Sentence examples for approximation of the input from inspiring English sources

The architecture is designed to generate an output per clock cycle, and the detailed component and the approximation of the input signal are available alternately.

- The first key difference from PCA is that PLS computes an orthogonal factorization of the input vector X and response y (note: y can also be a vector) in the process of computing the projection matrix W. - The second key difference from PCA is that the least squares model for K-PLS is based on approximation of the input and response data, not the original data.

We have recently shown that multivariate metamodelling based on PLSR and our nonlinear extension HC-PLSR 8 provides good approximations of the input-output mappings 8 as well as informative insight into complex interaction patterns between parameters 9 of advanced nonlinear dynamic models.

Weyl defined real functions as mappings correlating each interval in the choice sequence determining the argument with an interval in the choice sequence determining the value "interval by interval" as it were, the idea being that approximations to the input of the function should lead effectively to corresponding approximations to the input.

The approximation of the original input signal is obtained by applying a low-pass filter to the output of interpolators in order to suppress the high-frequency components of the interpolated signal.

The analysis demonstrated the existence of piecewise-constant approximations to the input-vector probability density function, which is optimal for the proposed geometric piecewise-uniform vector quantizer.

This paper proposes and studies an algorithm for task-level control based on a radial basis function network approximation of the optimal task input vector on parameters of the task.

Perceptual inference is, from the predictive coding perspective, understood as an iterative process of prediction error minimization; therefore the internal models of the sensory input (and thus predictions generated by it) are only more (leading to smaller prediction error) or less (leading to larger prediction error) accurate approximations of the sensory input.

This input profile is a simple approximation of the orientation-tuned inputs which are known to feed neurons in primary visual cortex.

The derivative of a function at a chosen input value describes the best linear approximation of the function near that input value.

A simultaneous sparse coding algorithm makes approximation of several input signals at the same time using different linear combinations of the same elementary signals [28].