Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Data-Driven Participation Factors for Nonlinear Systems Based on Koopman
  Mode Decomposition   This paper develops a novel data-driven technique to compute the
participation factors for nonlinear systems based on the Koopman mode
decomposition. Provided that certain conditions are satisfied, it is shown that
the proposed technique generalizes the original definition of the linear
mode-in-state participation factors. Two numerical examples are provided to
demonstrate the performance of our approach: one relying on a canonical
nonlinear dynamical system, and the other based on the two-area four-machine
power system. The Koopman mode decomposition is capable of coping with a large
class of nonlinearity, thereby making our technique able to deal with
oscillations arising in practice due to nonlinearities while being fast to
compute and compatible with real-time applications.

27
The categories of this paper are: comp-gas
30
The categories of this paper are: q-alg
9
The categories of this paper are: nlin
7
The categories of this paper are: hep-th
22
The categories of this paper are: chao-dyn
13
The categories of this paper are: quant-ph
6
The categories of this paper are: astro-ph
2
The categories of this paper are: math
25
The categories of this paper are: patt-sol
14
The categories of this paper are: math-ph
11
The categories of this paper are: hep-lat
28
The categories of this paper are: alg-geom
36
The categories of this paper are: cmp-lg
26
The categories of this paper are: bayes-an
8
The categories of this paper are: hep-ex
12
The categories of this paper are: nucl-th