The problem of two-dimensional direction finding is approached by using a multi-layer Lshaped array. The proposed method is based on two sequential sparse representations,fulfilling respectively the estimation of elev...The problem of two-dimensional direction finding is approached by using a multi-layer Lshaped array. The proposed method is based on two sequential sparse representations,fulfilling respectively the estimation of elevation angles,and azimuth angles. For the estimation of elevation angles,the weighted sub-array smoothing technique for perfect data decorrelation is used to produce a covariance vector suitable for exact sparse representation,related only to the elevation angles. The estimates of elevation angles are then obtained by sparse restoration associated with this elevation angle dependent covariance vector. The estimates of elevation angles are further incorporated with weighted sub-array smoothing to yield a second covariance vector for precise sparse representation related to both elevation angles,and azimuth angles. The estimates of azimuth angles,automatically paired with the estimates of elevation angles,are finally obtained by sparse restoration associated with this latter elevation-azimuth angle related covariance vector. Simulation results are included to illustrate the performance of the proposed method.展开更多
A prodouct modeling and a process planning that are two essential basses of realizing concurrent engineering are investigated , a logical modeling technique , grammar representation scheme of technology knowledge and...A prodouct modeling and a process planning that are two essential basses of realizing concurrent engineering are investigated , a logical modeling technique , grammar representation scheme of technology knowledge and architecture of expert system for process planning within con- current engineering environment are proposed. They have been utilized in a real reaserch project.展开更多
A direction of arrival（DOA） estimation algorithm is proposed using the concept of sparse representation. In particular, a new sparse signal representation model called the smoothed covariance vector（SCV） is establ...A direction of arrival（DOA） estimation algorithm is proposed using the concept of sparse representation. In particular, a new sparse signal representation model called the smoothed covariance vector（SCV） is established, which is constructed using the lower left diagonals of the covariance matrix. DOA estimation is then achieved from the SCV by sparse recovering, where two distinguished error limit estimation methods of the constrained optimization are proposed to make the algorithms more robust. The algorithm shows robust performance on DOA estimation in a uniform array, especially for coherent signals. Furthermore, it significantly reduces the computational load compared with those algorithms based on multiple measurement vectors（MMVs）. Simulation results validate the effectiveness and efficiency of the proposed algorithm.展开更多
Process representation or modeling plays an important role in business process engineering. Process modeling languages can be evaluated by the extent to which they provide constructs useful for representing and reason...Process representation or modeling plays an important role in business process engineering. Process modeling languages can be evaluated by the extent to which they provide constructs useful for representing and reasoning about the aspects of a process, and subsequently are chosen for a certain purpose. This paper reviews process modeling language paradigms and points out their advantages and disadvantages.展开更多
Imparting human-like commonsense to machines is a long-term goal in the artificial intelligence community.To achieve this goal,constructing large-scale commonsense knowledge resources is an important step.In recent ye...Imparting human-like commonsense to machines is a long-term goal in the artificial intelligence community.To achieve this goal,constructing large-scale commonsense knowledge resources is an important step.In recent years,due to increasing demand,commonsense knowledge has become a rapidly growing research field,resulting in a surge of new acquisition methods and corresponding resources.These advances have empowered a variety of downstream AI tasks.However,constructing large-scale commonsense knowledge resources remains an ongoing and challenging task.It is still difficult to efficiently collect large-scale,high-quality commonsense knowledge.In this paper,we systematically review recent advances in commonsense knowledge acquisition methods and resources,providing a comprehensive summary of recent research scope,the characteristics of different resources,and unsolved challenges.展开更多
基金Supported by the National Natural Science Foundation of China(61331019,61490691)
文摘The problem of two-dimensional direction finding is approached by using a multi-layer Lshaped array. The proposed method is based on two sequential sparse representations,fulfilling respectively the estimation of elevation angles,and azimuth angles. For the estimation of elevation angles,the weighted sub-array smoothing technique for perfect data decorrelation is used to produce a covariance vector suitable for exact sparse representation,related only to the elevation angles. The estimates of elevation angles are then obtained by sparse restoration associated with this elevation angle dependent covariance vector. The estimates of elevation angles are further incorporated with weighted sub-array smoothing to yield a second covariance vector for precise sparse representation related to both elevation angles,and azimuth angles. The estimates of azimuth angles,automatically paired with the estimates of elevation angles,are finally obtained by sparse restoration associated with this latter elevation-azimuth angle related covariance vector. Simulation results are included to illustrate the performance of the proposed method.
文摘A prodouct modeling and a process planning that are two essential basses of realizing concurrent engineering are investigated , a logical modeling technique , grammar representation scheme of technology knowledge and architecture of expert system for process planning within con- current engineering environment are proposed. They have been utilized in a real reaserch project.
基金supported by the National Natural Science Foundation of China(6127130061405150)
文摘A direction of arrival（DOA） estimation algorithm is proposed using the concept of sparse representation. In particular, a new sparse signal representation model called the smoothed covariance vector（SCV） is established, which is constructed using the lower left diagonals of the covariance matrix. DOA estimation is then achieved from the SCV by sparse recovering, where two distinguished error limit estimation methods of the constrained optimization are proposed to make the algorithms more robust. The algorithm shows robust performance on DOA estimation in a uniform array, especially for coherent signals. Furthermore, it significantly reduces the computational load compared with those algorithms based on multiple measurement vectors（MMVs）. Simulation results validate the effectiveness and efficiency of the proposed algorithm.
基金The projectis supported by the Scientific Research Foundation for the Returned Overseas ChineseScholars,State Education Ministry
文摘Process representation or modeling plays an important role in business process engineering. Process modeling languages can be evaluated by the extent to which they provide constructs useful for representing and reasoning about the aspects of a process, and subsequently are chosen for a certain purpose. This paper reviews process modeling language paradigms and points out their advantages and disadvantages.
基金supported by the National Key Research and Development Program of China(No.2020AAA 0106400)the National Natural Science Foundation of China(Nos.61976211 and 62176257)+1 种基金supported by the Strategic Priority Research Program of Chinese Academy of Sciences,China(No.XDA27020100)the Youth Innovation Promotion Association CAS,China,and Yunnan Provincial Major Science and Technology Special Plan Projects,China(No.202202AD 080004).
文摘Imparting human-like commonsense to machines is a long-term goal in the artificial intelligence community.To achieve this goal,constructing large-scale commonsense knowledge resources is an important step.In recent years,due to increasing demand,commonsense knowledge has become a rapidly growing research field,resulting in a surge of new acquisition methods and corresponding resources.These advances have empowered a variety of downstream AI tasks.However,constructing large-scale commonsense knowledge resources remains an ongoing and challenging task.It is still difficult to efficiently collect large-scale,high-quality commonsense knowledge.In this paper,we systematically review recent advances in commonsense knowledge acquisition methods and resources,providing a comprehensive summary of recent research scope,the characteristics of different resources,and unsolved challenges.
