Sentence examples for by a forward model from inspiring English sources

The estimated data vector (varvec{G} varvec{theta })) was calculated by a forward model with fault parameter (varvec{theta }) under an elastic half-space medium.

Our model approximates inverse dynamics by means of predictions, i.e. by a forward model based on sensory and pre-motor signals.

The Born ratio data is then multiplied by a forward model of transmittance to create a normalized fluorescence data set that is inherently calibrated to the arbitrary source strength of the model [ 32].

One possibility is that a predictive signal generated by a forward model representing the likely future pattern of visual input is simply added to the incoming test pattern, thereby boosting compatible signals and reducing threshold.

Extraction of tissue optical properties from diffuse reflectance measurements is typically achieved by establishing a forward model to predict the diffuse reflectance given average optical properties of the bulk tissue and then fitting the predicted reflectance to the measured data or comparing the measured data to a pre-calculated database.

However, it has recently been hypothesized that the brain constantly calibrates its time estimation by comparing the predictions of a forward model about future positions of the moving object with the visual feedback [4], [8], [21].

The crucial point here is that active inference works by providing proprioceptive predictions (from a forward model) to reflex arcs (the inverse mapping), which automatically generate motor commands.

This is done by solving the problem described by a new forward model (4) begin{aligned} underset{x_e}{{text {argmin}}} ; left{ left| C tilde{P} (tilde{x_0} + x_e) - d right| _2^2 + phi (x_e) right} end{aligned} (4 where (x_e) is a correction term added to the initial reconstruction.

In DCM, the hidden neuronal dynamics described by equation (3) is linked to predicted BOLD responses by a hemodynamic forward model (Friston et al. 2003).

In general, the relationship between the measurement vector y (measured spectrum) and the state vector x to be retrieved can be expressed by a nonlinear forward model F describing the radiative transfer in the atmosphere: {mathbf{y}} = {mathbf{F}}({mathbf{x}},{mathbf{b}}) + {varvec{upvarepsilon}}, (3)where b is the additional not-retrieved state vector and ε the measurement error vector.

Generally speaking – when modelling biological time series – data features that cannot be produced by a plausible forward model are probably measurement noise or the product of hidden processes not included explicitly in the model.