Sentence examples for model order detection from inspiring English sources
Once the association parameters for all proteins in the candidate PPIN were identified for each protein, significant protein associations were determined using the interaction model order detection method based on estimated association abilities, that is, to detect the interaction number M i in (2).
The problem is formulated in terms of a model order detection problem, where a set of active and inactive sensors can be distinguished, thus allowing the detector to operate with a rank-reduced version of the observed covariance matrix.
To remove false positive PPIs from each candidate PPIN for different biological conditions, we used both a PPI model and a model order detection method to prune each candidate PPIN using the corresponding microarray data to approach the actual PPIN.
Once the association parameters for all proteins in the candidate PPI network were identified for each protein, the significant protein associations were determined using the interaction model order detection method based on the estimated association abilities.
Finally, we prune away the insignificant regulatory genes by AIC model order detection method in system identification [ 22] to refine the gene regulatory network of inflammatory response to bacterial endotoxin.
After organizing the cancer microarray data and PPI data, we used a PPI model, the maximum likelihood parameter estimation method and a model order detection method together to prune each candidate PPIN by the corresponding microarray data to approach the actual PPIN of each cancer.
This problem will occur whenever the number of signal components is unknown, and that is why the conventional GLRT poses some limitations in this type of nested or model order-based detection problems.
The next step is to substitute the expression in (24) into (15) and perform the joint PU signal detection and model order selection from l = 1,…,K.
However, the model order selection scheme in (29) yields a Probability of correct Detection (PoD) inferior to the some MOS techniques found in the literature.
We found that the optimal Markov model order differed for different motifs: in 40 repeat runs, optimal model orders were zero for detection of blocks 06, 22 and 29, first for 10, 25 and 30, second for 23 and 28, and third for 08 and 20.
