Sentence examples for a tuning model from inspiring English sources

In this article, we propose a tuning model for adaptive computations.

In this article, we have presented a tuning model for the performance improvement of applications in JEE servers.

The primary contributions of this article are: A tuning model for controlling the resource allocation between business functions and adaptive computations by upgrading and degrading the autonomic levels of adaptive computations dynamically.

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.

In this paper, we adopt a general tuning model which takes recent ensemble activity into account.

Another way to build a better tuning model is to explain the unknown factors using multidimensional hidden states [ 27, 28].

The help comes in the shape of an adaptation tuning model designed to improve the performance of adaptive applications, implemented for JEE servers, by upgrading or downgrading autonomic levels, according to available resources.

An example of a linear neural tuning model is shown in Figure 2C, and an example of a quadratic neural tuning model is shown in Figure 2D. Figure 2D depicts example autoregressive (AR 1 vs AR n) movement models (Figure 2D).

Figure 2 shows a comparison of the standard Kalman filter (Figure 2A) and the n-th order unscented Kalman filter (Figure 2B), as well as examples of a linear neural tuning model (Figure 2C), quadratic neural tuning model (Figure 2D), and autoregressive (AR 1 vs AR n) movement models (Figure 2D).

Since the importance weights are updated by the discrepancy between the neural firings and the tuning model, a well-defined tuning model is necessary to an accurate estimation of posterior density.

In such cases, our tuning model allows an AC to specify a pinnedLevel S i (i∈[0,3]).