吉林大学学报(工学版) ›› 2013, Vol. 43 ›› Issue (02): 532-537.

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Fast convergence parameter estimation method based on expectation-maximum algorithm

WANG Ge, YU Hong-yi, SHEN Zhi-xiang, HU Yun-peng   

  1. Institute Information Engineering, The PLA Information Engineering University, Zhengzhou 450002, China
  • Received:2012-02-10 Online:2013-03-01 Published:2013-03-01

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Abstract: A fast convergence parameter estimation method based on Expectation-Maximum (EM) algorithm is developed. This method modifies the priori probability with posteriori probability in the iteration of the EM algorithm. The relationship between the CRB of parameter estimation and the convergence speed of the EM algorithm is analyzed. It is shown that to decrease the CRB of parameter estimation can accelerate the convergence speed of the EM algorithm. The mechanism to accelerate the convergence speed by the modified algorithm is proved, that is to reduce the entropy of the missing data. It is also proved that the modified algorithm can converge to the likelihood function as the non-modified algorithm. Taking phase estimation as example, the modified method is compared with traditional method based on EM algorithm. Simulation results show that, without affecting the estimation performance, the convergence speed of the modified method is faster.

Key words: communication technology, expectation-maximization algorithm, priori probability, convergence speed, synchronization parameters estimation, CRB

CLC Number: 

  • TN911.23
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