Wave nature of fractal lacunarity: a higher resolution scale to capture subtle changes in ECG signals

Esgiar, A.N.; Chakravorty, Pragnan

doi:10.1109/cic.2005.1588281

Cited by 2 publications

(1 citation statement)

References 3 publications

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“…The changes in lacunarity under different scales are described in Figure A. The lacunarity undulates and decreases with the increase of scales, which confirms the result in Esgiar and Chakravorty . In Figure B, the slopes of the lines represent the LCRs derived via least squares fitting.…”

Section: Experiments and Analysissupporting

confidence: 74%

Communication emitter individual identification via 3D‐Hilbert energy spectrum‐based multiscale segmentation features

Han¹,

Zhang²,

Qiu³

et al. 2018

Int J Communication

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Specific emitter identification can detect emitters automatically by extracting and analyzing features. A novel specific emitter identification method based on 3D-Hilbert energy spectrum-based multiscale segmentation (3D-HESMS) is proposed. First, the time-frequency energy spectrum is derived via the Hilbert-Huang transform, that is, a complicated curved surface in a 3D space, namely, the 3D-Hilbert energy spectrum. The differential box dimension, multifractal dimension, lacunarity change rate, and 3D-Hilbert energy entropy are extracted to compose the feature vector under multiscale segmentation using fractal theory. Subsequently, communication emitter individual identification is obtained using the 4 features. Finally, the performance and complexity of the 3D-HESMS method are compared with those of 2 existing methods. Experiments show that the performance of the 3D-HESMS method is better than those of the 2 other methods. The extracted features with high stability, sufficiency, and identifiability can overcome the negative effects of the changes in signal-to-noise ratio and the number of training samples.

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Section: Experiments and Analysissupporting

confidence: 74%