Extreme-mass-ratio inspirals (EMRIs) of compact objects with mass m ∼ 1 − 10 M into massive black holes with mass M ∼ 10 M can serve as excellent probes of strongfield general relativity. The Laser Interferometer Space Antenna (LISA) is expected to detect gravitational wave signals from ∼ 100 EMRIs per year, but the data analysis of EMRI signals poses a unique set of challenges due to their lon...

In this survey paper we introduce the reader to the notion of the fractional Fourier transform, which may be considered as a fractional power of the classical Fourier transform. It has been intensely studied during the last decade, an attention it may have partially gained because of the vivid interest in timefrequency analysis methods of signal processing, like wavelets. Like the complex expon...

This paper describes some new approaches for the feature extraction of SSVEP signal in EEG signal processing. One of them is Canonical Correlation Analysis (CCA) and another one is CWT along with ANN. Basically CCA is applied to analyze the frequency components of SSVEP in EEG. The essence of this method is to extract narrowband frequency components of SSVEP in EEG. The CWT offers a valuable to...

We extend the Wigner distribution (WD) to conjugate unitary operators A, and Bp. The resulting “ABWD” is defined both as an a-b representation and as a timefrequency representation. Important properties and relations of the WD are generalized to the AB-WD.

In the present paper, we propose a software package developed by the authors and based on the continuous wavelet transform that allows to perform the direct and inverse continuous wavelet transform, 2C and 3C polarization analysis and filtering, modeling the dispersed and attenuated wave propagation in the timefrequency domain and optimization in signal and wavelet domains with the aim to extra...

A significant problem with unit selection based speech synthesis is the listener perception of sound discontinuities at which the speech waveforms are joined. This work demonstrates the application of three different perceptually motivated timefrequency representations and associated measures to the identification of such discontinuities.

Deep Neural Networks (DNN) have become a popular approach for speech enhancement, and singing voice separation. DNNs are typically trained to estimate a timefrequency mask using ground truth examples. In this submission, we combine DNN estimation as a first step with traditional refinement via F0 estimation, using the YINFFT algorithm.

1 Facultatea de Electronică şi Telecomunicaţii, Departamentul Comunicaţii Bd. V. Pârvan Nr. 2, 300223 Timişoara, e-mail [email protected] Abstract – This paper presents a generalization of the concept of adapted filter to a frequency modulated signal. This generalization is inspired by the timefrequency representations theory. A new time-frequency filter is proposed, the tracking filter. I...

This work presents the application of three different timefrequency methods to pressure and structure-borne sound signals to improve combustion diagnosis of internal combustion engines. Increasing engine efficiency and reduction of pollutants imply enhanced knowledge of the combustion process. The methods presented deepen the understanding of the measured signal and stimulate improved algorithm...

INTRODUCTION Surface electromyography (sEMG) is a typical part of instrumented gait assessment for the child with cerebral palsy (CP). Numerous methods exist to characterize the sEMG in order to gain insight into the neuromuscular impairments that exist in CP, including the use of muscle onset and offset and amplitude. However, these methods have focused upon one aspect of the sEMG to character...