using tracking error and approximate error. A finite‐time convergent differentiator is adopted to avoid the problem of “explosion of complexity.” By theoretical analysis, all the signals of system are proved to be bounded, the outputs can track the desired signals in a finite time, and full‐state constraints are not transgressed. Finally, comparative simulations are offered to confirm the validity of the proposed control scheme.     

Local map fusion for real‐time indoor simultaneous localization and mapping

Among the solutions to the simultaneous localization and mapping (SLAM) problem with probabilistic techniques, the extended Kalman filter (EKF) is a very common approach. There are several approaches to deal with its computational cost, usually based on an adequate selection of features to be updated in real time, while the whole map update is delayed or processed in a background task, allowing one to map larger environments or to carry out multirobot experiments. Although these solutions are theoretically sound, there is a great lack of real experiments in large indoor environments due to several previously unknown problems derived from the geometric model of the map features and the inconsistency of the SLAM‐EKF algorithm. For the first time, these problems are described and solved, and the implementation of the algorithms and solutions presented in this paper achieve excellent results in experiments in different real large indoor environments. © 2006 Wiley Periodicals, Inc.     

Developing multi‐agent systems with a FIPA‐compliant agent framework

To ease large‐scale realization of agent applications there is an urgent need for frameworks, methodologies and toolkits that support the effective development of agent systems. Moreover, since one of the main tasks for which agent systems were invented is the integration between heterogeneous software, independently developed agents should be able to interact successfully. In this paper, we present JADE (Java Agent Development Environment), a software framework to build agent systems for the management of networked information resources in compliance with the FIPA specifications for inter‐operable intelligent multi‐agent systems. The goal of JADE is to simplify development while ensuring standard compliance through a comprehensive set of system services and agents. JADE can then be considered to be an agent middle‐ware that implements an efficient agent platform and supports the development of multi‐agent systems. It deals with all the aspects that are not peculiar to agent internals and that are independent of the applications, such as message transport, encoding and parsing, or agent life‐cycle management. Copyright © 2001 John Wiley & Sons, Ltd.     

Topological localization with kidnap recovery using sonar grid map matching in a home environment

This paper presents a method of topological localization with kidnap recovery capability in a home environment using only low-cost sonar sensors. The proposed method considers both pose tracking and relocation problems. The pose tracking is achieved by calculating node probability using grid-map matching and relative motion model. The relocation method detects the kidnap automatically and recovers it using multiple hypothesis tracking. After kidnap recovery, it also provides a criterion for selecting a reasonable hypothesis for returning to the pose tracking stage autonomously. Experimental results in a real home environment verify that the proposed localization method provides a reliable and convergent node probability when the robot is kidnapped.     

Ultra‐low‐power LTPS TFT‐LCD technology using a multi‐bit pixel memory circuit

Abstract— Two types of low‐temperature poly‐Si TFT LCDs, which integrate a multi‐bit memory circuit and a liquid‐crystal driver within a pixel, have been developed using two different TFT process technologies. Both a 1.3‐in. 116‐ppi LCD having a 2‐bit pixel memory and a 1.5‐in. 130‐ppi LCD having a 5‐bit pixel memory consume very little power, less than 100 μW, which indicates that this technology is promising for mobile displays.