scholarly journals Territorial black-capped chickadee males respond faster to high- than to low-frequency songs in experimentally elevated noise conditions

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e3257 ◽  
Author(s):  
Stefanie E. LaZerte ◽  
Hans Slabbekoorn ◽  
Ken A. Otter
Keyword(s):  
High Frequency ◽  
Background Noise ◽  
Noise Exposure ◽  
Signal To Noise Ratio ◽  
Low Frequency ◽  
Trade Offs ◽  
Dependent Signal ◽  
Noisy Conditions ◽  
Carry Over ◽  
Free Ranging

Low-frequency urban noise can interfere with avian communication through masking. Some species are able to shift the frequency of their vocalizations upwards in noisy conditions, which may reduce the effects of masking. However, results from playback studies investigating whether or not such vocal changes improve audibility in noisy conditions are not clear; the responses of free-ranging individuals to shifted signals are potentially confounded by functional trade-offs between masking-related audibility and frequency-dependent signal quality. Black-capped chickadees (Poecile atricapillus) naturally sing their songs at several different frequencies as they pitch-shift to match conspecifics during song-matching contests. They are also known to switch to higher song frequencies in response to experimental noise exposure. Each male produces both high- and low-frequency songs and absolute frequency is not a signal of aggression or dominance, making this an interesting species in which to test whether higher-frequency songs are more audible than lower-frequency songs in noisy conditions. We conducted playback studies across southern and central British Columbia, Canada, using paired song stimuli (high- vs low-frequency songs, n = 24 pairs) embedded in synthetic background noise created to match typical urban sound profiles. Over the course of each playback, the signal-to-noise ratio of the song stimuli was gradually increased by raising the amplitude of the song stimuli while maintaining background noise at a constant amplitude. We evaluated variation in how quickly and aggressively territorial males reacted to each of the paired stimuli. We found that males responded more quickly to playbacks of high- than low-frequency songs when high-frequency songs were presented first, but not when low-frequency songs were first. This difference may be explained by high-frequency songs being more audible combined with a carry-over effect resulting in slower responses to the second stimulus due to habituation. We observed no difference in overall aggression between stimuli. These results suggest that high-frequency songs may be more audible under noisy conditions.

Denoising for full-waveform inversion with expanded prediction-error filters

Geophysics ◽  
2021 ◽  
pp. 1-54
Author(s):  
Milad Bader ◽  
Robert G. Clapp ◽  
Biondo Biondi
Keyword(s):  
High Frequency ◽  
Prediction Error ◽  
Signal To Noise Ratio ◽  
Waveform Inversion ◽  
Low Frequency ◽  
Full Waveform Inversion ◽  
Frequency Data ◽  
Signal To Noise ◽  
Frequency Signal ◽  
Full Waveform

Low-frequency data below 5 Hz are essential to the convergence of full-waveform inversion towards a useful solution. They help build the velocity model low wavenumbers and reduce the risk of cycle-skipping. In marine environments, low-frequency data are characterized by a low signal-to-noise ratio and can lead to erroneous models when inverted, especially if the noise contains coherent components. Often field data are high-pass filtered before any processing step, sacrificing weak but essential signal for full-waveform inversion. We propose to denoise the low-frequency data using prediction-error filters that we estimate from a high-frequency component with a high signal-to-noise ratio. The constructed filter captures the multi-dimensional spectrum of the high-frequency signal. We expand the filter's axes in the time-space domain to compress its spectrum towards the low frequencies and wavenumbers. The expanded filter becomes a predictor of the target low-frequency signal, and we incorporate it in a minimization scheme to attenuate noise. To account for data non-stationarity while retaining the simplicity of stationary filters, we divide the data into non-overlapping patches and linearly interpolate stationary filters at each data sample. We apply our method to synthetic stationary and non-stationary data, and we show it improves the full-waveform inversion results initialized at 2.5 Hz using the Marmousi model. We also demonstrate that the denoising attenuates non-stationary shear energy recorded by the vertical component of ocean-bottom nodes.

scholarly journals RESEARCH OF RELATION OF SAMPLERS FREQUENCY CHARACTERISTICS

2021 ◽  
Vol 13 (0) ◽  
pp. 1-5
Author(s):  
Tomaš Tankeliun
Keyword(s):  
High Frequency ◽  
Signal To Noise Ratio ◽  
Low Frequency ◽  
Vertical Channel ◽  
Discrete Elements ◽  
Sampling Device ◽  
High Frequency Signal ◽  
Analog To Digital ◽  
Amplitude Noise ◽  
Sampling Oscilloscope

The approach to reduce the amplitude noise of a vertical channel of the sampling oscilloscope is presented in this paper. In general, the vertical channel of the sampling oscilloscope consists of a high-frequency sampling circuit and a relatively low-frequency sample transmission path along with a high bit resolution analogto-digital converter. The paper presents a method to improve the sensitivity of the vertical channel of a stroboscopic oscilloscope by extending the conventional channel architecture. The main vertical channel unit of the oscilloscope is a sampling device (sampler), which made of discrete elements and usually implemented using high frequency diodes. The sampler performs a transformation of the sample of the high-frequency signal under test into a low-frequency equivalent signal (otherwise called a balance impulse). In a conventional sampling device, this pulse is quantized once the amplitude is at its highest, thus achieving the best signal-to-noise ratio. The paper analyzes the operating parameters of the sampling device circuit and their influence on the output signal of the sampler. In this approach uses the fastest (15 MHz) high-resolution (18-bit) analog-to-digital converters currently on the market to reduce the amplitude noise of vertical channel based on conventional architecture. Our research has shown that it is possible to obtain an increase in the signal-tonoise ratio of almost 1.3 times.

High-frequency analysis of seismic background noise as a function of wind speed and shallow depth

1996 ◽  
Vol 86 (5) ◽  
pp. 1507-1515 ◽  
Author(s):  
Mitchell M. Withers ◽  
Richard C. Aster ◽  
Christopher J. Young ◽  
Eric P. Chael
Keyword(s):  
Wind Speed ◽  
High Frequency ◽  
Background Noise ◽  
Signal To Noise Ratio ◽  
Shallow Depth ◽  
High Frequency Signal ◽  
Wind Speeds ◽  
Noise Characteristics ◽  
Cultural Noise ◽  
Seismic Background

Abstract We used a deep (1500 m) cased borehole near the town of Datil in west-central New Mexico to study high-frequency (>1 Hz) seismic noise characteristics. The remote site had very low levels of cultural noise, but strong winds (winter and spring) made the site an excellent candidate to study the effects of wind noise on seismograms. Along with a three-component set of surface sensors (Teledyne Geotech GS-13), a vertical borehole seismometer (GS-28) was deployed at a variety of depths (5, 43, and 85 m) to investigate signal and noise variations. Wind speed was measured with an anemometer. Event-triggered and time-triggered data streams were recorded on a RefTek 72-02 data acquisition system located at the site. Our data show little cultural noise and a strong correlation between wind speed and seismic background noise. The minimum wind speed at which the seismic background noise appears to be influenced varies with depth: 3 m/sec at the surface, 3.5 m/sec at 43 m in depth, and 4 m/sec at 85 m in depth. For wind speed below 3 to 4 m/sec, we observe omni-directional background noise that is coherent at frequencies below 15 Hz. This coherence is destroyed when wind speeds exceed 3 to 4 m/sec. We use a test event (Md ∼ 1.6) and superimposed noise to investigate signal-to-noise ratio (SNR) improvement with sensor depth. For the low Q valley fill of the Datil borehole (DBH) site, we have found that SNR can be improved by as much as 20 to 40 dB between 23 and 55 Hz and 10 to 20 dB between 10 and 20 Hz, by deploying at a 43-m depth rather than at the surface. At the surface, there is little signal above noise in the 23- to 55-Hz frequency band for wind speeds greater than 8 m/sec. Thus, high-frequency signal information that is lost at the surface can be recorded by deploying at the relatively shallow depth of 40 m. Because we observe only minor further reductions in seismic background noise (SBN) at deeper depths, 40 m is likely to be a reasonable deployment depth for other high-frequency-monitoring sites in similar environmental and geologic conditions.

scholarly journals Comparative Study of Image Reconstruction Based on Compressive Sensing

2018 ◽  
pp. 243-247
Author(s):  
Himani A. Shah ◽  
Mr. Dipak Agrawal ◽  
Mr. Nimit Modi ◽  
Dr. Sheshang Degadwala
Keyword(s):  
Image Reconstruction ◽  
Compressive Sensing ◽  
High Frequency ◽  
Signal To Noise Ratio ◽  
Low Frequency ◽  
Sparse Signal ◽  
Large Problem ◽  
Matrix Measure ◽  
Performance Guarantees ◽  
Frequency Components

Compressive sensing based image reconstruction that improves the algorithm to applying different approach which is DWT and DCT. First, by using wavelet transform, wavelet low frequency of the sub bands in which the image is decomposed in to low frequency and high frequency wavelet coefficients, second is to applied DCT on low frequency coordinates and construct the different transformation matrix. Use the measurement matrix measure the high frequency coefficient components and combine with DCT low frequency components image and sparse signal output is applied on compressive sensing. In compressive sensing, random measurement matrices are generally used and ?1minimisation algorithms often use linear programming to cover sparse signal vectors. But explicitly constructible measurement matrices providing performance guarantees were and ?1minimisation algorithms are often demanding in computational complexity for applications involving very large problem dimensions. To improve the PSNR (pick signal to noise ratio) of reconstructions image uses different coding such as Huffman and Arithmetic.

scholarly journals Scattering Attenuation of the Martian Interior through Coda-Wave Analysis

2021 ◽  
Author(s):  
Foivos Karakostas ◽  
Nicholas Schmerr ◽  
Ross Maguire ◽  
Quancheng Huang ◽  
Doyeon Kim ◽  
...  
Keyword(s):  
High Frequency ◽  
Low Frequency ◽  
Scattered Wave ◽  
Coda Wave ◽  
Very High Frequency ◽  
Scattering Layer ◽  
Scattering Attenuation ◽  
Trade Offs ◽  
Scattering Strength ◽  
Diffusive Layer

ABSTRACT We investigate the scattering attenuation characteristics of the Martian crust and uppermost mantle to understand the structure of the Martian interior. We examine the energy decay of the spectral envelopes for 21 high-quality Martian seismic events from sols 128 to 500 of InSight operations. We use the model of Dainty, Toksöz, et al. (1974) to approximate the behavior of energy envelopes resulting from scattered wave propagation through a single diffusive layer over an elastic half-space. Using a grid search, we mapped the layer parameters that fit the observed InSight data envelopes. The single diffusive layer model provided better fits to the observed energy envelopes for high-frequency (HF) and very-high-frequency (VF) than for the low-frequency and broadband events. This result is consistent with the suggested source depths (Giardini et al., 2020) for these families of events and their expected interaction with a shallow scattering layer. The shapes of the observed data envelopes do not show a consistent pattern with event distance, suggesting that the diffusivity and scattering layer thickness is nonuniform in the vicinity of InSight at Mars. Given the consistency in the envelope shapes between HF and VF events across epicentral distances and the trade-offs between the parameters that control scattering, the dimensions of the scattering layer remain unconstrained but require that scattering strength decreases with depth and that the rate of decay in scattering strength is the fastest near the surface. This is generally consistent with the processes that would form scattering structures in planetary lithospheres.

Variations in broadband seismic noise at IRIS/IDA stations in the USSR with implications for event detection

1990 ◽  
Vol 80 (6B) ◽  
pp. 2072-2088 ◽  
Author(s):  
Holly K. Given
Keyword(s):  
Noise Reduction ◽  
High Frequency ◽  
Signal To Noise Ratio ◽  
Low Frequency ◽  
Time Of Day ◽  
Signal Frequency ◽  
Seasonal Effect ◽  
Noise Levels ◽  
Power Spectral ◽  
Lower Noise

Abstract Ambient noise conditions at four IRIS/IDA sites in the USSR are characterized from 0.01 to 100 Hz as part of a study to ascertain the utility of broadband three-component seismic stations in monitoring regional Eurasian seismicity. Estimates of the power spectral density of noise levels were computed for a 5-day period in two seasons (winter and summer), at two times of the day. Of these periods, lower noise conditions were found at night in the summer. In general, at 1 Hz and above, noise levels and their variations correlate predictably with the soundness of vault construction and the proximity of the station to civilization. Absolute noise levels at the IRIS/IDA/USSR sites range from a high of about −120 dB to a low of −155 dB relative to (1 m/s2)2/Hz, between 1 and 5 Hz. A time-of-day variation in noise was observed at all sites, with noise levels during the work day ranging from 7 to 14 dB higher than night levels, depending on the site. This effect was observed only for frequencies above about 1 Hz. Observed seasonal variations (winter versus summer) are highly station dependent, although the seasonal effect is restricted to frequencies below 1 Hz and is in general centered on the microseism peak (0.1 to 0.2 Hz). Below 0.1 Hz, noise levels are influenced by the thermal and barometric isolation of the site. Low-frequency levels were not studied below 0.01 Hz. Minimum detectable magnitudes are estimated for the IRIS/IDA stations using the observed noise levels over 1 Hz. In general, a magnitude 3 event should be detectable at 1,000 km by all stations under night noise conditions if the dominant signal frequency is 1 Hz; the magnitude estimates increase with increasing frequency. These detectability estimates assume a conservative signal-to-noise ratio of 6. High-frequency data recorded by independent equipment co-located with the IRIS/IDA system during a 2-week experiment allow estimation of noise levels at the sites up to 100 Hz. Borehole versus surface noise levels recorded during the high-frequency experiment showed significant noise reduction (20 dB) can be achieved by borehole deployment at sites with exposed surface vaults. With well-isolated surface vaults, borehole noise reduction is about a factor of 2. Absolute noise levels between 1 to 10 Hz observed at IRIS/IDA/USSR sites are systematically higher than average NORESS noise by about 7 dB to 25 dB, depending on the station.

IMAGE FUSION METHOD BASED ON SHORT SUPPORT SYMMETRIC NON-SEPARABLE WAVELET

2004 ◽  
Vol 02 (01) ◽  
pp. 87-98 ◽  
Author(s):  
LIU BIN ◽  
JIAXIONG PENG
Keyword(s):  
Standard Deviation ◽  
Image Fusion ◽  
High Frequency ◽  
Signal To Noise Ratio ◽  
Low Frequency ◽  
Activity Measurement ◽  
Fusion Method ◽  
Fusion Algorithm ◽  
Dilation Matrix ◽  
Image Fusion Method

In this paper, image fusion method based on a new class of wavelet — non-separable wavelet with compactly supported, linear phase, orthogonal and dilation matrix [Formula: see text] is presented. We first construct a non-separable wavelet filter bank. Using these filters, the images involved are decomposed into wavelet pyramids. Then the following fusion algorithm was proposed: for low-frequency part, the average value is selected for new pixel value, For the three high-frequency parts of each level, the standard deviation of each image patch over 3×3 window in the high-frequency sub-images is computed as activity measurement. If the standard deviation of the area 3×3 window is bigger than the standard deviation of the corresponding 3×3 window in the other high-frequency sub-image. The center pixel values of the area window that the weighted area energy is bigger are selected. Otherwise the weighted value of the pixel is computed. Then a new fused image is reconstructed. The performance of the method is evaluated using the entropy, cross-entropy, fusion symmetry, root mean square error and peak-to-peak signal-to-noise ratio. The experiment results show that the non-separable wavelet fusion method proposed in this paper is very close to the performance of the Haar separable wavelet fusion method.

scholarly journals Shallow crustal imaging using distant, high-magnitude earthquakes

2019 ◽  
Vol 219 (2) ◽  
pp. 1082-1091 ◽  
Author(s):  
Johno van IJsseldijk ◽  
Elmer Ruigrok ◽  
Arie Verdel ◽  
Cornelis Weemstra
Keyword(s):  
High Frequency ◽  
Structural Information ◽  
Signal To Noise Ratio ◽  
Low Frequency ◽  
Seismic Interferometry ◽  
Sedimentary Structure ◽  
Frequency Signal ◽  
High Frequency Signal ◽  
Midcontinent Rift ◽  
High Magnitude

SUMMARY Global phases, viz. seismic phases that travel through the Earth’s core, can be used to locally image the crust by means of seismic interferometry. This method is known as Global Phase Seismic Interferometry (GloPSI). Traditionally, GloPSI retrieves low-frequency information (up to 1 Hz). Recent studies, however, suggest that there is high-frequency signal present in the coda of strong, distant earthquakes. This research quantifies the potential of these high-frequency signals, by analysing recordings of a multitude of high-magnitude earthquakes (≥6.4 Mw) and their coda on a selection of permanent USArray stations. Nearly half of the P, PKP and PKIKP phases are recorded with a signal-to-noise ratio of at least 5 dB at 3 Hz. To assess the viability of using the high-frequency signal, the second half of the paper highlights two case studies. First, a known sedimentary structure is imaged in Malargüe, Argentina. Secondly, the method is used to reveal the structure of the Midcontinent Rift below the SPREE array in Minnesota, USA. Both studies demonstrate that structural information of the shallow crust (≤5 km) below the arrays can be retrieved. In particular, the interpreted thickness of the sedimentary layer below the Malargüe array is in agreement with earlier studies in the same area. Being able to use global phases and direct P-phases with large epicentral distances (>80°) to recover the Earth’s sedimentary structure suggests that GloPSI can be applied in an industrial context.

Comparisons of downhole geophones and hydrophones

Geophysics ◽  
1992 ◽  
Vol 57 (6) ◽  
pp. 841-847 ◽  
Author(s):  
Christine E. Krohn ◽  
S. T. Chen
Keyword(s):  
High Frequency ◽  
Background Noise ◽  
Low Frequency ◽  
Measured Signal ◽  
Coherent Noise ◽  
Low Frequencies ◽  
Prototype Tool ◽  
The Difference ◽  
Borehole Seismic ◽  
Seismic Applications

Receiver tests were conducted to compare the responses of downhole geophones and hydrophones. Commercial receiver tools use a maximum of eight geophone levels; however, we use hydrophones because we can record 48 levels simultaneously. For frequencies above 300 Hz, signal‐to‐background‐noise ratios for hydrophones and geophones in a prototype tool were comparable. (This prototype tool is a lightweight, large‐clamping‐force device that can record higher frequencies than commercial geophone tools.) For frequencies below 300 Hz, signal‐to‐noise ratios were greater for the geophones than for the hydrophones. A commercial geophone tool had lower low‐frequency signal‐to‐background‐noise ratios than the prototype tool, but greater than those of the hydrophones. Further analysis was performed to determine why the signal‐to‐background‐noise ratios for geophones were greater than those for hydrophones at low frequencies. The measured signal level for a hydrophone was 2.4 times that for a geophone, compared with a theoretical prediction of 1.8. Thus, the signal levels do not explain the difference in signal‐to‐background‐noise ratios. The low‐frequency background noise was attributed to coherent noise in the form of tube waves, a noise type to which hydrophones are much more susceptible than are geophones. Thus, the low signal‐to‐background‐noise ratios at frequencies below 300 Hz for hydrophones resulted from ambient noise propagating as tube waves in the borehole. The high‐frequency background noise was attributed to random seismic noise in the environment and not to instrument noise. These results show that hydrophones, which do not need to be clamped to the borehole wall, are preferable to geophones for high‐frequency borehole seismic applications using first arrivals. Geophones are preferable to hydrophones for borehole seismic applications using reflector arrivals, because these later‐arriving events are obscured by source‐generated tube waves in hydrophone data. Development of a method to reduce both the source‐generated and ambient tube‐wave noise detected by hydrophones would result in high‐quality borehole seismic data at a greatly reduced cost.

Vibrational and Stochastic Resonance in FitzHugh-Nagumo Neural Model with Time-Delay and Colored Additive Noise

2011 ◽  
Vol 117-119 ◽  
pp. 685-689 ◽  
Author(s):  
Yu Rong Zhou ◽  
Zheng You He
Keyword(s):  
Stochastic Resonance ◽  
High Frequency ◽  
Adiabatic Approximation ◽  
Additive Noise ◽  
Signal To Noise Ratio ◽  
Low Frequency ◽  
Neural Model ◽  
Vibrational Resonance ◽  
Model Driven ◽  
Delayed Time

The vibrational resonance (VR) and stochastic resonance (SR) phenomena in time-delayed FitzHugh-Nagumo (FHN) neural model, driven by one high-frequency (HF) signal and one low-frequency (LF) signal, with coupled multiplicative and colored additive noise, is investigated. For the case that the frequency of the HF signal is much higher than that of the LF signal, under the adiabatic approximation condition, the expression of the signal-to-noise ratio (SNR) with respect to the LF signal is obtained. It is shown that, the SNR is a non-monotonous function of the amplitude and frequency of the HF signal. In addition, the SNR varies non-monotonically with increasing the intensities of the multiplicative and additive noise, with increasing the delayed-time as well as increasing the system parameters of the FHN model. The influence of the correlation time of the colored additive noise and the coupling strength between the multiplicative and additive noise on the SNR is discussed.

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