Sentence examples for input in the context of from inspiring English sources

In the previous work on rank-2 NMF [32] that takes a term-document matrix as input in the context of text clustering, sparse dense matrix multiplication (SpMM) was the main computational bottleneck for computing the solution.

We explore the limits of this methodology, as related to network complexity (size and number of node inputs) in the context of synchronously updated random Boolean networks.

The second component is the information that the observer expects in the input to categorize the stimulus, in the context of the other categories to discriminate in the task (e.g. the wide-opened eyes in "fear" vs. the wide-opened eyes and the open mouth in "surprise").

We show in Section 4.3 that the cut heuristic in combination with the ZOOPS model successfully allows discovery of multiple copies of the same motif within a single input sequence, in the context of motif discovery using sEM.

Studying different input modalities in the context of response inhibition might be of interest for investigating populations with disorders such as auditory processing disorder (APD) and attention-deficit/hyperactivity disorder (ADHD).

For intermediate values of f, the amplification of the voltage response reflects the interaction of the oscillatory inputs with an intrinsic vector field (for the autonomous system) that is correlated with the amplification of the voltage responses to instantaneous inputs discussed in the context of Fig. 4c for negative as compared to positive values of both α and ϵ (Figs. 4a and 4b).

Relevant examples include physiological rhythms induced by regular or periodic inputs occurring in the context of medical devices [1], synchronization of electronic genetic networks by an external voltage [2], and diverse regular or irregular rhythms induced by periodic stimuli of a squid giant axon [3].

Other examples include physiological rhythms stimulated by regular or periodic inputs occurring in the context of medical devices, synchronization of electronic genetic networks by an external forcing, i.e., external voltage [ 43], and a wide variety of regular and irregular rhythms induced by periodic stimulation of squid giant axons [ 21].

The neurons in each class are thus determined as follows: For every neuron reacting to a motion primitive, if its mean distance to input vectors given in the context of one goal is lower than the mean minus one standard deviation of the distance to input vectors from the second context, then the neuron is said to be specifically encoding the first goal.

This work focuses on the model predictive control design methodology that successfully accounts for the state and input constraints applied in the context of highly dissipative Kuramoto Sivashinsky (KS) partial differential equation (PDE) describing stability of a thin film thickness in the two-phase annular flow in vertical pipes.

Thus, NAR increases input dynamic range in the context of the natural ara system.