Broadband Background Noise Research Articles

On the spectral shape and a second component of broadband shock-cell noise

It is known that broadband shock-cell noise of an imperfectly expanded supersonic jet radiates primarily in the upstream direction. In addition to broadband shock-cell noise, fine scale turbulent mixing noise is also a dominant component in the upstream direction. As a result, broadband shock-cell noise, generally, appears as a small peak protruded above a broadband noise background. For this reason, the complete spectral shape of broadband shock-cell noise has not been found. The first objective of this investigation is to determine the full spectral shape of broadband shock-cell noise. In the course of carrying out this effort, unexpectedly, we found compelling evidence that there is a second component of broadband shock-cell noise. The two broadband shock-cell noise components are generated by two different sources and mechanisms. The quasi-periodic shock cells in the jet flow play a crucial role in their generation. All these findings are reported in this paper.

Background Noise Resistant Underwater Wireless Optical Communication Using Faraday Atomic Line Laser and Filter

High sensitive underwater wireless optical communication (UWOC) in shallow water or FSO-UWOC convergent applications suffers severely from solar noise and other background noise interference. This paper presents experimental demonstrations of broadband background noise resistant air-water and underwater wireless optical communication by using a pair of spectrum matched 852 nm Cs atomic Faraday line laser and filter, with a narrow passband of only 1 GHz. Experimental results show that by using the Faraday atomic line laser and filter, the Q factor can be improved by 3.37 dB compared to using the interference filter, and 14.67 dB compared to system without using noise resistant filter. A numerical model for UWOC system performance affected by broadband background noise with various filtering conditions is presented, where both the numerical and experimental results match each other quite well. Based on the experimental results substantiated model, performance of UWOC under solar noise interference is numerically studied. The numerical results show that under strong solar noise interference, the maximum depth of the receiver is extended from 0.77 m to 3.79 m for FSO-UWOC system and from 0.87 m to 3.54 m for UWOC system. It proves that FADOF can provide considerable performance improvement for both UWOC and FSO-UWOC system with broadband background noise interferences.

Search for dark-photon dark matter in the SuperMAG geomagnetic field dataset

In our recent companion paper [arXiv:2106.00022], we pointed out a novel signature of ultralight kinetically mixed dark-photon dark matter. This signature is a quasi-monochromatic, time-oscillating terrestrial magnetic field that takes a particular pattern over the surface of the Earth. In this work, we present a search for this signal in existing, unshielded magnetometer data recorded by geographically dispersed, geomagnetic stations. The dataset comes from the SuperMAG Collaboration and consists of measurements taken with one-minute cadence since 1970, with $\mathcal{O}(500)$ stations contributing in all. We aggregate the magnetic field measurements from all stations by projecting them onto a small set of global vector spherical harmonics (VSH) that capture the expected vectorial pattern of the signal at each station. Within each dark-photon coherence time, we use a data-driven technique to estimate the broadband background noise in the data, and search for excess narrowband power in this set of VSH components; we stack the searches in distinct coherence times incoherently. Following a Bayesian analysis approach that allows us to account for the stochastic nature of the dark-photon dark-matter field, we set exclusion bounds on the kinetic mixing parameter in the dark-photon dark-matter mass range $2\times10^{-18}\,\text{eV} \lesssim m_{A'} \lesssim 7\times10^{-17}\,\text{eV}$ (corresponding to frequencies $6\times 10^{-4}\,\text{Hz}\lesssim f_{A'} \lesssim 2\times 10^{-2}\,\text{Hz}$). These limits are complementary to various existing astrophysical constraints. Although our main analysis also identifies a number of candidate signals in the SuperMAG dataset, these appear to either fail or be in tension with various additional robustness checks we apply to those candidates. We report no robust and significant evidence for a dark-photon dark-matter signal in the SuperMAG dataset.

The First Derivative of the Electroencephalogram Facilitates Tracking of Electroencephalographic Alpha Band Activity During General Anesthesia.

Intraoperative neuromonitoring can help to navigate anesthesia. Pronounced alpha oscillations in the frontal electroencephalogram (EEG) appear to predict favorable perioperative neurocognitive outcomes and may also provide a measure of intraoperative antinociception. Monitoring the presence and strength of these alpha oscillations can be challenging, especially in elderly patients, because the EEG in these patients may be dominated by oscillations in other frequencies. Hence, the information regarding alpha oscillatory activity may be hidden and hard to visualize on a screen. Therefore, we developed an effective approach to improve the detection and presentation of alpha activity in the perioperative setting. We analyzed EEG records of 180 patients with a median age of 60 years (range, 18-90 years) undergoing noncardiac, nonneurologic surgery under general anesthesia with propofol induction and sevoflurane maintenance. We calculated the power spectral density (PSD) for the unprocessed EEG as well as for the time-discrete first derivative of the EEG (diffPSD) from 10-second epochs. Based on these data, we estimated the power-law coefficient κ of the PSD and diffPSD, as the EEG coarsely follows a 1/fκ distribution when displayed in double logarithmic coordinates. In addition, we calculated the alpha (7.8-12.1 Hz) to delta (0.4-4.3 Hz) ratio from the PSD as well as diffPSD. The median κ was 0.899 [first and third quartile: 0.786, 0.986] for the unaltered PSD, and κ = -0.092 [-0.202, -0.013] for the diffPSD, corresponding to an almost horizontal PSD of the differentiated EEG. The alpha-to-delta ratio of the diffPSD was strongly increased (median ratio = -8.0 dB [-10.5, -4.7 dB] for the unaltered PSD versus 30.1 dB [26.1, 33.8 dB] for the diffPSD). A strong narrowband oscillatory alpha power component (>20% of total alpha power) was detected in 23% using PSD, but in 96% of the diffPSD. We demonstrated that the calculation of the diffPSD from the time-discrete derivative of the intraoperative frontal EEG is a straightforward approach to improve the detection of alpha activity by eliminating the broadband background noise. This improvement in alpha peak detection and visualization could facilitate the guidance of general anesthesia and improve patient outcome.

Recent, Bioelectricity-Related Articles Selected by Ann M. Rajnicek, Media Editor of Bioelectricity.

Recent, Bioelectricity-Related Articles Selected by Ann M. Rajnicek, Media Editor of Bioelectricity.

Application of adaptive line enhancer based on NLMS algorithm in shaft-rate electric field signal detection

There is lots of useful signal feature in ship’s shaft-rate electric field. Extracting the signal feature is vital in underwater target recognition. In order to extract the feature of the shaft-rate electric field, the shaft-rate electric field is processed by ALE based on NLMS. The improved NLMS algorithm is proposed to construct an adaptive line-spectrum enhancer, and then the measured data of shaft-rate electric field is processed by ALE. The results show that the algorithm can effectively separate the weak shaft frequency electric field signal from the broadband background noise at low SNR. Compared with the ordinary ALE, the algorithm has more significant effect in improving SNR, faster convergence speed and smaller steady-state error, which greatly improves the detection ability of ship shaft frequency electric field.

Detection of Ship Shaft-rate Electromagnetic Field Signal Based on NLMS Algorithm

Ship shaft-rate electromagnetic field signal contains a lot of valuable target feature information, and effectively extracting its line spectrum components plays an extremely important role in underwater target recognition. In order to effectively separate the characteristic line spectrum of ship shaft-rate electromagnetic field from broadband background noise, this paper studies and analyzes the shaft-rate electric field by using the line spectrum enhancement algorithm based on adaptive filtering. Firstly, the application principle of adaptive line spectrum enhancement and NLMS algorithm in ship shaft-rate signal detection is briefly described. Then, an adaptive line spectrum enhancer is constructed according to the improved NLMS algorithm, and the obtained shaft-rate electric field data are processed and analyzed by this method. Finally, it is verified by simulation data and experimental data. The results show that the algorithm can effectively suppress the background noise, significantly improve the signal-to-noise ratio, and enhance the detection ability of ship electromagnetic field signals in practical applications.

Convergence to the tiniest detail: vocal sac structure in torrent-dwelling frogs

Abstract Cascades and fast-flowing streams impose severe restrictions on acoustic communication, with loud broadband background noise hampering signal detection and recognition. In this context, diverse behavioural features, such as ultrasound production and visual displays, have arisen in the evolutionary history of torrent-dwelling amphibians. The importance of the vocal sac in multimodal communication is being increasingly recognized, and recently a new vocal sac visual display has been discovered: unilateral inflation of paired vocal sacs. In the diurnal stream-breeding Hylodidae from the Atlantic forest, where it was first described, this behaviour is likely to be enabled by a unique anatomical configuration of the vocal sacs. To assess whether other taxa share this exceptional structure, we surveyed torrent-dwelling species with paired vocal sacs across the anuran tree of life and examined the vocal sac anatomy of exemplar species across 18 families. We found striking anatomical convergence among hylodids and species of the distantly related basal ranid genera Staurois, Huia, Meristogenys and Amolops. Ancestral character state reconstruction identified three new synapomorphies for Ranidae. Furthermore, we surveyed the vocal sac configuration of other anuran species that perform visual displays and report observations on what appears to be unilateral inflation of paired vocal sacs, in Staurois guttatus – an extremely rare behaviour in anurans.

Imaging enhancement based on stimulated Brillouin amplification in optical fiber.

The detection of weak optical signals embedded in strong background illumination has broad application prospects. We propose an imaging enhancement method based on stimulated Brillouin scattering (SBS) in a single-mode fiber, which is capable of amplifying the weak optical signal while neglecting the broadband background noise because of its narrow gain bandwidth. In experiment, a high gain of 60 dB was achieved. An imaging enhancement experiment was carried out, where a target which cannot be seen because of transmission loss could be clearly captured with the amplification of SBS in the fiber. Because of the employment of continuous pump rather than a pulsed pump, this system has wide application in the monitoring of non-cooperative targets.

Mode selective up-conversion detection for LIDAR applications.

We study mode selective up-conversion detection as a viable approach to improving signal-to-noise and ranging resolution in LIDAR applications. It involves pumping a nonlinear waveguide at the edge of phase matching with picosecond pulses, so that only the backscattered signal photons in a single or few desirable time-frequency modes are efficiently up-converted while the broadband background noise in all other modes is rejected. We demonstrate a 41-dB increase in the signal-to-noise ratio for single-photon counting compared to that of direct detection using a commercial InGaAs single-photon detector, while achieving sub-millimeter ranging resolution with few detected photons. The proposed technique implies new LIDAR capabilities for ranging and imaging.

Understanding the LIGO GW150914 event

We present a simplified method for the extraction of meaningful signals from Hanford and Livingston 32 second data for the GW150914 event made publicly available by the LIGO collaboration, and demonstrate its ability to reproduce the LIGO collaboration's own results quantitatively given the assumption that all narrow peaks in the power spectrum are a consequence of physically uninteresting signals and can be removed. After the clipping of these peaks and return to the time domain, the GW150914 event is readily distinguished from broadband background noise. This simple technique allows us to identify the GW150914 event without any assumption regarding its physical origin and with minimal assumptions regarding its shape. We also confirm that the LIGO GW150914 event is uniquely correlated in the Hanford and Livingston detectors for the full 4096 second data at the level of 6–7 σ with a temporal displacement of τ = 6.9 ± 0.4 ms. We have also identified a few events that are morphologically close to GW150914 but less strongly cross correlated with it.

Optimum Design of Broadband Passive Sonar

In this paper, a new design principle is proposed for the frontend-hardware (FEHW) chain of broadband passive sonars. This principle embraces the ultimate purpose of broadband passive sonars, which is to maximize the detection of passive targets. FEHW chains were conventionally designed as noise whiteners to guarantee the data bit dynamic range in analog-to-digital converters (ADCs) rather than being optimized for target detection. The conventional design was due to the restriction of electronic hardware in the early days and is still used in modern broadband passive sonars even with the great relaxation of hardware restriction today. The proposed principle optimizes the frequency response function (FRF) of FEHW chains by means of maximizing the output signal-to-noise ratio (SNR). The optimal FRF obtained using the design principle counts for the spectral characteristics of the entire sonar system (hydrophones, FEHW chain, and beamformer) as well as those of broadband passive sources and background noise. It turns out that maximizing the SNR is equivalent to maximizing the so-called deflection ratio (DR) in broadband passive sonars, but the former is directly used as a statistical test in the sonar engineering. The relationship between the optimal FRF and the Eckart filter is also discussed, with both of them counting for spectral shapes at their input, but with the former also counting for the change of spectral shapes after its output. Design examples are included to demonstrate the merit of the optimal FRF over the noise whitener with both theoretical and simulation results.

Lateralization of noise bursts in interaurally correlated or uncorrelated background noise using interaural level differences

The interaural level difference (ILD) of a lateralized target source may be effectively reduced when the target is presented together with background noise containing zero ILD. It is not certain whether listeners perceive a position congruent with the reduced ILD or the actual target ILD in a lateralization task. Two sets of behavioral experiments revealed that many listeners perceived a position at or even larger than that corresponding to the presented target ILD when a temporal onset/offset asynchrony between the broadband target and the broadband background noise was present. When no temporal asynchrony was present, however, the perceived lateral position indicated a dependency on the coherence of the background noise for several listeners. With interaurally correlated background noise, listeners reported a reduced ILD resulting from the combined target and background noise stimulus. In contrast, several of the listeners made a reasonable estimate of the position corresponding to the target ILD for interaurally uncorrelated, broadband, background noise. No obvious difference in performance was seen between low- or high-frequency stimuli. Extension of a weighting template to the output of a standard equalization-cancellation model was shown to remove a lateral bias on the predicted target ILD resulting from the presence of background noise. Provided that an appropriate weighting template is applied based on knowledge of the background noise coherence, good prediction of the behavioral data is possible.

Edit Detection in Speech Recordings via Instantaneous Electric Network Frequency Variations

In this paper, an edit detection method for forensic audio analysis is proposed. It develops and improves a previous method through changes in the signal processing chain and a novel detection criterion. As with the original method, electrical network frequency (ENF) analysis is central to the novel edit detector, for it allows monitoring anomalous variations of the ENF related to audio edit events. Working in unsupervised manner, the edit detector compares the extent of ENF variations, centered at its nominal frequency, with a variable threshold that defines the upper limit for normal variations observed in unedited signals. The ENF variations caused by edits in the signal are likely to exceed the threshold providing a mechanism for their detection. The proposed method is evaluated in both qualitative and quantitative terms via two distinct annotated databases. Results are reported for originally noisy database signals as well as versions of them further degraded under controlled conditions. A comparative performance evaluation, in terms of equal error rate (EER) detection, reveals that, for one of the tested databases, an improvement from 7% to 4% EER is achieved, respectively, from the original to the new edit detection method. When the signals are amplitude clipped or corrupted by broadband background noise, the performance figures of the novel method follow the same profile of those of the original method.

Listening Effort and Perceived Clarity for Normal-Hearing Children With the Use of Digital Noise Reduction

The goal of this study was to evaluate how digital noise reduction (DNR) impacts listening effort and judgment of sound clarity in children with normal hearing. It was hypothesized that when two DNR algorithms differing in signal-to-noise ratio (SNR) output are compared, the algorithm that provides the greatest improvement in overall output SNR will reduce listening effort and receive a better clarity rating from child listeners. A secondary goal was to evaluate the relation between the inversion method measurements and listening effort with DNR processing. Twenty-four children with normal hearing (ages 7 to 12 years) participated in a speech recognition task in which consonant-vowel-consonant nonwords were presented in broadband background noise. Test stimuli were recorded through two hearing aids with DNR off and DNR on at 0 dB and +5 dB input SNR. Stimuli were presented to listeners and verbal response time (VRT) and phoneme recognition scores were measured. The underlying assumption was that an increase in VRT reflects an increase in listening effort. Children rated the sound clarity for each condition. The two commercially available HAs were chosen based on: (1) an inversion technique, which was used to quantify the magnitude of change in SNR with the activation of DNR, and (2) a measure of magnitude-squared coherence, which was used to ensure that DNR in both devices preserved the spectrum. One device provided a greater improvement in overall output SNR than the other. Both DNR algorithms resulted in minimal spectral distortion as measured using coherence. For both devices, VRT decreased for the DNR-on condition, suggesting that listening effort decreased with DNR in both devices. Clarity ratings were also better in the DNR-on condition for both devices. The device showing the greatest improvement in output SNR with DNR engaged improved phoneme recognition scores. The magnitude of this improved phoneme recognition was not accurately predicted with measurements of output SNR. Measured output SNR varied in the ability to predict other outcomes. Overall, results suggest that DNR effectively reduces listening effort and improves subjective clarity ratings in children with normal hearing but that these improvements are not necessarily related to the output SNR improvements or preserved speech spectra provided by the DNR.

Improvement of intelligibility of ideal binary-masked noisy speech by adding background noise

When a target-speech/masker mixture is processed with the signal-separation technique, ideal binary mask (IBM), intelligibility of target speech is remarkably improved in both normal-hearing listeners and hearing-impaired listeners. Intelligibility of speech can also be improved by filling in speech gaps with un-modulated broadband noise. This study investigated whether intelligibility of target speech in the IBM-treated target-speech/masker mixture can be further improved by adding a broadband-noise background. The results of this study show that following the IBM manipulation, which remarkably released target speech from speech-spectrum noise, foreign-speech, or native-speech masking (experiment 1), adding a broadband-noise background with the signal-to-noise ratio no less than 4 dB significantly improved intelligibility of target speech when the masker was either noise (experiment 2) or speech (experiment 3). The results suggest that since adding the noise background shallows the areas of silence in the time-frequency domain of the IBM-treated target-speech/masker mixture, the abruption of transient changes in the mixture is smoothed and the perceived continuity of target-speech components becomes enhanced, leading to improved target-speech intelligibility. The findings are useful for advancing computational auditory scene analysis, hearing-aid/cochlear-implant designs, and understanding of speech perception under "cocktail-party" conditions.

Spatial distribution of spectral parameters of high latitude geomagnetic disturbances in the Pc5/Pi3 frequency range

Abstract. We analyze spectral parameters of the geomagnetic disturbances within the 1–4 mHz (Pc5/Pi3) frequency range for 29 observatories from polar to auroral latitudes. The main object of this study is the broadband (noise) background under quiet and moderately disturbed conditions. To obtain a quantitative description of background high-latitude long period ULF activity the log-log dependence of the spectral power on frequency is expanded over Legendre polynomials, and the coefficients of this expansion (spectral moments) are used to describe the most common features of these spectra. Not only the spectral power, but also the spectral slope and higher spectral moments, averaged over relatively long time intervals, demonstrate a systematic dependence on corrected geomagnetic (CGM) latitude, Φ, and magnetic local time, MLT. The 2-D distributions of the spectral moments in Φ-MLT coordinates are characterized by existence of structures, narrow in latitude and extended in MLT, which can be attributed to the projections of different magnetospheric domains. Spatio-temporal distributions of spectral power of elliptically (P-component) and randomly (N-component) polarized signal are similar, but not identical. The N-component contribution to the total signal becomes non-negligible in regions with a high local activity, such as the auroral oval and dayside polar cusp. The spectral slope indicates a larger relative contribution of higher frequencies upon the latitude decrease, probably, as a result of the resonant effects in the ULF noise. The higher spectral moments are also controlled mostly by CGM latitude and MLT and are fundamentally different for the polarized and non-polarized components. This study is a step towards the construction of an empirical model of the ULF wave power in Earth's magnetosphere.

Improving the Response of Accelerometers for Automotive Applications by Using LMS Adaptive Filters

In this paper, the least-mean-squares (LMS) algorithm was used to eliminate noise corrupting the important information coming from a piezoresisitive accelerometer for automotive applications. This kind of accelerometer is designed to be easily mounted in hard to reach places on vehicles under test, and they usually feature ranges from 50 to 2,000 g (where is the gravitational acceleration, 9.81 m/s2) and frequency responses to 3,000 Hz or higher, with DC response, durable cables, reliable performance and relatively low cost. However, here we show that the response of the sensor under test had a lot of noise and we carried out the signal processing stage by using both conventional and optimal adaptive filtering. Usually, designers have to build their specific analog and digital signal processing circuits, and this fact increases considerably the cost of the entire sensor system and the results are not always satisfactory, because the relevant signal is sometimes buried in a broad-band noise background where the unwanted information and the relevant signal sometimes share a very similar frequency band. Thus, in order to deal with this problem, here we used the LMS adaptive filtering algorithm and compare it with others based on the kind of filters that are typically used for automotive applications. The experimental results are satisfactory.

Emotional learning enhances stimulus-specific top-down modulation of sensorimotor gating in socially reared rats but not isolation-reared rats

Prepulse inhibition (PPI), the suppression of the startle reflex by a preceding sensory stimulus (prepulse), can be top-down modulated in both humans and rats. This study investigated whether emotional-learning-induced enhancement of PPI in rats is prepulse specific. The results show that in socially reared rats, PPI elicited by a narrowband-noise prepulse on the broadband-noise background (masker) was enhanced after the prepulse became fear conditioned. This fear-conditioning-modulated PPI was further enhanced by introducing a perceived spatial separation between the conditioned prepulse and the broadband-noise masker. However, these PPI enhancements disappeared if the conditioned prepulse was replaced by a different narrowband-noise prepulse that was not fear conditioned. In isolation-reared rats, who had both enhanced baseline startle and reduced PPI before conditioning, neither fear conditioning of the prepulse nor perceived spatial separation between the conditioned prepulse and noise masker could enhance PPI. Thus, the emotional-learning-induced enhancement of PPI in socially reared rats is prepulse specific, indicating that auditory processing interacts with mnemonic signaling in the formation of top-down modulation of PPI. Since the deficiency of attentional modulation of PPI in schizophrenic patients is correlated with the symptom severity, the deficiency of top-down modulations of PPI in isolation-reared rats is useful for modeling schizophrenia.

Sequentially Adapted Parallel Feedforward Active Noise Control of Noisy Sinusoidal Signals

A large class of acoustic noise sources has an underlying periodic process that generates a periodic noise component, and thus their acoustic noise can in general be modeled as the sum of a periodic signal and a randomly fluctuating signal (usually a broadband background noise). Active control of periodic noise (i.e., for a mixture of sinusoids) is more effective than that of random noise. For mixtures of sinusoids in a background broadband random noise, conventional FXLMS‐based single filter method does not reach the maximum achievable Noise Attenuation Level (NALmax ). In this paper, an alternative approach is taken and the idea of a parallel active noise control (ANC) architecture for cancelling mixtures of periodic and random signals is presented. The proposed ANC system separates the noise into periodic and random components and generates corresponding antinoises via separate noise cancelling filters, and tends to reach NALmax consistently. The derivation of NALmax is presented. Both the separation and noise cancellation are based on adaptive filtering. Experimental results verify the analytical development by showing superior performance of the proposed method, over the single‐filter approach, for several cases of sinusoids in white noise.