Sentence examples for convergence input from inspiring English sources

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The controller is designed to satisfy minimum gain and phase margins, tracking specifications for robust performance, fast convergence, input disturbance rejection and sensor noise attenuation.

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Apart from transient part of the responses, the model predictions for both angular and translational accelerations show reasonably acceptable convergence with input accelerations of the system.

During motor control, the convergence of input from the premotor cortex and sensory structures makes the cerebellum an ideal cite for calculating in real time the error between intended and actual movement, and using this error to improve motor performance [49].

While reconstructions of individual axons have been studied in detail, such results cannot be used to reliably infer the convergence of input onto an individual projection neuron.

Nearly all AOB output neurons project to the MeA, however, the convergence of input in the MeA lead to a different pattern of sensory responses, such that the fraction of MeA neurons responding to any given stimulus is smaller, and the specificity of MeA responses elicited by sensory stimuli is greater than observed in the AOB.

This, in turn, implies a high convergence of inputs from LGN to a V1 neuron, that is, each individual V1 neuron receives input from many LGN neurons (Peters and Payne 1993).

The perception of our body orientation is achieved by the convergence of inputs from multiple sources, including vestibular, visual, and somatosensory information [1].

Alternatively, nonlinearities at the level of the IC could reflect convergence of inputs, for example, from binaural neurons in MSO, LSO, and DNLL (McAlpine et al., 1998).

(A ) Tuning to interaural time difference (ITD) emerges from the convergence of inputs selective for the same ITD but different frequencies (F1 F3) (Takahashi and Konishi, 1986 ; Mazer, 1998 ; Pena and Konishi, 2000 ; best ITD indicated by the dashed line).

Furthermore, the statistics of single-neuron spike trains in our model show great variations due to the random connectivity, which also imposes a variance in the convergence of inputs.

According to one proposal, neural response properties in area TE are viewed as built-up by a convergence of inputs from early, unimodal visual cortical areas (V4, TEO, posterior TE [TEp]) (Kobatake and Tanaka 1994).

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