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Complex network based Fourier analysis for signal processing
Vijayan Vijesh, K. Satheesh Kumar, Mohanachandran Nair Sindhu Swapna, Sankaranarayana Iyer Sankararaman, 2024, published scientific conference contribution

Keywords: fourier analysis, complex network, signal processing
Published in RUNG: 15.04.2024; Views: 636; Downloads: 0
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Audio tampering identification : phase portrait analysis as a promising tool for audio forensics
S. S. Aswathy, Mohanachandran Nair Sindhu Swapna, Sankaranarayana Iyer Sankararaman, 2023, published scientific conference contribution abstract

Keywords: audio forensics, tampering, signal processing
Published in RUNG: 09.01.2024; Views: 727; Downloads: 2
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Unwrapping the phase portrait features of adventitious crackle for auscultation and classification: A machine learning approach
Mohanachandran Nair Sindhu Swapna, 2021, original scientific article

Abstract: The paper delves into the plausibility of applying fractal, spectral, and nonlinear time series analyses for lung auscultation. The thirty-five sound signals of bronchial (BB) and pulmonary crackle (PC) analysed by fast Fourier transform and wavelet not only give the details of number, nature, and time of occurrence of the frequency components but also throw light onto the embedded air flow during breathing. Fractal dimension, phase portrait, and sample entropy help in divulging the greater randomness, antipersistent nature, and complexity of airflow dynamics in BB than PC. The potential of principal component analysis through the spectral feature extraction categorises BB, fine crackles, and coarse crackles. The phase portrait feature-based supervised classification proves to be better compared to the unsupervised machine learning technique. The present work elucidates phase portrait features as a better choice of classification, as it takes into consideration the temporal correlation between the data points of the time series signal, and thereby suggesting a novel surrogate method for the diagnosis in pulmonology. The study suggests the possible application of the techniques in the auscultation of coronavirus disease 2019 seriously affecting the respiratory system.
Keywords: Auscultation, Biomedical signal processing, Fractals, Machine learning, Phase portrait, Pulmonary crackle.
Published in RUNG: 30.06.2022; Views: 1258; Downloads: 0
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First upper limits on the radar cross section of cosmic-ray induced extensive air showers
R.U. Abbasi, Jon Paul Lundquist, 2017, original scientific article

Abstract: TARA (Telescope Array Radar) is a cosmic ray radar detection experiment colocated with Telescope Array, the conventional surface scintillation detector (SD) and fluorescence telescope detector (FD) near Delta, Utah, U.S.A. The TARA detector combines a 40 kW, 54.1 MHz VHF transmitter and high-gain transmitting antenna which broadcasts the radar carrier over the SD array and within the FD field of view, towards a 250 MS/s DAQ receiver. TARA has been collecting data since 2013 with the primary goal of observing the radar signatures of extensive air showers (EAS). Simulations indicate that echoes are expected to be short in duration (∼ 10 µs) and exhibit rapidly changing frequency, with rates on the order 1 MHz/µs. The EAS radar cross-section (RCS) is currently unknown although it is the subject of over 70 years of speculation. A novel signal search technique is described in which the expected radar echo of a particular air shower is used as a matched filter template and compared to waveforms obtained by triggering the radar DAQ using the Telescope Array fluorescence detector. No evidence for the scattering of radio frequency radiation by EAS is obtained to date. We report the first quantitative RCS upper limits using EAS that triggered the Telescope Array Fluorescence Detector.
Keywords: Cosmic ray, Radar, Digital signal processing, Radar cross-section
Published in RUNG: 27.04.2020; Views: 2849; Downloads: 0
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