Given a set U which is consisted of strings defined on alphabet Σ, string cross pattern matching is to find all the matches between every two strings in U. It is utilized in text processing like removing the duplicat...Given a set U which is consisted of strings defined on alphabet Σ, string cross pattern matching is to find all the matches between every two strings in U. It is utilized in text processing like removing the duplication of strings. This paper presents a fast string cross pattern matching algorithm based on extracting high frequency strings. Compared with existing algorithms including single-pattern algorithms and multi-pattern matching algorithms, this algorithm is featured by both low time complexity and low space complexity. Because Chinese alphabet is large and the average length of Chinese words is much short, this algorithm is more suitable to process the text written by Chinese, especially when the size of Σ is large and the number of strings is far more than the maximum length of strings of set U.展开更多
Magnetic sensors can be applied in vehicle recognition.Most of the existing vehicle recognition algorithms use one sensor node to measure a vehicle’s signature.However,vehicle speed variation and environmental distur...Magnetic sensors can be applied in vehicle recognition.Most of the existing vehicle recognition algorithms use one sensor node to measure a vehicle’s signature.However,vehicle speed variation and environmental disturbances usually cause errors during such a process.In this paper we propose a method using multiple sensor nodes to accomplish vehicle recognition.Based on the matching result of one vehicle’s signature obtained by different nodes,this method determines vehicle status and corrects signature segmentation.The co-relationship between signatures is also obtained,and the time offset is corrected by such a co-relationship.The corrected signatures are fused via maximum likelihood estimation,so as to obtain more accurate vehicle signatures.Examples show that the proposed algorithm can provide input parameters with higher accuracy.It improves the average accuracy of vehicle recognition from 94.0%to 96.1%,and especially the bus recognition accuracy from 77.6%to 92.8%.展开更多
This Letter presents an original technique to design and synthesize an inhomogeneous asymmetrical lens resulting in a special fan-beam radiation pattern in a wide frequency bandwidth. The vertical and horizontal plane...This Letter presents an original technique to design and synthesize an inhomogeneous asymmetrical lens resulting in a special fan-beam radiation pattern in a wide frequency bandwidth. The vertical and horizontal planes of the fan-beam radiation pattern can be determined separately. Wide angle search and detection are achievable by using this type of lens antenna because of its suitable radiation pattern. The proposed relative index profile is validated by the means of commercial CST software and an FDTD scheme.展开更多
文摘Given a set U which is consisted of strings defined on alphabet Σ, string cross pattern matching is to find all the matches between every two strings in U. It is utilized in text processing like removing the duplication of strings. This paper presents a fast string cross pattern matching algorithm based on extracting high frequency strings. Compared with existing algorithms including single-pattern algorithms and multi-pattern matching algorithms, this algorithm is featured by both low time complexity and low space complexity. Because Chinese alphabet is large and the average length of Chinese words is much short, this algorithm is more suitable to process the text written by Chinese, especially when the size of Σ is large and the number of strings is far more than the maximum length of strings of set U.
基金supported by the National Natural Science Foundation of China(No.61104164)the National High-Tech R&D Program(863)of China(No.2012AA112401)
文摘Magnetic sensors can be applied in vehicle recognition.Most of the existing vehicle recognition algorithms use one sensor node to measure a vehicle’s signature.However,vehicle speed variation and environmental disturbances usually cause errors during such a process.In this paper we propose a method using multiple sensor nodes to accomplish vehicle recognition.Based on the matching result of one vehicle’s signature obtained by different nodes,this method determines vehicle status and corrects signature segmentation.The co-relationship between signatures is also obtained,and the time offset is corrected by such a co-relationship.The corrected signatures are fused via maximum likelihood estimation,so as to obtain more accurate vehicle signatures.Examples show that the proposed algorithm can provide input parameters with higher accuracy.It improves the average accuracy of vehicle recognition from 94.0%to 96.1%,and especially the bus recognition accuracy from 77.6%to 92.8%.
文摘This Letter presents an original technique to design and synthesize an inhomogeneous asymmetrical lens resulting in a special fan-beam radiation pattern in a wide frequency bandwidth. The vertical and horizontal planes of the fan-beam radiation pattern can be determined separately. Wide angle search and detection are achievable by using this type of lens antenna because of its suitable radiation pattern. The proposed relative index profile is validated by the means of commercial CST software and an FDTD scheme.
