An improved method for nonstationary signals components extraction based on the ICI rule

This paper presents an automatic adaptive method to localize and extract signal components from a noisy multicomponent signal TFD. (Additional details can be found in the comprehensive book on Time-Frequency Signal Analysis and Processing (see http://www.elsevier.com/locate/isbn/0080443354). In addition, the most recent upgrade of the original software package that calculates Time-Frequency Distributions and Instantaneous Frequency estimators can be downloaded from the web site: www.time-frequency.net. This was the first software developed in the field, and it was first released publicly in 1987 at the 1st ISSPA conference held in Brisbane, Australia, and then continuously updated).This paper proposes an improved adaptive algorithm for components localization and extraction from a noisy multicomponent signal time-frequency distribution (TFD). The algorithm, based on the intersection of confidence intervals (ICI) rule, does not require any a priori knowledge of signal components and their mixture. Its efficiency is significantly enhanced by using high resolution and reduced cross-terms TFDs. The obtained results are compared for different signal-to-noise ratios (SNRs) and various time and lag window types used in the modified B-distribution (MBD) calculation, proving the method to be a valuable tool in noisy multicomponent signals components extraction in the time-frequency (TF) domain

Gender gap in parental leave intentions: Evidence from 37 countries

This is the final version. Available from Wiley via the DOI in this record. Despite global commitments and efforts, a gender-based division of paid and unpaid work persists. To identify how psychological factors, national policies, and the broader sociocultural context contribute to this inequality, we assessed parental-leave intentions in young adults (18–30years old) planning to have children (N = 13,942; 8,880 identified as women; 5,062 identified as men) across 37 countries that varied in parental-leave policies and societal gender equality. In all countries, women intended to take longer leave than men. National parental-leave policies and women’s political representation partially explained cross-national variations in the gender gap. Gender gaps in leave intentions were paradoxically larger in countries with more gender-egalitarian parental-leave policies (i.e., longer leave available to both fathers and mothers). Interestingly, this cross-national variation in the gender gap was driven by cross-national variations in women’s (rather than men’s) leave intentions. Financially generous leave and gender-egalitarian policies (linked to men’s higher uptake in prior research) were not associated with leave intentions in men. Rather, men’s leave intentions were related to their individual gender attitudes. Leave intentions were inversely related to career ambitions. The potential for existing policies to foster gender equality in paid and unpaid work is discussed.SSHRC Insight Development GrantSSHRC Insight GrantEconomic and Social Research CouncilState Research AgencyGuangdong 13th-five Philosophy and Social Science Planning ProjectNational Natural Science Foundation of ChinaSwiss National Science FoundationSwiss National Science FoundationCenter for Social Conflict and Cohesion StudiesCenter for Intercultural and Indigenous ResearchSSHRC Postdoctoral FellowshipSlovak Research and Development AgencySwiss National Science FoundationCanada Research ChairsSocial Sciences and Humanities Research Council of CanadaOntario Ministry of Research and InnovationHSE University, RFFaculty of Arts, Masaryk Universit

A resolution performance measure for quadratic time-frequency distributions

This paper presents two novel results which are significant for the application of time-frequency signal analysis techniques to real life signals. First, we introduce a measure for comparing the resolution performance of TFDs in separating closely spaced components in the time-frequency domain. The measure takes into account key attributes of TFDs such as main-lobes, side-lobes, and cross-terms. The introduction of this measure is an improvement of current techniques which rely on visual inspection of plots

Adaptive Thresholding for Sparse Image Reconstruction

The performance of the class of sparse reconstruction algorithms which is based on the iterative thresholding is highly dependent on a selection of the appropriate threshold value, controlling a trade-off between the algorithm execution time and the solution accuracy. This is why most of the state-of-the-art reconstruction algorithms employ some method of decreasing the threshold value as the solution converges toward the optimal one. To address this problem we propose a data-driven adaptive threshold selection method based on the fast intersection of confidence intervals (FICI) method, with which we have augmented the two-step iterative shrinkage thresholding (TwIST) algorithm. The performance of the proposed algorithm, denoted as the FICI-TwIST algorithm, has been evaluated on a problem of image reconstruction with the missing pixels, exploiting image sparsity in the discrete cosine transformation domain. The obtained results have shown competitive performance in comparison with a number of state-of-the-art sparse reconstruction algorithms, even outperforming them in some scenarios

A cross-terms geometry based method for components instantaneous frequency estimation using the Cross Wigner-Ville distribution

A novel method for the signal components instantaneous frequency (IF) estimation based on the CrossWigner-Ville distribution (XWVD) is presented. The cross-terms in the XWVD are deliberately formed between the analyzed signal and a reference signal. The proposed method yields a scaled and time shifted image that closely resembles the instantaneous frequency laws of the components present in the signal. As the interferences location follow geometrical rules, and by using a reference signal well localized in time and frequency, the time-frequency coordinates of the analyzed signal components IF can be calculated by an automatic procedure described below. The performance of the method is tested on both synthetic and real-life signals, showing improvements over another recently proposed components extraction method.Scopu

Heart Sound Analysis Using MFCC and Time Frequency Distribution

This paper presents heart sound analysis method based on Time-Frequency Distribution (TFD) analysis and Mel Frequency Cepstrum Coefficient (MFCC). TFD represents the heart sound in term of time and frequency simultaneously which while the MFCC defines a signal in term of frequency coefficient corresponding to the Mel filter scale. There are 100 normal data and 100 data with disease obtained from the hospital which consists of various kinds of problems including mitral regurgitation and stenosis, tricuspid regurgitation and stenosis, ventricular septal defect and other structural related disease. B-Distribution is chosen from a number of time-frequency analysis methods due its capability to represent the signal in the most efficient way in term of noise and cross term reduction. The advantage of MFCC is that it is good in error reduction and able to produce a robust feature when the signal is affected by noise. SVD/PCA technique is used to extract the important features out of the B-Distribution representation. The coefficient obtained from SVD-PCA and MFCC is later used for classification Artificial Neural Network. The results show that the system is able to produce the accuracy up to 90.0% using the TFD and 80.0% using the MFCC

A comparison of quadratic TFDs for entropy based detection of components time supports in multicomponent nonstationary signal mixtures

This paper presents a method for extraction of different signal components from multicomponent mixtures by exploiting the information of the local components Renyi entropy. (Additional details can be found in the comprehensive book on Time-Frequency Signal Analysis and Processing (see http://www.elsevier.com/locate/isbn/0080443354). In addition, the most recent upgrade of the original software package that calculates Time-Frequency Distributions and Instantaneous Frequency estimators can be downloaded from the web site: www.time-frequency.net. This was the first software developed in the field, and it was first released publicly in 1987 at the 1st ISSPA conference held in Brisbane, Australia, and then continuously updated).Separation of different signal components, produced by one or more sources, is a problem encountered in many signal processing applications. This paper proposes a fully automatic undetermined blind source separation method, based on a peak detection and extraction technique from a signal time-frequency distribution (TFD). Information on the local number of components is obtained from the TFD Short-term Rényi entropy. It also allows to detect components time supports in the time-frequency plane, with no need for predefined thresholds on the components amplitude. This approach allows to extract different signal components without prior knowledge about the signal. The method is also used as a quality criterion to compare Quadratic TFDs. Results for synthetic and real data are reported for different TFDs, including the recently introduced Extended Modified B distribution

Renyi entropy of quadratic time-frequency distributions: effects of signal’s parameters

The Renyi Entropy (ER) of a time-frequency distribution (TFD) has been used for estimating the signal information content and the TFD complexity in the time-frequency (TF) plane. In this paper we provide an experimental comparison of the performance of ER obtained from Wigner-Ville distribution (WVD), Spectrogram (SP), Choi-William Distribution (CWD), Born-Jordan Distribution (BJD) and Modified B Distribution (MBD). The performances are tested on two component Gabor logon and LFM signals with the goal of illustrating the effects on ER obtained from different TFDs when signalpsilas TF parameters varies. The presented analysis shows that high-resolution TFDs, such as the MBD, result into consistent ER measures

Signal content estimation based on the short-term time-frequency Rényi entropy of the S-method time-frequency distribution

A key characteristic of a nonstationary signal, when analyzed in the time-frequency domain, is the signal complexity, quantified as the number of components in the signal. This paper describes a method for the estimation of this number of components of a signal using the short-term Rényi entropy of its time-frequency distribution (TFD). We focus on the characteristics of TFDs that make them suitable for such a task. The performance of the proposed algorithm is studied with respect to the parameters of the S-method TFD, which combines the virtues of both the spectrogram and the Wigner-Ville distribution. Once the optimal parameters of the TFD have been determined, the applicability of the method in the analysis of signals in low SNRs and real life signals is assessedScopu