D.Ichim, P.Ciarlini, F.Pavese, A. Premoli, M.L. Rastello, Comparison of LS techniques for the linear approximation of data affected by heteroschedastic errors in both variables with uncertainty estimation, This
In the same way as a linear model provides the approximation of system behavior at a given operating condition, an LPV model provides the approximation of the behavior over a span on operating conditions. A common approach for constructing the LPV model is by batch trimming and linearization, fo...
Tustin with Prewarping Bilinear (Tustin) approximation with frequency prewarping. Also specify the prewarp frequency in Prewarp frequency (rad/s). For more information, see Tustin Approximation. This method usually performs better in the frequency domain. Use this method to ensure matching at freque...
Whole-brain models have proven to be useful to understand the emergence of collective activity among neural populations or brain regions. These models combine connectivity matrices, or connectomes, with local node dynamics, noise, and, eventually, transm
Finally, a linear autoregressive model can automatically capture a linear approximation of the HRF dynamics48, precisely as present in the observed time series. Ultimately, our results encourage a side-by-side comparison of models with and without the inclusion of an HRF component to assess the ...
Note also that λk provides an approximation for the solution of the dual problem (see for example, Problems 9.1 and 9.2). • Step 2: Stop if the primal and dual values of the objective functions are approximately equal. Else set k=k+1 and repeat from step 1. Note that in step 2...
A standard state-space model treatment results in an approximation to the results of the diffuse Kalman filter. However, estimate uses all of the data to fit the model, and filter and smooth return filtered and smoothed estimates for all periods, respectively. Explicitly create a one-dimensional...
Normal Approximation to Linear Combinations of Independently Distributed Random Variablesdoi:10.1080/05695558008974501A general method for determining the minimum number of independently distributed random variables needed in a linear combination to allow the distribution of the linear combination to be ...
L. Approximation of functions of several variables by linear methods in the space Sp, Acta Sci. Math. 80 (2014), no. 3-4, 477-489.Savchuk V.V.; Shidlich, A.L. Approximation of functions of several variables by linear methods in the space Sp. Acta Sci. Math. 80, No. 3-4, ...
The intuition why a normal distribution should be a good approximation is that in this case the linear hull is the sum of a huge amount of pairwise(!) independent random variables. However, it turns out to be wrong. In particular, for any n, the correlation of the cipher actually takes...