The US Department of Defense （DoD） routinely uses wireless sensor networks （WSNs） for military tactical communications. Sensor node die-out has a significant impact on the topology of a tactical WSN. This is probl...The US Department of Defense （DoD） routinely uses wireless sensor networks （WSNs） for military tactical communications. Sensor node die-out has a significant impact on the topology of a tactical WSN. This is problematic for military applications where situational data is critical to tactical decision making. To increase the amount of time all sensor nodes remain active within the network and to control the network topology tactically, energy efficient routing mechanisms must be employed. In this paper, we aim to provide realistic insights on the practical advantages and disadvantages of using established routing techniques for tactical WSNs. We investigate the following established routing algorithms： direct routing, minimum transmission energy （MTE）, Low Energy Adaptive Cluster Head routing （LEACH）, and zone clustering. Based on the node die out statistics observed with these algorithms and the topological impact the node die outs have on the network, we develop a novel, energy efficient zone clustering algorithm called EZone. Via extensive simulations using MATLAB, we analyze the effectiveness of these algorithms on network performance for single and multiple gateway scenarios and show that the EZone algorithm tactically controls the topology of the network, thereby maintaining significant service area coverage when compared to the other routing algorithms.展开更多
A novel neural network based on iterated unscented Kalman filter （IUKF） algorithm is established to model and com- pensate for the fiber optic gyro （FOG） bias drift caused by temperature. In the network, FOG tempe...A novel neural network based on iterated unscented Kalman filter （IUKF） algorithm is established to model and com- pensate for the fiber optic gyro （FOG） bias drift caused by temperature. In the network, FOG temperature and its gradient are set as input and the FOG bias drift is set as the expected output. A 2-5-1 network trained with IUKF algorithm is established. The IUKF algorithm is developed on the basis of the unscented Kalman filter （UKF）. The weight and bias vectors of the hidden layer are set as the state of the UKF and its process and measurement equations are deduced according to the network architecture. To solve the unavoidable estimation deviation of the mean and covariance of the states in the UKF algorithm, iterative computation is introduced into the UKF after the measurement update. While the measure- ment noise R is extended into the state vectors before iteration in order to meet the statistic orthogonality of estimate and mea- surement noise. The IUKF algorithm can provide the optimized estimation for the neural network because of its state expansion and iteration. Temperature rise （-20-20℃） and drop （70-20℃） tests for FOG are carried out in an attemperator. The temperature drift model is built with neural network, and it is trained respectively with BP, UKF and IUKF algorithms. The results prove that the proposed model has higher precision compared with the back- propagation （BP） and UKF network models.展开更多
A new thermal ring-opening polymerization technique for 1, 1, 3, 3-tetra-ph enyl-1, 3-disilacyclobutane （TPDC） based on the use of metal nanoparticles produced by pulsed laser ablation was investigated. This method ...A new thermal ring-opening polymerization technique for 1, 1, 3, 3-tetra-ph enyl-1, 3-disilacyclobutane （TPDC） based on the use of metal nanoparticles produced by pulsed laser ablation was investigated. This method facilitates the synthesis of polydiphenysilylenemethyle （PDPhSM） thin film, which is difficult to make by conventional methods because of its insolubility and high melting point. TPDC was first evaporated on silicon substrates and then exposed to metal nanoparticles deposition by pulsed laser ablation prior to heat treatment.The TPDC films with metal nanoparticles were heated in an electric furnace in air atmosphere to induce ring-opening polymerization of TPDC. The film thicknesses before and after polymerization were measured by a stylus profilometer. Since the polymerization process competes with re-evaporation of TPDC during the heating, the thickness ratio of the polymer to the monomer was defined as the polymerization efficiency, which depends greatly on the technology conditions. Therefore, a well trained radial base function neural network model was constructed to approach the complex nonlinear relationship. Moreover, a particle swarm algorithm was firstly introduced to search for an optimum technology directly from RBF neural network model. This ensures that the fabrication of thin film with appropriate properties using pulsed laser ablation requires no in-depth understanding of the entire behavior of the technology conditions.展开更多
One of the important aspects of seamless communication for ubiquitous computing is the dynamic selection of the best access network for a multimodal device in a heterogeneous wireless environment. In this paper, we co...One of the important aspects of seamless communication for ubiquitous computing is the dynamic selection of the best access network for a multimodal device in a heterogeneous wireless environment. In this paper, we consider available bandwidth as a dynamic parameter to select the network in heterogeneous environments. A bootstrap approximation based technique is firstly utilized to estimate the available bandwidth and compare it with hidden Markov model based estimation to check its accuracy. It is then used for the selection of the best suitable network in the heterogeneous environment consisting of 2G and 3G standards based wireless networks. The proposed algorithm is implemented in temporal and spatial domains to check its robustness. The numerical results show that the proposed algorithm gives improved performance in terms of estimation error （less than 15%）, overhead （varies from 0.45% to 72.91%） and reliability （approx. 99%）as compared to the existing algorithm.展开更多
随着嵌入式技术的不断发展,HMPU逐渐广泛应用于高性能计算领域。异构多核处理器,即具有两个或以上处理器内核的处理器,因其计算效率高,且可针对不同应用调整结构,其应用相当广泛。在具体应用中,多核处理器的不同处理器核之间需要进行大...随着嵌入式技术的不断发展,HMPU逐渐广泛应用于高性能计算领域。异构多核处理器,即具有两个或以上处理器内核的处理器,因其计算效率高,且可针对不同应用调整结构,其应用相当广泛。在具体应用中,多核处理器的不同处理器核之间需要进行大量的、频繁的数据交换,因此,处理器核间的通信效率严重影响处理器的性能。目前通过调查研究,异构多核处理器芯片核间通信领域已经在国内外取得了一些显著研究成果。该文结合以上研究成果,针对电子系统数据与信号处理融合及IO综合管理需求,综合不同类型处理器的功能性能需求,以先进SoC为技术手段,基于国内现有IP和自主工艺平台,在单芯片上实现数据处理及信号处理、多数据接口、高精度采集以及异构多核可定制信息处理为目的,提出一种基于"CPU+DSP+FPGA+IO"结构的异构多核处理器芯片(heterogeneous multi-processor unit, HMPU)的设计方案,采用共享总线的Mailbox异构多核间通信机制,以满足信号采样处理、总线协议处理、数据处理及控制功能。重点阐述了HMPU的体系架构设计、详细设计及实现、虚拟仿真验证及FPGA原型验证等关键技术。目前HMPU已经流片成功,并成功应用在多个领域。展开更多
基于SOPC技术设计了一个综合应用系统:实现了键值数据采集、显示,并将采集到的数据通过串口送给上位机;也可以接收上位机送来的数据,控制点亮相应的二极管且将接收到的数据显示在数码管上。系统硬件由FPGA及外围电路组成,采用了性能优良...基于SOPC技术设计了一个综合应用系统:实现了键值数据采集、显示,并将采集到的数据通过串口送给上位机;也可以接收上位机送来的数据,控制点亮相应的二极管且将接收到的数据显示在数码管上。系统硬件由FPGA及外围电路组成,采用了性能优良的Nios II软核处理器;软件在Altera公司的软件集成开发工具Nios II IDE下应用C语言编程。该系统工作可靠,在实际的应用设计中有一定的参考价值。展开更多
文摘The US Department of Defense （DoD） routinely uses wireless sensor networks （WSNs） for military tactical communications. Sensor node die-out has a significant impact on the topology of a tactical WSN. This is problematic for military applications where situational data is critical to tactical decision making. To increase the amount of time all sensor nodes remain active within the network and to control the network topology tactically, energy efficient routing mechanisms must be employed. In this paper, we aim to provide realistic insights on the practical advantages and disadvantages of using established routing techniques for tactical WSNs. We investigate the following established routing algorithms： direct routing, minimum transmission energy （MTE）, Low Energy Adaptive Cluster Head routing （LEACH）, and zone clustering. Based on the node die out statistics observed with these algorithms and the topological impact the node die outs have on the network, we develop a novel, energy efficient zone clustering algorithm called EZone. Via extensive simulations using MATLAB, we analyze the effectiveness of these algorithms on network performance for single and multiple gateway scenarios and show that the EZone algorithm tactically controls the topology of the network, thereby maintaining significant service area coverage when compared to the other routing algorithms.
基金supported by the National Natural Science Foundation of China(6110418440904018)+3 种基金the National Key Scientific Instrument and Equipment Development Project(2011YQ12004502)the Research Foundation of General Armament Department(201300000008)the Doctor Innovation Fund of Naval University of Engineering(HGBSCXJJ2011008)the Youth Natural Science Foundation of Naval University of Engineering(HGDQNJJ12028)
文摘A novel neural network based on iterated unscented Kalman filter （IUKF） algorithm is established to model and com- pensate for the fiber optic gyro （FOG） bias drift caused by temperature. In the network, FOG temperature and its gradient are set as input and the FOG bias drift is set as the expected output. A 2-5-1 network trained with IUKF algorithm is established. The IUKF algorithm is developed on the basis of the unscented Kalman filter （UKF）. The weight and bias vectors of the hidden layer are set as the state of the UKF and its process and measurement equations are deduced according to the network architecture. To solve the unavoidable estimation deviation of the mean and covariance of the states in the UKF algorithm, iterative computation is introduced into the UKF after the measurement update. While the measure- ment noise R is extended into the state vectors before iteration in order to meet the statistic orthogonality of estimate and mea- surement noise. The IUKF algorithm can provide the optimized estimation for the neural network because of its state expansion and iteration. Temperature rise （-20-20℃） and drop （70-20℃） tests for FOG are carried out in an attemperator. The temperature drift model is built with neural network, and it is trained respectively with BP, UKF and IUKF algorithms. The results prove that the proposed model has higher precision compared with the back- propagation （BP） and UKF network models.
基金Funded by the Zhejiang Provincial Natural Science Foundation of China(No.R405031)Jiaxing Science Planning Project(2009 2007)the Educa-tion Department of Zhejiang Province (No.20051441)
文摘A new thermal ring-opening polymerization technique for 1, 1, 3, 3-tetra-ph enyl-1, 3-disilacyclobutane （TPDC） based on the use of metal nanoparticles produced by pulsed laser ablation was investigated. This method facilitates the synthesis of polydiphenysilylenemethyle （PDPhSM） thin film, which is difficult to make by conventional methods because of its insolubility and high melting point. TPDC was first evaporated on silicon substrates and then exposed to metal nanoparticles deposition by pulsed laser ablation prior to heat treatment.The TPDC films with metal nanoparticles were heated in an electric furnace in air atmosphere to induce ring-opening polymerization of TPDC. The film thicknesses before and after polymerization were measured by a stylus profilometer. Since the polymerization process competes with re-evaporation of TPDC during the heating, the thickness ratio of the polymer to the monomer was defined as the polymerization efficiency, which depends greatly on the technology conditions. Therefore, a well trained radial base function neural network model was constructed to approach the complex nonlinear relationship. Moreover, a particle swarm algorithm was firstly introduced to search for an optimum technology directly from RBF neural network model. This ensures that the fabrication of thin film with appropriate properties using pulsed laser ablation requires no in-depth understanding of the entire behavior of the technology conditions.
文摘One of the important aspects of seamless communication for ubiquitous computing is the dynamic selection of the best access network for a multimodal device in a heterogeneous wireless environment. In this paper, we consider available bandwidth as a dynamic parameter to select the network in heterogeneous environments. A bootstrap approximation based technique is firstly utilized to estimate the available bandwidth and compare it with hidden Markov model based estimation to check its accuracy. It is then used for the selection of the best suitable network in the heterogeneous environment consisting of 2G and 3G standards based wireless networks. The proposed algorithm is implemented in temporal and spatial domains to check its robustness. The numerical results show that the proposed algorithm gives improved performance in terms of estimation error （less than 15%）, overhead （varies from 0.45% to 72.91%） and reliability （approx. 99%）as compared to the existing algorithm.
文摘随着嵌入式技术的不断发展,HMPU逐渐广泛应用于高性能计算领域。异构多核处理器,即具有两个或以上处理器内核的处理器,因其计算效率高,且可针对不同应用调整结构,其应用相当广泛。在具体应用中,多核处理器的不同处理器核之间需要进行大量的、频繁的数据交换,因此,处理器核间的通信效率严重影响处理器的性能。目前通过调查研究,异构多核处理器芯片核间通信领域已经在国内外取得了一些显著研究成果。该文结合以上研究成果,针对电子系统数据与信号处理融合及IO综合管理需求,综合不同类型处理器的功能性能需求,以先进SoC为技术手段,基于国内现有IP和自主工艺平台,在单芯片上实现数据处理及信号处理、多数据接口、高精度采集以及异构多核可定制信息处理为目的,提出一种基于"CPU+DSP+FPGA+IO"结构的异构多核处理器芯片(heterogeneous multi-processor unit, HMPU)的设计方案,采用共享总线的Mailbox异构多核间通信机制,以满足信号采样处理、总线协议处理、数据处理及控制功能。重点阐述了HMPU的体系架构设计、详细设计及实现、虚拟仿真验证及FPGA原型验证等关键技术。目前HMPU已经流片成功,并成功应用在多个领域。
文摘基于SOPC技术设计了一个综合应用系统:实现了键值数据采集、显示,并将采集到的数据通过串口送给上位机;也可以接收上位机送来的数据,控制点亮相应的二极管且将接收到的数据显示在数码管上。系统硬件由FPGA及外围电路组成,采用了性能优良的Nios II软核处理器;软件在Altera公司的软件集成开发工具Nios II IDE下应用C语言编程。该系统工作可靠,在实际的应用设计中有一定的参考价值。
