A teleseism-specific detection algorithm for single short-period traces

1983 ◽  
Vol 73 (4) ◽  
pp. 1173-1186
Author(s):  
John R. Evans ◽  
Stephen S. Allen
Keyword(s):  
Frequency Band ◽  
High Frequency ◽  
Vertical Component ◽  
Low Frequency ◽  
Field Studies ◽  
Detection Algorithm ◽  
P Waves ◽  
Data Set ◽  
Short Period ◽  
Worldwide Network

abstract An algorithm for microprocessor-controlled seismographic recorders is described which reliably detects major phases from earthquakes more than 3° from the sensor but rejects noise events and most earthquakes closer than 3°. Unusually large earthquakes within 3° also are detected. The algorithm is applicable to field studies using triggered seismographs to record teleseismic P waves, to worldwide network automation, and to scanning records for teleseisms. It uses two band-pass filtered data streams evolved from a single short-period vertical-component seismometer to differentiate (low-frequency) teleseisms from other signals; the low-frequency band (0.5 to 2.0 Hz) declares “triggers” while the high-frequency band (3.0 to 8.0 Hz) inhibits any of these triggers generated by broadband signals such as local earthquakes. Locally generated noise is usually high frequency and does not excite the low-frequency band. A 16-bit fixed-word-length implementation of this algorithm detected 82 per cent of good P phases (readable to ±0.25 sec) occurring more than 20° from the seismograph, and 50 per cent of earthquakes between 3° and 20°, in a test data set comprising 23 hr of data in 93 segments. The same implementation of the algorithm rejected most noise and 91 per cent of earthquakes within 3° of the seismograph.

Despeckling of Sar Images Using Shrinkage of Two-Dimensional Discrete Orthonormal S-Transform

2020 ◽  
pp. 2150023
Author(s):  
Priya R. Kamath ◽  
Kedarnath Senapati ◽  
P. Jidesh
Keyword(s):  
High Frequency ◽  
Low Frequency ◽  
Relevant Information ◽  
Detection Algorithm ◽  
Two Dimensional ◽  
Sar Images ◽  
S Transform ◽  
Processing Step ◽  
Frequency Components ◽  
Shock Filter

Speckles are inherent to SAR. They hide and undermine several relevant information contained in the SAR images. In this paper, a despeckling algorithm using the shrinkage of two-dimensional discrete orthonormal S-transform (2D-DOST) coefficients in the transform domain along with shock filter is proposed. Also, an attempt has been made as a post-processing step to preserve the edges and other details while removing the speckle. The proposed strategy involves decomposing the SAR image into low and high-frequency components and processing them separately. A shock filter is used to smooth out the small variations in low-frequency components, and the high-frequency components are treated with a shrinkage of 2D-DOST coefficients. The edges, for enhancement, are detected using a ratio-based edge detection algorithm. The proposed method is tested, verified, and compared with some well-known models on C-band and X-band SAR images. A detailed experimental analysis is illustrated.

scholarly journals Statistical analysis of Stromboli VLP tremor in the band [0.1–0.5] Hz: some consequences for vibrating structures

2006 ◽  
Vol 13 (4) ◽  
pp. 393-400 ◽  
Author(s):  
E. De Lauro ◽  
S. De Martino ◽  
M. Falanga ◽  
M. Palo
Keyword(s):  
Frequency Band ◽  
High Frequency ◽  
Noise Source ◽  
Volcanic Tremor ◽  
Large Data ◽  
Musical Instruments ◽  
Data Set ◽  
Long Period ◽  
Vibrating Structures ◽  
Analyze Time Series

Abstract. We analyze time series of Strombolian volcanic tremor, focusing our attention on the frequency band [0.1–0.5] Hz (very long period (VLP) tremor). Although this frequency band is largely affected by noise, we evidence two significant components by using Independent Component Analysis with the frequencies, respectively, of ~0.2 and ~0.4 Hz. We show that these components display wavefield features similar to those of the high frequency Strombolian signals (>0.5 Hz). In fact, they are radially polarised and located within the crater area. This characterization is lost when an enhancement of energy appears. In this case, the presence of microseismic noise becomes relevant. Investigating the entire large data set available, we determine how microseismic noise influences the signals. We ascribe the microseismic noise source to Scirocco wind. Moreover, our analysis allows one to evidence that the Strombolian conduit vibrates like the asymmetric cavity associated with musical instruments generating self-sustained tones.

L1 pseudo-Vz estimation and deghosting of single-component marine towed-streamer data

Geophysics ◽  
2013 ◽  
Vol 78 (2) ◽  
pp. WA21-WA6 ◽  
Author(s):  
Ralf Ferber ◽  
Philippe Caprioli ◽  
Lee West
Keyword(s):  
Particle Motion ◽  
Pressure Wave ◽  
Vertical Component ◽  
Low Frequency ◽  
Single Component ◽  
Pressure Data ◽  
Data Set ◽  
Low Frequencies ◽  
Motion Data ◽  
Streamer Data

We present a novel technique estimating the vertical component of particle motion from marine single-component pressure data. The particle motion data, bar an angle-dependent obliquity factor, is computed by convolution of the output from L1 deconvolution of the pressure ghost wavelet with the corresponding ghost wavelet of the particle motion. The estimated particle motion data is then used in a conventional 2D technique for receiver ghost attenuation by combination with the original pressure-wave data. The proposed new technique operates in the τ-[Formula: see text] domain of individual shot-streamer records and in overlapping windows along the intercept-time axis. In each window, the L1 deconvolution is achieved by an iteratively reweighted-norm least squares algorithm. We applied our technique to deep-tow streamer data of a 3D over/sparse-under marine survey, in which six streamers were towed at a shallow depth, with two additional streamers towed deeper. Over/sparse-under technology allows using seismic measurements from a shallow streamer to be complemented by a low-frequency limited measurement from a deep streamer to achieve an estimate of the up-going pressure wave recording. The low frequencies of the deep streamer are used to boost the low frequencies of the shallow streamer, which have been heavily attenuated by the shallow tow ghost response. Our technique achieves, on this particular data, set improvements in bandwidth of the single-component pressure data, while not fully reaching the quality of the optimally deghosted data from the over/sparse-under survey.

A Novel Accelerometer Mounting Method for Sensing Performance Improvement in Acoustic Measurements From the Knee

2020 ◽  
Vol 143 (3) ◽  
Author(s):  
Goktug C. Ozmen ◽  
Mohsen Safaei ◽  
Lan Lan ◽  
Omer T. Inan
Keyword(s):  
Frequency Band ◽  
High Frequency ◽  
Low Frequency ◽  
Adhesive Tape ◽  
Spectral Centroid ◽  
Wearable Systems ◽  
Electrodynamic Shaker ◽  
3D Printed ◽  
The Mean ◽  
Sensing Performance

Abstract In this study, we propose a new mounting method to improve accelerometer sensing performance in the 50 Hz–10 kHz frequency band for knee sound measurement. The proposed method includes a thin double-sided adhesive tape for mounting and a 3D-printed custom-designed backing prototype. In our mechanical setup with an electrodynamic shaker, the measurements showed a 13 dB increase in the accelerometer's sensing performance in the 1–10 kHz frequency band when it is mounted with the craft tape under 2 N backing force applied through low-friction tape. As a proof-of-concept study, knee sounds of healthy subjects (n = 10) were recorded. When the backing force was applied, we observed statistically significant (p < 0.01) incremental changes in spectral centroid, spectral roll-off frequencies, and high-frequency (1–10 kHz) root-mean-square (RMS) acceleration, while low-frequency (50 Hz–1 kHz) RMS acceleration remained unchanged. The mean spectral centroid and spectral roll-off frequencies increased from 0.8 kHz and 4.15 kHz to 1.35 kHz and 5.9 kHz, respectively. The mean high-frequency acceleration increased from 0.45 mgRMS to 0.9 mgRMS with backing. We showed that the backing force improves the sensing performance of the accelerometer when mounted with the craft tape and the proposed backing prototype. This new method has the potential to be implemented in today's wearable systems to improve the sensing performance of accelerometers in knee sound measurements.

scholarly journals Ferrite-Loaded Spidron Fractal Loop VHF Antenna for UAV Applications

2020 ◽  
Vol 10 (15) ◽  
pp. 5392 ◽  
Author(s):  
Won Bin Park ◽  
Young-Mi Park ◽  
Keum Cheol Hwang
Keyword(s):  
Frequency Band ◽  
High Frequency ◽  
Magnetic Loss ◽  
Low Frequency ◽  
Loop Antenna ◽  
High Frequency Band ◽  
Ferrite Material ◽  
Aerial Vehicle ◽  
Flat Ground ◽  
Good Agreement

In this letter, an electrically small Spidron fractal loop antenna operating in the VHF band is proposed. The ferrite material, which consists of a nickel-zinc combination, is loaded into inside of the loop antenna to increase the gain of the antenna in the low frequency band. To minimize the magnetic loss of the ferrite in the high frequency band, the amount and configuration of the ferrite are optimized using a genetic algorithm. Through this optimization step, the amount of the ferrite is decreased to 37.5% and the gain of the antenna in the high frequency band is improved. The size of the proposed antenna is 0.0242 × 0.0242 × 0.0051 λL3 at the lowest operating frequency. The proposed antenna was fabricated to verify the performance, and the simulated and measured results are in good agreement. The measured peak gains varied from −31.6 to −1.9 dBi within the measured frequency band. To examine the performance of the proposed antenna mounted on an unmanned aerial vehicle model (UAV), the antenna on a UAV was also simulated and the results were discussed. The simulated realized peak gains of the antenna on the UAV and on flat ground are similar.

Dual-band low-profile planar antenna for mobile communication application

2015 ◽  
Vol 9 (2) ◽  
pp. 447-452 ◽  
Author(s):  
Xi-Wang Dai ◽  
Tao Zhou ◽  
Bo-Ran Guan
Keyword(s):  
Frequency Band ◽  
Mobile Communication ◽  
High Frequency ◽  
Microstrip Line ◽  
Low Frequency ◽  
Dual Band ◽  
Planar Antenna ◽  
Frequency Resonance ◽  
Low Profile ◽  
High Frequency Resonance

A novel dual-band planar antenna with a low profile for mobile communication system is proposed in this paper. The antenna is composed of one shorted patch with two radiating notches for low frequency resonance and one square patch for high frequency resonance. The low profile is achieved via the shorting patch, which introduces the parallel electrical field between the reflector and antenna. A step-impedance microstrip line is used to feed the antenna. The coupling between the square patch and microstrip line cancels out the inductance of shorting probe, which increases the working bandwidth of proposed antenna. A prototype with a low profile of 0.0286λ is fabricated and measured. The antenna achieves dual impedance bandwidths of 1.6% for the low frequency band and 60% for the high frequency band, covering the frequency range 851–865 MHz and 1.97–3.65 GHz, respectively. The measured results show good agreements with the simulated ones.

scholarly journals Postoperative seizure outcome-guided machine learning for interictal electrocorticography in neocortical epilepsy

2018 ◽  
Vol 119 (6) ◽  
pp. 2265-2275 ◽  
Author(s):  
Seong-Cheol Park ◽  
Chun Kee Chung
Keyword(s):  
Machine Learning ◽  
Free Group ◽  
High Frequency ◽  
Low Frequency ◽  
Outcome Data ◽  
Training Data ◽  
Seizure Outcome ◽  
Data Set ◽  
Neocortical Epilepsy ◽  
Postoperative Seizure

The objective of this study was to introduce a new machine learning guided by outcome of resective epilepsy surgery defined as the presence/absence of seizures to improve data mining for interictal pathological activities in neocortical epilepsy. Electrocorticographies for 39 patients with medically intractable neocortical epilepsy were analyzed. We separately analyzed 38 frequencies from 0.9 to 800 Hz including both high-frequency activities and low-frequency activities to select bands related to seizure outcome. An automatic detector using amplitude-duration-number thresholds was used. Interictal electrocorticography data sets of 8 min for each patient were selected. In the first training data set of 20 patients, the automatic detector was optimized to best differentiate the seizure-free group from not-seizure-free-group based on ranks of resection percentages of activities detected using a genetic algorithm. The optimization was validated in a different data set of 19 patients. There were 16 (41%) seizure-free patients. The mean follow-up duration was 21 ± 11 mo (range, 13–44 mo). After validation, frequencies significantly related to seizure outcome were 5.8, 8.4–25, 30, 36, 52, and 75 among low-frequency activities and 108 and 800 Hz among high-frequency activities. Resection for 5.8, 8.4–25, 108, and 800 Hz activities consistently improved seizure outcome. Resection effects of 17–36, 52, and 75 Hz activities on seizure outcome were variable according to thresholds. We developed and validated an automated detector for monitoring interictal pathological and inhibitory/physiological activities in neocortical epilepsy using a data-driven approach through outcome-guided machine learning. NEW & NOTEWORTHY Outcome-guided machine learning based on seizure outcome was used to improve detections for interictal electrocorticographic low- and high-frequency activities. This method resulted in better separation of seizure outcome groups than others reported in the literature. The automatic detector can be trained without human intervention and no prior information. It is based only on objective seizure outcome data without relying on an expert’s manual annotations. Using the method, we could find and characterize pathological and inhibitory activities.

Heart rate variability and dissociation in panic disorder

2011 ◽  
Vol 26 (S2) ◽  
pp. 147-147
Author(s):  
T. Diveky ◽  
D. Kamaradova ◽  
A. Grambal ◽  
K. Latalova ◽  
J. Prasko ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Panic Disorder ◽  
Frequency Band ◽  
High Frequency ◽  
Power Spectra ◽  
Low Frequency ◽  
Very Low Frequency ◽  
Significant Difference ◽  
Before And After

The aim of our study is to measure very low frequency band (VLF), low frequency band (LF) and high frequency band (HF) components of R-R interval during orthostatic experiment in panic disorder patients before and after treatment.MethodsWe assessed heart rate variability in 19 patients with panic disorder before and after 6-weeks treatment with antidepressants combined with CBT and 18 healthy controls. They were regularly assessed on the CGI, BAI and BDI. Heart rate variability was assessed during 5 min standing, 5 min supine and 5 min standing positions before and after the treatment. Power spectra were computed using a fast Fourier transformation for very low frequency - VLF (0.0033 - 0.04 Hz), low-frequency - LF (0.04-0.15 Hz) and high frequency - HF (0.15-0.40 Hz) powers.Results19 panic disorder patients entered a 6-week open-label treatment study with combination of SSRI and cognitive behavioral therapy. A combination of CBT and pharmacotherapy proved to be the effective treatment of patients. They significantly improved in all rating scales. There were highly statistical significant differences between panic patients and control group in all components of power spectral analysis in 2nd and in two component of 3rd (LF and HF in standing) positions. There was also statistically significant difference between these two groups in LF/HF ratio in supine position (2nd). During therapy there was tendency to increasing values in all three positions in components of HRV power spectra, but there was only statistically significant increasing in HF1 component.Supported by project IGA MZ ČR NS 10301-3/2009

Fusion Algorithm of Infrared and Visible Images Based on Multiresolution Decomposition

2012 ◽  
Vol 239-240 ◽  
pp. 229-232
Author(s):  
Chen Ding
Keyword(s):  
Statistical Model ◽  
Image Fusion ◽  
Frequency Band ◽  
High Frequency ◽  
Wavelet Coefficient ◽  
Low Frequency ◽  
High Frequency Band ◽  
Fusion Algorithm ◽  
Regional Energy ◽  
Multiresolution Decomposition

Information redundancy and complementarity are existing between the images obtained by multi-sensor, image fusion can improve the certainty and reliability of the information. Traditional method of image fusion based on multiresolution decomposition is susceptible to high frequency noise, fusion is often ineffective. A image fusion algorithm has been studied based on the wavelet multiresolution decomposition which is regional energy maximum for low-frequency decomposition image, and the bivariate statistical model for high-frequency part. The results show that: in the conditions of Daubechies 3 wavelet basis function, decomposition level 5 multiresolution decomposition, the bivariate statistical model for the high-frequency band is robust to noise based on the joint probability of wavelet coefficient pair - a wavelet coefficient and its parent; in the same time, the regional energy maximum for low-frequency band can be effective on the high-frequency band based on the bivariate statistical model. The fusion image has the biggish contrast, the preferable details, the higher gray level resolution.

scholarly journals Acoustical study on spectral characteristics of teachers’ English vocalization

2021 ◽  
Vol 257 ◽  
pp. 02027
Author(s):  
Yao Xiao ◽  
Yue-Zhe Zhao
Keyword(s):  
Frequency Band ◽  
High Frequency ◽  
Sound Pressure ◽  
Spectral Characteristics ◽  
Low Frequency ◽  
Sound Intensity ◽  
English Teaching ◽  
Female Teachers ◽  
Acoustical Study ◽  
Second Peak

With the increase of English teaching courses, the specific vocal characteristics of teachers in English teaching are studied and used as the basic data for the design of teachers’ spatial acoustics. In order to study this problem, three different English voice materials were read in a anechoic room under three sound intensity levels: large, medium and small, respectively, so as to analyse the equivalent continuous sound pressure level (SPL) and frequency characteristic curves of male and female teachers at 0.3m. In the low frequency band, the SPL increases as the frequency increases. In the mid-frequency band, the SPL reaches the first peak, then decreases briefly as the frequency increases, then increases again to the second peak, and then decreases again briefly as the frequency increases. Then increase again to the third peak. In the high frequency band, the SPL decreases as the frequency increases.

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