Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Triad State Space Construction for Chaotic Signal Classification with
  Deep Learning   Inspired by the well-known permutation entropy (PE), an effective image
encoding scheme for chaotic time series, Triad State Space Construction (TSSC),
is proposed. The TSSC image can recognize higher-order temporal patterns and
identify new forbidden regions in time series motifs beyond the Bandt-Pompe
probabilities. The Convolutional Neural Network (ConvNet) is widely used in
image classification. The ConvNet classifier based on TSSC images
(TSSC-ConvNet) are highly accurate and very robust in the chaotic signal
classification.

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The categories of this paper are: cmp-lg
18
The categories of this paper are: econ
12
The categories of this paper are: nucl-th
27
The categories of this paper are: comp-gas
0
The categories of this paper are: hep-ph
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The categories of this paper are: mtrl-th
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The categories of this paper are: eess
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The categories of this paper are: solv-int
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The categories of this paper are: astro-ph
7
The categories of this paper are: hep-th
15
The categories of this paper are: nucl-ex
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The categories of this paper are: plasm-ph
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The categories of this paper are: alg-geom
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The categories of this paper are: q-bio
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The categories of this paper are: funct-an
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The categories of this paper are: chem-ph