The problem of distributed detection fusion using multiple sensors for remote underwater target detection is studied. Considering that multiple access channel （MAC） schemes are able to offer high efficiency in bandw...The problem of distributed detection fusion using multiple sensors for remote underwater target detection is studied. Considering that multiple access channel （MAC） schemes are able to offer high efficiency in bandwidth usage and consume less energy than the parallel access channel （PAC）, the MAC scheme is introduced into the underwater target detection field. The model of underwater distributed detection fusion based on MAC schemes is established. A new method for detection fusion of MAC based on deflection coefficient maximization （DCM） and Neyman-Pearson （NP） rule is proposed. Under the power constraint of local sensors, this paper uses the DCM theory to derive the optimal weight coefficients and offsets. The closed-form expressions of detection probability and false alarm probability for fusion systems are obtained. The optimal detection performance of fusion systems is analyzed and deeply researched. Both the theory analysis and simulation experiments indicate that the proposed method could improve the detection performance and decrease the error probability effectively under power constraints of local sensors and low signal to noise ratio.展开更多
With a NP hard problem given, we may find a equivalent physical world. The rule of the changing of the physical states is simply the algorithm for solving the original NP hard problem .It is the most natural algorithm...With a NP hard problem given, we may find a equivalent physical world. The rule of the changing of the physical states is simply the algorithm for solving the original NP hard problem .It is the most natural algorithm for solving NP hard problems. In this paper we deal with a famous example , the well known NP hard problem——Circles Packing. It shows that our algorithm is dramatically very efficient. We are inspired that, the concrete physics algorithm will always be very efficient for NP hard problem.展开更多
In the privacy preservation of association rules, sensitivity analysis should be reported after the quantification of items in terms of their occurrence. The traditional methodologies, used for preserving confidential...In the privacy preservation of association rules, sensitivity analysis should be reported after the quantification of items in terms of their occurrence. The traditional methodologies, used for preserving confidentiality of association rules, are based on the assumptions while safeguarding susceptible information rather than recognition of insightful items. Therefore, it is time to go one step ahead in order to remove such assumptions in the protection of responsive information especially in XML association rule mining. Thus, we focus on this central and highly researched area in terms of generating XML association rule mining without arguing on the disclosure risks involvement in such mining process. Hence, we described the identification of susceptible items in order to hide the confidential information through a supervised learning technique. These susceptible items show the high dependency on other items that are measured in terms of statistical significance with Bayesian Network. Thus, we proposed two methodologies based on items probabilistic occurrence and mode of items. Additionally, all this information is modeled and named PPDM (Privacy Preservation in Data Mining) model for XARs. Furthermore, the PPDM model is helpful for sharing markets information among competitors with a lower chance of generating monopoly. Finally, PPDM model introduces great accuracy in computing sensitivity of items and opens new dimensions to the academia for the standardization of such NP-hard problems.展开更多
基金supported by the National Natural Science Foundation of China (60972152)Northwestern Polytechnical University Foun dations for Fundamental Research (JC201027 JC20100223)
文摘The problem of distributed detection fusion using multiple sensors for remote underwater target detection is studied. Considering that multiple access channel （MAC） schemes are able to offer high efficiency in bandwidth usage and consume less energy than the parallel access channel （PAC）, the MAC scheme is introduced into the underwater target detection field. The model of underwater distributed detection fusion based on MAC schemes is established. A new method for detection fusion of MAC based on deflection coefficient maximization （DCM） and Neyman-Pearson （NP） rule is proposed. Under the power constraint of local sensors, this paper uses the DCM theory to derive the optimal weight coefficients and offsets. The closed-form expressions of detection probability and false alarm probability for fusion systems are obtained. The optimal detection performance of fusion systems is analyzed and deeply researched. Both the theory analysis and simulation experiments indicate that the proposed method could improve the detection performance and decrease the error probability effectively under power constraints of local sensors and low signal to noise ratio.
基金86 3National High-Tech Program of China(86 3-30 6 -0 5 -0 3-1) National Natural Science Foundation of China(193310 5 0 ) Chi
文摘With a NP hard problem given, we may find a equivalent physical world. The rule of the changing of the physical states is simply the algorithm for solving the original NP hard problem .It is the most natural algorithm for solving NP hard problems. In this paper we deal with a famous example , the well known NP hard problem——Circles Packing. It shows that our algorithm is dramatically very efficient. We are inspired that, the concrete physics algorithm will always be very efficient for NP hard problem.
文摘In the privacy preservation of association rules, sensitivity analysis should be reported after the quantification of items in terms of their occurrence. The traditional methodologies, used for preserving confidentiality of association rules, are based on the assumptions while safeguarding susceptible information rather than recognition of insightful items. Therefore, it is time to go one step ahead in order to remove such assumptions in the protection of responsive information especially in XML association rule mining. Thus, we focus on this central and highly researched area in terms of generating XML association rule mining without arguing on the disclosure risks involvement in such mining process. Hence, we described the identification of susceptible items in order to hide the confidential information through a supervised learning technique. These susceptible items show the high dependency on other items that are measured in terms of statistical significance with Bayesian Network. Thus, we proposed two methodologies based on items probabilistic occurrence and mode of items. Additionally, all this information is modeled and named PPDM (Privacy Preservation in Data Mining) model for XARs. Furthermore, the PPDM model is helpful for sharing markets information among competitors with a lower chance of generating monopoly. Finally, PPDM model introduces great accuracy in computing sensitivity of items and opens new dimensions to the academia for the standardization of such NP-hard problems.
