There are considerable literatures on the Bit Error Rate(BER)evaluation of DifferentialDetection of Gaussian Minimum Shift Keying(DDGMSK)system using Decision Feedback(DF),butmost of them give the performance based on...There are considerable literatures on the Bit Error Rate(BER)evaluation of DifferentialDetection of Gaussian Minimum Shift Keying(DDGMSK)system using Decision Feedback(DF),butmost of them give the performance based on the Monte Carlo Error Counting(MCEC)technique.Fromthe probability distribution of the phase angle between two vectors perturbed by Gaussian noises,theformulae of BER are derived for the performance analysis of DDGMSK system with DF in this letter.Considering the m-bit dock-tailed sequence,the new formulae of Gaussian Minimum Shift Keying(GMSK)modulated phase and the Time-Varying Signal to Noise Ratio(TVSNR)of the demodulatedsignal are presented,and it is proved that the relationship between the TVSNR of the demodulatedsignal and the size of eye opening is not inevitable.Simulation results show that the theoretical in-vestigation gives analogous results with the MCEC technique.The formulae presented are useful for theperformance analysis of systems using GMSK as modulating and demodulating method,for instance,the analysis of synchronous performance of frequency-hopping communication system.展开更多
The aggregation of fuzzy opinions is an important component of group decision analysis with fuzzy information. This paper proposes two new approaches for the assessment of the weights to be associated with fuzzy opini...The aggregation of fuzzy opinions is an important component of group decision analysis with fuzzy information. This paper proposes two new approaches for the assessment of the weights to be associated with fuzzy opinions. These approaches involve,respectively,the minimization of the sum of squared differences between the individual weighted fuzzy opinion and the weighted mean value of all fuzzy opinions,which is called the weighted minimum variance method (WMVM),and the minimax difference of any two adjacent individual weighted fuzzy opinions,which is called the mean value minimax differences method (MVMDM). The two approaches are developed and numerical examples are presented to illustrate their simplicity and effectiveness in aggregating fuzzy opinions.展开更多
This paper proposes a novel de-noising algorithm based on ensemble empirical mode decomposition(EEMD) and the variable step size least mean square(VS-LMS) adaptive filter.The noise of the high frequency part of spectr...This paper proposes a novel de-noising algorithm based on ensemble empirical mode decomposition(EEMD) and the variable step size least mean square(VS-LMS) adaptive filter.The noise of the high frequency part of spectrum will be removed through EEMD,and then the VS-LMS algorithm is utilized for overall de-noising.The EEMD combined with VS-LMS algorithm can not only preserve the detail and envelope of the effective signal,but also improve the system stability.When the method is used on pure R6G,the signal-to-noise ratio(SNR) of Raman spectrum is lower than 10dB.The de-noising superiority of the proposed method in Raman spectrum can be verified by three evaluation standards of SNR,root mean square error(RMSE) and the correlation coefficient ρ.展开更多
基金the National Natural Science Foundation of China(No.60132030,60572147)the 111 Project(B08033).
文摘There are considerable literatures on the Bit Error Rate(BER)evaluation of DifferentialDetection of Gaussian Minimum Shift Keying(DDGMSK)system using Decision Feedback(DF),butmost of them give the performance based on the Monte Carlo Error Counting(MCEC)technique.Fromthe probability distribution of the phase angle between two vectors perturbed by Gaussian noises,theformulae of BER are derived for the performance analysis of DDGMSK system with DF in this letter.Considering the m-bit dock-tailed sequence,the new formulae of Gaussian Minimum Shift Keying(GMSK)modulated phase and the Time-Varying Signal to Noise Ratio(TVSNR)of the demodulatedsignal are presented,and it is proved that the relationship between the TVSNR of the demodulatedsignal and the size of eye opening is not inevitable.Simulation results show that the theoretical in-vestigation gives analogous results with the MCEC technique.The formulae presented are useful for theperformance analysis of systems using GMSK as modulating and demodulating method,for instance,the analysis of synchronous performance of frequency-hopping communication system.
文摘The aggregation of fuzzy opinions is an important component of group decision analysis with fuzzy information. This paper proposes two new approaches for the assessment of the weights to be associated with fuzzy opinions. These approaches involve,respectively,the minimization of the sum of squared differences between the individual weighted fuzzy opinion and the weighted mean value of all fuzzy opinions,which is called the weighted minimum variance method (WMVM),and the minimax difference of any two adjacent individual weighted fuzzy opinions,which is called the mean value minimax differences method (MVMDM). The two approaches are developed and numerical examples are presented to illustrate their simplicity and effectiveness in aggregating fuzzy opinions.
基金supported by the National Natural Science Foundation of China(No.61308120)the Doctor Startup Project of Xinjiang University(No.BS120122)+1 种基金the Young Talents Project in Xinjiang Uygur Autonomous Region(No.2013731003)the Xinjiang Science and Technology Project(Nos.201412107 and 2014211B003)
文摘This paper proposes a novel de-noising algorithm based on ensemble empirical mode decomposition(EEMD) and the variable step size least mean square(VS-LMS) adaptive filter.The noise of the high frequency part of spectrum will be removed through EEMD,and then the VS-LMS algorithm is utilized for overall de-noising.The EEMD combined with VS-LMS algorithm can not only preserve the detail and envelope of the effective signal,but also improve the system stability.When the method is used on pure R6G,the signal-to-noise ratio(SNR) of Raman spectrum is lower than 10dB.The de-noising superiority of the proposed method in Raman spectrum can be verified by three evaluation standards of SNR,root mean square error(RMSE) and the correlation coefficient ρ.
