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cut – Stand-alone implementation of k-feasible cut computation, used for technology mapping.
Despite its success in different fields, it is still faced with several design problems, in particular the determination of the number and parameters of the different models representative of the system as well as the choice of the adequate method of validities computation used for multimodel output deduction.
The computation used for the utility given in Eq. 1 defines a new rank for the Design Patterns results which reflect to the user's opinion regarding the utility of each Design Pattern.
To get the same information with likelihood-based methods would require a huge amount of additional computation whereas, with ABC, the largest proportion of computation used for estimating parameters can be recycled in a bias/precision analysis.
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Finally, the results of computation are used for noise prediction.
Evolutionary computation is used for tuning the parameters of the classifiers and looking for the best minimal ECOC code configuration.
The measurement variances used in KF computation were used for the standardization of the measurement residuals.
A mass-based computation was used for better evaluation of the treatment process.
Computation methods used for FPGA dramatically differ from classic methods used in Von Neumann PCs or even SIMD processing units like GPUs or DSPs.
The same computation was used for gene ontology analyses of the initial gene list.
Furthermore, experimental and computation methods used for the study and the analysis of these biomarkers are presented.
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