Sentence examples for systems in computational from inspiring English sources

With the development of many CML systems in computational chemistry and physics we need to be able to support nm, pm and atomic units (Bohr).

Psychological descriptions, then, are simply descriptions of these brain systems in computational or information-processing terms; generally they appeal to representations, decision rules and algorithms that brain systems process.

The usefulness of these features covered by BioDNA for representing DNA/RNA sequence information have been sufficiently demonstrated by a number of published studies of the development of machine learning classification systems in computational genomics and genome sequence analysis.

FETI methods are powerful solvers for large-scale finite element systems in computational mechanics.

The large-scale nature of real-world systems results in computational difficulties in obtaining this exact solution, and so we provide an approximate formulation that is easier to solve and which becomes exact as the fleet size becomes large.

Although it is well-established that dopamine neurons compute signed TD errors (Bayer & Glimcher, 2005; Montague et al., 1996; Schultz et al., 1997; Tobler, Fiorillo, & Schultz, 2005), the role of the midbrain dopamine system in computing counterfactual computational signals is less clear.

A common technique for modeling complex systems in many computational engineering domains is the finite element method.

Avida is a software platform for performing experimental studies on evolving systems in a computational setting.

Both qualitative and quantitative model learning frameworks for biochemical systems have been studied in computational systems biology.

Mathematical models for revealing the dynamics and interactions properties of biological systems play an important role in computational systems biology.

Further, the implementation of ANFIS technique to match soft computing results with the analytic results makes our study to deal with complex dynamic behavior of the machining system in efficient computational manner by incorporating many realistic features.