Abstract: We study the conditions for the unique response in a class of nonlinear control systems subject to random inputs using statistical linearization approximation. As in the case of sinusoidal ...
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 ...
Probabilistic Neural Operators — FNO/DeepONet extended with uncertainty quantification via linearized Laplace approximation. Neural operators learn mappings between infinite-dimensional function ...
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 ...
One question for my optimization friends: For me a "linearization" is a linear approximation (with some error) and a "linear reformulation" would be an equivalent (!) linear formulation of a nonlinear ...
The problem with efficiently linearizing large language models (LLMs) is multifaceted. The quadratic attention mechanism in traditional Transformer-based LLMs, while powerful, is computationally ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results