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We describe a novel method of combining distance matrices by selecting the minimum pairwise distance.
However, by selecting the minimum number of features and deleting most background pixels, we were able to significantly reduce the level of computational complexity.
These T lists are then used to compute the LLR values by selecting the minimum distances for symbol vectors from these lists having 0 or 1 in the desired bit position where the LLR value is to be computed.
Then, each node propagates its current component id to its neighbors, and updates its own component id by selecting the minimum value between its current component id and the received component ids from its neighbors.
After each technology is evaluated in terms of the attributes (i.e., x1 through x9), for each attribute, the overall attribute score of a system is calculated by adding the technology scores of the system or by selecting the minimum technology score of the system.
Finally, one simple way to approximate the ML distance and LLRs is by selecting the minimum over all t in (28) and (31), respectively: begin{array}{cc}{d}^{mathrm{ML}}& approx underset{t=1,cdots kern0.3em,T}{ min}left({d}_t^{mathrm{WL}}right),kern2em {varLambda}_{n,k}^{mathrm{ML}}approx underset{t=1,cdots kern0.3em,T}{ min}left({varLambda}_{n,k,t}^{mathrm{WL}}right).end{array} (32).
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More specifically, the block is estimated by selecting the mode with minimum matching error from the following three modes of motion compensation.
Akaike's Information Criteria (AIC) [17] has been shown to be a highly reliable way of choosing the best model by selecting the model with the minimum AIC score [14].
(iv) The procedure was completed by selecting the oligonucleotide having the minimum number of non specific target and smallest distance to the 3' end of the query.
When multiple ProbeSets were present for a single Entrez Gene ID they were collapsed by selecting the ProbeSet with the minimum p-value.
The nine maximum-likelihood models of gene-expression evolution were compared by the Akaike Information Criterion AICC) and the best fitting evolutionary model was determined by selecting the one with the minimum AIC value.
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