Following Jaynes-Cummings model,the evolution of the field entropy in the system of a two-level atom interacting with the single mode coherent field is investigated under rotating-wave approximation.The typical case &...Following Jaynes-Cummings model,the evolution of the field entropy in the system of a two-level atom interacting with the single mode coherent field is investigated under rotating-wave approximation.The typical case "the field frequency variance with time in the form of sine ω=ω0+usin(wt) has been considered.The influences of the amplitude and angle frequency of the field frequency variance on entropy evolution of the field are discussed by numerical calculations.Calculation results indicate that the field frequency variance influences violently the behavior of field entropy evolution;the larger the amplitude of the field frequency variance is,the stronger the influence of the field frequency variance on the time evolution of field entropy is.展开更多
The time-varying autoregressive （TVAR） modeling of a non-stationary signal is studied. In the proposed method, time-varying parametric identification of a non-stationary signal can be translated into a linear time-i...The time-varying autoregressive （TVAR） modeling of a non-stationary signal is studied. In the proposed method, time-varying parametric identification of a non-stationary signal can be translated into a linear time-invariant problem by introducing a set of basic functions. Then, the parameters are estimated by using a recursive least square algorithm with a forgetting factor and an adaptive time-frequency distribution is achieved. The simulation results show that the proposed approach is superior to the short-time Fourier transform and Wigner distribution. And finally, the proposed method is applied to the fault diagnosis of a bearing , and the experiment result shows that the proposed method is effective in feature extraction.展开更多
To improve the transmission performance of XCTD channel, this paper proposes a method to measure directly and fit the channel transmission characteristics by using frequency sweeping method. Sinusoidal signals with a ...To improve the transmission performance of XCTD channel, this paper proposes a method to measure directly and fit the channel transmission characteristics by using frequency sweeping method. Sinusoidal signals with a frequency range of 100 Hz to 10 k Hz and an interval of 100 Hz are used to measure transmission characteristics of channels with lengths of 300 m, 800 m, 1300 m, and 1800 m. The correctness of the fitted channel characteristics by transmitting square wave, composite waves of different frequencies, and ASK modulation are verified. The results show that when the frequency of the signal is below 1500 Hz, the channel has very little effect on the signal. The signal compensated for amplitude and phase at the receiver is not as good as the uncompensated signal.Alternatively, when the signal frequency is above 1500 Hz, the channel distorts the signal. The quality of signal compensated for amplitude and phase at receiver is better than that of the uncompensated signal. Thus, we can select the appropriate frequency for XCTD system and the appropriate way to process the received signals. Signals below1500 Hz can be directly used at the receiving end. Signals above 1500 Hz are used after amplitude and phase compensation at the receiving end.展开更多
A method utilizing single channel recordings to blindly separate the multicomponents overlapped in time and frequency domains is proposed in this paper. Based on the time varying AR model, the instantaneous frequency ...A method utilizing single channel recordings to blindly separate the multicomponents overlapped in time and frequency domains is proposed in this paper. Based on the time varying AR model, the instantaneous frequency and amplitude of each signal component are estimated respectively, thus the signal component separation is achieved. By using prolate spheroidal sequence as basis functions to expand the time varying parameters of the AR model, the method turns the problem of linear time varying parameters estimation to a linear time invariant parameter estimation problem, then the parameters are estimated by a recursive algorithm. The computation of this method is simple, and no prior knowledge of the signals is needed. Simulation results demonstrate validity and excellent performance of this method.展开更多
基金Natural Science Foundation of Fujian Province under Grant(No.2008J0217)
文摘Following Jaynes-Cummings model,the evolution of the field entropy in the system of a two-level atom interacting with the single mode coherent field is investigated under rotating-wave approximation.The typical case "the field frequency variance with time in the form of sine ω=ω0+usin(wt) has been considered.The influences of the amplitude and angle frequency of the field frequency variance on entropy evolution of the field are discussed by numerical calculations.Calculation results indicate that the field frequency variance influences violently the behavior of field entropy evolution;the larger the amplitude of the field frequency variance is,the stronger the influence of the field frequency variance on the time evolution of field entropy is.
基金This paper is supported by National Natural Science Foundation of China under Grant No.50675209 InnovationFund for Outstanding Scholar of Henan Province under Grant No. 0621000500
文摘The time-varying autoregressive （TVAR） modeling of a non-stationary signal is studied. In the proposed method, time-varying parametric identification of a non-stationary signal can be translated into a linear time-invariant problem by introducing a set of basic functions. Then, the parameters are estimated by using a recursive least square algorithm with a forgetting factor and an adaptive time-frequency distribution is achieved. The simulation results show that the proposed approach is superior to the short-time Fourier transform and Wigner distribution. And finally, the proposed method is applied to the fault diagnosis of a bearing , and the experiment result shows that the proposed method is effective in feature extraction.
基金financially supported by the National Key Research and Development Program of China(Grant No.2016YFC1400400)
文摘To improve the transmission performance of XCTD channel, this paper proposes a method to measure directly and fit the channel transmission characteristics by using frequency sweeping method. Sinusoidal signals with a frequency range of 100 Hz to 10 k Hz and an interval of 100 Hz are used to measure transmission characteristics of channels with lengths of 300 m, 800 m, 1300 m, and 1800 m. The correctness of the fitted channel characteristics by transmitting square wave, composite waves of different frequencies, and ASK modulation are verified. The results show that when the frequency of the signal is below 1500 Hz, the channel has very little effect on the signal. The signal compensated for amplitude and phase at the receiver is not as good as the uncompensated signal.Alternatively, when the signal frequency is above 1500 Hz, the channel distorts the signal. The quality of signal compensated for amplitude and phase at receiver is better than that of the uncompensated signal. Thus, we can select the appropriate frequency for XCTD system and the appropriate way to process the received signals. Signals below1500 Hz can be directly used at the receiving end. Signals above 1500 Hz are used after amplitude and phase compensation at the receiving end.
基金Supported by the Program for New Century Excellent Talents in University, Ministry of Education, China (Grant No. NCET-05-0803)
文摘A method utilizing single channel recordings to blindly separate the multicomponents overlapped in time and frequency domains is proposed in this paper. Based on the time varying AR model, the instantaneous frequency and amplitude of each signal component are estimated respectively, thus the signal component separation is achieved. By using prolate spheroidal sequence as basis functions to expand the time varying parameters of the AR model, the method turns the problem of linear time varying parameters estimation to a linear time invariant parameter estimation problem, then the parameters are estimated by a recursive algorithm. The computation of this method is simple, and no prior knowledge of the signals is needed. Simulation results demonstrate validity and excellent performance of this method.
