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Inspired by the well-known permutation entropy (PE), an effective imageencoding scheme for chaotic time series, Triad State Space Construction (TSSC),is proposed. The TSSC image can recognize higher-order temporal patterns andidentify new forbidden regions in time series motifs beyond the Bandt-Pompeprobabilities. The Convolutional Neural Network (ConvNet) is widely used inimage classification. The ConvNet classifier based on TSSC images(TSSC-ConvNet) are highly accurate and very robust in the chaotic signalclassification.

Triad State Space Construction for Chaotic Signal Classification with Deep Learning