We present a method for solving nonlinear eigenvalue problems (NEPs) using rational approximation. The method uses the Antoulas\textendash Anderson algorithm (AAA) of Nakatsukasa, Sète and Trefethen ...
Abstract: In this paper, we discuss a generalization of the extended Luenberger observer. Our approach can be interpreted as an approximate error linearization. The ...
Abstract: This paper presents a new algorithm for piecewise affine (PWA) approximation of nonlinear systems. Such an approximation is very important to enable a reduction in the complexity of models ...
ABSTRACT: In this paper, we propose a method for finding the best piecewise linearization of nonlinear functions. For this aim, we try to obtain the best approximation of a nonlinear function as a ...
This paper considers the optimal control problem for the bilinear system based on state feedback. Based on the concept of relative order of the output with respect to the input, first we change a ...
Probabilistic Neural Operators — FNO/DeepONet extended with uncertainty quantification via linearized Laplace approximation. Neural operators learn mappings between infinite-dimensional function ...
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