Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: System Identification for Hybrid Systems using Neural Networks   With new advances in machine learning and in particular powerful learning
libraries, we illustrate some of the new possibilities they enable in terms of
nonlinear system identification. For a large class of hybrid systems, we
explain how these tools allow for identification of complex dynamics using
neural networks. We illustrate the method by examining the performance on a
quad-rotor example.

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The categories of this paper are: hep-ph
13
The categories of this paper are: quant-ph
34
The categories of this paper are: chem-ph
25
The categories of this paper are: patt-sol
11
The categories of this paper are: hep-lat
37
The categories of this paper are: supr-con
24
The categories of this paper are: dg-ga
30
The categories of this paper are: q-alg
19
The categories of this paper are: eess
16
The categories of this paper are: stat
33
The categories of this paper are: plasm-ph
4
The categories of this paper are: cond-mat
32
The categories of this paper are: atom-ph
35
The categories of this paper are: mtrl-th
20
The categories of this paper are: acc-phys
15
The categories of this paper are: nucl-ex