Aiming at source number determination and direction of arrival(DOA) estimation under the case of time-varying source number,a method of DOA estimation with an unknown number of sources was proposed.Firstly,an algorith...Aiming at source number determination and direction of arrival(DOA) estimation under the case of time-varying source number,a method of DOA estimation with an unknown number of sources was proposed.Firstly,an algorithm based on crossvalidation technique was introduced to determine the number of sources.Then dynamic DOAs of source were estimated using an algorithm based on blind source separation(BSS) under the case that number of sources were unknown in advance and it was timevarying.The effectiveness of the proposed method was validated by simulation of time-invariant and time-varying numbers of source.Compared with other conventional methods,the proposed method has superior evaluation performances The proposed method can estimate m(the numbers of sensor) DOAs while other conventional methods estimate less than m DOAs.The R_(mse) of the proposed method in the case of low signal-to-noise ratio(SNR)(equal or lower than 30 dB) is smaller than 0.2 while R_(mse) of other conventional methods are greater than 0.8.展开更多
Blind source separation and estimation of the number of sources usually demand that the number of sensors should be greater than or equal to that of the sources, which, however, is very difficult to satisfy for the co...Blind source separation and estimation of the number of sources usually demand that the number of sensors should be greater than or equal to that of the sources, which, however, is very difficult to satisfy for the complex systems. A new estimating method based on power spectral density （PSD） is presented. When the relation between the number of sensors and that of sources is unknown, the PSD matrix is first obtained by the ratio of PSD of the observation signals, and then the bound of the number of correlated sources with common frequencies can be estimated by comparing every column vector of PSD matrix. The effectiveness of the proposed method is verified by theoretical analysis and experiments, and the influence of noise on the estimation of number of source is simulated.展开更多
We consider the MAP/PH/N retrial queue with a finite number of sources operating in a finite state Markovian random environment. Two different types of multi-dimensional Markov chains are investigated describing the b...We consider the MAP/PH/N retrial queue with a finite number of sources operating in a finite state Markovian random environment. Two different types of multi-dimensional Markov chains are investigated describing the behavior of the system based on state space arrangements. The special features of the two formulations are discussed. The algorithms for calculating the stationary state probabilities are elaborated, based on which the main performance measures are obtained, and numerical examples are presented as well.展开更多
基金National Natural Science Foundation of China(No.51309116)the Foundation of Fujian Education Committee for Distinguished Young Scholars,China(No.JA14169)+2 种基金the Scientific Research Foundations of Jimei University,China(Nos.ZQ2013001,ZC2013012)Open Project of Artificial Intelligence Key Laboratory of Sichuan Province,China(No.2014RYJ03)Natural Science Foundation of Fujian Province,China(No.2016J01736)
文摘Aiming at source number determination and direction of arrival(DOA) estimation under the case of time-varying source number,a method of DOA estimation with an unknown number of sources was proposed.Firstly,an algorithm based on crossvalidation technique was introduced to determine the number of sources.Then dynamic DOAs of source were estimated using an algorithm based on blind source separation(BSS) under the case that number of sources were unknown in advance and it was timevarying.The effectiveness of the proposed method was validated by simulation of time-invariant and time-varying numbers of source.Compared with other conventional methods,the proposed method has superior evaluation performances The proposed method can estimate m(the numbers of sensor) DOAs while other conventional methods estimate less than m DOAs.The R_(mse) of the proposed method in the case of low signal-to-noise ratio(SNR)(equal or lower than 30 dB) is smaller than 0.2 while R_(mse) of other conventional methods are greater than 0.8.
基金This project is supported by National Natural Science Foundation of China(No.50675076).
文摘Blind source separation and estimation of the number of sources usually demand that the number of sensors should be greater than or equal to that of the sources, which, however, is very difficult to satisfy for the complex systems. A new estimating method based on power spectral density （PSD） is presented. When the relation between the number of sensors and that of sources is unknown, the PSD matrix is first obtained by the ratio of PSD of the observation signals, and then the bound of the number of correlated sources with common frequencies can be estimated by comparing every column vector of PSD matrix. The effectiveness of the proposed method is verified by theoretical analysis and experiments, and the influence of noise on the estimation of number of source is simulated.
基金Supported by National Social Science Foundation of China(No.11BTJ011)Humanities and Social Sciences Foundation of Ministry of Education of China,2012(No.12YJAZH173)
文摘We consider the MAP/PH/N retrial queue with a finite number of sources operating in a finite state Markovian random environment. Two different types of multi-dimensional Markov chains are investigated describing the behavior of the system based on state space arrangements. The special features of the two formulations are discussed. The algorithms for calculating the stationary state probabilities are elaborated, based on which the main performance measures are obtained, and numerical examples are presented as well.
