Sentence examples for representations to track from inspiring English sources
Using representations to track the flow energy; Defining fundamental concepts; Handling anomalous results; Incorporating scientists' ideas.
During the development of LSET, the difference between processes and interactions manifested itself in the following ways: Using representations to track the flow energy; Defining fundamental concepts; Handling anomalous results; Incorporating scientists' ideas.
These results confirm the substantial difference that exists between great apes and dogs with regard to mental representation abilities required to track the invisible displacements of objects.
Since the scale s can be related to frequency, the CWT can be used to obtain simultaneous time frequency representations of dynamic responses to track frequency shifts in the system natural frequencies (e.g. Aguirre et al. 2013).
In this representation, it is easier to track the different phases of the viral life cycle (entry, endocytosis, transcription/translation, assembly, and budding).
To share representations of the target and to track the target robustly, we have proposed a Hierarchical Invariants Perception Model (HIPM) (Figure 1).
As in many previous studies (cf. Norman et al., 2006; Cichy et al., 2014), the extra sensitivity achieved by combining multiple features supported the use of multivariate analysis to track neural representations.
We have moved the univariate classification analysis to the supplement, leaving just the following in the main text: "As in many previous studies (cf. Cichy et al., 2014; Norman et al., 2006), the extra sensitivity achieved by combining multiple features supported the use of multivariate analysis to track neural representations".
To fulfill this demanding agenda, we used time-resolved MEG and EEG recordings to track the internal representation of a flashed stimulus under visible and invisible conditions.
To track the cortical representation of the target location through time, we trained multivariate pattern classifiers separately at every time sample to predict the target location from the recorded brain signals (see 'Materials and methods').
