Abstract Electroencephalography (EEG) allows recording of cortical activity at high temporal resolution. Creating features useful for the analysis EEG can be challenging. Here we introduce a new method pre-processing time-series resting state and binary task classification using recurrence quantification (RQA) compare it with existing state-of-the-art approach based on signal embedding. To reve...

Laser AE method is a non-contact AE detection technique, which utilizes laser interferometer as sensor. This method is less subjected to environmental difficulties and can be adaptive for wider target than conventional PZT sensors. However, laser AE method has to improve its sensitivity because the noise level of laser interferometer is higher than PZT sensors. In this study, a method to reduce...

Two standard tools for signal analysis are the short{time Fourier transform and the continuous wavelet transform. These tools arise as matrix coeecients of square integrable representations of the Heisenberg and aane groups respectively, and discrete frame decompositions of L 2 arise from approximations of corresponding reproducing formulae. Here we study two groups, the so-called aane Weyl-Hei...

Time-varying spectra of non-stationary time-series commonly used are spectrograms from the Short-Time Fourier Transform (STFT). The most prominent limitation of the Fourier Transform is that of frequency resolution. To overcome the limitation the Wavelet Transform, Wigner-Ville Distribution and the Min-Norm subspace method have been applied for spectrum estimation of non-stationary signals caus...