Sentence examples for model discussed before from inspiring English sources

Assuming that the physical model discussed before is the underlying dispersion mechanism, we may obtain a measurement model for a sensor at a position r j and at time t k as y(r j,t k ) = c(r j,t k ) + e(r j,t k ) + b, where c(r j,t k ) is the concentration of interest, b is a bias term, and e ( r j, t k ) ∼ N ( 0, σ 2 ) is the sensor noise assumed to be independent in both time and space.

Electro-thermal models are equally important as compared to the other physics-based models discussed before because temperature is an important factor governing the set and reset processes.

What follows below is a discussion of several issues that have initially been identified in relation to the two transitivity models discussed, before continuing to suggest potential means by which to deal with such issues and, furthermore, assist the discourse analyst in carrying out a more detailed and systematic analysis of written or spoken texts.

As discussed before, modeling symbol insertions in pair-HMMs can lead to subtle issues with potentially negative effects, and considering that our ultimate goal lies in finding an accurate sequence alignment through effective estimation of the symbol alignment probabilities, a method that can directly estimate these probabilities without explicitly modeling insertions/deletions would be desirable.

Secondly, as discussed before, our model predicts an inverted U-shaped utility function.

However, as discussed before, these models may be inadequate to evaluate the therapeutic potential of cardiac glycosides.

As discussed before, the content-based model is based on generating documents from aggregating content as bulk with regards to the tweet timestamps.

As discussed before, the encoding (quantization) process is modeled through the auxiliary variable with and statistically independent of (see, e.g., [3, 14] for further details).

The connection between the phase field model B (Cahn-Hilliard equation) and the diffusion-controlled LSW theory was discussed before by Bray (1994).

As discussed before, the receptive field of a neuron in our model is a multi-columnar feature.

"That's never been discussed before adequately".