电流型电路具有功耗低、速度快的特点,是当今集成电路研究的一个热点.文章基于阈算术代数系统,改进了非相交分解算法;设计了电流型互补金属氧化物半导体(complementary metal oxide semiconductor, CMOS)的异或门电路,并利用改进后的新...电流型电路具有功耗低、速度快的特点,是当今集成电路研究的一个热点.文章基于阈算术代数系统,改进了非相交分解算法;设计了电流型互补金属氧化物半导体(complementary metal oxide semiconductor, CMOS)的异或门电路,并利用改进后的新算法,将n变量函数分解成3变量函数,实现了任意n变量函数电路.模拟测试证明所设计的电路结构简单,且具有正确的逻辑功能.展开更多
Rising energy costs and growing environmental awareness motivate a critical revision of the design of distillation units. Systematic design techniques, such as the rectification body, column profile map, and temperatu...Rising energy costs and growing environmental awareness motivate a critical revision of the design of distillation units. Systematic design techniques, such as the rectification body, column profile map, and temperature collocation methods, require exact knowledge of all pinch points in a particular system, because these stationary points delineate the possible composition trajectories realizable in separation columns. This paper demonstrates novel methods for rigorously determining all pinch points for the constant relative volatility, ideal and non-ideal systems. Constant relative volatility and ideal solution systems are transformed into one-dimensional polynomial and nonlinear functions, regardless of the number of the components. A deflation method is proposed to locate all zeros in ideal and non-ideal zeotropic problems. For more challenging non-ideal problems, a novel hybrid sequential niche algorithm is used to solve hard azeotropic problems successfully. Finally, the design implications of these pinch point locations are investigated to show how new separation configurations can be devised. Methodically the paper points out the use of rigorous pinch point computations in conjunction with continuous composition profiles for robust distillation design.展开更多
Mobile edge computing （MEC） is a novel technique that can reduce mobiles＇ com- putational burden by tasks offioading, which emerges as a promising paradigm to provide computing capabilities in close proximity to mo...Mobile edge computing （MEC） is a novel technique that can reduce mobiles＇ com- putational burden by tasks offioading, which emerges as a promising paradigm to provide computing capabilities in close proximity to mobile users. In this paper, we will study the scenario where multiple mobiles upload tasks to a MEC server in a sing cell, and allocating the limited server resources and wireless chan- nels between mobiles becomes a challenge. We formulate the optimization problem for the energy saved on mobiles with the tasks being dividable, and utilize a greedy choice to solve the problem. A Select Maximum Saved Energy First （SMSEF） algorithm is proposed to realize the solving process. We examined the saved energy at different number of nodes and channels, and the results show that the proposed scheme can effectively help mobiles to save energy in the MEC system.展开更多
To improve the accuracy of strapdown inertial navigation system(SINS) for long term applications,the rotation technique is employed to modulate the errors of the inertial sensors into periodically varied signals,and,a...To improve the accuracy of strapdown inertial navigation system(SINS) for long term applications,the rotation technique is employed to modulate the errors of the inertial sensors into periodically varied signals,and,as a result,to suppress the divergence of SINS errors.However,the errors of rotation platform will be introduced into SINS and might affect the final navigation accuracy.Considering the disadvantages of the conventional navigation computation scheme,an improved computation scheme of the SINS using rotation technique is proposed which can reduce the effects of the rotation platform errors.And,the error characteristics of the SINS with this navigation computation scheme are analyzed.Theoretical analysis,simulations and real test results show that the proposed navigation computation scheme outperforms the conventional navigation computation scheme,meanwhile reduces the requirement to the measurement accuracy of rotation angles.展开更多
A Fault detection and isolation(FDI)scheme for discrete time-delay system is proposed in this paper,which can not only detect but also isolate the faults.A time delay operator is introduced to resolve the problem bro...A Fault detection and isolation(FDI)scheme for discrete time-delay system is proposed in this paper,which can not only detect but also isolate the faults.A time delay operator is introduced to resolve the problem brought by the time-delay system.The design and computation for the FDI system is carried by computer math tool Maple,which can easily deal with the symbolic computation.Residuals in the form of parity space can be deduced from the recursion of the system equations.Further more,a generalized residual set is created using the freedom of the parity space redundancy.Thus,both fault detection and fault isolation have been accomplished.The proposed method has been verified by a numerical example.展开更多
The randomness and complexity of urban traffic scenes make it a difficult task for self-driving cars to detect drivable areas, Inspired by human driving behaviors, we propose a novel method of drivable area detection ...The randomness and complexity of urban traffic scenes make it a difficult task for self-driving cars to detect drivable areas, Inspired by human driving behaviors, we propose a novel method of drivable area detection for self-driving cars based on fusing pixel information from a monocular camera with spatial information from a light detection and ranging （LIDAR） scanner, Similar to the bijection of collineation, a new concept called co-point mapping, which is a bijection that maps points from the LIDAR scanner to points on the edge of the image segmentation, is introduced in the proposed method, Our method posi- tions candidate drivable areas through self-learning models based on the initial drivable areas that are obtained by fusing obstacle information with superpixels, In addition, a fusion of four features is applied in order to achieve a more robust performance, In particular, a feature called drivable degree （DD） is pro- posed to characterize the drivable degree of the LIDAR points, After the initial drivable area is characterized by the features obtained through self-learning, a Bayesian framework is utilized to calculate the final probability map of the drivable area, Our approach introduces no common hypothesis and requires no training steps; yet it yields a state-of-art performance when tested on the ROAD-KITTI benchmark, Experimental results demonstrate that the proposed method is a general and efficient approach for detecting drivable area,展开更多
文摘电流型电路具有功耗低、速度快的特点,是当今集成电路研究的一个热点.文章基于阈算术代数系统,改进了非相交分解算法;设计了电流型互补金属氧化物半导体(complementary metal oxide semiconductor, CMOS)的异或门电路,并利用改进后的新算法,将n变量函数分解成3变量函数,实现了任意n变量函数电路.模拟测试证明所设计的电路结构简单,且具有正确的逻辑功能.
文摘Rising energy costs and growing environmental awareness motivate a critical revision of the design of distillation units. Systematic design techniques, such as the rectification body, column profile map, and temperature collocation methods, require exact knowledge of all pinch points in a particular system, because these stationary points delineate the possible composition trajectories realizable in separation columns. This paper demonstrates novel methods for rigorously determining all pinch points for the constant relative volatility, ideal and non-ideal systems. Constant relative volatility and ideal solution systems are transformed into one-dimensional polynomial and nonlinear functions, regardless of the number of the components. A deflation method is proposed to locate all zeros in ideal and non-ideal zeotropic problems. For more challenging non-ideal problems, a novel hybrid sequential niche algorithm is used to solve hard azeotropic problems successfully. Finally, the design implications of these pinch point locations are investigated to show how new separation configurations can be devised. Methodically the paper points out the use of rigorous pinch point computations in conjunction with continuous composition profiles for robust distillation design.
基金supported by NSFC(No. 61571055)fund of SKL of MMW (No. K201815)Important National Science & Technology Specific Projects(2017ZX03001028)
文摘Mobile edge computing （MEC） is a novel technique that can reduce mobiles＇ com- putational burden by tasks offioading, which emerges as a promising paradigm to provide computing capabilities in close proximity to mobile users. In this paper, we will study the scenario where multiple mobiles upload tasks to a MEC server in a sing cell, and allocating the limited server resources and wireless chan- nels between mobiles becomes a challenge. We formulate the optimization problem for the energy saved on mobiles with the tasks being dividable, and utilize a greedy choice to solve the problem. A Select Maximum Saved Energy First （SMSEF） algorithm is proposed to realize the solving process. We examined the saved energy at different number of nodes and channels, and the results show that the proposed scheme can effectively help mobiles to save energy in the MEC system.
基金Project(60604011) supported by the National Natural Science Foundation of China
文摘To improve the accuracy of strapdown inertial navigation system(SINS) for long term applications,the rotation technique is employed to modulate the errors of the inertial sensors into periodically varied signals,and,as a result,to suppress the divergence of SINS errors.However,the errors of rotation platform will be introduced into SINS and might affect the final navigation accuracy.Considering the disadvantages of the conventional navigation computation scheme,an improved computation scheme of the SINS using rotation technique is proposed which can reduce the effects of the rotation platform errors.And,the error characteristics of the SINS with this navigation computation scheme are analyzed.Theoretical analysis,simulations and real test results show that the proposed navigation computation scheme outperforms the conventional navigation computation scheme,meanwhile reduces the requirement to the measurement accuracy of rotation angles.
基金National Natural Science Foundation of China(No.60574081)
文摘A Fault detection and isolation(FDI)scheme for discrete time-delay system is proposed in this paper,which can not only detect but also isolate the faults.A time delay operator is introduced to resolve the problem brought by the time-delay system.The design and computation for the FDI system is carried by computer math tool Maple,which can easily deal with the symbolic computation.Residuals in the form of parity space can be deduced from the recursion of the system equations.Further more,a generalized residual set is created using the freedom of the parity space redundancy.Thus,both fault detection and fault isolation have been accomplished.The proposed method has been verified by a numerical example.
基金This research was partially supported by the National Natural Science Foundation of China （61773312）, the National Key Research and Development Plan （2017YFC0803905）, and the Program of Introducing Talents of Discipline to University （B13043）.
文摘The randomness and complexity of urban traffic scenes make it a difficult task for self-driving cars to detect drivable areas, Inspired by human driving behaviors, we propose a novel method of drivable area detection for self-driving cars based on fusing pixel information from a monocular camera with spatial information from a light detection and ranging （LIDAR） scanner, Similar to the bijection of collineation, a new concept called co-point mapping, which is a bijection that maps points from the LIDAR scanner to points on the edge of the image segmentation, is introduced in the proposed method, Our method posi- tions candidate drivable areas through self-learning models based on the initial drivable areas that are obtained by fusing obstacle information with superpixels, In addition, a fusion of four features is applied in order to achieve a more robust performance, In particular, a feature called drivable degree （DD） is pro- posed to characterize the drivable degree of the LIDAR points, After the initial drivable area is characterized by the features obtained through self-learning, a Bayesian framework is utilized to calculate the final probability map of the drivable area, Our approach introduces no common hypothesis and requires no training steps; yet it yields a state-of-art performance when tested on the ROAD-KITTI benchmark, Experimental results demonstrate that the proposed method is a general and efficient approach for detecting drivable area,
