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 ...

Abstract: In the input-output feedback linearization design, the time derivatives of the output function have to be taken successively for the presence of the control signal. Uncertainties in the ...

This paper offers a qualitative theoretical analysis of the error that may arise when a linear programming calculation is used to solve a problem involving some ...

Accurately modeling nonlinear dynamical systems using observable data remains a significant challenge across various fields such as fluid dynamics, climate science, and mechanical engineering.

Carleman linearization is a powerful technique for converting nonlinear dynamical systems into equivalent linear systems of higher dimension. This package provides tools to: Construct Carleman ...

The problem with efficiently linearizing large language models (LLMs) is multifaceted. The quadratic attention mechanism in traditional Transformer-based LLMs, while powerful, is computationally ...

Considering the characteristics of spatial straightness error, this paper puts forward a kind of evaluation method of spatial straightness error using Geometric ...