Time-frequency Representation Method Research Articles

APPLICATION OF INTRINSIC TIME-SCALE DECOMPOSITION (ITD) TO EEG SIGNALS FOR AUTOMATED SEIZURE PREDICTION

Intrinsic time-scale decomposition (ITD) is a new nonlinear method of time-frequency representation which can decipher the minute changes in the nonlinear EEG signals. In this work, we have automatically classified normal, interictal and ictal EEG signals using the features derived from the ITD representation. The energy, fractal dimension and sample entropy features computed on ITD representation coupled with decision tree classifier has yielded an average classification accuracy of 95.67%, sensitivity and specificity of 99% and 99.5%, respectively using 10-fold cross validation scheme. With application of the nonlinear ITD representation, along with conceptual advancement and improvement of the accuracy, the developed system is clinically ready for mass screening in resource constrained and emerging economy scenarios.

Chirplet Signal and Empirical Mode Decompositions of Ultrasonic Signals for Echo Detection and Estimation

In this study, the performance of chirplet signal decomposition (CSD) and empirical mode decomposition (EMD) coupled with Hilbert spectrum have been evaluated and compared for ultrasonic imaging applications. Numerical and experimental results indicate that both the EMD and CSD are able to decompose sparsely distributed chirplets from noise. In case of signals consisting of multiple interfering chirplets, the CSD algorithm, based on successive search for estimating optimal chirplet parameters, outperforms the EMD algorithm which estimates a series of intrinsic mode functions (IMFs). In particular, we have utilized the EMD as a signal conditioning method for Hilbert time-frequency representation in order to estimate the arrival time and center frequency of chirplets in order to quantify the ultrasonic signals. Experimental results clearly exhibit that the combined EMD and CSD is an effective processing tools to analyze ultrasonic signals for target detection and pattern recognition.

Detecting unstable periodic orbits from oil-gas-water three-phase slug flows

We use the close return method combined with adaptive threshold selection to detect the unstable periodic orbits from the signals measured from experimental oil-gas-water three-phase slug flows, and find that the period of the emulsion type slug flow is longer than that of oil in water type slug flow. Especially, the orbit of oil in water type slug flow is basically composed of one big loop and one small loop, and the emulsion type slug flow orbit is composed of two big smooth loops. In addition, we employ the method of adaptive optimal kernel time-frequency representation to investigate the flow behaviors of two typical oil-gas-water three-phase slug flows and indicate that the energy of the oil in water slug flow exhibits a dispersed distribution and its frequency spectrum consists of various components distributes in a wide range. In contrast, the energy of emulsion type slug flow is distributed in a rather concentrated region and the high frequency component in its frequency spectrum is much less than that of the oil in water slug flow. These results are well consistent with the detected structure of unstable periodic orbit, further suggesting that the fluid mechanism underlying oil in water type slug flow is more complicated than that of the emulsion type slug flow.

Experimental investigation of pressure instabilities affected by cavitation for a double-suction centrifugal pump

Cavitation is a common fault which has a close relationship with pressure instabilities in centrifugal pumps. In order to investigate the hydroacoustic response to cavitation phenomena, a pressure fluctuation experimental is carried out on a double-suction centrifugal pump. Frequency spectrum analysis and time-frequency joint analysis of pressure fluctuations in semi-spiral suction chamber and volute casing are presented based on fast Fourier transform (FFT) and adaptive optimal-kernel time-frequency representation (AOK TFR) methods. The results show that in semi-spiral suction chamber, as the available NPSH value continuously decreases, the frequencies affected by cavitation transfer to a lower frequency range and become relative higher concentrate in time-frequency representation. In volute casing, blade passage frequency (BPF), specific frequency at 1/2 of blade passage frequency (147 Hz) and some frequency bands are well captured. The amplitudes of BPF and BPF/2 are shown to have a reasonable dependence on available NPSH value, though the measuring location relative to volute tongue should be taken into account. Strong pulsation characteristics are observed on relative low available NPSH value conditions. Pressure fluctuation at impeller rotating frequency is shown to be sensitive with cavitation process, of which the amplitude sharply increases at first and then decreases.

New method of time-frequency representation for ISAR imaging of ship targets

New method of time-frequency representation for ISAR imaging of ship targets

Event-related oscillations in the parietal cortex of adult alcohol-preferring (P) and alcohol-nonpreferring rats (NP)

The selectively bred alcohol-preferring (P) and -nonpreferring (NP) lines were developed from Wistar rats to model high and low voluntary alcohol consumption and have been demonstrated to exhibit many of the characteristics of human alcohol dependence. Electrophysiologic studies have shown P rats exhibit more electroencephalographic fast frequency activity and reduced P3 amplitude in the parietal cortex than NP rats, findings that are more common in alcohol-dependent individuals. Event-related oscillations (EROs) have been suggested to be good endophenotypes associated with ethanol dependence in clinical studies. Recently EROs have also been demonstrated to occur in rodents in response to stimuli that are similar to that used in human clinical studies. The objective of the present study was to characterize EROs in adult P and NP rats. A time-frequency representation method was used to determine delta, theta, and alpha/beta ERO energy and the degree of phase variation in the parietal cortex of adult P and NP rats. The present results suggest that the decrease in P3 amplitudes previously shown in P rats were not associated with changes in ERO energy but were significantly associated with decreases in evoked delta and alpha/beta phase locking. These studies demonstrate ERO measures may also be good endophenotypes in animal models of alcoholism.

Effects of adolescent ethanol exposure on event-related oscillations (EROs) in the hippocampus of adult rats

Electrophysiological studies have shown that adolescent ethanol (EtOH) exposure can produce long-term changes in hippocampal EEG and ERP activity. Recently, evidence has emerged suggesting that event-related oscillations (EROs) may be good indices of alcoholism risk in humans, however, have not been evaluated for their ability to index the effects of EtOH exposure. The objective of the present study was to characterize EROs generated in hippocampus in adult rats exposed to EtOH during adolescence. Adolescent male Sprague–Dawley rats were exposed to EtOH vapor for 12 h/d for 10 days. A time–frequency representation method was used to determine delta, theta, alpha and beta ERO energy and the degree of phase variation in the hippocampus of adult rats exposed to EtOH and age-matched controls. The present results suggest that the decrease in P3 amplitudes, previously observed in adult rats exposed to EtOH during adolescence, is associated with increases in evoked theta ERO energy. These studies suggest that EROs are suitable for characterizing the long-term effects of adolescent EtOH exposure. Further studies are needed to determine the relationship between the mechanisms that regulate these neurophysiological endophenotypes and the consequences of adolescent EtOH exposure.

Time-frequency and advanced frequency estimation techniques for the investigation of bat echolocation calls

In this paper, techniques for time-frequency analysis and investigation of bat echolocation calls are studied. Particularly, enhanced resolution techniques are developed and/or used in this specific context for the first time. When compared to traditional time-frequency representation methods, the proposed techniques are more capable of showing previously unseen features in the structure of bat echolocation calls. It should be emphasized that although the study is focused on bat echolocation recordings, the results are more general and applicable to many other types of signal.

Deconvolutive Short-Time Fourier Transform Spectrogram

The short-time Fourier transform (STFT) spectrogram, which is the squared modulus of the STFT, is a smoothed version of the Wigner-Ville distribution (WVD). The STFT spectrogram is 2-D convolution of the the signal WVD and the window function WVD. In this letter, we propose a deconvolutive short-time Fourier transform (DSTFT) spectrogram method, which improves the time-frequency resolution and reduces the cross-terms simultaneously by applying a 2-D deconvolution operation on the STFT spectrogram. Compared to the STFT spectrogram, the spectrogram obtained by the proposed method shows a clear improvement in the time-frequency resolution. Computer simulations are provided to illustrate the good performance of the proposed method, compared with some traditional time-frequency representation (TFR) methods.

Event-related oscillations as risk markers in genetic mouse models of high alcohol preference

Mouse models have been developed to simulate several relevant human traits associated with alcohol use and dependence. However, the neurophysiological substrates regulating these traits remain to be completely elucidated. We have previously demonstrated that differences in the event-related potential (ERP) responses can be found that distinguish high-alcohol preferring from low alcohol preferring mice that resemble differences seen in human studies of individuals with high and low risk for alcohol dependence. Recently, evidence of genes that affect event-related oscillations (EROs) and the risk for alcohol dependence has emerged, however, to date EROs have not been evaluated in genetic mouse models of high and low alcohol preference. Therefore, the objective of the present study was to characterize EROs in mouse models of high (C57BL/6 [B6] and high alcohol preference 1 [HAP-1] mice) and low (DBA/2J [D2] and low alcohol preference-1 [LAP-1] mice) alcohol preference. A time-frequency representation method was used to determine delta, theta and alpha/beta ERO energy and the degree of phase variation in these mouse models. The present results suggest that the decrease in P3 amplitudes previously shown in B6 mice, compared to D2 mice, is related to reductions in evoked delta ERO energy and delta and theta phase locking. In contrast, the increase in P1 amplitudes reported in HAP-1 mice, compared to LAP-1 mice, is associated with increases in evoked theta ERO energy. These studies suggest that differences in delta and theta ERO measures in mice mirror changes observed between groups at high- and low-risk for alcoholism where changes in EROs were found to be more significant than group differences in P3 amplitudes, further suggesting that ERO measures are more stable endophenotypes in the study of alcohol dependence. Further studies are needed to determine the relationship between expression of these neurophysiological endophenotypes and the genetic profile of these mouse models.

Hilbert-Huang versus Morlet wavelet transformation on mismatch negativity of children in uninterrupted sound paradigm

BackgroundCompared to the waveform or spectrum analysis of event-related potentials (ERPs), time-frequency representation (TFR) has the advantage of revealing the ERPs time and frequency domain information simultaneously. As the human brain could be modeled as a complicated nonlinear system, it is interesting from the view of psychological knowledge to study the performance of the nonlinear and linear time-frequency representation methods for ERP research. In this study Hilbert-Huang transformation (HHT) and Morlet wavelet transformation (MWT) were performed on mismatch negativity (MMN) of children. Participants were 102 children aged 8–16 years. MMN was elicited in a passive oddball paradigm with duration deviants. The stimuli consisted of an uninterrupted sound including two alternating 100 ms tones (600 and 800 Hz) with infrequent 50 ms or 30 ms 600 Hz deviant tones. In theory larger deviant should elicit larger MMN. This theoretical expectation is used as a criterion to test two TFR methods in this study. For statistical analysis MMN support to absence ratio (SAR) could be utilized to qualify TFR of MMN.ResultsCompared to MWT, the TFR of MMN with HHT was much sharper, sparser, and clearer. Statistically, SAR showed significant difference between the MMNs elicited by two deviants with HHT but not with MWT, and the larger deviant elicited MMN with larger SAR.ConclusionSupport to absence ratio of Hilbert-Huang Transformation on mismatch negativity meets the theoretical expectations, i.e., the more deviant stimulus elicits larger MMN. However, Morlet wavelet transformation does not reveal that. Thus, HHT seems more appropriate in analyzing event-related potentials in the time-frequency domain. HHT appears to evaluate ERPs more accurately and provide theoretically valid information of the brain responses.

A new technique to reduce cross terms in the Wigner distribution

A new method for time-frequency representation (TFR) of a signal, which combines the Fourier–Bessel (FB) expansion and the Wigner–Ville distribution (WVD) has been presented in this paper. The FB expansion decomposes a multicomponent signal into a number of monocomponent signals, and then the WVD technique is applied on each component of the composite signal to analyze its time-frequency distribution (TFD). The simulation results show that the proposed technique based on the FB decomposition is a powerful tool for analyzing multicomponent nonstationary signals and for obtaining the TFR of the signal without introducing cross terms.

Evoked gamma band response in male adolescent subjects at high risk for alcoholism during a visual oddball task

This study investigates early evoked gamma band activity in male adolescent subjects at high risk for alcoholism (HR; n = 68) and normal controls (LR; n = 27) during a visual oddball task. A time–frequency representation method was applied to EEG data in order to obtain stimulus related early evoked (phase-locked) gamma band activity (29–45 Hz) and was analyzed within a 0–150 ms time window range. Significant reduction of the early evoked gamma band response in the frontal and parietal regions during target stimulus processing was observed in HR subjects compared to LR subjects. Additionally, the HR group showed less differentiation between target and non-target stimuli in both frontal and parietal regions compared to the LR group, indicating difficulty in early stimulus processing, probably due to a dysfunctional frontoparietal attentional network. The results indicate that the deficient early evoked gamma band response may precede the development of alcoholism and could be a potential endophenotypic marker of alcoholism risk.

Suppression of early evoked gamma band response in male alcoholics during a visual oddball task

We investigated the early evoked gamma frequency band activity in alcoholics ( n = 122) and normal controls ( n = 72) during a visual oddball task. A time–frequency representation method was applied to EEG data in order to obtain phase-locked gamma band activity (29–45 Hz) and was analyzed within a 0–150 ms time window range. Significant reduction of the gamma band response in the frontal region during target stimulus processing was observed in alcoholic compared to control subjects. In contrast, significantly higher gamma band response for the non-target stimulus was observed in alcoholics compared to controls. It is suggested that the reduction in early evoked frontal gamma band response to targets may be associated with frontal lobe dysfunction commonly observed in alcoholics. This perhaps can be characterized by a deficient top-down processing mechanism.

High-resolution time–frequency distributions for manoeuvring target detection in over-the-horizon radars

A novel high-resolution time-frequency representation method is proposed for source detection and classification in over-the-horizon radar (OTHR) systems. A data-dependent kernel is applied in the ambiguity domain to capture the target signal components, which are then resolved using root-MUSIC based coherent spectrum estimation. This two-step procedure is particularly effective for analysing a multicomponent signal with time-varying complex time-Doppler signatures. By using the different time-Doppler signatures, important target manoeuvring information, which is difficult to extract using other linear and bilinear time-frequency representation methods, can be easily revealed using the proposed method.

Performance of time-frequency representation techniques to measure blood flow turbulence with pulsed-wave Doppler ultrasound

The current processing performed by commercial instruments to obtain the time-frequency representation (TFR) of pulsed-wave Doppler signals may not be adequate to characterize turbulent flow motions. The assessment of the intensity of turbulence is of high clinical importance and measuring high-frequency (small-scale) flow motions, using Doppler ultrasound (US), is a difficult problem that has been studied very little. The objective was to optimize the performance of the spectrogram (SPEC), autoregressive modeling (AR), Choi–Williams distribution (CWD), Choi–Williams reduced interference distribution (CW-RID), Bessel distribution (BD), and matching pursuit method (MP) for mean velocity waveform estimation and turbulence detection. The intensity of turbulence was measured from the fluctuations of the Doppler mean velocity obtained from a simulation model under pulsatile flow. The Kolmogorov spectrum, which is used to determine the frequency of the fluctuations and, thus, the scale of the turbulent motions, was also computed for each method. The best set of parameters for each TFR method was determined by minimizing the error of the absolute frequency fluctuations and Kolmogorov spectral bandwidth measured from the simulated and computed Doppler spectra. The results showed that different parameters must be used for each method to minimize the velocity variance of the estimator, to optimize the detection of the turbulent frequency fluctuations, and to estimate the Kolmogorov spectrum. To minimize the variance and to measure the absolute turbulent frequency fluctuations, four methods provided similar results: SPEC (10-ms sine-cosine windows), AR (10-ms rectangular windows, model order = 8), CWD (wN and wM = 10-ms rectangular windows, σ = 0.01), and BD (wN = 10-ms rectangular windows, α = 16). The velocity variance in the absence of turbulence was on the order of 0.04 m/s (coefficient of variation ranging from 8.0% to 14.5%, depending on the method). With these spectral techniques, the peak of the turbulence intensity was adequately estimated (velocity bias < 0.01 m/s). To track the frequency of turbulence, the best method was BD (wN = 2-ms rectangular windows, α = 2). The bias in the estimate of the −10 dB bandwidth of the Kolmogorov spectrum was 354 ± 51 Hz in the absence of turbulence (the true bandwidth should be 0 Hz), and −193 ± 371 Hz with turbulence (the simulated −10-dB bandwidth was estimated at 1256 Hz instead of 1449 Hz). In conclusion, several TFR methods can be used to measure the magnitude of the turbulent fluctuations. To track eddies ranging from large vortex to small turbulent fluctuations (wide Kolmogorov spectrum), the Bessel distribution with appropriate set of parameters is recommended. (E-mail: cloutig@ircm.qc.ca)

The use of a filter bank and the Wigner-Ville distribution for time-frequency representation

We present a new method for time-frequency representation, which combines a filter bank and the Wigner-Ville distribution (WVD). The filter bank decomposes a multicomponent signal into a number of single component signals before the WVD is applied. Cross-terms as well as noise are reduced significantly, whereas high time-frequency concentration is attained. Properties of the proposed time-frequency distribution (TFD) are investigated, and the requirements for the filter bank to fulfil these are given. The ability of the proposed non-Cohen's (1995) class TFD to reduce cross-terms as well as noise as well as its ability to approximately reconstruct signals are illustrated by examples. The results are compared with those from the WVD, the Choi-Williams (1989) distribution (CWD), and spectrogram.