968 resultados para Time-frequency distribution


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In this paper, we propose features extracted from the heart rate variability (HRV) based on the first and second conditional moments of time-frequency distribution (TFD) as an additional guide for seizure detection in newborn. The features of HRV in the low frequency band (LF: 0-0.07 Hz), mid frequency band (MF: 0.07-0.15 Hz), and high frequency band (HF: 0.15-0.6 Hz) have been obtained by means of the time-frequency analysis using the modified-B distribution (MBD). Results of ongoing time-frequency research are presented. Based on our preliminary results, the first conditional moment of HRV which is also known as the mean/central frequency in the LF band and the second conditional moment of HRV which is also known as the variance/instantaneous bandwidth (IB) in the HF band can be used as a good feature to discriminate the newborn seizure from the non-seizure

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In this paper, a new method for characterizing the newborn heart rate variability (HRV) is proposed. The central of the method is the newly proposed technique for instantaneous frequency (IF) estimation specifically designed for nonstationary multicomponen signals such as HRV. The new method attempts to characterize the newborn HRV using features extracted from the time–frequency (TF) domain of the signal. These features comprise the IF, the instantaneous bandwidth (IB) and instantaneous energy (IE) of the different TF components of the HRV. Applied to the HRV of both normal and seizure suffering newborns, this method clearly reveals the locations of the spectral peaks and their time-varying nature. The total energy of HRV components, ET and ratio of energy concentrated in the low-frequency (LF) to that in high frequency (HF) components have been shown to be significant features in identifying the HRV of newborn with seizures.

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Carrying out information about the microstructure and stress behaviour of ferromagnetic steels, magnetic Barkhausen noise (MBN) has been used as a basis for effective non-destructive testing methods, opening new areas in industrial applications. One of the factors that determines the quality and reliability of the MBN analysis is the way information is extracted from the signal. Commonly, simple scalar parameters are used to characterize the information content, such as amplitude maxima and signal root mean square. This paper presents a new approach based on the time-frequency analysis. The experimental test case relates the use of MBN signals to characterize hardness gradients in a AISI4140 steel. To that purpose different time-frequency (TFR) and time-scale (TSR) representations such as the spectrogram, the Wigner-Ville distribution, the Capongram, the ARgram obtained from an AutoRegressive model, the scalogram, and the Mellingram obtained from a Mellin transform are assessed. It is shown that, due to nonstationary characteristics of the MBN, TFRs can provide a rich and new panorama of these signals. Extraction techniques of some time-frequency parameters are used to allow a diagnostic process. Comparison with results obtained by the classical method highlights the improvement on the diagnosis provided by the method proposed.

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This correspondence studies the formulation of members ofthe Cohen-Posch class of positive time-frequency energy distributions.Minimization of cross-entropy measures with respect to different priorsand the case of no prior or maximum entropy were considered. It isconcluded that, in general, the information provided by the classicalmarginal constraints is very limited, and thus, the final distributionheavily depends on the prior distribution. To overcome this limitation,joint time and frequency marginals are derived based on a "directioninvariance" criterion on the time-frequency plane that are directly relatedto the fractional Fourier transform.

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Sonar signal processing comprises of a large number of signal processing algorithms for implementing functions such as Target Detection, Localisation, Classification, Tracking and Parameter estimation. Current implementations of these functions rely on conventional techniques largely based on Fourier Techniques, primarily meant for stationary signals. Interestingly enough, the signals received by the sonar sensors are often non-stationary and hence processing methods capable of handling the non-stationarity will definitely fare better than Fourier transform based methods.Time-frequency methods(TFMs) are known as one of the best DSP tools for nonstationary signal processing, with which one can analyze signals in time and frequency domains simultaneously. But, other than STFT, TFMs have been largely limited to academic research because of the complexity of the algorithms and the limitations of computing power. With the availability of fast processors, many applications of TFMs have been reported in the fields of speech and image processing and biomedical applications, but not many in sonar processing. A structured effort, to fill these lacunae by exploring the potential of TFMs in sonar applications, is the net outcome of this thesis. To this end, four TFMs have been explored in detail viz. Wavelet Transform, Fractional Fourier Transfonn, Wigner Ville Distribution and Ambiguity Function and their potential in implementing five major sonar functions has been demonstrated with very promising results. What has been conclusively brought out in this thesis, is that there is no "one best TFM" for all applications, but there is "one best TFM" for each application. Accordingly, the TFM has to be adapted and tailored in many ways in order to develop specific algorithms for each of the applications.

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A new approach, the four-window technique, was developed to measure optical phase-space-time-frequency tomography (OPSTFT). The four-window technique is based on balanced heterodyne detection with two local oscillator (LO) fields. This technique can provide independent control of position, momentum, time and frequency resolution. The OPSTFT is a Wigner distribution function of two independent Fourier transform pairs, phase-space and time-frequency. The OPSTFT can be applied for early disease detection.

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Aims. We derive for the first time the size-frequency distribution of boulders on a comet, 67P/Churyumov-Gerasimenko (67P), computed from the images taken by the Rosetta/OSIRIS imaging system. We highlight the possible physical processes that lead to these boulder size distributions. Methods. We used images acquired by the OSIRIS Narrow Angle Camera, NAC, on 5 and 6 August 2014. The scale of these images (2.44−2.03 m/px) is such that boulders ≥7 m can be identified and manually extracted from the datasets with the software ArcGIS. We derived both global and localized size-frequency distributions. The three-pixel sampling detection, coupled with the favorable shadowing of the surface (observation phase angle ranging from 48° to 53°), enables unequivocally detecting boulders scattered all over the illuminated side of 67P. Results. We identify 3546 boulders larger than 7 m on the imaged surface (36.4 km2), with a global number density of nearly 100/km2 and a cumulative size-frequency distribution represented by a power-law with index of −3.6 +0.2/−0.3. The two lobes of 67P appear to have slightly different distributions, with an index of −3.5 +0.2/−0.3 for the main lobe (body) and −4.0 +0.3/−0.2 for the small lobe (head). The steeper distribution of the small lobe might be due to a more pervasive fracturing. The difference of the distribution for the connecting region (neck) is much more significant, with an index value of −2.2 +0.2/−0.2. We propose that the boulder field located in the neck area is the result of blocks falling from the contiguous Hathor cliff. The lower slope of the size-frequency distribution we see today in the neck area might be due to the concurrent processes acting on the smallest boulders, such as i) disintegration or fragmentation and vanishing through sublimation; ii) uplifting by gas drag and consequent redistribution; and iii) burial beneath a debris blanket. We also derived the cumulative size-frequency distribution per km2 of localized areas on 67P. By comparing the cumulative size-frequency distributions of similar geomorphological settings, we derived similar power-law index values. This suggests that despite the selected locations on different and often opposite sides of the comet, similar sublimation or activity processes, pit formation or collapses, as well as thermal stresses or fracturing events occurred on multiple areas of the comet, shaping its surface into the appearance we see today.

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At sites 390 and 392 (Deep Sea Drilling Project, Leg 44) on the Blake nose, thoroughly lithified Lower Cretaceous limestone more than 250 m thick is abruptly overlain by a condensed sequence of Barremian to Eocene pelagic carbonate ooze. The Lower Cretaceous sediments consist of three units: limestone with moldic porosity (base), oolitic limestone, and fenestral limestone. Subaerial diagenesis of the limestone section is recorded by (1) caverns with vertical dimensions of up to 10 m, (2) stalactitic intergranular cement, and (3) meniscus sediment (or cement). Compatible with these subaerial features are mud cracks, fenestral fabrics, intraclasts, and cryptalgal structures. Inasmuch as these shallow-water and tidal-flat deposits are now beneath 2,607 m of sea water (plus 99 m of younger sediments), they serve to dramatize the apparent degree of Barremian and later subsidence of this part of the Atlantic outer continental shelf. Porosity and permeability are high in vuggy samples, which are common in the skelmoldic limestone. Cementation has destroyed most of the extensive primary porosity of the two younger units.