To improve the detection accuracy of the balise uplink signal transmitted in a strong noise environment,we use chaotic oscillator to detect the balise uplink signal based on the characteristics of the chaotic system t...To improve the detection accuracy of the balise uplink signal transmitted in a strong noise environment,we use chaotic oscillator to detect the balise uplink signal based on the characteristics of the chaotic system that is sensitive to initial conditions and immune to noise.Combining with the principle of Duffing oscillator system used in weak signal detection and uplink signal feature,the methods and steps of using Duffing oscillator to detect the balise signal are presented.Furthermore,the Lyapunov exponent algorithm is used to calculate the critical threshold of the Duffing oscillator detection system.Thus,the output states of the system can be quantitatively judged to achieve demodulation of the balise signal.The simulation results show that the chaotic oscillator detection method for balise signal based on Lyapunov exponent algorithm not only improves the accuracy and efficiency of threshold setting,but also ensures the reliability of balise signal detection.展开更多
Recently, privacy concerns about data collection have received an increasing amount of attention. In data collection process, a data collector （an agency） assumed that all respondents would be comfortable with submi...Recently, privacy concerns about data collection have received an increasing amount of attention. In data collection process, a data collector （an agency） assumed that all respondents would be comfortable with submitting their data if the published data was anonymous. We believe that this assumption is not realistic because the increase in privacy concerns causes some re- spondents to refuse participation or to submit inaccurate data to such agencies. If respondents submit inaccurate data, then the usefulness of the results from analysis of the collected data cannot be guaranteed. Furthermore, we note that the level of anonymity （i.e., k-anonymity） guaranteed by an agency cannot be verified by respondents since they generally do not have access to all of the data that is released. Therefore, we introduce the notion of ki-anonymity, where ki is the level of anonymity preferred by each respondent i. Instead of placing full trust in an agency, our solution increases respondent confidence by allowing each to decide the preferred level of protection. As such, our protocol ensures that respondents achieve their preferred kranonymity during data collection and guarantees that the collected records are genuine and useful for data analysis.展开更多
基金National Natural Science Foundation of China(No.61763025)。
文摘To improve the detection accuracy of the balise uplink signal transmitted in a strong noise environment,we use chaotic oscillator to detect the balise uplink signal based on the characteristics of the chaotic system that is sensitive to initial conditions and immune to noise.Combining with the principle of Duffing oscillator system used in weak signal detection and uplink signal feature,the methods and steps of using Duffing oscillator to detect the balise signal are presented.Furthermore,the Lyapunov exponent algorithm is used to calculate the critical threshold of the Duffing oscillator detection system.Thus,the output states of the system can be quantitatively judged to achieve demodulation of the balise signal.The simulation results show that the chaotic oscillator detection method for balise signal based on Lyapunov exponent algorithm not only improves the accuracy and efficiency of threshold setting,but also ensures the reliability of balise signal detection.
基金supported by the Basic Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(No.NRF-2014R1A1A2058695)
文摘Recently, privacy concerns about data collection have received an increasing amount of attention. In data collection process, a data collector （an agency） assumed that all respondents would be comfortable with submitting their data if the published data was anonymous. We believe that this assumption is not realistic because the increase in privacy concerns causes some re- spondents to refuse participation or to submit inaccurate data to such agencies. If respondents submit inaccurate data, then the usefulness of the results from analysis of the collected data cannot be guaranteed. Furthermore, we note that the level of anonymity （i.e., k-anonymity） guaranteed by an agency cannot be verified by respondents since they generally do not have access to all of the data that is released. Therefore, we introduce the notion of ki-anonymity, where ki is the level of anonymity preferred by each respondent i. Instead of placing full trust in an agency, our solution increases respondent confidence by allowing each to decide the preferred level of protection. As such, our protocol ensures that respondents achieve their preferred kranonymity during data collection and guarantees that the collected records are genuine and useful for data analysis.
