Sentence examples for training generated by from inspiring English sources

Although some training generated by EIP projects has occurred during the course of the CDC-based Epidemic Intelligence Service prograndand other CDC-based staff have gotten experience with data analysis, most training has occurred at the EIP sites as a result of the partnership in each site with an academic center.

The spike train generated by the presynaptic neurons will change the membrane potential calculated as the sum of individual PSPs generated by incoming spikes.

Their performances were assessed using multiple neuronal spike trains generated by a biophysical neuron model and by a directional tuning model of the primary motor cortex.

We illustrate our approach by considering spike trains generated by simulated as well as experimental data obtained from single-unit recordings of first-order sensory neurons in the vestibular system.

The vocal tract can be modeled as a slowly time-varying, low-order all-pole filter, while the glottal excitation can be represented either by a white noise sequence (for unvoiced sounds), or by an impulse train generated by periodic vibrations of the vocal chords (for voiced sounds).

A similar reduction of variability also occurs in completely irregular spike trains generated by Poisson processes [32], but only when there are many more active convergent inputs.

Specifically, we used this model to compare the Gsyn evoked by recorded SS trains with that of simulated spike trains generated by inhomogeneous Poisson processes of the same modulated firing rates.

Thus, in order to find the best working conditions, i.e., the set of parameters which maximize the AUC, we tested such methods on the synthetic spike trains generated by a particular realization of the EI model.

Here, this method is implemented as described by Wirth et al. (2003) to filter the simulated spike trains generated by the model in order to estimate the firing rate underlying the spiking activity.

The expansion seed train generated by the tool for this configuration, using the rules defined in the Bioprocess Economics Model section, was: three T-500 units for stage 1, six cT units for stage 2, and four cL-36 units for stage 3.

GlimerHMM [ 37], SNAP [ 38], and Augustus [ 25] were trained with the training set generated by PASA; Geneid [ 26] used the parameter of Cucumis spp.; and GeneMark.hmm-ES [ 39] only used unmasked genomic data and was self-trained.