E-STEPExpanded Ships Technical Publication (System)
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Accordingly, a closed-form expression can be derived in the E-step and the complexity of the proposed algorithm can be significantly reduced.
In the M-step, we take three-dimensional feature vectors learned from E-step into account as input and continue using (4) as our learning formula.
As we said, the EM algorithm consists of two steps: E-step and M-step in each iteration.
Initialize parameters first and start with the E-Step computations
E-Step. Assume that we have an estimate of [[??].sup.(j-1)] as the (j - 1) th iteration of EM completed.
E-Step. Given p([[omega].sub.j] | [z.sub.k]) and p([z.sub.k] | [d.sub.i]), estimate p([z.sub.k] | [d.sub.i], [w.sub.j]):
(1) E-step: given the observations Y and the last estimates [theta] = {[h.sub.1], [h.sub.2]}, compute the expectation Q([theta] | [[??].sup.(i)]) of the log-likelihood of the complete data [Y.sub.c], which is also the conditional expectation of (13),
Then, the E-step and M-step of the SAGE algorithm for DOA and perturbation parameters estimation are derived.
where [epsilon] is a small constant (which determines the number of iteration times and the estimate accuracy), [MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII], otherwise, i = i + 1, go to E-step.
M-step: given the estimated p([z.sub.k] |[d.sub.i], [[omega].sub.j]) in E-step, and n([d.sub.i], [[omega].sub.j]), estimate p([[omega].sub.j] | [z.sub.k]) and p([z.sub.k] | [d.sub.i])
Meanwhile, the Dubai Land Department is offering an e-step service, which allows people to finalise the property sale procedures at their doorstep.
M-step, take [S.sup.(t)] estimated from E-step instead complete data sufficient statistics S, and then take into formula (4) we get [[theta].sup.(t+1)]