A mixed EM algorithm based on partial E-steps method was presented which can reduce the intensity of computation,make it adapted to the scale of data sets better and have the standard convergence guarantee of EM.

In the paper, Gaussian mixture model is used to describe the residuals of matches in the new robust algorithm for fundamental matrix estimation, and an improved split-merge EM (SMEM) algorithm is used to classify the matches, so that the false matches can be detected and rejected by the least mean absolute residual criteria.

We derived the EM-like algorithm to estimate the model parameters through optimizing the system cost function.

In the paper, Gaussian mixture model is used to describe the residuals of matches in the new robust algorithm for fundamental matrix estimation, and an improved split-merge EM (SMEM) algorithm is used to classify the matches, so that the false matches can be detected and rejected by the least mean absolute residual criteria.

An EM algorithm is derived to compute maximum likelihood estimate.

The three-dimensional reconstruction algorithm based on Susan operator and optical flow method and expectation maximization algorithm was introduced to slove the problem about the low degree of automation and inefficient in process of selecting feature points in target object in three-dimensional retrieval based three-dimensional reconstruction.

Study of an adaptive technology for estimating the parameters of single ion channel signal based on EM algorithm;

A multipath time delay estimation algorithm based on EM algorithm under α-stable distribution impulse noise environment;

Parameter estimation of incomplete data using α-EM algorithm;