Reconstructing signals from noisy data with unknown signal and noise covariance.

PubMed

Oppermann, Niels; Robbers, Georg; Ensslin, Torsten A

2011-10-01

We derive a method to reconstruct Gaussian signals from linear measurements with Gaussian noise. This new algorithm is intended for applications in astrophysics and other sciences. The starting point of our considerations is the principle of minimum Gibbs free energy, which was previously used to derive a signal reconstruction algorithm handling uncertainties in the signal covariance. We extend this algorithm to simultaneously uncertain noise and signal covariances using the same principles in the derivation. The resulting equations are general enough to be applied in many different contexts. We demonstrate the performance of the algorithm by applying it to specific example situations and compare it to algorithms not allowing for uncertainties in the noise covariance. The results show that the method we suggest performs very well under a variety of circumstances and is indeed qualitatively superior to the other methods in cases where uncertainty in the noise covariance is present.

Biologically-based signal processing system applied to noise removal for signal extraction

DOEpatents

Fu, Chi Yung; Petrich, Loren I.

2004-07-13

The method and system described herein use a biologically-based signal processing system for noise removal for signal extraction. A wavelet transform may be used in conjunction with a neural network to imitate a biological system. The neural network may be trained using ideal data derived from physical principles or noiseless signals to determine to remove noise from the signal.

Incorporating signal-dependent noise for hyperspectral target detection

NASA Astrophysics Data System (ADS)

Morman, Christopher J.; Meola, Joseph

2015-05-01

The majority of hyperspectral target detection algorithms are developed from statistical data models employing stationary background statistics or white Gaussian noise models. Stationary background models are inaccurate as a result of two separate physical processes. First, varying background classes often exist in the imagery that possess different clutter statistics. Many algorithms can account for this variability through the use of subspaces or clustering techniques. The second physical process, which is often ignored, is a signal-dependent sensor noise term. For photon counting sensors that are often used in hyperspectral imaging systems, sensor noise increases as the measured signal level increases as a result of Poisson random processes. This work investigates the impact of this sensor noise on target detection performance. A linear noise model is developed describing sensor noise variance as a linear function of signal level. The linear noise model is then incorporated for detection of targets using data collected at Wright Patterson Air Force Base.

Identification and modification of dominant noise sources in diesel engines

NASA Astrophysics Data System (ADS)

Hayward, Michael D.

Determination of dominant noise sources in diesel engines is an integral step in the creation of quiet engines, but is a process which can involve an extensive series of expensive, time-consuming fired and motored tests. The goal of this research is to determine dominant noise source characteristics of a diesel engine in the near and far-fields with data from fewer tests than is currently required. Pre-conditioning and use of numerically robust methods to solve a set of cross-spectral density equations results in accurate calculation of the transfer paths between the near- and far-field measurement points. Application of singular value decomposition to an input cross-spectral matrix determines the spectral characteristics of a set of independent virtual sources, that, when scaled and added, result in the input cross spectral matrix. Each virtual source power spectral density is a singular value resulting from the decomposition performed over a range of frequencies. The complex relationship between virtual and physical sources is estimated through determination of virtual source contributions to each input measurement power spectral density. The method is made more user-friendly through use of a percentage contribution color plotting technique, where different normalizations can be used to help determine the presence of sources and the strengths of their contributions. Convolution of input measurements with the estimated path impulse responses results in a set of far-field components, to which the same singular value contribution plotting technique can be applied, thus allowing dominant noise source characteristics in the far-field to also be examined. Application of the methods presented results in determination of the spectral characteristics of dominant noise sources both in the near- and far-fields from one fired test, which significantly reduces the need for extensive fired and motored testing. Finally, it is shown that the far-field noise time history of a

Signal processing method and system for noise removal and signal extraction

DOEpatents

Fu, Chi Yung; Petrich, Loren

2009-04-14

A signal processing method and system combining smooth level wavelet pre-processing together with artificial neural networks all in the wavelet domain for signal denoising and extraction. Upon receiving a signal corrupted with noise, an n-level decomposition of the signal is performed using a discrete wavelet transform to produce a smooth component and a rough component for each decomposition level. The n.sup.th level smooth component is then inputted into a corresponding neural network pre-trained to filter out noise in that component by pattern recognition in the wavelet domain. Additional rough components, beginning at the highest level, may also be retained and inputted into corresponding neural networks pre-trained to filter out noise in those components also by pattern recognition in the wavelet domain. In any case, an inverse discrete wavelet transform is performed on the combined output from all the neural networks to recover a clean signal back in the time domain.

Signal-to-noise ratios in coherent soft limiters

NASA Technical Reports Server (NTRS)

Lesh, J. R.

1973-01-01

Expressions for the output signal-to-noise power ratio of a bandpass soft limiter followed by a coherent detection device are presented and discussed. It is found that a significant improvement in the output signal-to-noise ratio at low input SNRs can be achieved by such soft limiters as compared to hard limiters. This indicates that the soft limiter may be of some use in the area of threshold extension. Approximation methods for determining output signal-to-noise spectral densities are also presented.

Complementary aspects of spatial resolution and signal-to-noise ratio in computational imaging

NASA Astrophysics Data System (ADS)

Gureyev, T. E.; Paganin, D. M.; Kozlov, A.; Nesterets, Ya. I.; Quiney, H. M.

2018-05-01

A generic computational imaging setup is considered which assumes sequential illumination of a semitransparent object by an arbitrary set of structured coherent illumination patterns. For each incident illumination pattern, all transmitted light is collected by a photon-counting bucket (single-pixel) detector. The transmission coefficients measured in this way are then used to reconstruct the spatial distribution of the object's projected transmission. It is demonstrated that the square of the spatial resolution of such a setup is usually equal to the ratio of the image area to the number of linearly independent illumination patterns. If the noise in the measured transmission coefficients is dominated by photon shot noise, then the ratio of the square of the mean signal to the noise variance is proportional to the ratio of the mean number of registered photons to the number of illumination patterns. The signal-to-noise ratio in a reconstructed transmission distribution is always lower if the illumination patterns are nonorthogonal, because of spatial correlations in the measured data. Examples of imaging methods relevant to the presented analysis include conventional imaging with a pixelated detector, computational ghost imaging, compressive sensing, super-resolution imaging, and computed tomography.

a Universal De-Noising Algorithm for Ground-Based LIDAR Signal

NASA Astrophysics Data System (ADS)

Ma, Xin; Xiang, Chengzhi; Gong, Wei

2016-06-01

Ground-based lidar, working as an effective remote sensing tool, plays an irreplaceable role in the study of atmosphere, since it has the ability to provide the atmospheric vertical profile. However, the appearance of noise in a lidar signal is unavoidable, which leads to difficulties and complexities when searching for more information. Every de-noising method has its own characteristic but with a certain limitation, since the lidar signal will vary with the atmosphere changes. In this paper, a universal de-noising algorithm is proposed to enhance the SNR of a ground-based lidar signal, which is based on signal segmentation and reconstruction. The signal segmentation serving as the keystone of the algorithm, segments the lidar signal into three different parts, which are processed by different de-noising method according to their own characteristics. The signal reconstruction is a relatively simple procedure that is to splice the signal sections end to end. Finally, a series of simulation signal tests and real dual field-of-view lidar signal shows the feasibility of the universal de-noising algorithm.

Velocity interferometer signal de-noising using modified Wiener filter

NASA Astrophysics Data System (ADS)

Rav, Amit; Joshi, K. D.; Roy, Kallol; Kaushik, T. C.

2017-05-01

The accuracy and precision of the non-contact velocity interferometer system for any reflector (VISAR) depends not only on the good optical design and linear optical-to- electrical conversion system, but also on accurate and robust post-processing techniques. The performance of these techniques, such as the phase unwrapping algorithm, depends on the signal-to-noise ratio (SNR) of the recorded signal. In the present work, a novel method of improving the SNR of the recorded VISAR signal, based on the knowledge of the noise characteristic of the signal conversion and recording system, is presented. The proposed method uses a modified Wiener filter, for which the signal power spectrum estimation is obtained using a spectral subtraction method (SSM), and the noise power spectrum estimation is obtained by taking the average of the recorded signal during the period when no target movement is expected. Since the noise power spectrum estimate is dynamic in nature, and obtained for each experimental record individually, the improved signal quality is high. The proposed method is applied to the simulated standard signals, and is not only found to be better than the SSM, but is also less sensitive to the selection of the noise floor during signal power spectrum estimation. Finally, the proposed method is applied to the recorded experimental signal and an improvement in the SNR is reported.

Removing Background Noise with Phased Array Signal Processing

NASA Technical Reports Server (NTRS)

Podboy, Gary; Stephens, David

2015-01-01

Preliminary results are presented from a test conducted to determine how well microphone phased array processing software could pull an acoustic signal out of background noise. The array consisted of 24 microphones in an aerodynamic fairing designed to be mounted in-flow. The processing was conducted using Functional Beam forming software developed by Optinav combined with cross spectral matrix subtraction. The test was conducted in the free-jet of the Nozzle Acoustic Test Rig at NASA GRC. The background noise was produced by the interaction of the free-jet flow with the solid surfaces in the flow. The acoustic signals were produced by acoustic drivers. The results show that the phased array processing was able to pull the acoustic signal out of the background noise provided the signal was no more than 20 dB below the background noise level measured using a conventional single microphone equipped with an aerodynamic forebody.

Study on De-noising Technology of Radar Life Signal

NASA Astrophysics Data System (ADS)

Yang, Xiu-Fang; Wang, Lian-Huan; Ma, Jiang-Fei; Wang, Pei-Pei

2016-05-01

Radar detection is a kind of novel life detection technology, which can be applied to medical monitoring, anti-terrorism and disaster relief street fighting, etc. As the radar life signal is very weak, it is often submerged in the noise. Because of non-stationary and randomness of these clutter signals, it is necessary to denoise efficiently before extracting and separating the useful signal. This paper improves the radar life signal's theoretical model of the continuous wave, does de-noising processing by introducing lifting wavelet transform and determine the best threshold function through comparing the de-noising effects of different threshold functions. The result indicates that both SNR and MSE of the signal are better than the traditional ones by introducing lifting wave transform and using a new improved soft threshold function de-noising method..

Digital Construction and Characterization of Noise-like Spread Spectrum Signals

DTIC Science & Technology

2016-11-01

Digital Construction and Characterization of Noise -like Spread Spectrum Signals Donald C. Buzanowski II, Frederick J. Block, Thomas C. Royster MIT...Lincoln Laboratory Lexington, MA 02420 Abstract—A new method for generating digital noise -like spread spectrum signals is proposed. A standard binary...employing signals that are noise -like (e.g., [1]). Direct sequence spread spectrum (DSSS) signals provide benefits such as protection against jamming, low

Shot-noise dominant regime of a nanoparticle in a laser beam

NASA Astrophysics Data System (ADS)

Zhong, Changchun; Robicheaux, Francis

2017-04-01

The technique of laser levitation of nanoparticles has become increasingly promising in the study of cooling and controlling mesoscopic quantum systems. Unlike a mechanical system, the levitated nanoparticle is less exposed to thermalization and decoherence due to the absence of direct contact with a thermal environment. In ultrahigh vacuum, the dominant source of decoherence comes from the unavoidable photon recoil from the optical trap which sets an ultimate bound for the control of levitated systems. In this paper, we study the shot noise heating and the parametric feedback cooling of an optically trapped anisotropic nanoparticle in the laser shot noise dominant regime. The rotational trapping frequency and shot noise heating rate have a dependence on the shape of the trapped particle. For an ellipsoidal particle, the ratio of the axis lengths and the overall size controls the shot noise heating rate relative to the rotational frequency. For a near spherical nanoparticle, the effective heating rate for the rotational degrees of freedom is smaller than that for translation suggesting that the librational ground state may be easier to achieve than the vibrational ground state.

Empirical mode decomposition of the ECG signal for noise removal

NASA Astrophysics Data System (ADS)

Khan, Jesmin; Bhuiyan, Sharif; Murphy, Gregory; Alam, Mohammad

2011-04-01

Electrocardiography is a diagnostic procedure for the detection and diagnosis of heart abnormalities. The electrocardiogram (ECG) signal contains important information that is utilized by physicians for the diagnosis and analysis of heart diseases. So good quality ECG signal plays a vital role for the interpretation and identification of pathological, anatomical and physiological aspects of the whole cardiac muscle. However, the ECG signals are corrupted by noise which severely limit the utility of the recorded ECG signal for medical evaluation. The most common noise presents in the ECG signal is the high frequency noise caused by the forces acting on the electrodes. In this paper, we propose a new ECG denoising method based on the empirical mode decomposition (EMD). The proposed method is able to enhance the ECG signal upon removing the noise with minimum signal distortion. Simulation is done on the MIT-BIH database to verify the efficacy of the proposed algorithm. Experiments show that the presented method offers very good results to remove noise from the ECG signal.

Near-room-temperature Mid-infrared Photoconductor Signal and Noise Characterization

DTIC Science & Technology

2012-09-01

Near-room-temperature Mid-infrared Photoconductor Signal and Noise Characterization by Justin R. Bickford, Neal K. Bambha, and Wayne H. Chang...Adelphi, MD 20783-1197 ARL-TR-6169 September 2012 Near-room-temperature Mid-infrared Photoconductor Signal and Noise Characterization...temperature Mid-infrared Photoconductor Signal and Noise Characterization 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6

Phase noise mitigation of QPSK signal utilizing phase-locked multiplexing of signal harmonics and amplitude saturation.

PubMed

Mohajerin-Ariaei, Amirhossein; Ziyadi, Morteza; Chitgarha, Mohammad Reza; Almaiman, Ahmed; Cao, Yinwen; Shamee, Bishara; Yang, Jeng-Yuan; Akasaka, Youichi; Sekiya, Motoyoshi; Takasaka, Shigehiro; Sugizaki, Ryuichi; Touch, Joseph D; Tur, Moshe; Langrock, Carsten; Fejer, Martin M; Willner, Alan E

2015-07-15

We demonstrate an all-optical phase noise mitigation scheme based on the generation, delay, and coherent summation of higher order signal harmonics. The signal, its third-order harmonic, and their corresponding delayed variant conjugates create a staircase phase-transfer function that quantizes the phase of quadrature-phase-shift-keying (QPSK) signal to mitigate phase noise. The signal and the harmonics are automatically phase-locked multiplexed, avoiding the need for phase-based feedback loop and injection locking to maintain coherency. The residual phase noise converts to amplitude noise in the quantizer stage, which is suppressed by parametric amplification in the saturation regime. Phase noise reduction of ∼40% and OSNR-gain of ∼3  dB at BER 10(-3) are experimentally demonstrated for 20- and 30-Gbaud QPSK input signals.

Combining Absorption and Dispersion Signals to Improve Signal-to-noise for Rapid Scan EPR Imaging

PubMed Central

Tseitlin, Mark; Quine, Richard W.; Rinard, George A.; Eaton, Sandra S.; Eaton, Gareth R.

2010-01-01

Direct detection of the rapid scan EPR signal with quadrature detection and without automatic frequency control provides both the absorption and dispersion components of the signal. The use of a cross-loop resonator results in similar signal-to-noise in the two channels. The dispersion signal can be converted to an equivalent absorption signal by means of Kramers-Kronig relations. The converted signal is added to the directly-measured absorption signal. Since the noise in the two channels is not correlated, this procedure increases the signal-to-noise ratio of the resultant absorption signal by up to a factor of √2. The utility of this method was demonstrated for 2D spectral-spatial imaging of a phantom containing 3 tubes of LiPc with different oxygen concentrations and therefore different linewidths. PMID:20181505

Analytical estimation of laser phase noise induced BER floor in coherent receiver with digital signal processing.

PubMed

Vanin, Evgeny; Jacobsen, Gunnar

2010-03-01

The Bit-Error-Ratio (BER) floor caused by the laser phase noise in the optical fiber communication system with differential quadrature phase shift keying (DQPSK) and coherent detection followed by digital signal processing (DSP) is analytically evaluated. An in-phase and quadrature (I&Q) receiver with a carrier phase recovery using DSP is considered. The carrier phase recovery is based on a phase estimation of a finite sum (block) of the signal samples raised to the power of four and the phase unwrapping at transitions between blocks. It is demonstrated that errors generated at block transitions cause the dominating contribution to the system BER floor when the impact of the additive noise is negligibly small in comparison with the effect of the laser phase noise. Even the BER floor in the case when the phase unwrapping is omitted is analytically derived and applied to emphasize the crucial importance of this signal processing operation. The analytical results are verified by full Monte Carlo simulations. The BER for another type of DQPSK receiver operation, which is based on differential phase detection, is also obtained in the analytical form using the principle of conditional probability. The principle of conditional probability is justified in the case of differential phase detection due to statistical independency of the laser phase noise induced signal phase error and the additive noise contributions. Based on the achieved analytical results the laser linewidth tolerance is calculated for different system cases.

Robust stochastic resonance: Signal detection and adaptation in impulsive noise

NASA Astrophysics Data System (ADS)

Kosko, Bart; Mitaim, Sanya

2001-11-01

Stochastic resonance (SR) occurs when noise improves a system performance measure such as a spectral signal-to-noise ratio or a cross-correlation measure. All SR studies have assumed that the forcing noise has finite variance. Most have further assumed that the noise is Gaussian. We show that SR still occurs for the more general case of impulsive or infinite-variance noise. The SR effect fades as the noise grows more impulsive. We study this fading effect on the family of symmetric α-stable bell curves that includes the Gaussian bell curve as a special case. These bell curves have thicker tails as the parameter α falls from 2 (the Gaussian case) to 1 (the Cauchy case) to even lower values. Thicker tails create more frequent and more violent noise impulses. The main feedback and feedforward models in the SR literature show this fading SR effect for periodic forcing signals when we plot either the signal-to-noise ratio or a signal correlation measure against the dispersion of the α-stable noise. Linear regression shows that an exponential law γopt(α)=cAα describes this relation between the impulsive index α and the SR-optimal noise dispersion γopt. The results show that SR is robust against noise ``outliers.'' So SR may be more widespread in nature than previously believed. Such robustness also favors the use of SR in engineering systems. We further show that an adaptive system can learn the optimal noise dispersion for two standard SR models (the quartic bistable model and the FitzHugh-Nagumo neuron model) for the signal-to-noise ratio performance measure. This also favors practical applications of SR and suggests that evolution may have tuned the noise-sensitive parameters of biological systems.

Estimating the signal-to-noise ratio of AVIRIS data

NASA Technical Reports Server (NTRS)

Curran, Paul J.; Dungan, Jennifer L.

1988-01-01

To make the best use of narrowband airborne visible/infrared imaging spectrometer (AVIRIS) data, an investigator needs to know the ratio of signal to random variability or noise (signal-to-noise ratio or SNR). The signal is land cover dependent and varies with both wavelength and atmospheric absorption; random noise comprises sensor noise and intrapixel variability (i.e., variability within a pixel). The three existing methods for estimating the SNR are inadequate, since typical laboratory methods inflate while dark current and image methods deflate the SNR. A new procedure is proposed called the geostatistical method. It is based on the removal of periodic noise by notch filtering in the frequency domain and the isolation of sensor noise and intrapixel variability using the semi-variogram. This procedure was applied easily and successfully to five sets of AVIRIS data from the 1987 flying season and could be applied to remotely sensed data from broadband sensors.

[Detection of Weak Speech Signals from Strong Noise Background Based on Adaptive Stochastic Resonance].

PubMed

Lu, Huanhuan; Wang, Fuzhong; Zhang, Huichun

2016-04-01

Traditional speech detection methods regard the noise as a jamming signal to filter,but under the strong noise background,these methods lost part of the original speech signal while eliminating noise.Stochastic resonance can use noise energy to amplify the weak signal and suppress the noise.According to stochastic resonance theory,a new method based on adaptive stochastic resonance to extract weak speech signals is proposed.This method,combined with twice sampling,realizes the detection of weak speech signals from strong noise.The parameters of the systema,b are adjusted adaptively by evaluating the signal-to-noise ratio of the output signal,and then the weak speech signal is optimally detected.Experimental simulation analysis showed that under the background of strong noise,the output signal-to-noise ratio increased from the initial value-7dB to about 0.86 dB,with the gain of signalto-noise ratio is 7.86 dB.This method obviously raises the signal-to-noise ratio of the output speech signals,which gives a new idea to detect the weak speech signals in strong noise environment.

Novel Signal Noise Reduction Method through Cluster Analysis, Applied to Photoplethysmography.

PubMed

Waugh, William; Allen, John; Wightman, James; Sims, Andrew J; Beale, Thomas A W

2018-01-01

Physiological signals can often become contaminated by noise from a variety of origins. In this paper, an algorithm is described for the reduction of sporadic noise from a continuous periodic signal. The design can be used where a sample of a periodic signal is required, for example, when an average pulse is needed for pulse wave analysis and characterization. The algorithm is based on cluster analysis for selecting similar repetitions or pulses from a periodic single. This method selects individual pulses without noise, returns a clean pulse signal, and terminates when a sufficiently clean and representative signal is received. The algorithm is designed to be sufficiently compact to be implemented on a microcontroller embedded within a medical device. It has been validated through the removal of noise from an exemplar photoplethysmography (PPG) signal, showing increasing benefit as the noise contamination of the signal increases. The algorithm design is generalised to be applicable for a wide range of physiological (physical) signals.

Signal processing and electronic noise in LZ

NASA Astrophysics Data System (ADS)

Khaitan, D.

2016-03-01

The electronics of the LUX-ZEPLIN (LZ) experiment, the 10-tonne dark matter detector to be installed at the Sanford Underground Research Facility (SURF), consists of low-noise dual-gain amplifiers and a 100-MHz, 14-bit data acquisition system for the TPC PMTs. Pre-prototypes of the analog amplifiers and the 32-channel digitizers were tested extensively with simulated pulses that are similar to the prompt scintillation light and the electroluminescence signals expected in LZ. These studies are used to characterize the noise and to measure the linearity of the system. By increasing the amplitude of the test signals, the effect of saturating the amplifier and the digitizers was studied. The RMS ADC noise of the digitizer channels was measured to be 1.19± 0.01 ADCC. When a high-energy channel of the amplifier is connected to the digitizer, the measured noise remained virtually unchanged, while the noise added by a low-energy channel was estimated to be 0.38 ± 0.02 ADCC (46 ± 2 μV). A test facility is under construction to study saturation, mitigate noise and measure the performance of the LZ electronics and data acquisition chain.

Optical signal-to-noise ratio measurement by optical homodyne tomography.

PubMed

Martelli, P; Pietralunga, S M; Ranzani, L; Siano, R; Martinelli, M

2006-02-01

An all-fiber optical homodyne tomography setup is introduced that measures the optical signal-to-noise ratio through reconstruction of the photon statistics. The scheme described has been conceived for applications to optical communications. In particular, the signal-to-noise ratio has been evaluated at lambda= 1.55 microm as a function of the received power. From the experimental data, in the case of optically amplified signals, the amplifier noise figure can be estimated.

Noise-aware dictionary-learning-based sparse representation framework for detection and removal of single and combined noises from ECG signal

PubMed Central

Ramkumar, Barathram; Sabarimalai Manikandan, M.

2017-01-01

Automatic electrocardiogram (ECG) signal enhancement has become a crucial pre-processing step in most ECG signal analysis applications. In this Letter, the authors propose an automated noise-aware dictionary learning-based generalised ECG signal enhancement framework which can automatically learn the dictionaries based on the ECG noise type for effective representation of ECG signal and noises, and can reduce the computational load of sparse representation-based ECG enhancement system. The proposed framework consists of noise detection and identification, noise-aware dictionary learning, sparse signal decomposition and reconstruction. The noise detection and identification is performed based on the moving average filter, first-order difference, and temporal features such as number of turning points, maximum absolute amplitude, zerocrossings, and autocorrelation features. The representation dictionary is learned based on the type of noise identified in the previous stage. The proposed framework is evaluated using noise-free and noisy ECG signals. Results demonstrate that the proposed method can significantly reduce computational load as compared with conventional dictionary learning-based ECG denoising approaches. Further, comparative results show that the method outperforms existing methods in automatically removing noises such as baseline wanders, power-line interference, muscle artefacts and their combinations without distorting the morphological content of local waves of ECG signal. PMID:28529758

Noise-aware dictionary-learning-based sparse representation framework for detection and removal of single and combined noises from ECG signal.

PubMed

Satija, Udit; Ramkumar, Barathram; Sabarimalai Manikandan, M

2017-02-01

Automatic electrocardiogram (ECG) signal enhancement has become a crucial pre-processing step in most ECG signal analysis applications. In this Letter, the authors propose an automated noise-aware dictionary learning-based generalised ECG signal enhancement framework which can automatically learn the dictionaries based on the ECG noise type for effective representation of ECG signal and noises, and can reduce the computational load of sparse representation-based ECG enhancement system. The proposed framework consists of noise detection and identification, noise-aware dictionary learning, sparse signal decomposition and reconstruction. The noise detection and identification is performed based on the moving average filter, first-order difference, and temporal features such as number of turning points, maximum absolute amplitude, zerocrossings, and autocorrelation features. The representation dictionary is learned based on the type of noise identified in the previous stage. The proposed framework is evaluated using noise-free and noisy ECG signals. Results demonstrate that the proposed method can significantly reduce computational load as compared with conventional dictionary learning-based ECG denoising approaches. Further, comparative results show that the method outperforms existing methods in automatically removing noises such as baseline wanders, power-line interference, muscle artefacts and their combinations without distorting the morphological content of local waves of ECG signal.

Maximum likelihood estimation of signal-to-noise ratio and combiner weight

NASA Technical Reports Server (NTRS)

Kalson, S.; Dolinar, S. J.

1986-01-01

An algorithm for estimating signal to noise ratio and combiner weight parameters for a discrete time series is presented. The algorithm is based upon the joint maximum likelihood estimate of the signal and noise power. The discrete-time series are the sufficient statistics obtained after matched filtering of a biphase modulated signal in additive white Gaussian noise, before maximum likelihood decoding is performed.

Image restoration by Wiener filtering in the presence of signal-dependent noise.

PubMed

Kondo, K; Ichioka, Y; Suzuki, T

1977-09-01

An optimum filter to restore the degraded image due to blurring and the signal-dependent noise is obtained on the basis of the theory of Wiener filtering. Computer simulations of image restoration using signal-dependent noise models are carried out. It becomes clear that the optimum filter, which makes use of a priori information on the signal-dependent nature of the noise and the spectral density of the signal and the noise showing significant spatial correlation, is potentially advantageous.

Coil-to-coil physiological noise correlations and their impact on functional MRI time-series signal-to-noise ratio.

PubMed

Triantafyllou, Christina; Polimeni, Jonathan R; Keil, Boris; Wald, Lawrence L

2016-12-01

Physiological nuisance fluctuations ("physiological noise") are a major contribution to the time-series signal-to-noise ratio (tSNR) of functional imaging. While thermal noise correlations between array coil elements have a well-characterized effect on the image Signal to Noise Ratio (SNR 0 ), the element-to-element covariance matrix of the time-series fluctuations has not yet been analyzed. We examine this effect with a goal of ultimately improving the combination of multichannel array data. We extend the theoretical relationship between tSNR and SNR 0 to include a time-series noise covariance matrix Ψ t , distinct from the thermal noise covariance matrix Ψ 0 , and compare its structure to Ψ 0 and the signal coupling matrix SS H formed from the signal intensity vectors S. Inclusion of the measured time-series noise covariance matrix into the model relating tSNR and SNR 0 improves the fit of experimental multichannel data and is shown to be distinct from Ψ 0 or SS H . Time-series noise covariances in array coils are found to differ from Ψ 0 and more surprisingly, from the signal coupling matrix SS H . Correct characterization of the time-series noise has implications for the analysis of time-series data and for improving the coil element combination process. Magn Reson Med 76:1708-1719, 2016. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Comparison of methods for removing electromagnetic noise from electromyographic signals.

PubMed

Defreitas, Jason M; Beck, Travis W; Stock, Matt S

2012-02-01

The purpose of this investigation was to compare three different methods of removing noise from monopolar electromyographic (EMG) signals: (a) electrical shielding with a Faraday cage, (b) denoising with a digital notch-filter and (c) applying a bipolar differentiation with another monopolar EMG signal. Ten men and ten women (mean age = 24.0 years) performed isometric muscle actions of the leg extensors at 10-100% of their maximal voluntary contraction on two separate occasions. One trial was performed inside a Faraday tent (a flexible Faraday cage made from conductive material), and the other was performed outside the Faraday tent. The EMG signals collected outside the Faraday tent were analyzed three separate ways: as a raw signal, as a bipolar signal, and as a signal digitally notch filtered to remove 60 Hz noise and its harmonics. The signal-to-noise ratios were greatest after notch-filtering (range: 3.0-33.8), and lowest for the bipolar arrangement (1.6-10.2). Linear slope coefficients for the EMG amplitude versus force relationship were also used to compare the methods of noise removal. The results showed that a bipolar arrangement had a significantly lower linear slope coefficient when compared to the three other conditions (raw, notch and tent). These results suggested that an appropriately filtered monopolar EMG signal can be useful in situations that require a large pick-up area. Furthermore, although it is helpful, a Faraday tent (or cage) is not required to achieve an appropriate signal-to-noise ratio, as long as the correct filters are applied.

Signal-Induced Noise Effects in a Photon Counting System for Stratospheric Ozone Measurement

NASA Technical Reports Server (NTRS)

Harper, David B.; DeYoung, Russell J.

1998-01-01

A significant source of error in making atmospheric differential absorption lidar ozone measurements is the saturation of the photomultiplier tube by the strong, near field light return. Some time after the near field light signal is gone, the photomultiplier tube gate is opened and a noise signal, called signal-induced noise, is observed. Research reported here gives experimental results from measurement of photomultiplier signal-induced noise. Results show that signal-induced noise has several decaying exponential signals, suggesting that electrons are slowly emitted from different surfaces internal to the photomultiplier tube.

Seismic signal and noise on Europa

NASA Astrophysics Data System (ADS)

Panning, Mark; Stähler, Simon; Bills, Bruce; Castillo Castellanos, Jorge; Huang, Hsin-Hua; Husker, Allen; Kedar, Sharon; Lorenz, Ralph; Pike, William T.; Schmerr, Nicholas; Tsai, Victor; Vance, Steven

2017-10-01

Seismology is one of our best tools for detailing interior structure of planetary bodies, and a seismometer is included in the baseline and threshold mission design for the upcoming Europa Lander mission. Guiding mission design and planning for adequate science return, though, requires modeling of both the anticipated signal and noise. Assuming ice seismicity on Europa behaves according to statistical properties observed in Earth catalogs and scaling cumulative seismic moment release to the moon, we can simulate long seismic records and estimate background noise and peak signal amplitudes (Panning et al., 2017). This suggests a sensitive instrument comparable to many broadband terrestrial instruments or the SP instrument from the InSight mission to Mars will be able to record signals, while high frequency geophones are likely inadequate. We extend this analysis to also begin incorporation of spatial and temporal variation due to the tidal cycle, which can help inform landing site selection. We also begin exploration of how chaotic terrane at the bottom of the ice shell and inter-ice heterogeneities (i.e. internal melt structures) may affect anticipated seismic observations using 2D numerical seismic simulations.M. P. Panning, S. C. Stähler, H.-H. Huang, S. D. Vance, S. Kedar, V. C. Tsai, W. T. Pike, R. D. Lorenz, “Expected seismicity and the seismic noise environment of Europa,” J. Geophys. Res., in revision, 2017.

Lidar signal-to-noise ratio improvements: Considerations and techniques

NASA Astrophysics Data System (ADS)

Hassebo, Yasser Y.

The primary objective of this study is to improve lidar signal-to-noise ratio (SNR) and hence extend attainable lidar ranges through reduction of the sky background noise (BGP), which dominates other sources of noise in daytime operations. This is particularly important for Raman lidar techniques where the Raman backscattered signal of interest is relatively weak compared with the elastic backscatter lidars. Two approaches for reduction of sky background noise are considered: (1) Improvements in lidar SNR by optimization of the design of the lidar receiver were examined by a series of simulations. This part of the research concentrated on biaxial lidar systems, where overlap between laser beam and receiver field of view (FOV) is an important aspect of noise considerations. The first optimized design evolved is a wedge shaped aperture. While this design has the virtue of greatly reducing background light, it is difficult to implement practically, requiring both changes in area and position with lidar range. A second more practical approach, which preserves some of the advantages of the wedge design, was also evolved. This uses a smaller area circular aperture optimally located in the image plane for desired ranges. Simulated numerical results for a biaxial lidar have shown that the best receiver parameters selection is one using a small circular aperture (field stop) with a small telescope focal length f, to ensure the minimum FOV that accepts all return signals over the entire lidar range while at the same time minimizing detected BGP and hence maximizing lidar SNR and attainable lidar ranges. The improvement in lidar SNR was up to 18%. (2) A polarization selection technique was implemented to reduce sky background signal for linearly polarized monostatic elastic backscatter lidar measurements. The technique takes advantage of naturally occurring polarization properties in scattered sky light, and then ensures that both the lidar transmitter and receiver track and

Elevated cAMP improves signal-to-noise ratio in amphibian rod photoreceptors

PubMed Central

Govardovskii, Victor I.

2017-01-01

The absolute sensitivity of vertebrate retinas is set by a background noise, called dark noise, which originates from several different cell types and is generated by different molecular mechanisms. The major share of dark noise is produced by photoreceptors and consists of two components, discrete and continuous. Discrete noise is generated by spontaneous thermal activations of visual pigment. These events are undistinguishable from real single-photon responses (SPRs) and might be considered an equivalent of the signal. Continuous noise is produced by spontaneous fluctuations of the catalytic activity of the cGMP phosphodiesterase. This masks both SPR and spontaneous SPR-like responses. Circadian rhythms affect photoreceptors, among other systems by periodically increasing intracellular cAMP levels ([cAMP]in), which increases the size and changes the shape of SPRs. Here, we show that forskolin, a tool that increases [cAMP]in, affects the magnitude and frequency spectrum of the continuous and discrete components of dark noise in photoreceptors. By changing both components of rod signaling, the signal and the noise, cAMP is able to increase the photoreceptor signal-to-noise ratio by twofold. We propose that this results in a substantial improvement of signal detection, without compromising noise rejection, at the rod bipolar cell synapse. PMID:28611079

Eddy-covariance data with low signal-to-noise ratio: time-lag determination, uncertainties and limit of detection

NASA Astrophysics Data System (ADS)

Langford, B.; Acton, W.; Ammann, C.; Valach, A.; Nemitz, E.

2015-10-01

All eddy-covariance flux measurements are associated with random uncertainties which are a combination of sampling error due to natural variability in turbulence and sensor noise. The former is the principal error for systems where the signal-to-noise ratio of the analyser is high, as is usually the case when measuring fluxes of heat, CO2 or H2O. Where signal is limited, which is often the case for measurements of other trace gases and aerosols, instrument uncertainties dominate. Here, we are applying a consistent approach based on auto- and cross-covariance functions to quantify the total random flux error and the random error due to instrument noise separately. As with previous approaches, the random error quantification assumes that the time lag between wind and concentration measurement is known. However, if combined with commonly used automated methods that identify the individual time lag by looking for the maximum in the cross-covariance function of the two entities, analyser noise additionally leads to a systematic bias in the fluxes. Combining data sets from several analysers and using simulations, we show that the method of time-lag determination becomes increasingly important as the magnitude of the instrument error approaches that of the sampling error. The flux bias can be particularly significant for disjunct data, whereas using a prescribed time lag eliminates these effects (provided the time lag does not fluctuate unduly over time). We also demonstrate that when sampling at higher elevations, where low frequency turbulence dominates and covariance peaks are broader, both the probability and magnitude of bias are magnified. We show that the statistical significance of noisy flux data can be increased (limit of detection can be decreased) by appropriate averaging of individual fluxes, but only if systematic biases are avoided by using a prescribed time lag. Finally, we make recommendations for the analysis and reporting of data with low signal-to-noise

Eddy-covariance data with low signal-to-noise ratio: time-lag determination, uncertainties and limit of detection

NASA Astrophysics Data System (ADS)

Langford, B.; Acton, W.; Ammann, C.; Valach, A.; Nemitz, E.

2015-03-01

All eddy-covariance flux measurements are associated with random uncertainties which are a combination of sampling error due to natural variability in turbulence and sensor noise. The former is the principal error for systems where the signal-to-noise ratio of the analyser is high, as is usually the case when measuring fluxes of heat, CO2 or H2O. Where signal is limited, which is often the case for measurements of other trace gases and aerosols, instrument uncertainties dominate. We are here applying a consistent approach based on auto- and cross-covariance functions to quantifying the total random flux error and the random error due to instrument noise separately. As with previous approaches, the random error quantification assumes that the time-lag between wind and concentration measurement is known. However, if combined with commonly used automated methods that identify the individual time-lag by looking for the maximum in the cross-covariance function of the two entities, analyser noise additionally leads to a systematic bias in the fluxes. Combining datasets from several analysers and using simulations we show that the method of time-lag determination becomes increasingly important as the magnitude of the instrument error approaches that of the sampling error. The flux bias can be particularly significant for disjunct data, whereas using a prescribed time-lag eliminates these effects (provided the time-lag does not fluctuate unduly over time). We also demonstrate that when sampling at higher elevations, where low frequency turbulence dominates and covariance peaks are broader, both the probability and magnitude of bias are magnified. We show that the statistical significance of noisy flux data can be increased (limit of detection can be decreased) by appropriate averaging of individual fluxes, but only if systematic biases are avoided by using a prescribed time-lag. Finally, we make recommendations for the analysis and reporting of data with low signal-to-noise

Downhole microseismic signal-to-noise ratio enhancement via strip matching shearlet transform

NASA Astrophysics Data System (ADS)

Li, Juan; Ji, Shuo; Li, Yue; Qian, Zhihong; Lu, Weili

2018-04-01

Shearlet transform has been proved effective in noise attenuation. However, because of the low magnitude and high frequency of downhole microseismic signals, the coefficient values of valid signals and noise are similar in the shearlet domain. As a result, it is hard to suppress the noise. In this paper, we present a novel signal-to-noise ratio enhancement scheme called strip matching shearlet transform. The method takes into account the directivity of microseismic events and shearlets. Through strip matching, the matching degree in direction between them has been promoted. Then the coefficient values of valid signals are much larger than those of the noise. Consequently, we can separate them well with the help of thresholding. The experimental results on both synthetic records and field data illustrate that our proposed method preserves the useful components and attenuates the noise well.

A New Method for Reduction of Photomultiplier Signal-Induced Noise

NASA Technical Reports Server (NTRS)

Koble, Andrea; DeYoung, Russell

2000-01-01

For lidar measurements of ozone, photomultiplier tube (PMT) detector signal-induced noise represents a fundamental problem that complicates the extraction of information from lidar data. A new method is developed to significantly reduce signal-induced noise in lidar receiver PMT detectors. The electron optics of the lidar photomultiplier detector is modified to filter the source of signal-induced noise. A mesh electrode external to the PMT is utilized to control photoemission and disorient electron trajectories from the photocathode to the first dynode. Experiments were taken both with simulated and actual lidar return signals at Langley Research Center. Results show at least 40 percent more accurate ozone number density values with a mesh voltage of 60 V applied than with no voltage applied.

Noise in Neural Networks: Thresholds, Hysteresis, and Neuromodulation of Signal-To-Noise

NASA Astrophysics Data System (ADS)

Keeler, James D.; Pichler, Elgar E.; Ross, John

1989-03-01

We study a neural-network model including Gaussian noise, higher-order neuronal interactions, and neuromodulation. For a first-order network, there is a threshold in the noise level (phase transition) above which the network displays only disorganized behavior and critical slowing down near the noise threshold. The network can tolerate more noise if it has higher-order feedback interactions, which also lead to hysteresis and multistability in the network dynamics. The signal-to-noise ratio can be adjusted in a biological neural network by neuromodulators such as norepinephrine. Comparisons are made to experimental results and further investigations are suggested to test the effects of hysteresis and neuromodulation in pattern recognition and learning. We propose that norepinephrine may ``quench'' the neural patterns of activity to enhance the ability to learn details.

3-dB signal-ASE beat noise reduction of coherent multi-carrier signal utilizing phase sensitive amplification.

PubMed

Umeki, Takeshi; Takara, Hidehiko; Miyamoto, Yutaka; Asobe, Masaki

2012-10-22

We demonstrated the simultaneous amplification of a coherent multi-carrier signal using a χ(2)-based non-degenerate phase sensitive amplifier (PSA). The signal-to-noise ratio (SNR), which is degraded by the additional amplified spontaneous emission (ASE) noise, can be recovered due to the gain difference between a phase-correlated signal-idler pair and uncorrelated excess noise. Utilizing the second harmonic pumping of a χ(2)-based PSA enables us to observe the SNR recovery directly by comparing the SNR for the input with that for the PSA output. A 3-dB optical-SNR (OSNR) improvement was obtained as a result of the gain difference. We also achieved a 3-dB SNR improvement in the electric domain by reducing the signal-ASE beat noise. The receiver sensitivity for a 10 Gbit/s phase shift keying signal was clearly improved with the PSA.

Analysis of signals under compositional noise with applications to SONAR data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tucker, J. Derek; Wu, Wei; Srivastava, Anuj

2013-07-09

In this paper, we consider the problem of denoising and classification of SONAR signals observed under compositional noise, i.e., they have been warped randomly along the x-axis. The traditional techniques do not account for such noise and, consequently, cannot provide a robust classification of signals. We apply a recent framework that: 1) uses a distance-based objective function for data alignment and noise reduction; and 2) leads to warping-invariant distances between signals for robust clustering and classification. We use this framework to introduce two distances that can be used for signal classification: a) a y-distance, which is the distance between themore » aligned signals; and b) an x-distance that measures the amount of warping needed to align the signals. We focus on the task of clustering and classifying objects, using acoustic spectrum (acoustic color), which is complicated by the uncertainties in aspect angles at data collections. Small changes in the aspect angles corrupt signals in a way that amounts to compositional noise. As a result, we demonstrate the use of the developed metrics in classification of acoustic color data and highlight improvements in signal classification over current methods.« less

Optical Correlation of Images With Signal-Dependent Noise Using Constrained-Modulation Filter Devices

NASA Technical Reports Server (NTRS)

Downie, John D.

1995-01-01

Images with signal-dependent noise present challenges beyond those of images with additive white or colored signal-independent noise in terms of designing the optimal 4-f correlation filter that maximizes correlation-peak signal-to-noise ratio, or combinations of correlation-peak metrics. Determining the proper design becomes more difficult when the filter is to be implemented on a constrained-modulation spatial light modulator device. The design issues involved for updatable optical filters for images with signal-dependent film-grain noise and speckle noise are examined. It is shown that although design of the optimal linear filter in the Fourier domain is impossible for images with signal-dependent noise, proper nonlinear preprocessing of the images allows the application of previously developed design rules for optimal filters to be implemented on constrained-modulation devices. Thus the nonlinear preprocessing becomes necessary for correlation in optical systems with current spatial light modulator technology. These results are illustrated with computer simulations of images with signal-dependent noise correlated with binary-phase-only filters and ternary-phase-amplitude filters.

Powerline noise elimination in biomedical signals via blind source separation and wavelet analysis.

PubMed

Akwei-Sekyere, Samuel

2015-01-01

The distortion of biomedical signals by powerline noise from recording biomedical devices has the potential to reduce the quality and convolute the interpretations of the data. Usually, powerline noise in biomedical recordings are extinguished via band-stop filters. However, due to the instability of biomedical signals, the distribution of signals filtered out may not be centered at 50/60 Hz. As a result, self-correction methods are needed to optimize the performance of these filters. Since powerline noise is additive in nature, it is intuitive to model powerline noise in a raw recording and subtract it from the raw data in order to obtain a relatively clean signal. This paper proposes a method that utilizes this approach by decomposing the recorded signal and extracting powerline noise via blind source separation and wavelet analysis. The performance of this algorithm was compared with that of a 4th order band-stop Butterworth filter, empirical mode decomposition, independent component analysis and, a combination of empirical mode decomposition with independent component analysis. The proposed method was able to expel sinusoidal signals within powerline noise frequency range with higher fidelity in comparison with the mentioned techniques, especially at low signal-to-noise ratio.

Separating Decision and Encoding Noise in Signal Detection Tasks

PubMed Central

Cabrera, Carlos Alexander; Lu, Zhong-Lin; Dosher, Barbara Anne

2015-01-01

In this paper we develop an extension to the Signal Detection Theory (SDT) framework to separately estimate internal noise arising from representational and decision processes. Our approach constrains SDT models with decision noise by combining a multi-pass external noise paradigm with confidence rating responses. In a simulation study we present evidence that representation and decision noise can be separately estimated over a range of representative underlying representational and decision noise level configurations. These results also hold across a number of decision rules and show resilience to rule miss-specification. The new theoretical framework is applied to a visual detection confidence-rating task with three and five response categories. This study compliments and extends the recent efforts of researchers (Benjamin, Diaz, & Wee, 2009; Mueller & Weidemann, 2008; Rosner & Kochanski, 2009, Kellen, Klauer, & Singmann, 2012) to separate and quantify underlying sources of response variability in signal detection tasks. PMID:26120907

Improved wavelet de-noising method of rail vibration signal for wheel tread detection

NASA Astrophysics Data System (ADS)

Zhao, Quan-ke; Zhao, Quanke; Gao, Xiao-rong; Luo, Lin

2011-12-01

The irregularities of wheel tread can be detected by processing acceleration vibration signal of railway. Various kinds of noise from different sources such as wheel-rail resonance, bad weather and artificial reasons are the key factors influencing detection accuracy. A method which uses wavelet threshold de-noising is investigated to reduce noise in the detection signal, and an improved signal processing algorithm based on it has been established. The results of simulations and field experiments show that the proposed method can increase signal-to-noise ratio (SNR) of the rail vibration signal effectively, and improve the detection accuracy.

Noise Reduction Effect of Multiple-Sampling-Based Signal-Readout Circuits for Ultra-Low Noise CMOS Image Sensors

PubMed Central

Kawahito, Shoji; Seo, Min-Woong

2016-01-01

This paper discusses the noise reduction effect of multiple-sampling-based signal readout circuits for implementing ultra-low-noise image sensors. The correlated multiple sampling (CMS) technique has recently become an important technology for high-gain column readout circuits in low-noise CMOS image sensors (CISs). This paper reveals how the column CMS circuits, together with a pixel having a high-conversion-gain charge detector and low-noise transistor, realizes deep sub-electron read noise levels based on the analysis of noise components in the signal readout chain from a pixel to the column analog-to-digital converter (ADC). The noise measurement results of experimental CISs are compared with the noise analysis and the effect of noise reduction to the sampling number is discussed at the deep sub-electron level. Images taken with three CMS gains of two, 16, and 128 show distinct advantage of image contrast for the gain of 128 (noise(median): 0.29 e−rms) when compared with the CMS gain of two (2.4 e−rms), or 16 (1.1 e−rms). PMID:27827972

Noise Reduction Effect of Multiple-Sampling-Based Signal-Readout Circuits for Ultra-Low Noise CMOS Image Sensors.

PubMed

Kawahito, Shoji; Seo, Min-Woong

2016-11-06

This paper discusses the noise reduction effect of multiple-sampling-based signal readout circuits for implementing ultra-low-noise image sensors. The correlated multiple sampling (CMS) technique has recently become an important technology for high-gain column readout circuits in low-noise CMOS image sensors (CISs). This paper reveals how the column CMS circuits, together with a pixel having a high-conversion-gain charge detector and low-noise transistor, realizes deep sub-electron read noise levels based on the analysis of noise components in the signal readout chain from a pixel to the column analog-to-digital converter (ADC). The noise measurement results of experimental CISs are compared with the noise analysis and the effect of noise reduction to the sampling number is discussed at the deep sub-electron level. Images taken with three CMS gains of two, 16, and 128 show distinct advantage of image contrast for the gain of 128 (noise(median): 0.29 e - rms ) when compared with the CMS gain of two (2.4 e - rms ), or 16 (1.1 e - rms ).

Photonic microwave signals with zeptosecond-level absolute timing noise

NASA Astrophysics Data System (ADS)

Xie, Xiaopeng; Bouchand, Romain; Nicolodi, Daniele; Giunta, Michele; Hänsel, Wolfgang; Lezius, Matthias; Joshi, Abhay; Datta, Shubhashish; Alexandre, Christophe; Lours, Michel; Tremblin, Pierre-Alain; Santarelli, Giorgio; Holzwarth, Ronald; Le Coq, Yann

2017-01-01

Photonic synthesis of radiofrequency (RF) waveforms revived the quest for unrivalled microwave purity because of its ability to convey the benefits of optics to the microwave world. In this work, we perform a high-fidelity transfer of frequency stability between an optical reference and a microwave signal via a low-noise fibre-based frequency comb and cutting-edge photodetection techniques. We demonstrate the generation of the purest microwave signal with a fractional frequency stability below 6.5 × 10-16 at 1 s and a timing noise floor below 41 zs Hz-1/2 (phase noise below -173 dBc Hz-1 for a 12 GHz carrier). This outperforms existing sources and promises a new era for state-of-the-art microwave generation. The characterization is achieved through a heterodyne cross-correlation scheme with the lowermost detection noise. This unprecedented level of purity can impact domains such as radar systems, telecommunications and time-frequency metrology. The measurement methods developed here can benefit the characterization of a broad range of signals.

Mapping the MRI voxel volume in which thermal noise matches physiological noise--implications for fMRI.

PubMed

Bodurka, J; Ye, F; Petridou, N; Murphy, K; Bandettini, P A

2007-01-15

This work addresses the choice of the imaging voxel volume in blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI). Noise of physiological origin that is present in the voxel time course is a prohibitive factor in the detection of small activation-induced BOLD signal changes. If the physiological noise contribution dominates over the temporal fluctuation contribution in the imaging voxel, further increases in the voxel signal-to-noise ratio (SNR) will have diminished corresponding increases in temporal signal-to-noise (TSNR), resulting in reduced corresponding increases in the ability to detect activation induced signal changes. On the other hand, if the thermal and system noise dominate (suggesting a relatively low SNR) further decreases in SNR can prohibit detection of activation-induced signal changes. Here we have proposed and called the "suggested" voxel volume for fMRI the volume where thermal plus system-related and physiological noise variances are equal. Based on this condition we have created maps of fMRI suggested voxel volume from our experimental data at 3T, since this value will spatially vary depending on the contribution of physiologic noise in each voxel. Based on our fast EPI segmentation technique we have found that for gray matter (GM), white matter (WM), and cerebral spinal fluid (CSF) brain compartments the mean suggested cubical voxel volume is: (1.8 mm)3, (2.1 mm)3 and (1.4 mm)3, respectively. Serendipitously, (1.8 mm)3 cubical voxel volume for GM approximately matches the cortical thickness, thus optimizing BOLD contrast by minimizing partial volume averaging. The introduced suggested fMRI voxel volume can be a useful parameter for choice of imaging volume for functional studies.

Averaging of phase noise in PSK signals by an opto-electrical feed-forward circuit

NASA Astrophysics Data System (ADS)

Inoue, K.; Ohta, M.

2013-10-01

This paper proposes an opto-electrical feed-forward circuit that reduces phase noise in binary PSK signals by averaging the noise. Random and independent phase noise is averaged over several bit slots by externally modulating a phase-fluctuating PSK signal with feed-forward signal obtained from signal processing of the outputs of delay interferometers. The simulation results demonstrate a reduction in the phase noise.

Agatha: Disentangling period signals from correlated noise in a periodogram framework

NASA Astrophysics Data System (ADS)

Feng, F.; Tuomi, M.; Jones, H. R. A.

2018-04-01

Agatha is a framework of periodograms to disentangle periodic signals from correlated noise and to solve the two-dimensional model selection problem: signal dimension and noise model dimension. These periodograms are calculated by applying likelihood maximization and marginalization and combined in a self-consistent way. Agatha can be used to select the optimal noise model and to test the consistency of signals in time and can be applied to time series analyses in other astronomical and scientific disciplines. An interactive web implementation of the software is also available at http://agatha.herts.ac.uk/.

Linear signal noise summer accurately determines and controls S/N ratio

NASA Technical Reports Server (NTRS)

Sundry, J. L.

1966-01-01

Linear signal noise summer precisely controls the relative power levels of signal and noise, and mixes them linearly in accurately known ratios. The S/N ratio accuracy and stability are greatly improved by this technique and are attained simultaneously.

Investigation on phase noise of the signal from a singly resonant optical parametric oscillator

NASA Astrophysics Data System (ADS)

Jinxia, Feng; Yuanji, Li; Kuanshou, Zhang

2018-04-01

The phase noise of the signal from a singly resonant optical parametric oscillator (SRO) is investigated theoretically and experimentally. An SRO based on periodically poled lithium niobate is built up that generates the signal with a maximum power of 5.2 W at 1.5 µm. The intensity noise of the signal reaches the shot noise level for frequencies above 5 MHz. The phase noise of the signal oscillates depending on the analysis frequency, and there are phase noise peaks above the shot noise level at the peak frequencies. To explain the phase noise feature of the signal, a semi-classical theoretical model of SROs including the guided acoustic wave Brillouin scattering effect within the nonlinear crystal is developed. The theoretical predictions are in good agreement with the experimental results.

Algorithm for astronomical, point source, signal to noise ratio calculations

NASA Technical Reports Server (NTRS)

Jayroe, R. R.; Schroeder, D. J.

1984-01-01

An algorithm was developed to simulate the expected signal to noise ratios as a function of observation time in the charge coupled device detector plane of an optical telescope located outside the Earth's atmosphere for a signal star, and an optional secondary star, embedded in a uniform cosmic background. By choosing the appropriate input values, the expected point source signal to noise ratio can be computed for the Hubble Space Telescope using the Wide Field/Planetary Camera science instrument.

Measuring signal-to-noise ratio automatically

NASA Technical Reports Server (NTRS)

Bergman, L. A.; Johnston, A. R.

1980-01-01

Automated method of measuring signal-to-noise ratio in digital communication channels is more precise and 100 times faster than previous methods used. Method based on bit-error-rate (B&R) measurement can be used with cable, microwave radio, or optical links.

Noise Estimation in Electroencephalogram Signal by Using Volterra Series Coefficients

PubMed Central

Hassani, Malihe; Karami, Mohammad Reza

2015-01-01

The Volterra model is widely used for nonlinearity identification in practical applications. In this paper, we employed Volterra model to find the nonlinearity relation between electroencephalogram (EEG) signal and the noise that is a novel approach to estimate noise in EEG signal. We show that by employing this method. We can considerably improve the signal to noise ratio by the ratio of at least 1.54. An important issue in implementing Volterra model is its computation complexity, especially when the degree of nonlinearity is increased. Hence, in many applications it is urgent to reduce the complexity of computation. In this paper, we use the property of EEG signal and propose a new and good approximation of delayed input signal to its adjacent samples in order to reduce the computation of finding Volterra series coefficients. The computation complexity is reduced by the ratio of at least 1/3 when the filter memory is 3. PMID:26284176

Signal-to-Noise Ratio in Physical Education Settings

ERIC Educational Resources Information Center

Ryan, Stu; Grube, Dan; Mokgwathi, Martin M.

2010-01-01

It is generally known that in educational settings, excessive noise masks what the teacher is saying; thus, and for maximum learning to occur, the teacher's voice must be highly intelligible to all children (Crandell, Smaldino, & Flexer, 1995). The difference between what the teacher is saying (signal) and the classroom noise level is commonly…

Signal-dependent noise determines motor planning

NASA Astrophysics Data System (ADS)

Harris, Christopher M.; Wolpert, Daniel M.

1998-08-01

When we make saccadic eye movements or goal-directed arm movements, there is an infinite number of possible trajectories that the eye or arm could take to reach the target,. However, humans show highly stereotyped trajectories in which velocity profiles of both the eye and hand are smooth and symmetric for brief movements,. Here we present a unifying theory of eye and arm movements based on the single physiological assumption that the neural control signals are corrupted by noise whose variance increases with the size of the control signal. We propose that in the presence of such signal-dependent noise, the shape of a trajectory is selected to minimize the variance of the final eye or arm position. This minimum-variance theory accurately predicts the trajectories of both saccades and arm movements and the speed-accuracy trade-off described by Fitt's law. These profiles are robust to changes in the dynamics of the eye or arm, as found empirically,. Moreover, the relation between path curvature and hand velocity during drawing movements reproduces the empirical `two-thirds power law',. This theory provides a simple and powerful unifying perspective for both eye and arm movement control.

Balanced detection for self-mixing interferometry to improve signal-to-noise ratio

NASA Astrophysics Data System (ADS)

Zhao, Changming; Norgia, Michele; Li, Kun

2018-01-01

We apply balanced detection to self-mixing interferometry for displacement and vibration measurement, using two photodiodes for implementing a differential acquisition. The method is based on the phase opposition of the self-mixing signal measured between the two laser diode facet outputs. The balanced signal obtained by enlarging the self-mixing signal, also by canceling of the common-due noises mainly due to disturbances on laser supply and transimpedance amplifier. Experimental results demonstrate the signal-to-noise ratio significantly improves, with almost twice signals enhancement and more than half noise decreasing. This method allows for more robust, longer-distance measurement systems, especially using fringe-counting.

Wavelet threshold method of resolving noise interference in periodic short-impulse signals chaotic detection

NASA Astrophysics Data System (ADS)

Deng, Ke; Zhang, Lu; Luo, Mao-Kang

2010-03-01

The chaotic oscillator has already been considered as a powerful method to detect weak signals, even weak signals accompanied with noises. However, many examples, analyses and simulations indicate that chaotic oscillator detection system cannot guarantee the immunity to noises (even white noise). In fact the randomness of noises has a serious or even a destructive effect on the detection results in many cases. To solve this problem, we present a new detecting method based on wavelet threshold processing that can detect the chaotic weak signal accompanied with noise. All theoretical analyses and simulation experiments indicate that the new method reduces the noise interferences to detection significantly, thereby making the corresponding chaotic oscillator that detects the weak signals accompanied with noises more stable and reliable.

Geostatistical estimation of signal-to-noise ratios for spectral vegetation indices

USGS Publications Warehouse

Ji, Lei; Zhang, Li; Rover, Jennifer R.; Wylie, Bruce K.; Chen, Xuexia

2014-01-01

In the past 40 years, many spectral vegetation indices have been developed to quantify vegetation biophysical parameters. An ideal vegetation index should contain the maximum level of signal related to specific biophysical characteristics and the minimum level of noise such as background soil influences and atmospheric effects. However, accurate quantification of signal and noise in a vegetation index remains a challenge, because it requires a large number of field measurements or laboratory experiments. In this study, we applied a geostatistical method to estimate signal-to-noise ratio (S/N) for spectral vegetation indices. Based on the sample semivariogram of vegetation index images, we used the standardized noise to quantify the noise component of vegetation indices. In a case study in the grasslands and shrublands of the western United States, we demonstrated the geostatistical method for evaluating S/N for a series of soil-adjusted vegetation indices derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. The soil-adjusted vegetation indices were found to have higher S/N values than the traditional normalized difference vegetation index (NDVI) and simple ratio (SR) in the sparsely vegetated areas. This study shows that the proposed geostatistical analysis can constitute an efficient technique for estimating signal and noise components in vegetation indices.

Cascaded analysis of signal and noise propagation through a heterogeneous breast model.

PubMed

Mainprize, James G; Yaffe, Martin J

2010-10-01

The detectability of lesions in radiographic images can be impaired by patterns caused by the surrounding anatomic structures. The presence of such patterns is often referred to as anatomic noise. Others have previously extended signal and noise propagation theory to include variable background structure as an additional noise term and used in simulations for analysis by human and ideal observers. Here, the analytic forms of the signal and noise transfer are derived to obtain an exact expression for any input random distribution and the "power law" filter used to generate the texture of the tissue distribution. A cascaded analysis of propagation through a heterogeneous model is derived for x-ray projection through simulated heterogeneous backgrounds. This is achieved by considering transmission through the breast as a correlated amplification point process. The analytic forms of the cascaded analysis were compared to monoenergetic Monte Carlo simulations of x-ray propagation through power law structured backgrounds. As expected, it was found that although the quantum noise power component scales linearly with the x-ray signal, the anatomic noise will scale with the square of the x-ray signal. There was a good agreement between results obtained using analytic expressions for the noise power and those from Monte Carlo simulations for different background textures, random input functions, and x-ray fluence. Analytic equations for the signal and noise properties of heterogeneous backgrounds were derived. These may be used in direct analysis or as a tool to validate simulations in evaluating detectability.

Time-frequency peak filtering for random noise attenuation of magnetic resonance sounding signal

NASA Astrophysics Data System (ADS)

Lin, Tingting; Zhang, Yang; Yi, Xiaofeng; Fan, Tiehu; Wan, Ling

2018-05-01

When measuring in a geomagnetic field, the method of magnetic resonance sounding (MRS) is often limited because of the notably low signal-to-noise ratio (SNR). Most current studies focus on discarding spiky noise and power-line harmonic noise cancellation. However, the effects of random noise should not be underestimated. The common method for random noise attenuation is stacking, but collecting multiple recordings merely to suppress random noise is time-consuming. Moreover, stacking is insufficient to suppress high-level random noise. Here, we propose the use of time-frequency peak filtering for random noise attenuation, which is performed after the traditional de-spiking and power-line harmonic removal method. By encoding the noisy signal with frequency modulation and estimating the instantaneous frequency using the peak of the time-frequency representation of the encoded signal, the desired MRS signal can be acquired from only one stack. The performance of the proposed method is tested on synthetic envelope signals and field data from different surveys. Good estimations of the signal parameters are obtained at different SNRs. Moreover, an attempt to use the proposed method to handle a single recording provides better results compared to 16 stacks. Our results suggest that the number of stacks can be appropriately reduced to shorten the measurement time and improve the measurement efficiency.

Noncoherent Detection of Coherent Optical Heterodyne Signals Corrupted by Laser Phase Noise

DTIC Science & Technology

1991-03-01

replicated speech at the receiving end through the photoelectric effect . Bell’s photophone was the first practical use of light as a transmission...source dominates system performance. An analyti- cal expression representing the effect of laser phase noise on system performance is derived based on a...decision threshold analysis illustrates which noise source dominates system performance. An analytical expression representing the effect of laser phase

Noise considerations for remote detection of life signs with microwave Doppler radar.

PubMed

Nguyen, Dung; Yamada, Shuhei; Park, Byung-Kwon; Lubecke, Victor; Boric-Lubecke, Olga; Host-Madsen, Anders

2007-01-01

This paper describes and quantifies three main sources of baseband noise affecting physiological signals in a direct conversion microwave Doppler radar for life signs detection. They are thermal noise, residual phase noise, and Flicker noise. In order to increase the SNR of physiological signals at baseband, the noise floor, in which the Flicker noise is the most dominant factor, needs to be minimized. This paper shows that with the consideration of the noise factor in our Doppler radar, Flicker noise canceling techniques may drastically reduce the power requirement for heart rate signal detection by as much as a factor of 100.

Cluster signal-to-noise analysis for evaluation of the information content in an image.

PubMed

Weerawanich, Warangkana; Shimizu, Mayumi; Takeshita, Yohei; Okamura, Kazutoshi; Yoshida, Shoko; Yoshiura, Kazunori

2018-01-01

(1) To develop an observer-free method of analysing image quality related to the observer performance in the detection task and (2) to analyse observer behaviour patterns in the detection of small mass changes in cone-beam CT images. 13 observers detected holes in a Teflon phantom in cone-beam CT images. Using the same images, we developed a new method, cluster signal-to-noise analysis, to detect the holes by applying various cut-off values using ImageJ and reconstructing cluster signal-to-noise curves. We then evaluated the correlation between cluster signal-to-noise analysis and the observer performance test. We measured the background noise in each image to evaluate the relationship with false positive rates (FPRs) of the observers. Correlations between mean FPRs and intra- and interobserver variations were also evaluated. Moreover, we calculated true positive rates (TPRs) and accuracies from background noise and evaluated their correlations with TPRs from observers. Cluster signal-to-noise curves were derived in cluster signal-to-noise analysis. They yield the detection of signals (true holes) related to noise (false holes). This method correlated highly with the observer performance test (R 2 = 0.9296). In noisy images, increasing background noise resulted in higher FPRs and larger intra- and interobserver variations. TPRs and accuracies calculated from background noise had high correlation with actual TPRs from observers; R 2 was 0.9244 and 0.9338, respectively. Cluster signal-to-noise analysis can simulate the detection performance of observers and thus replace the observer performance test in the evaluation of image quality. Erroneous decision-making increased with increasing background noise.

Removal of Stationary Sinusoidal Noise from Random Vibration Signals.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, Brian; Cap, Jerome S.

In random vibration environments, sinusoidal line noise may appear in the vibration signal and can affect analysis of the resulting data. We studied two methods which remove stationary sine tones from random noise: a matrix inversion algorithm and a chirp-z transform algorithm. In addition, we developed new methods to determine the frequency of the tonal noise. The results show that both of the removal methods can eliminate sine tones in prefabricated random vibration data when the sine-to-random ratio is at least 0.25. For smaller ratios down to 0.02 only the matrix inversion technique can remove the tones, but the metricsmore » to evaluate its effectiveness also degrade. We also found that using fast Fourier transforms best identified the tonal noise, and determined that band-pass-filtering the signals prior to the process improved sine removal. When applied to actual vibration test data, the methods were not as effective at removing harmonic tones, which we believe to be a result of mixed-phase sinusoidal noise.« less

Ultrasonic correlator versus signal averager as a signal to noise enhancement instrument

NASA Technical Reports Server (NTRS)

Kishoni, Doron; Pietsch, Benjamin E.

1989-01-01

Ultrasonic inspection of thick and attenuating materials is hampered by the reduced amplitudes of the propagated waves to a degree that the noise is too high to enable meaningful interpretation of the data. In order to overcome the low Signal to Noise (S/N) ratio, a correlation technique has been developed. In this method, a continuous pseudo-random pattern generated digitally is transmitted and detected by piezoelectric transducers. A correlation is performed in the instrument between the received signal and a variable delayed image of the transmitted one. The result is shown to be proportional to the impulse response of the investigated material, analogous to a signal received from a pulsed system, with an improved S/N ratio. The degree of S/N enhancement depends on the sweep rate. This paper describes the correlator, and compares it to the method of enhancing S/N ratio by averaging the signals. The similarities and differences between the two are highlighted and the potential advantage of the correlator system is explained.

Ultrasonic correlator versus signal averager as a signal to noise enhancement instrument

NASA Technical Reports Server (NTRS)

Kishoni, Doron; Pietsch, Benjamin E.

1990-01-01

Ultrasonic inspection of thick and attenuating materials is hampered by the reduce amplitudes of the propagated waves to a degree that the noise is too high to enable meaningful interpretation of the data. In order to overcome the low signal to noise ratio (S/N), a correlation technique has been developed. In this method, a continuous pseudo-random pattern generated digitally is transmitted and detected by piezoelectric transducers. A correlation is performed in the instrument between the received signal and a variable delayed image of the transmitted one. The result is shown to be proportional to the impulse response of the investigated material, analogous to a signal received from a pulsed system, with an improved S/N ratio. The degree of S/N enhancement depends on the sweep rate. The correlator is described, and it is compared to the method of enhancing S/N ratio by averaging the signals. The similarities and differences between the two are highlighted and the potential advantage of the correlator system is explained.

Reducing Noise by Repetition: Introduction to Signal Averaging

ERIC Educational Resources Information Center

Hassan, Umer; Anwar, Muhammad Sabieh

2010-01-01

This paper describes theory and experiments, taken from biophysics and physiological measurements, to illustrate the technique of signal averaging. In the process, students are introduced to the basic concepts of signal processing, such as digital filtering, Fourier transformation, baseline correction, pink and Gaussian noise, and the cross- and…

Quantum issues in optical communication. [noise reduction in signal reception

NASA Technical Reports Server (NTRS)

Kennedy, R. S.

1973-01-01

Various approaches to the problem of controlling quantum noise, the dominant noise in an optical communications system, are discussed. It is shown that, no matter which way the problem is approached, there always remain uncertainties. These uncertainties exist because, to date, only very few communication problems have been solved in their full quantum form.

Non-heuristic automatic techniques for overcoming low signal-to-noise-ratio bias of localization microscopy and multiple signal classification algorithm.

PubMed

Agarwal, Krishna; Macháň, Radek; Prasad, Dilip K

2018-03-21

Localization microscopy and multiple signal classification algorithm use temporal stack of image frames of sparse emissions from fluorophores to provide super-resolution images. Localization microscopy localizes emissions in each image independently and later collates the localizations in all the frames, giving same weight to each frame irrespective of its signal-to-noise ratio. This results in a bias towards frames with low signal-to-noise ratio and causes cluttered background in the super-resolved image. User-defined heuristic computational filters are employed to remove a set of localizations in an attempt to overcome this bias. Multiple signal classification performs eigen-decomposition of the entire stack, irrespective of the relative signal-to-noise ratios of the frames, and uses a threshold to classify eigenimages into signal and null subspaces. This results in under-representation of frames with low signal-to-noise ratio in the signal space and over-representation in the null space. Thus, multiple signal classification algorithms is biased against frames with low signal-to-noise ratio resulting into suppression of the corresponding fluorophores. This paper presents techniques to automatically debias localization microscopy and multiple signal classification algorithm of these biases without compromising their resolution and without employing heuristics, user-defined criteria. The effect of debiasing is demonstrated through five datasets of invitro and fixed cell samples.

Nonlinear Transfer of Signal and Noise Correlations in Cortical Networks

PubMed Central

Lyamzin, Dmitry R.; Barnes, Samuel J.; Donato, Roberta; Garcia-Lazaro, Jose A.; Keck, Tara

2015-01-01

Signal and noise correlations, a prominent feature of cortical activity, reflect the structure and function of networks during sensory processing. However, in addition to reflecting network properties, correlations are also shaped by intrinsic neuronal mechanisms. Here we show that spike threshold transforms correlations by creating nonlinear interactions between signal and noise inputs; even when input noise correlation is constant, spiking noise correlation varies with both the strength and correlation of signal inputs. We characterize these effects systematically in vitro in mice and demonstrate their impact on sensory processing in vivo in gerbils. We also find that the effects of nonlinear correlation transfer on cortical responses are stronger in the synchronized state than in the desynchronized state, and show that they can be reproduced and understood in a model with a simple threshold nonlinearity. Since these effects arise from an intrinsic neuronal property, they are likely to be present across sensory systems and, thus, our results are a critical step toward a general understanding of how correlated spiking relates to the structure and function of cortical networks. PMID:26019325

Light field reconstruction robust to signal dependent noise

NASA Astrophysics Data System (ADS)

Ren, Kun; Bian, Liheng; Suo, Jinli; Dai, Qionghai

2014-11-01

Capturing four dimensional light field data sequentially using a coded aperture camera is an effective approach but suffers from low signal noise ratio. Although multiplexing can help raise the acquisition quality, noise is still a big issue especially for fast acquisition. To address this problem, this paper proposes a noise robust light field reconstruction method. Firstly, scene dependent noise model is studied and incorporated into the light field reconstruction framework. Then, we derive an optimization algorithm for the final reconstruction. We build a prototype by hacking an off-the-shelf camera for data capturing and prove the concept. The effectiveness of this method is validated with experiments on the real captured data.

Noise and noise figure of vertical-cavity semiconductor optical amplifiers (VCSOAs) operated in reflection mode

NASA Astrophysics Data System (ADS)

Wen, Pengyue; Sanchez, Michael; Gross, Matthias; Esener, Sadik C.

2003-05-01

In this paper, the noise properties of vertical cavity semiconductor optical amplifiers (VCSOAs) operated in reflection mode are studied. Expressions for noise sources contributing to the total noise detected at amplifier output are derived, based on the photon statistics master equations. The noise figure, defined as the degradation of signal-to-noise ratio (SNR), is analyzed using the assumption that spontaneous emission-signal beat noise dominates. The analysis shows that the noise figure of reflection mode VCSOAs has the same values as that in transmission mode as long as amplifier gain is high (G>>1). Furthermore, simulations depict the dependence of noise figure on device parameters and bias conditions, as well as reveal the importance of the low reflectivity front mirror and the high reflectivity rear mirror for low noise operation. In addition, the noise figure analysis results are compared with experimental measurements, in which amplified spontaneous emission (ASE) power is measured by an optical spectrum analyzer and the noise figure is obtained from the ASE power and the amplifier gain. The measured data are in good agreement with the theoretical predictions.

Technical note: Signal resolution increase and noise reduction in a CCD digitizer.

PubMed

González, A; Martínez, J A; Tobarra, B

2004-03-01

Increasing output resolution is assumed to improve noise characteristics of a CCD digitizer. In this work, however, we have found that as the quantization step becomes lower than the analog noise (present in the signal before its conversion to digital) the noise reduction becomes significantly lower than expected. That is the case for values of sigma(an)/delta larger than 0.6, where sigma(an) is the standard deviation of the analog noise and delta is the quantization step. The procedure is applied to a commercially available CCD digitizer, and noise reduction by means of signal resolution increase is compared to that obtained by low pass filtering.

The invariant statistical rule of aerosol scattering pulse signal modulated by random noise

NASA Astrophysics Data System (ADS)

Yan, Zhen-gang; Bian, Bao-Min; Yang, Juan; Peng, Gang; Li, Zhen-hua

2010-11-01

A model of the random background noise acting on particle signals is established to study the impact of the background noise of the photoelectric sensor in the laser airborne particle counter on the statistical character of the aerosol scattering pulse signals. The results show that the noises broaden the statistical distribution of the particle's measurement. Further numerical research shows that the output of the signal amplitude still has the same distribution when the airborne particle with the lognormal distribution was modulated by random noise which has lognormal distribution. Namely it follows the statistics law of invariance. Based on this model, the background noise of photoelectric sensor and the counting distributions of random signal for aerosol's scattering pulse are obtained and analyzed by using a high-speed data acquisition card PCI-9812. It is found that the experiment results and simulation results are well consistent.

ECG signal performance de-noising assessment based on threshold tuning of dual-tree wavelet transform.

PubMed

El B'charri, Oussama; Latif, Rachid; Elmansouri, Khalifa; Abenaou, Abdenbi; Jenkal, Wissam

2017-02-07

Since the electrocardiogram (ECG) signal has a low frequency and a weak amplitude, it is sensitive to miscellaneous mixed noises, which may reduce the diagnostic accuracy and hinder the physician's correct decision on patients. The dual tree wavelet transform (DT-WT) is one of the most recent enhanced versions of discrete wavelet transform. However, threshold tuning on this method for noise removal from ECG signal has not been investigated yet. In this work, we shall provide a comprehensive study on the impact of the choice of threshold algorithm, threshold value, and the appropriate wavelet decomposition level to evaluate the ECG signal de-noising performance. A set of simulations is performed on both synthetic and real ECG signals to achieve the promised results. First, the synthetic ECG signal is used to observe the algorithm response. The evaluation results of synthetic ECG signal corrupted by various types of noise has showed that the modified unified threshold and wavelet hyperbolic threshold de-noising method is better in realistic and colored noises. The tuned threshold is then used on real ECG signals from the MIT-BIH database. The results has shown that the proposed method achieves higher performance than the ordinary dual tree wavelet transform into all kinds of noise removal from ECG signal. The simulation results indicate that the algorithm is robust for all kinds of noises with varying degrees of input noise, providing a high quality clean signal. Moreover, the algorithm is quite simple and can be used in real time ECG monitoring.

Cellular Signaling Networks Function as Generalized Wiener-Kolmogorov Filters to Suppress Noise

NASA Astrophysics Data System (ADS)

Hinczewski, Michael; Thirumalai, D.

2014-10-01

Cellular signaling involves the transmission of environmental information through cascades of stochastic biochemical reactions, inevitably introducing noise that compromises signal fidelity. Each stage of the cascade often takes the form of a kinase-phosphatase push-pull network, a basic unit of signaling pathways whose malfunction is linked with a host of cancers. We show that this ubiquitous enzymatic network motif effectively behaves as a Wiener-Kolmogorov optimal noise filter. Using concepts from umbral calculus, we generalize the linear Wiener-Kolmogorov theory, originally introduced in the context of communication and control engineering, to take nonlinear signal transduction and discrete molecule populations into account. This allows us to derive rigorous constraints for efficient noise reduction in this biochemical system. Our mathematical formalism yields bounds on filter performance in cases important to cellular function—such as ultrasensitive response to stimuli. We highlight features of the system relevant for optimizing filter efficiency, encoded in a single, measurable, dimensionless parameter. Our theory, which describes noise control in a large class of signal transduction networks, is also useful both for the design of synthetic biochemical signaling pathways and the manipulation of pathways through experimental probes such as oscillatory input.

Signal Analysis of Helicopter Blade-Vortex-Interaction Acoustic Noise Data

NASA Technical Reports Server (NTRS)

Rogers, James C.; Dai, Renshou

1998-01-01

Blade-Vortex-Interaction (BVI) produces annoying high-intensity impulsive noise. NASA Ames collected several sets of BVI noise data during in-flight and wind tunnel tests. The goal of this work is to extract the essential features of the BVI signals from the in-flight data and examine the feasibility of extracting those features from BVI noise recorded inside a large wind tunnel. BVI noise generating mechanisms and BVI radiation patterns an are considered and a simple mathematical-physical model is presented. It allows the construction of simple synthetic BVI events that are comparable to free flight data. The boundary effects of the wind tunnel floor and ceiling are identified and more complex synthetic BVI events are constructed to account for features observed in the wind tunnel data. It is demonstrated that improved recording of BVI events can be attained by changing the geometry of the rotor hub, floor, ceiling and microphone. The Euclidean distance measure is used to align BVI events from each blade and improved BVI signals are obtained by time-domain averaging the aligned data. The differences between BVI events for individual blades are then apparent. Removal of wind tunnel background noise by optimal Wiener-filtering is shown to be effective provided representative noise-only data have been recorded. Elimination of wind tunnel reflections by cepstral and optimal filtering deconvolution is examined. It is seen that the cepstral method is not applicable but that a pragmatic optimal filtering approach gives encouraging results. Recommendations for further work include: altering measurement geometry, real-time data observation and evaluation, examining reflection signals (particularly those from the ceiling) and performing further analysis of expected BVI signals for flight conditions of interest so that microphone placement can be optimized for each condition.

Noise effect on performance of IR PVDF pyroelectric detector

NASA Astrophysics Data System (ADS)

Abdullah, K. Al; Batal, M. Anwar; Hamdan, Rawad; Khalil, Toni; Salame, Chafic

2018-05-01

The spin-casting and casting technology were used to make IR pyroelectric PVDF detectors, where the operational amplifier, TC75S63TU, is used to amplify pyroelectrical signal. The pyroelectric coefficient is measured by charge integration method, which is 23 µC/m2K. The voltage responsivity and noise equivalent power depending on the dielectric constant, specific conductivity and loss tangent, which are measured at various frequencies, is estimated where changing of detector capacitance and resistor with frequency is taken into account. Maximum voltage responsivity was for detector thickness d=116.05 µm at chopping frequency (f=0.8Hz). Influence of thermal, Johnson and amplifier noises on output voltage are studied. At frequencies (<1kHz), Johnson noise dominates whereas at frequencies (>1kHz), amplifier voltage noise dominates. The thinner detector, the lower noise affects on output voltage. The optimal signal to noise ratio (SNR) of pyroelectrical detector is for thickness d=30.1 µm at frequency f=20Hz. The reducing electrode area decreases slightly total noise at low frequency and enhances slightly SNR of pyroelectrical detector.

Internal curvature signal and noise in low- and high-level vision

PubMed Central

Grabowecky, Marcia; Kim, Yee Joon; Suzuki, Satoru

2011-01-01

How does internal processing contribute to visual pattern perception? By modeling visual search performance, we estimated internal signal and noise relevant to perception of curvature, a basic feature important for encoding of three-dimensional surfaces and objects. We used isolated, sparse, crowded, and face contexts to determine how internal curvature signal and noise depended on image crowding, lateral feature interactions, and level of pattern processing. Observers reported the curvature of a briefly flashed segment, which was presented alone (without lateral interaction) or among multiple straight segments (with lateral interaction). Each segment was presented with no context (engaging low-to-intermediate-level curvature processing), embedded within a face context as the mouth (engaging high-level face processing), or embedded within an inverted-scrambled-face context as a control for crowding. Using a simple, biologically plausible model of curvature perception, we estimated internal curvature signal and noise as the mean and standard deviation, respectively, of the Gaussian-distributed population activity of local curvature-tuned channels that best simulated behavioral curvature responses. Internal noise was increased by crowding but not by face context (irrespective of lateral interactions), suggesting prevention of noise accumulation in high-level pattern processing. In contrast, internal curvature signal was unaffected by crowding but modulated by lateral interactions. Lateral interactions (with straight segments) increased curvature signal when no contextual elements were added, but equivalent interactions reduced curvature signal when each segment was presented within a face. These opposing effects of lateral interactions are consistent with the phenomena of local-feature contrast in low-level processing and global-feature averaging in high-level processing. PMID:21209356

An algorithm for the estimation of the signal-to-noise ratio in surface myoelectric signals generated during cyclic movements.

PubMed

Agostini, Valentina; Knaflitz, Marco

2012-01-01

In many applications requiring the study of the surface myoelectric signal (SMES) acquired in dynamic conditions, it is essential to have a quantitative evaluation of the quality of the collected signals. When the activation pattern of a muscle has to be obtained by means of single- or double-threshold statistical detectors, the background noise level e (noise) of the signal is a necessary input parameter. Moreover, the detection strategy of double-threshold detectors may be properly tuned when the SNR and the duty cycle (DC) of the signal are known. The aim of this paper is to present an algorithm for the estimation of e (noise), SNR, and DC of an SMES collected during cyclic movements. The algorithm is validated on synthetic signals with statistical properties similar to those of SMES, as well as on more than 100 real signals. © 2011 IEEE

Intrinsic noise analysis and stochastic simulation on transforming growth factor beta signal pathway

NASA Astrophysics Data System (ADS)

Wang, Lu; Ouyang, Qi

2010-10-01

A typical biological cell lives in a small volume at room temperature; the noise effect on the cell signal transduction pathway may play an important role in its dynamics. Here, using the transforming growth factor-β signal transduction pathway as an example, we report our stochastic simulations of the dynamics of the pathway and introduce a linear noise approximation method to calculate the transient intrinsic noise of pathway components. We compare the numerical solutions of the linear noise approximation with the statistic results of chemical Langevin equations, and find that they are quantitatively in agreement with the other. When transforming growth factor-β dose decreases to a low level, the time evolution of noise fluctuation of nuclear Smad2—Smad4 complex indicates the abnormal enhancement in the transient signal activation process.

Seismometer Self-Noise and Measuring Methods

USGS Publications Warehouse

Ringler, Adam; R. Sleeman,; Hutt, Charles R.; Gee, Lind S.

2014-01-01

Seismometer self-noise is usually not considered when selecting and using seismic waveform data in scientific research as it is typically assumed that the self-noise is negligibly small compared to seismic signals. However, instrumental noise is part of the noise in any seismic record, and in particular, at frequencies below a few mHz, the instrumental noise has a frequency-dependent character and may dominate the noise. When seismic noise itself is considered as a carrier of information, as in seismic interferometry (e.g., Chaput et al. 2012), it becomes extremely important to estimate the contribution of instrumental noise to the recordings.

Benchmarking the Algorithms to Detect Seasonal Signals Under Different Noise Conditions

NASA Astrophysics Data System (ADS)

Klos, A.; Bogusz, J.; Bos, M. S.

2017-12-01

Global Positioning System (GPS) position time series contain seasonal signals. Among the others, annual and semi-annual are the most powerful. Widely, these oscillations are modelled as curves with constant amplitudes, using the Weighted Least-Squares (WLS) algorithm. However, in reality, the seasonal signatures vary over time, as their geophysical causes are not constant. Different algorithms have been already used to cover this time-variability, as Wavelet Decomposition (WD), Singular Spectrum Analysis (SSA), Chebyshev Polynomial (CP) or Kalman Filter (KF). In this research, we employed 376 globally distributed GPS stations which time series contributed to the newest International Terrestrial Reference Frame (ITRF2014). We show that for c.a. 20% of stations the amplitudes of seasonal signal varies over time of more than 1.0 mm. Then, we compare the WD, SSA, CP and KF algorithms for a set of synthetic time series to quantify them under different noise conditions. We show that when variations of seasonal signals are ignored, the power-law character is biased towards flicker noise. The most reliable estimates of the variations were found to be given by SSA and KF. These methods also perform the best for other noise levels while WD, and to a lesser extend also CP, have trouble in separating the seasonal signal from the noise which leads to an underestimation in the spectral index of power-law noise of around 0.1. For real ITRF2014 GPS data we discovered, that SSA and KF are capable to model 49-84% and 77-90% of the variance of the true varying seasonal signals, respectively.

Analysis of signal to noise enhancement using a highly selective modulation tracking filter

NASA Technical Reports Server (NTRS)

Haden, C. R.; Alworth, C. W.

1972-01-01

Experiments are reported which utilize photodielectric effects in semiconductor loaded superconducting resonant circuits for suppressing noise in RF communication systems. The superconducting tunable cavity acts as a narrow band tracking filter for detecting conventional RF signals. Analytical techniques were developed which lead to prediction of signal-to-noise improvements. Progress is reported in optimization of the experimental variables. These include improved Q, new semiconductors, improved optics, and simplification of the electronics. Information bearing signals were passed through the system, and noise was introduced into the computer model.

Life Outside the Golden Window: Statistical Angles on the Signal-to-Noise Problem

NASA Astrophysics Data System (ADS)

Wagman, Michael

2018-03-01

Lattice QCD simulations of multi-baryon correlation functions can predict the structure and reactions of nuclei without encountering the baryon chemical potential sign problem. However, they suffer from a signal-to-noise problem where Monte Carlo estimates of observables have quantum fluctuations that are exponentially larger than their average values. Recent lattice QCD results demonstrate that the complex phase of baryon correlations functions relates the baryon signal-to-noise problem to a sign problem and exhibits unexpected statistical behavior resembling a heavy-tailed random walk on the unit circle. Estimators based on differences of correlation function phases evaluated at different Euclidean times are discussed that avoid the usual signal-to-noise problem, instead facing a signal-to-noise problem as the time interval associated with the phase difference is increased, and allow hadronic observables to be determined from arbitrarily large-time correlation functions.

Filtering device. [removing electromagnetic noise from voice communication signals

NASA Technical Reports Server (NTRS)

Edwards, T. R.; Zeanah, H. W. (Inventor)

1976-01-01

An electrical filter for removing noise from a voice communications signal is reported; seven sample values of the signal are obtained continuously, updated and subjected to filtering. Filtering is accomplished by adding balanced, with respect to a mid-point sample, spaced pairs of the sampled values, and then multiplying each pair by a selected filter constant. The signal products thus obtained are summed to provide a filtered version of the original signal.

Image informative maps for component-wise estimating parameters of signal-dependent noise

NASA Astrophysics Data System (ADS)

Uss, Mykhail L.; Vozel, Benoit; Lukin, Vladimir V.; Chehdi, Kacem

2013-01-01

We deal with the problem of blind parameter estimation of signal-dependent noise from mono-component image data. Multispectral or color images can be processed in a component-wise manner. The main results obtained rest on the assumption that the image texture and noise parameters estimation problems are interdependent. A two-dimensional fractal Brownian motion (fBm) model is used for locally describing image texture. A polynomial model is assumed for the purpose of describing the signal-dependent noise variance dependence on image intensity. Using the maximum likelihood approach, estimates of both fBm-model and noise parameters are obtained. It is demonstrated that Fisher information (FI) on noise parameters contained in an image is distributed nonuniformly over intensity coordinates (an image intensity range). It is also shown how to find the most informative intensities and the corresponding image areas for a given noisy image. The proposed estimator benefits from these detected areas to improve the estimation accuracy of signal-dependent noise parameters. Finally, the potential estimation accuracy (Cramér-Rao Lower Bound, or CRLB) of noise parameters is derived, providing confidence intervals of these estimates for a given image. In the experiment, the proposed and existing state-of-the-art noise variance estimators are compared for a large image database using CRLB-based statistical efficiency criteria.

Detecting modulated signals in modulated noise: (II) neural thresholds in the songbird forebrain.

PubMed

Bee, Mark A; Buschermöhle, Michael; Klump, Georg M

2007-10-01

Sounds in the real world fluctuate in amplitude. The vertebrate auditory system exploits patterns of amplitude fluctuations to improve signal detection in noise. One experimental paradigm demonstrating these general effects has been used in psychophysical studies of 'comodulation detection difference' (CDD). The CDD effect refers to the fact that thresholds for detecting a modulated, narrowband noise signal are lower when the envelopes of flanking bands of modulated noise are comodulated with each other, but fluctuate independently of the signal compared with conditions in which the envelopes of the signal and flanking bands are all comodulated. Here, we report results from a study of the neural correlates of CDD in European starlings (Sturnus vulgaris). We manipulated: (i) the envelope correlations between a narrowband noise signal and a masker comprised of six flanking bands of noise; (ii) the signal onset delay relative to masker onset; (iii) signal duration; and (iv) masker spectrum level. Masked detection thresholds were determined from neural responses using signal detection theory. Across conditions, the magnitude of neural CDD ranged between 2 and 8 dB, which is similar to that reported in a companion psychophysical study of starlings [U. Langemann & G.M. Klump (2007) Eur. J. Neurosci., 26, 1969-1978]. We found little evidence to suggest that neural CDD resulted from the across-channel processing of auditory grouping cues related to common envelope fluctuations and synchronous onsets between the signal and flanking bands. We discuss a within-channel model of peripheral processing that explains many of our results.

The Combined Effect of Periodic Signals and Noise on the Dilution of Precision of GNSS Station Velocity Uncertainties

NASA Astrophysics Data System (ADS)

Klos, Anna; Olivares, German; Teferle, Felix Norman; Bogusz, Janusz

2016-04-01

Station velocity uncertainties determined from a series of Global Navigation Satellite System (GNSS) position estimates depend on both the deterministic and stochastic models applied to the time series. While the deterministic model generally includes parameters for a linear and several periodic terms the stochastic model is a representation of the noise character of the time series in form of a power-law process. For both of these models the optimal model may vary from one time series to another while the models also depend, to some degree, on each other. In the past various power-law processes have been shown to fit the time series and the sources for the apparent temporally-correlated noise were attributed to, for example, mismodelling of satellites orbits, antenna phase centre variations, troposphere, Earth Orientation Parameters, mass loading effects and monument instabilities. Blewitt and Lavallée (2002) demonstrated how improperly modelled seasonal signals affected the estimates of station velocity uncertainties. However, in their study they assumed that the time series followed a white noise process with no consideration of additional temporally-correlated noise. Bos et al. (2010) empirically showed for a small number of stations that the noise character was much more important for the reliable estimation of station velocity uncertainties than the seasonal signals. In this presentation we pick up from Blewitt and Lavallée (2002) and Bos et al. (2010), and have derived formulas for the computation of the General Dilution of Precision (GDP) under presence of periodic signals and temporally-correlated noise in the time series. We show, based on simulated and real time series from globally distributed IGS (International GNSS Service) stations processed by the Jet Propulsion Laboratory (JPL), that periodic signals dominate the effect on the velocity uncertainties at short time scales while for those beyond four years, the type of noise becomes much more

Signal Detection with Criterion Noise: Applications to Recognition Memory

ERIC Educational Resources Information Center

Benjamin, Aaron S.; Diaz, Michael; Wee, Serena

2009-01-01

A tacit but fundamental assumption of the theory of signal detection is that criterion placement is a noise-free process. This article challenges that assumption on theoretical and empirical grounds and presents the noisy decision theory of signal detection (ND-TSD). Generalized equations for the isosensitivity function and for measures of…

On noise treatment in radio measurements of cosmic ray air showers

NASA Astrophysics Data System (ADS)

Schröder, F. G.; Apel, W. D.; Arteaga, J. C.; Asch, T.; Bähren, L.; Bekk, K.; Bertaina, M.; Biermann, P. L.; Blümer, J.; Bozdog, H.; Brancus, I. M.; Buchholz, P.; Buitink, S.; Cantoni, E.; Chiavassa, A.; Daumiller, K.; de Souza, V.; Doll, P.; Engel, R.; Falcke, H.; Finger, M.; Fuhrmann, D.; Gemmeke, H.; Grupen, C.; Haungs, A.; Heck, D.; Hörandel, J. R.; Horneffer, A.; Huber, D.; Huege, T.; Isar, P. G.; Kampert, K.-H.; Kang, D.; Krömer, O.; Kuijpers, J.; Lafebre, S.; Link, K.; Łuczak, P.; Ludwig, M.; Mathes, H. J.; Melissas, M.; Morello, C.; Nehls, S.; Oehlschläger, J.; Palmieri, N.; Pierog, T.; Rautenberg, J.; Rebel, H.; Roth, M.; Rühle, C.; Saftoiu, A.; Schieler, H.; Schmidt, A.; Sima, O.; Toma, G.; Trinchero, G. C.; Weindl, A.; Wochele, J.; Wommer, M.; Zabierowski, J.; Zensus, J. A.

2012-01-01

Precise measurements of the radio emission by cosmic ray air showers require an adequate treatment of noise. Unlike to usual experiments in particle physics, where noise always adds to the signal, radio noise can in principle decrease or increase the signal if it interferes by chance destructively or constructively. Consequently, noise cannot simply be subtracted from the signal, and its influence on amplitude and time measurement of radio pulses must be studied with care. First, noise has to be determined consistently with the definition of the radio signal which typically is the maximum field strength of the radio pulse. Second, the average impact of noise on radio pulse measurements at individual antennas is studied for LOPES. It is shown that a correct treatment of noise is especially important at low signal-to-noise ratios: noise can be the dominant source of uncertainty for pulse height and time measurements, and it can systematically flatten the slope of lateral distributions. The presented method can also be transferred to other experiments in radio and acoustic detection of cosmic rays and neutrinos.

Image motion environments: background noise for movement-based animal signals.

PubMed

Peters, Richard; Hemmi, Jan; Zeil, Jochen

2008-05-01

Understanding the evolution of animal signals has to include consideration of the structure of signal and noise, and the sensory mechanisms that detect the signals. Considerable progress has been made in understanding sounds and colour signals, however, the degree to which movement-based signals are constrained by the particular patterns of environmental image motion is poorly understood. Here we have quantified the image motion generated by wind-blown plants at 12 sites in the coastal habitat of the Australian lizard Amphibolurus muricatus. Sampling across different plant communities and meteorological conditions revealed distinct image motion environments. At all locations, image motion became more directional and apparent speed increased as wind speeds increased. The magnitude of these changes and the spatial distribution of image motion, however, varied between locations probably as a function of plant structure and the topographic location. In addition, we show that the background motion noise depends strongly on the particular depth-structure of the environment and argue that such micro-habitat differences suggest specific strategies to preserve signal efficacy. Movement-based signals and motion processing mechanisms, therefore, may reveal the same type of habitat specific structural variation that we see for signals from other modalities.

An adaptive segment method for smoothing lidar signal based on noise estimation

NASA Astrophysics Data System (ADS)

Wang, Yuzhao; Luo, Pingping

2014-10-01

An adaptive segmentation smoothing method (ASSM) is introduced in the paper to smooth the signal and suppress the noise. In the ASSM, the noise is defined as the 3σ of the background signal. An integer number N is defined for finding the changing positions in the signal curve. If the difference of adjacent two points is greater than 3Nσ, the position is recorded as an end point of the smoothing segment. All the end points detected as above are recorded and the curves between them will be smoothed separately. In the traditional method, the end points of the smoothing windows in the signals are fixed. The ASSM creates changing end points in different signals and the smoothing windows could be set adaptively. The windows are always set as the half of the segmentations and then the average smoothing method will be applied in the segmentations. The Iterative process is required for reducing the end-point aberration effect in the average smoothing method and two or three times are enough. In ASSM, the signals are smoothed in the spacial area nor frequent area, that means the frequent disturbance will be avoided. A lidar echo was simulated in the experimental work. The echo was supposed to be created by a space-born lidar (e.g. CALIOP). And white Gaussian noise was added to the echo to act as the random noise resulted from environment and the detector. The novel method, ASSM, was applied to the noisy echo to filter the noise. In the test, N was set to 3 and the Iteration time is two. The results show that, the signal could be smoothed adaptively by the ASSM, but the N and the Iteration time might be optimized when the ASSM is applied in a different lidar.

Precision limits of lock-in amplifiers below unity signal-to-noise ratios

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gillies, G.T.; Allison, S.W.

1986-02-01

An investigation of noise-related performance limits of commercial-grade lock-in amplifiers has been carried out. The dependence of the output measurement error on the input signal-to-noise ratio was established in each case and measurements of noise-related gain variations were made.

Psychometric function for NU-6 word recognition in noise: effects of first language and dominant language.

PubMed

Shi, Lu-Feng; Zaki, Nancy A

2014-01-01

The present study attempted to establish psychometric function in individuals whose first language is not English. Psychometric function was obtained for one of the most commonly used clinical tests, the Northwestern University Auditory Test No. 6 (Tillman & Carhart 1966), so that findings could be directly applied to everyday clinical practice. Five groups of 14 normal-hearing, adult listeners differing in their first language and dominant language (English monolinguals, English- and Arabic-dominant Arabic-English bilinguals, and English- and Russian-dominant Russian-English bilinguals) participated. Both forms of the Northwestern University Auditory Test No. 6 test (8 lists of 50 monosyllabic English words) were presented. The lists were randomly assigned to eight signal-to-noise ratios (-3 to 18 dB in 3 dB steps). Listeners responded verbally and in writing. Psychometric functions were derived via logistic regression and described by two parameters: the 50% correct performance level (θ) and the slope (k). Both English-dominant bilingual groups obtained psychometric functions comparable with monolinguals. The θ and k of the functions for these three groups of participants were consistent with the literature. Compared with these three groups, non-English-dominant bilinguals' functions grew significantly more gradually (i.e., a significantly higher θ and a significantly lower k). No differences in either θ or k were found between bilinguals with the same dominant language but different first languages. Bilinguals reporting themselves to be dominant in English generate monolingual-like psychometric functions. By contrast, a different set of psychometric properties describes the function of bilinguals dominant in their first language. Because first language did not appear to be a significant factor in determining bilinguals' functions, it is concluded that English learning history and English proficiency are more important variables than first language for

An Application of Reassigned Time-Frequency Representations for Seismic Noise/Signal Decomposition

NASA Astrophysics Data System (ADS)

Mousavi, S. M.; Langston, C. A.

2016-12-01

Seismic data recorded by surface arrays are often strongly contaminated by unwanted noise. This background noise makes the detection of small magnitude events difficult. An automatic method for seismic noise/signal decomposition is presented based upon an enhanced time-frequency representation. Synchrosqueezing is a time-frequency reassignment method aimed at sharpening a time-frequency picture. Noise can be distinguished from the signal and suppressed more easily in this reassigned domain. The threshold level is estimated using a general cross validation approach that does not rely on any prior knowledge about the noise level. Efficiency of thresholding has been improved by adding a pre-processing step based on higher order statistics and a post-processing step based on adaptive hard-thresholding. In doing so, both accuracy and speed of the denoising have been improved compared to our previous algorithms (Mousavi and Langston, 2016a, 2016b; Mousavi et al., 2016). The proposed algorithm can either kill the noise (either white or colored) and keep the signal or kill the signal and keep the noise. Hence, It can be used in either normal denoising applications or in ambient noise studies. Application of the proposed method on synthetic and real seismic data shows the effectiveness of the method for denoising/designaling of local microseismic, and ocean bottom seismic data. References: Mousavi, S.M., C. A. Langston., and S. P. Horton (2016), Automatic Microseismic Denoising and Onset Detection Using the Synchrosqueezed-Continuous Wavelet Transform. Geophysics. 81, V341-V355, doi: 10.1190/GEO2015-0598.1. Mousavi, S.M., and C. A. Langston (2016a), Hybrid Seismic Denoising Using Higher-Order Statistics and Improved Wavelet Block Thresholding. Bull. Seismol. Soc. Am., 106, doi: 10.1785/0120150345. Mousavi, S.M., and C.A. Langston (2016b), Adaptive noise estimation and suppression for improving microseismic event detection, Journal of Applied Geophysics., doi: http

Signal enhancement in protein NMR using the spin-noise tuning optimum

PubMed Central

Nausner, Martin; Goger, Michael; Bendet-Taicher, Eli; Schlagnitweit, Judith

2010-01-01

We have assessed the potential of an alternative probe tuning strategy based on the spin-noise response for application in common high-resolution multi-dimensional biomolecular NMR experiments with water signal suppression on aqueous and salty samples. The method requires the adjustment of the optimal tuning condition, which may be offset by several 100 kHz from the conventional tuning settings using the noise response of the water protons as an indicator. Although the radio frequency-pulse durations are typically longer under such conditions, signal-to-noise gains of up to 22% were achieved. At salt concentrations up to 100 mM a substantial sensitivity gain was observed. PMID:20924647

Real Time Phase Noise Meter Based on a Digital Signal Processor

NASA Technical Reports Server (NTRS)

Angrisani, Leopoldo; D'Arco, Mauro; Greenhall, Charles A.; Schiano Lo Morille, Rosario

2006-01-01

A digital signal-processing meter for phase noise measurement on sinusoidal signals is dealt with. It enlists a special hardware architecture, made up of a core digital signal processor connected to a data acquisition board, and takes advantage of a quadrature demodulation-based measurement scheme, already proposed by the authors. Thanks to an efficient measurement process and an optimized implementation of its fundamental stages, the proposed meter succeeds in exploiting all hardware resources in such an effective way as to gain high performance and real-time operation. For input frequencies up to some hundreds of kilohertz, the meter is capable both of updating phase noise power spectrum while seamlessly capturing the analyzed signal into its memory, and granting as good frequency resolution as few units of hertz.

Active feedforward noise control and signal tracking of headsets: Electroacoustic analysis and system implementation.

PubMed

Bai, Mingsian R; Pan, Weichi; Chen, Hungyu

2018-03-01

Active noise control (ANC) of headsets is revisited in this paper. An in-depth electroacoustic analysis of the combined loudspeaker-cavity headset system is conducted on the basis of electro-mechano-acoustical analogous circuits. Model matching of the primary path and the secondary path leads to a feedforward control architecture. The ideal controller sheds some light on the key parameters that affect the noise reduction performance. Filtered-X least-mean-squares algorithm is employed to implement the feedforward controller on a digital signal processor. Since the relative delay of the primary path and the secondary path is crucial to the noise reduction performance, multirate signal processing with polyphase implementation is utilized to minimize the effective analog-digital conversion delay in the secondary path. Ad hoc decimation and interpolation filters are designed in order not to introduce excessive phase delays at the cutoff. Real-time experiments are undertaken to validate the implemented ANC system. Listening tests are also conducted to compare the fixed controller and the adaptive controller in terms of noise reduction and signal tracking performance for three noise types. The results have demonstrated that the fixed feedforward controller achieved satisfactory noise reduction performance and signal tracking quality.

Generalized stochastic resonance for a fractional harmonic oscillator with bias-signal-modulated trichotomous noise

NASA Astrophysics Data System (ADS)

Lin, Lifeng; Wang, Huiqi; Huang, Xipei; Wen, Yongxian

2018-03-01

For a fractional linear oscillator subjected to both parametric excitation of trichotomous noise and external excitation of bias-signal-modulated trichotomous noise, the generalized stochastic resonance (GSR) phenomena are investigated in this paper in case the noises are cross-correlative. First, the generalized Shapiro-Loginov formula and generalized fractional Shapiro-Loginov formula are derived. Then, by using the generalized (fractional) Shapiro-Loginov formula and the Laplace transformation technique, the exact expression of the first-order moment of the system’s steady response is obtained. The numerical results show that the evolution of the output amplitude amplification is nonmonotonic with the frequency of periodic signal, the noise parameters, and the fractional order. The GSR phenomena, including single-peak GSR, double-peak GSR and triple-peak GSR, are observed in this system. In addition, the interplay of the multiplicative trichotomous noise, bias-signal-modulated trichotomous noise and memory can induce and diversify the stochastic multi-resonance (SMR) phenomena, and the two kinds of trichotomous noises play opposite roles on the GSR.

Microwave oscillator with reduced phase noise by negative feedback incorporating microwave signals with suppressed carrier

NASA Technical Reports Server (NTRS)

Dick, G. J.; Saunders, J.

1989-01-01

Oscillator configurations which reduce the effect of 1/f noise sources for both direct feedback and stabilized local oscillator (STALO) circuits are developed and analyzed. By appropriate use of carrier suppression, a small signal is generated which suffers no loss of loop phase information or signal-to-noise ratio. This small signal can be amplified without degradation by multiplicative amplifier noise, and can be detected without saturation of the detector. Together with recent advances in microwave resonator Qs, these circuit improvements will make possible lower phase noise than can be presently achieved without the use of cryogenic devices.

Evaluating signal and noise spectral density of a qPlus sensor with an active feedback control

NASA Astrophysics Data System (ADS)

Lee, Manhee; An, Sangmin; Jhe, Wonho

2018-05-01

Q-control technique enables to actively change the quality factor of the probe oscillation in dynamic atomic force microscopy. The Q-control is realized by adding a self-feedback loop into the original actuation-detection system, in which a damping force with controllable damping coefficient in magnitude and sign is applied to the oscillating probe. While the applied force alters the total damping interaction and thus the overall `signal' of the probe motion, the added feedback system changes the `noise' of the motion as well. Here, we systematically investigate the signal, the noise, and the signal-to-noise ratio of the qPlus sensor under the active Q-control. We quantify the noise of the qPlus motion by measuring the noise spectral density, which is reproduced by a harmonic oscillator model including the thermal and the measurement noises. We show that the noise signal increases with the quality factor controlled, scaling as the square root of the quality factor. Because the overall signal is linearly proportional to the quality factor, the signal-to-noise ratio scales as the square root of the quality factor. The Q-controlled qPlus with a highly enhanced Q, up to 10,000 in air, leads to the minimum detectable force gradient of 0.001 N/m, which would enhance the capability of the qPlus sensor for atomic force microscopy and spectroscopy.

Effects of signal salience and noise on performance and stress in an abbreviated vigil

NASA Astrophysics Data System (ADS)

Helton, William Stokely

Vigilance or sustained attention tasks traditionally require observers to detect predetermined signals that occur unpredictably over periods of 30 min to several hours (Warm, 1984). These tasks are taxing and have been useful in revealing the effects of stress agents, such as infectious disease and drugs, on human performance (Alluisi, 1969; Damos & Parker, 1994; Warm, 1993). However, their long duration has been an inconvenience. Recently, Temple and his associates (Temple et al., 2000) developed an abbreviated 12-min vigilance task that duplicates many of the findings with longer duration vigils. The present study was designed to explore further the similarity of the abbreviated task to long-duration vigils by investigating the effects of signal salience and jet-aircraft engine noise on performance, operator stress, and coping strategies. Forty-eight observers (24 males and 24 females) were assigned at random to each of four conditions resulting from the factorial combination of signal salience (high and low contrast signals) and background noise (quiet and jet-aircraft noise). As is the case with long-duration vigils (Warm, 1993), signal detection in the abbreviated task was poorer for low salience than for high salience signals. In addition, stress scores, as indexed by the Dundee Stress State Questionnaire (Matthews, Joiner, Gilliland, Campbell, & Falconer, 1999), were elevated in the low as compared to the high salience condition. Unlike longer vigils, however, (Becker, Warm, Dember, & Hancock, 1996), signal detection in the abbreviated task was superior in the presence of aircraft noise than in quiet. Noise also attenuated the stress of the vigil, a result that is counter to previous findings regarding the effects of noise in a variety of other scenarios (Clark, 1984). Examination of observers' coping responses, as assessed by the Coping Inventory for Task Situations (Matthews & Campbell, 1998), indicated that problem-focused coping was the overwhelming

Signal-Preserving Erratic Noise Attenuation via Iterative Robust Sparsity-Promoting Filter

DOE PAGES

Zhao, Qiang; Du, Qizhen; Gong, Xufei; ...

2018-04-06

Sparse domain thresholding filters operating in a sparse domain are highly effective in removing Gaussian random noise under Gaussian distribution assumption. Erratic noise, which designates non-Gaussian noise that consists of large isolated events with known or unknown distribution, also needs to be explicitly taken into account. However, conventional sparse domain thresholding filters based on the least-squares (LS) criterion are severely sensitive to data with high-amplitude and non-Gaussian noise, i.e., the erratic noise, which makes the suppression of this type of noise extremely challenging. Here, in this paper, we present a robust sparsity-promoting denoising model, in which the LS criterion ismore » replaced by the Huber criterion to weaken the effects of erratic noise. The random and erratic noise is distinguished by using a data-adaptive parameter in the presented method, where random noise is described by mean square, while the erratic noise is downweighted through a damped weight. Different from conventional sparse domain thresholding filters, definition of the misfit between noisy data and recovered signal via the Huber criterion results in a nonlinear optimization problem. With the help of theoretical pseudoseismic data, an iterative robust sparsity-promoting filter is proposed to transform the nonlinear optimization problem into a linear LS problem through an iterative procedure. The main advantage of this transformation is that the nonlinear denoising filter can be solved by conventional LS solvers. Lastly, tests with several data sets demonstrate that the proposed denoising filter can successfully attenuate the erratic noise without damaging useful signal when compared with conventional denoising approaches based on the LS criterion.« less

Signal-Preserving Erratic Noise Attenuation via Iterative Robust Sparsity-Promoting Filter

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhao, Qiang; Du, Qizhen; Gong, Xufei

Sparse domain thresholding filters operating in a sparse domain are highly effective in removing Gaussian random noise under Gaussian distribution assumption. Erratic noise, which designates non-Gaussian noise that consists of large isolated events with known or unknown distribution, also needs to be explicitly taken into account. However, conventional sparse domain thresholding filters based on the least-squares (LS) criterion are severely sensitive to data with high-amplitude and non-Gaussian noise, i.e., the erratic noise, which makes the suppression of this type of noise extremely challenging. Here, in this paper, we present a robust sparsity-promoting denoising model, in which the LS criterion ismore » replaced by the Huber criterion to weaken the effects of erratic noise. The random and erratic noise is distinguished by using a data-adaptive parameter in the presented method, where random noise is described by mean square, while the erratic noise is downweighted through a damped weight. Different from conventional sparse domain thresholding filters, definition of the misfit between noisy data and recovered signal via the Huber criterion results in a nonlinear optimization problem. With the help of theoretical pseudoseismic data, an iterative robust sparsity-promoting filter is proposed to transform the nonlinear optimization problem into a linear LS problem through an iterative procedure. The main advantage of this transformation is that the nonlinear denoising filter can be solved by conventional LS solvers. Lastly, tests with several data sets demonstrate that the proposed denoising filter can successfully attenuate the erratic noise without damaging useful signal when compared with conventional denoising approaches based on the LS criterion.« less

Effect of signal jitter on the spectrum of rotor impulsive noise

NASA Technical Reports Server (NTRS)

Brooks, Thomas F.

1987-01-01

The effect of randomness or jitter of the acoustic waveform on the spectrum of rotor impulsive noise is studied because of its importance for data interpretation. An acoustic waveform train is modelled representing rotor impulsive noise. The amplitude, shape, and period between occurrences of individual pulses are allowed to be randomized assuming normal probability distributions. Results, in terms of the standard deviations of the variable quantities, are given for the autospectrum as well as special processed spectra designed to separate harmonic and broadband rotor noise components. Consideration is given to the effect of accuracy in triggering or keying to a rotor one per revolution signal. An example is given showing the resultant spectral smearing at the high frequencies due to the pulse signal period variability.

Effect of signal jitter on the spectrum of rotor impulsive noise

NASA Technical Reports Server (NTRS)

Brooks, Thomas F.

1988-01-01

The effect of randomness or jitter of the acoustic waveform on the spectrum of rotor impulsive noise is studied because of its importance for data interpretation. An acoustic waveform train is modeled representing rotor impulsive noise. The amplitude, shape, and period between occurrences of individual pulses are allowed to be randomized assuming normal probability distributions. Results, in terms of the standard deviations of the variable quantities, are given for the autospectrum as well as special processed spectra designed to separate harmonic and broadband rotor noise components. Consideration is given to the effect of accuracy in triggering or keying to a rotor one per revolution signal. An example is given showing the resultant spectral smearing at the high frequencies due to the pulse signal period variability.

Signal detection in power-law noise: effect of spectrum exponents.

PubMed

Burgess, Arthur E; Judy, Philip F

2007-12-01

Many natural backgrounds have approximately isotropic power spectra of the power-law form, P(f)=K/f(beta), where f is radial frequency. For natural scenes and mammograms, the values of the exponent, beta, range from 1.5 to 3.5. The ideal observer model predicts that for signals with certain properties and backgrounds that can be treated as random noise, a plot of log (contrast threshold) versus log (signal size) will be linear with slope, m, given by: m=(beta-2)/2. This plot is referred to as a contrast-detail (CD) diagram. It is interesting that this predicts a detection threshold that is independent of signal size for beta equal to 2. We present two-alternative forced-choice (2AFC) detection results for human and channelized model observers of a simple signal in filtered noise with exponents from 1.5 to 3.5. The CD diagram results are in good agreement with the prediction of this equation.

Signal-to-noise ratio for the wide field-planetary camera of the Space Telescope

NASA Technical Reports Server (NTRS)

Zissa, D. E.

1984-01-01

Signal-to-noise ratios for the Wide Field Camera and Planetary Camera of the Space Telescope were calculated as a function of integration time. Models of the optical systems and CCD detector arrays were used with a 27th visual magnitude point source and a 25th visual magnitude per arc-sq. second extended source. A 23rd visual magnitude per arc-sq. second background was assumed. The models predicted signal-to-noise ratios of 10 within 4 hours for the point source centered on a signal pixel. Signal-to-noise ratios approaching 10 are estimated for approximately 0.25 x 0.25 arc-second areas within the extended source after 10 hours integration.

Relationship Among Signal Fidelity, Hearing Loss, and Working Memory for Digital Noise Suppression.

PubMed

Arehart, Kathryn; Souza, Pamela; Kates, James; Lunner, Thomas; Pedersen, Michael Syskind

2015-01-01

This study considered speech modified by additive babble combined with noise-suppression processing. The purpose was to determine the relative importance of the signal modifications, individual peripheral hearing loss, and individual cognitive capacity on speech intelligibility and speech quality. The participant group consisted of 31 individuals with moderate high-frequency hearing loss ranging in age from 51 to 89 years (mean = 69.6 years). Speech intelligibility and speech quality were measured using low-context sentences presented in babble at several signal-to-noise ratios. Speech stimuli were processed with a binary mask noise-suppression strategy with systematic manipulations of two parameters (error rate and attenuation values). The cumulative effects of signal modification produced by babble and signal processing were quantified using an envelope-distortion metric. Working memory capacity was assessed with a reading span test. Analysis of variance was used to determine the effects of signal processing parameters on perceptual scores. Hierarchical linear modeling was used to determine the role of degree of hearing loss and working memory capacity in individual listener response to the processed noisy speech. The model also considered improvements in envelope fidelity caused by the binary mask and the degradations to envelope caused by error and noise. The participants showed significant benefits in terms of intelligibility scores and quality ratings for noisy speech processed by the ideal binary mask noise-suppression strategy. This benefit was observed across a range of signal-to-noise ratios and persisted when up to a 30% error rate was introduced into the processing. Average intelligibility scores and average quality ratings were well predicted by an objective metric of envelope fidelity. Degree of hearing loss and working memory capacity were significant factors in explaining individual listener's intelligibility scores for binary mask processing

Multi-Aperture-Based Probabilistic Noise Reduction of Random Telegraph Signal Noise and Photon Shot Noise in Semi-Photon-Counting Complementary-Metal-Oxide-Semiconductor Image Sensor

PubMed Central

Ishida, Haruki; Kagawa, Keiichiro; Komuro, Takashi; Zhang, Bo; Seo, Min-Woong; Takasawa, Taishi; Yasutomi, Keita; Kawahito, Shoji

2018-01-01

A probabilistic method to remove the random telegraph signal (RTS) noise and to increase the signal level is proposed, and was verified by simulation based on measured real sensor noise. Although semi-photon-counting-level (SPCL) ultra-low noise complementary-metal-oxide-semiconductor (CMOS) image sensors (CISs) with high conversion gain pixels have emerged, they still suffer from huge RTS noise, which is inherent to the CISs. The proposed method utilizes a multi-aperture (MA) camera that is composed of multiple sets of an SPCL CIS and a moderately fast and compact imaging lens to emulate a very fast single lens. Due to the redundancy of the MA camera, the RTS noise is removed by the maximum likelihood estimation where noise characteristics are modeled by the probability density distribution. In the proposed method, the photon shot noise is also relatively reduced because of the averaging effect, where the pixel values of all the multiple apertures are considered. An extremely low-light condition that the maximum number of electrons per aperture was the only 2e− was simulated. PSNRs of a test image for simple averaging, selective averaging (our previous method), and the proposed method were 11.92 dB, 11.61 dB, and 13.14 dB, respectively. The selective averaging, which can remove RTS noise, was worse than the simple averaging because it ignores the pixels with RTS noise and photon shot noise was less improved. The simulation results showed that the proposed method provided the best noise reduction performance. PMID:29587424

Hardware Design and Implementation of a Wavelet De-Noising Procedure for Medical Signal Preprocessing

PubMed Central

Chen, Szi-Wen; Chen, Yuan-Ho

2015-01-01

In this paper, a discrete wavelet transform (DWT) based de-noising with its applications into the noise reduction for medical signal preprocessing is introduced. This work focuses on the hardware realization of a real-time wavelet de-noising procedure. The proposed de-noising circuit mainly consists of three modules: a DWT, a thresholding, and an inverse DWT (IDWT) modular circuits. We also proposed a novel adaptive thresholding scheme and incorporated it into our wavelet de-noising procedure. Performance was then evaluated on both the architectural designs of the software and. In addition, the de-noising circuit was also implemented by downloading the Verilog codes to a field programmable gate array (FPGA) based platform so that its ability in noise reduction may be further validated in actual practice. Simulation experiment results produced by applying a set of simulated noise-contaminated electrocardiogram (ECG) signals into the de-noising circuit showed that the circuit could not only desirably meet the requirement of real-time processing, but also achieve satisfactory performance for noise reduction, while the sharp features of the ECG signals can be well preserved. The proposed de-noising circuit was further synthesized using the Synopsys Design Compiler with an Artisan Taiwan Semiconductor Manufacturing Company (TSMC, Hsinchu, Taiwan) 40 nm standard cell library. The integrated circuit (IC) synthesis simulation results showed that the proposed design can achieve a clock frequency of 200 MHz and the power consumption was only 17.4 mW, when operated at 200 MHz. PMID:26501290

Hardware design and implementation of a wavelet de-noising procedure for medical signal preprocessing.

PubMed

Chen, Szi-Wen; Chen, Yuan-Ho

2015-10-16

In this paper, a discrete wavelet transform (DWT) based de-noising with its applications into the noise reduction for medical signal preprocessing is introduced. This work focuses on the hardware realization of a real-time wavelet de-noising procedure. The proposed de-noising circuit mainly consists of three modules: a DWT, a thresholding, and an inverse DWT (IDWT) modular circuits. We also proposed a novel adaptive thresholding scheme and incorporated it into our wavelet de-noising procedure. Performance was then evaluated on both the architectural designs of the software and. In addition, the de-noising circuit was also implemented by downloading the Verilog codes to a field programmable gate array (FPGA) based platform so that its ability in noise reduction may be further validated in actual practice. Simulation experiment results produced by applying a set of simulated noise-contaminated electrocardiogram (ECG) signals into the de-noising circuit showed that the circuit could not only desirably meet the requirement of real-time processing, but also achieve satisfactory performance for noise reduction, while the sharp features of the ECG signals can be well preserved. The proposed de-noising circuit was further synthesized using the Synopsys Design Compiler with an Artisan Taiwan Semiconductor Manufacturing Company (TSMC, Hsinchu, Taiwan) 40 nm standard cell library. The integrated circuit (IC) synthesis simulation results showed that the proposed design can achieve a clock frequency of 200 MHz and the power consumption was only 17.4 mW, when operated at 200 MHz.

Optimization of noise in non-integrated instrumentation amplifier for the amplification of very low electrophysiological [corrected] signals. Case of electro cardio graphic signals (ECG).

PubMed

Ngounou, Guy Merlin; Kom, Martin

2014-12-01

In this paper we present an instrumentation amplifier with discrete elements and optimized noise for the amplification of very low signals. In amplifying signals of very weak amplitude, the noise can completely absorb these signals if the used amplifier does not present the optimal guarantee to minimize the noise. Based on related research and re-viewing of recent patents Journal of Medical Systems, 30:205-209, 2006, we suggest an approach of noise reduction in amplification much more thoroughly than re-viewing of recent patents and we deduce from it the general criteria necessary and essential to achieve this optimization. The comparison of these criteria with the provisions adopted in practice leads to the inadequacy of conventional amplifiers for effective noise reduction. The amplifier we propose is an instrumentation amplifier with active negative feedback and optimized noise for the amplification of signals with very low amplitude. The application of this method in the case of electro cardio graphic signals (ECG) provides simulation results fully in line with forecasts.

Motor noise is rich signal in autism research and pharmacological treatments.

PubMed

Torres, E B; Denisova, K

2016-11-21

The human body is in constant motion, from every breath that we take, to every visibly purposeful action that we perform. Remaining completely still on command is a major achievement as involuntary fluctuations in our motions are difficult to keep under control. Here we examine the noise-to-signal ratio of micro-movements present in time-series of head motions extracted from resting-state functional magnetic resonance imaging scans in 1048 participants. These included individuals with autism spectrum disorders (ASD) and healthy-controls in shared data from the Autism Brain Imaging Data Exchange (ABIDE) and the Attention-Deficit Hyperactivity Disorder (ADHD-200) databases. We find excess noise and randomness in the ASD cases, suggesting an uncertain motor-feedback signal. A power-law emerged describing an orderly relation between the dispersion and shape of the probability distribution functions best describing the stochastic properties under consideration with respect to intelligence quotient (IQ-scores). In ASD, deleterious patterns of noise are consistently exacerbated with the presence of secondary (comorbid) neuropsychiatric diagnoses, lower verbal and performance intelligence, and autism severity. Importantly, such patterns in ASD are present whether or not the participant takes psychotropic medication. These data unambiguously establish specific noise-to-signal levels of head micro-movements as a biologically informed core feature of ASD.

Radar antenna pointing for optimized signal to noise ratio.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Doerry, Armin Walter; Marquette, Brandeis

2013-01-01

The Signal-to-Noise Ratio (SNR) of a radar echo signal will vary across a range swath, due to spherical wavefront spreading, atmospheric attenuation, and antenna beam illumination. The antenna beam illumination will depend on antenna pointing. Calculations of geometry are complicated by the curved earth, and atmospheric refraction. This report investigates optimizing antenna pointing to maximize the minimum SNR across the range swath.

Signal/noise analysis to compare tests for measuring visual field loss and its progression.

PubMed

Artes, Paul H; Chauhan, Balwantray C

2009-10-01

To describe a methodology for establishing signal-to-noise ratios (SNRs) for different perimetric techniques, and to compare SNRs of frequency-doubling technology (FDT2) perimetry and standard automated perimetry (SAP). Fifteen patients with open-angle glaucoma (median MD, -2.6 dB, range +0.2 to -16.1 dB) were tested six times with FDT2 and SAP (SITA Standard program 24-2) within a 4-week period. Signals were estimated from the average superior-inferior difference between the mean deviation (MD) values in five mirror-pair sectors of the Glaucoma Hemifield Test, and noise from the dispersion of these differences over the six repeated tests. SNRs of FDT2 and SAP were compared by mixed-effects modeling. There was moderate correlation between the signals of FDT2 and SAP (r(2) = 0.68, P < 0.001), but no correlation of noise (r(2) = 0.01, P = 0.16). Although both signal as well as noise estimates were higher with FDT2 compared with SAP, 60% to 70% of sector pairs showed higher SNRs with FDT2. The SNRs of FDT2 were between 20% and 40% higher than those of SAP (P = 0.01). There were no meaningful differences between parametric and nonparametric estimates of signal, noise, or SNR. The higher SNRs of FDT2 suggest that this technique is at least as efficient as SAP at detecting localized visual field losses. Signal/noise analyses may provide a useful approach for comparing visual field tests independent of their decibel scales and may provide an initial indication of sensitivity to visual field change over time.

Table look-up estimation of signal and noise parameters from quantized observables

NASA Technical Reports Server (NTRS)

Vilnrotter, V. A.; Rodemich, E. R.

1986-01-01

A table look-up algorithm for estimating underlying signal and noise parameters from quantized observables is examined. A general mathematical model is developed, and a look-up table designed specifically for estimating parameters from four-bit quantized data is described. Estimator performance is evaluated both analytically and by means of numerical simulation, and an example is provided to illustrate the use of the look-up table for estimating signal-to-noise ratios commonly encountered in Voyager-type data.

IIR digital filter design for powerline noise cancellation of ECG signal using arduino platform

NASA Astrophysics Data System (ADS)

Rahmatillah, Akif; Ataulkarim

2017-05-01

Powerline noise has been one of significant noises of Electrocardiogram (ECG) signal measurement. This noise is characterized by a sinusoidal signal which has 50 Hz of noise and 0.3 mV of maximum amplitude. This paper describes the design of IIR Notch filter design to reject a 50 Hz power line noise. IIR filter coefficients were calculated using pole placement method with three variations of band stop cut off frequencies of (49-51)Hz, (48 - 52)Hz, and (47 - 53)Hz. The algorithm and coefficients of filter were embedded to Arduino DUE (ARM 32 bit microcontroller). IIR notch filter designed has been able to reject power line noise with average square of error value of 0.225 on (49-51) Hz filter design and 0.2831 on (48 - 52)Hz filter design.

Discretization in time gives rise to noise-induced improvement of the signal-to-noise ratio in static nonlinearities.

PubMed

Davidović, A; Huntington, E H; Frater, M R

2009-07-01

For some nonlinear systems the performance can improve with an increasing noise level. Such noise-induced improvement in static nonlinearities is of great interest for practical applications since many systems can be modeled in that way (e.g., sensors, quantizers, limiters, etc.). We present experimental evidence that noise-induced performance improvement occurs in those systems as a consequence of discretization in time with the achievable signal-to-noise ratio (SNR) gain increasing with decreasing ratio of input noise bandwidth and total measurement bandwidth. By modifying the input noise bandwidth, noise-induced improvement with SNR gain larger than unity is demonstrated in a system where it was not previously thought possible. Our experimental results bring closer two different theoretical models for the same class of nonlinearities and shed light on the behavior of static nonlinear discrete-time systems.

Desired Accuracy Estimation of Noise Function from ECG Signal by Fuzzy Approach

PubMed Central

Vahabi, Zahra; Kermani, Saeed

2012-01-01

Unknown noise and artifacts present in medical signals with non-linear fuzzy filter will be estimated and then removed. An adaptive neuro-fuzzy interference system which has a non-linear structure presented for the noise function prediction by before Samples. This paper is about a neuro-fuzzy method to estimate unknown noise of Electrocardiogram signal. Adaptive neural combined with Fuzzy System to construct a fuzzy Predictor. For this system setting parameters such as the number of Membership Functions for each input and output, training epochs, type of MFs for each input and output, learning algorithm and etc. is determined by learning data. At the end simulated experimental results are presented for proper validation. PMID:23717810

Using hyperentanglement to enhance resolution, signal-to-noise ratio, and measurement time

NASA Astrophysics Data System (ADS)

Smith, James F.

2017-03-01

A hyperentanglement-based atmospheric imaging/detection system involving only a signal and an ancilla photon will be considered for optical and infrared frequencies. Only the signal photon will propagate in the atmosphere and its loss will be classical. The ancilla photon will remain within the sensor experiencing low loss. Closed form expressions for the wave function, normalization, density operator, reduced density operator, symmetrized logarithmic derivative, quantum Fisher information, quantum Cramer-Rao lower bound, coincidence probabilities, probability of detection, probability of false alarm, probability of error after M measurements, signal-to-noise ratio, quantum Chernoff bound, time-on-target expressions related to probability of error, and resolution will be provided. The effect of noise in every mode will be included as well as loss. The system will provide the basic design for an imaging/detection system functioning at optical or infrared frequencies that offers better than classical angular and range resolution. Optimization for enhanced resolution will be included. The signal-to-noise ratio will be increased by a factor equal to the number of modes employed during the hyperentanglement process. Likewise, the measurement time can be reduced by the same factor. The hyperentanglement generator will typically make use of entanglement in polarization, energy-time, orbital angular momentum and so on. Mathematical results will be provided describing the system's performance as a function of loss mechanisms and noise.

Eye Dominance Predicts fMRI Signals in Human Retinotopic Cortex

PubMed Central

Mendola, Janine D.; Conner, Ian P.

2009-01-01

There have been many attempts to define eye dominance in normal subjects, but limited consensus exists, and relevant physiological data is scarce. In this study, we consider two different behavioral methods for assignment of eye dominance, and how well they predict fMRI signals evoked by monocular stimulation. Sighting eye dominance was assessed with two standard tests, the Porta Test, and a ‘hole in hand’ variation of the Miles Test. Acuity dominance was tested with a standard eye chart and with a computerized test of grating acuity. We found limited agreement between the sighting and acuity methods for assigning dominance in our individual subjects. We then compared the fMRI response generated by dominant eye stimulation to that generated by non-dominant eye, according to both methods, in 7 normal subjects. The stimulus consisted of a high contrast hemifield stimulus alternating with no stimulus in a blocked paradigm. In separate scans, we used standard techniques to label the borders of visual areas V1, V2, V3, VP, V4, V3A, and MT. These regions of interest (ROIs) were used to analyze each visual area separately. We found that percent change in fMRI BOLD signal was stronger for the dominant eye as defined by the acuity method, and this effect was significant for areas located in the ventral occipital territory (V1v, V2v, VP, V4). In contrast, assigning dominance based on sighting produced no significant interocular BOLD differences. We conclude that interocular BOLD differences in normal subjects exist, and may be predicted by acuity measures. PMID:17194544

Ultralow-phase-noise millimetre-wave signal generator assisted with an electro-optics-modulator-based optical frequency comb

PubMed Central

Ishizawa, A.; Nishikawa, T.; Goto, T.; Hitachi, K.; Sogawa, T.; Gotoh, H.

2016-01-01

Low-noise millimetre-wave signals are valuable for digital sampling systems, arbitrary waveform generation for ultra-wideband communications, and coherent radar systems. However, the phase noise of widely used conventional signal generators (SGs) will increase as the millimetre-wave frequency increases. Our goal has been to improve commercially available SGs so that they provide a low-phase-noise millimetre-wave signal with assistance from an electro-optics-modulator-based optical frequency comb (EOM-OFC). Here, we show that the phase noise can be greatly reduced by bridging the vast frequency difference between the gigahertz and terahertz ranges with an EOM-OFC. The EOM-OFC serves as a liaison that magnifies the phase noise of the SG. With the EOM-OFC used as a phase noise “booster” for a millimetre-wave signal, the phase noise of widely used SGs can be reduced at an arbitrary frequency f (6 ≦ f ≦ 72 GHz). PMID:27185040

Modeling Signal-to-Noise Ratio of Otoacoustic Emissions in Workers Exposed to Different Industrial Noise Levels

PubMed Central

Nassiri, Parvin; Zare, Sajad; Monazzam, Mohammad R.; Pourbakht, Akram; Azam, Kamal; Golmohammadi, Taghi

2016-01-01

Introduction: Noise is considered as the most common cause of harmful physical effects in the workplace. A sound that is generated from within the inner ear is known as an otoacoustic emission (OAE). Distortion-product otoacoustic emissions (DPOAEs) assess evoked emission and hearing capacity. The aim of this study was to assess the signal-to-noise ratio in different frequencies and at different times of the shift work in workers exposed to various levels of noise. It was also aimed to provide a statistical model for signal-to-noise ratio (SNR) of OAEs in different frequencies based on the two variables of sound pressure level (SPL) and exposure time. Materials and Methods: This case–control study was conducted on 45 workers during autumn 2014. The workers were divided into three groups based on the level of noise exposure. The SNR was measured in frequencies of 1000, 2000, 3000, 4000, and 6000 Hz in both ears, and in three different time intervals during the shift work. According to the inclusion criterion, SNR of 6 dB or greater was included in the study. The analysis was performed using repeated measurements of analysis of variance, spearman correlation coefficient, and paired samples t-test. Results: The results showed that there was no statistically significant difference between the three exposed groups in terms of the mean values of SNR (P > 0.05). Only in signal pressure levels of 88 dBA with an interval time of 10:30–11:00 AM, there was a statistically significant difference between the right and left ears with the mean SNR values of 3000 frequency (P = 0.038). The SPL had a significant effect on the SNR in both the right and left ears (P = 0.023, P = 0.041). The effect of the duration of measurement on the SNR was statistically significant in both the right and left ears (P = 0.027, P < 0.001). Conclusion: The findings of this study demonstrated that after noise exposure during the shift, SNR of OAEs reduced from the beginning to the end of the shift

Signal-noise separation based on self-similarity testing in 1D-timeseries data

NASA Astrophysics Data System (ADS)

Bourdin, Philippe A.

2015-08-01

The continuous improvement of the resolution delivered by modern instrumentation is a cost-intensive part of any new space- or ground-based observatory. Typically, scientists later reduce the resolution of the obtained raw-data, for example in the spatial, spectral, or temporal domain, in order to suppress the effects of noise in the measurements. In practice, only simple methods are used that just smear out the noise, instead of trying to remove it, so that the noise can nomore be seen. In high-precision 1D-timeseries data, this usually results in an unwanted quality-loss and corruption of power spectra at selected frequency ranges. Novel methods exist that are based on non-local averaging, which would conserve much of the initial resolution, but these methods are so far focusing on 2D or 3D data. We present here a method specialized for 1D-timeseries, e.g. as obtained by magnetic field measurements from the recently launched MMS satellites. To identify the noise, we use a self-similarity testing and non-local averaging method in order to separate different types of noise and signals, like the instrument noise, non-correlated fluctuations in the signal from heliospheric sources, and correlated fluctuations such as harmonic waves or shock fronts. In power spectra of test data, we are able to restore significant parts of a previously know signal from a noisy measurement. This method also works for high frequencies, where the background noise may have a larger contribution to the spectral power than the signal itself. We offer an easy-to-use software tools set, which enables scientists to use this novel technique on their own noisy data. This allows to use the maximum possible capacity of the instrumental hardware and helps to enhance the quality of the obtained scientific results.

Time-Distance Helioseismology: Noise Estimation

NASA Astrophysics Data System (ADS)

Gizon, L.; Birch, A. C.

2004-10-01

As in global helioseismology, the dominant source of noise in time-distance helioseismology measurements is realization noise due to the stochastic nature of the excitation mechanism of solar oscillations. Characterizing noise is important for the interpretation and inversion of time-distance measurements. In this paper we introduce a robust definition of travel time that can be applied to very noisy data. We then derive a simple model for the full covariance matrix of the travel-time measurements. This model depends only on the expectation value of the filtered power spectrum and assumes that solar oscillations are stationary and homogeneous on the solar surface. The validity of the model is confirmed through comparison with SOHO MDI measurements in a quiet-Sun region. We show that the correlation length of the noise in the travel times is about half the dominant wavelength of the filtered power spectrum. We also show that the signal-to-noise ratio in quiet-Sun travel-time maps increases roughly as the square root of the observation time and is at maximum for a distance near half the length scale of supergranulation.

Increasing signal-to-noise ratio of swept-source optical coherence tomography by oversampling in k-space

NASA Astrophysics Data System (ADS)

Nagib, Karim; Mezgebo, Biniyam; Thakur, Rahul; Fernando, Namal; Kordi, Behzad; Sherif, Sherif

2018-03-01

Optical coherence tomography systems suffer from noise that could reduce ability to interpret reconstructed images correctly. We describe a method to increase the signal-to-noise ratio of swept-source optical coherence tomography (SSOCT) using oversampling in k-space. Due to this oversampling, information redundancy would be introduced in the measured interferogram that could be used to reduce white noise in the reconstructed A-scan. We applied our novel scaled nonuniform discrete Fourier transform to oversampled SS-OCT interferograms to reconstruct images of a salamander egg. The peak-signal-to-noise (PSNR) between the reconstructed images using interferograms sampled at 250MS/s andz50MS/s demonstrate that this oversampling increased the signal-to-noise ratio by 25.22 dB.

Symbol signal-to-noise ratio loss in square-wave subcarrier downconversion

NASA Technical Reports Server (NTRS)

Feria, Y.; Statman, J.

1993-01-01

This article presents the simulated results of the signal-to-noise ratio (SNR) loss in the process of a square-wave subcarrier down conversion. In a previous article, the SNR degradation was evaluated at the output of the down converter based on the signal and noise power change. Unlike in the previous article, the SNR loss is defined here as the difference between the actual and theoretical symbol SNR's for the same symbol-error rate at the output of the symbol matched filter. The results show that an average SNR loss of 0.3 dB can be achieved with tenth-order infinite impulse response (IIR) filters. This loss is a 0.2-dB increase over the SNR degradation in the previous analysis where neither the signal distortion nor the symbol detector was considered.

Development of an ultra low noise, miniature signal conditioning device for vestibular evoked response recordings

PubMed Central

2014-01-01

Background Inner ear evoked potentials are small amplitude (<1 μVpk) signals that require a low noise signal acquisition protocol for successful extraction; an existing such technique is Electrocochleography (ECOG). A novel variant of ECOG called Electrovestibulography (EVestG) is currently investigated by our group, which captures vestibular responses to a whole body tilt. The objective is to design and implement a bio-signal amplifier optimized for ECOG and EVestG, which will be superior in noise performance compared to low noise, general purpose devices available commercially. Method A high gain configuration is required (>85 dB) for such small signal recordings; thus, background power line interference (PLI) can have adverse effects. Active electrode shielding and driven-right-leg circuitry optimized for EVestG/ECOG recordings were investigated for PLI suppression. A parallel pre-amplifier design approach was investigated to realize low voltage, and current noise figures for the bio-signal amplifier. Results In comparison to the currently used device, PLI is significantly suppressed by the designed prototype (by >20 dB in specific test scenarios), and the prototype amplifier generated noise was measured to be 4.8 nV/Hz @ 1 kHz (0.45 μVRMS with bandwidth 10 Hz-10 kHz), which is lower than the currently used device generated noise of 7.8 nV/Hz @ 1 kHz (0.76 μVRMS). A low noise (<1 nV/Hz) radio frequency interference filter was realized to minimize noise contribution from the pre-amplifier, while maintaining the required bandwidth in high impedance measurements. Validation of the prototype device was conducted for actual ECOG recordings on humans that showed an increase (p < 0.05) of ~5 dB in Signal-to-Noise ratio (SNR), and for EVestG recordings using a synthetic ear model that showed a ~4% improvement (p < 0.01) over the currently used amplifier. Conclusion This paper presents the design and evaluation of an ultra-low noise and miniaturized bio-signal

Signal and noise modeling in confocal laser scanning fluorescence microscopy.

PubMed

Herberich, Gerlind; Windoffer, Reinhard; Leube, Rudolf E; Aach, Til

2012-01-01

Fluorescence confocal laser scanning microscopy (CLSM) has revolutionized imaging of subcellular structures in biomedical research by enabling the acquisition of 3D time-series of fluorescently-tagged proteins in living cells, hence forming the basis for an automated quantification of their morphological and dynamic characteristics. Due to the inherently weak fluorescence, CLSM images exhibit a low SNR. We present a novel model for the transfer of signal and noise in CLSM that is both theoretically sound as well as corroborated by a rigorous analysis of the pixel intensity statistics via measurement of the 3D noise power spectra, signal-dependence and distribution. Our model provides a better fit to the data than previously proposed models. Further, it forms the basis for (i) the simulation of the CLSM imaging process indispensable for the quantitative evaluation of CLSM image analysis algorithms, (ii) the application of Poisson denoising algorithms and (iii) the reconstruction of the fluorescence signal.

Noise reduction in functional near-infrared spectroscopy signals by independent component analysis

NASA Astrophysics Data System (ADS)

Santosa, Hendrik; Jiyoun Hong, Melissa; Kim, Sung-Phil; Hong, Keum-Shik

2013-07-01

Functional near-infrared spectroscopy (fNIRS) is used to detect concentration changes of oxy-hemoglobin and deoxy-hemoglobin in the human brain. The main difficulty entailed in the analysis of fNIRS signals is the fact that the hemodynamic response to a specific neuronal activation is contaminated by physiological and instrument noises, motion artifacts, and other interferences. This paper proposes independent component analysis (ICA) as a means of identifying the original hemodynamic response in the presence of noises. The original hemodynamic response was reconstructed using the primary independent component (IC) and other, less-weighting-coefficient ICs. In order to generate experimental brain stimuli, arithmetic tasks were administered to eight volunteer subjects. The t-value of the reconstructed hemodynamic response was improved by using the ICs found in the measured data. The best t-value out of 16 low-pass-filtered signals was 37, and that of the reconstructed one was 51. Also, the average t-value of the eight subjects' reconstructed signals was 40, whereas that of all of their low-pass-filtered signals was only 20. Overall, the results showed the applicability of the ICA-based method to noise-contamination reduction in brain mapping.

Networking Sensors for Information Dominance - Joint Signal Processing and Communication Design

DTIC Science & Technology

2012-01-01

2012 4. TITLE AND SUBTITLE NETWORKING SENSORS FOR INFORMATION DOMINANCE - JOINT SIGNAL PROCESSING AND COMMUNICATION DESIGN, Final Report for FA9550...Rev. 2-89) Prescribed by ANSI Std. Z39-18 298-102 Public A AFRL-OSR-VA-TR-2012-0729 NETWORKING SENSORS FOR INFORMATION DOMINANCE - JOINT

Differential Effects of Noise and Music Signals on the Behavior of Children

NASA Astrophysics Data System (ADS)

ANDO, Y.

2001-03-01

A theory based on the model of how the auditory-brain system perceive primary sensations is used to explain the differential effects of noise and music signals on the sleep of babies and on the performance of mental tasks by children. In a previous study by Ando and Hattori, [1], it was found that sleeping babies (2-4 months old) whose mothers had begun living in a noisy area before conception or during the first five months of pregnancy did not react to daily aircraft noise but did react to music. In another previous study by Ando et al.[2], the percentage of the pupils in "V-type relaxation" state during an adding task in a quiet living area was much greater when pupils heard music than when they heard noise. These phenomena are explained here by the difference between the temporal factors extracted from the running autocorrelation function of the noise and music signals.

Identifying early-warning signals of critical transitions with strong noise by dynamical network markers

PubMed Central

Liu, Rui; Chen, Pei; Aihara, Kazuyuki; Chen, Luonan

2015-01-01

Identifying early-warning signals of a critical transition for a complex system is difficult, especially when the target system is constantly perturbed by big noise, which makes the traditional methods fail due to the strong fluctuations of the observed data. In this work, we show that the critical transition is not traditional state-transition but probability distribution-transition when the noise is not sufficiently small, which, however, is a ubiquitous case in real systems. We present a model-free computational method to detect the warning signals before such transitions. The key idea behind is a strategy: “making big noise smaller” by a distribution-embedding scheme, which transforms the data from the observed state-variables with big noise to their distribution-variables with small noise, and thus makes the traditional criteria effective because of the significantly reduced fluctuations. Specifically, increasing the dimension of the observed data by moment expansion that changes the system from state-dynamics to probability distribution-dynamics, we derive new data in a higher-dimensional space but with much smaller noise. Then, we develop a criterion based on the dynamical network marker (DNM) to signal the impending critical transition using the transformed higher-dimensional data. We also demonstrate the effectiveness of our method in biological, ecological and financial systems. PMID:26647650

Using temporal ICA to selectively remove global noise while preserving global signal in functional MRI data.

PubMed

Glasser, Matthew F; Coalson, Timothy S; Bijsterbosch, Janine D; Harrison, Samuel J; Harms, Michael P; Anticevic, Alan; Van Essen, David C; Smith, Stephen M

2018-06-02

Temporal fluctuations in functional Magnetic Resonance Imaging (fMRI) have been profitably used to study brain activity and connectivity for over two decades. Unfortunately, fMRI data also contain structured temporal "noise" from a variety of sources, including subject motion, subject physiology, and the MRI equipment. Recently, methods have been developed to automatically and selectively remove spatially specific structured noise from fMRI data using spatial Independent Components Analysis (ICA) and machine learning classifiers. Spatial ICA is particularly effective at removing spatially specific structured noise from high temporal and spatial resolution fMRI data of the type acquired by the Human Connectome Project and similar studies. However, spatial ICA is mathematically, by design, unable to separate spatially widespread "global" structured noise from fMRI data (e.g., blood flow modulations from subject respiration). No methods currently exist to selectively and completely remove global structured noise while retaining the global signal from neural activity. This has left the field in a quandary-to do or not to do global signal regression-given that both choices have substantial downsides. Here we show that temporal ICA can selectively segregate and remove global structured noise while retaining global neural signal in both task-based and resting state fMRI data. We compare the results before and after temporal ICA cleanup to those from global signal regression and show that temporal ICA cleanup removes the global positive biases caused by global physiological noise without inducing the network-specific negative biases of global signal regression. We believe that temporal ICA cleanup provides a "best of both worlds" solution to the global signal and global noise dilemma and that temporal ICA itself unlocks interesting neurobiological insights from fMRI data. Copyright © 2018 Elsevier Inc. All rights reserved.

Optimal causal filtering for 1 /fα-type noise in single-electrode EEG signals.

PubMed

Paris, Alan; Atia, George; Vosoughi, Azadeh; Berman, Stephen A

2016-08-01

Understanding the mode of generation and the statistical structure of neurological noise is one of the central problems of biomedical signal processing. We have developed a broad class of abstract biological noise sources we call hidden simplicial tissues. In the simplest cases, such tissue emits what we have named generalized van der Ziel-McWhorter (GVZM) noise which has a roughly 1/fα spectral roll-off. Our previous work focused on the statistical structure of GVZM frequency spectra. However, causality of processing operations (i.e., dependence only on the past) is an essential requirement for real-time applications to seizure detection and brain-computer interfacing. In this paper we outline the theoretical background for optimal causal time-domain filtering of deterministic signals embedded in GVZM noise. We present some of our early findings concerning the optimal filtering of EEG signals for the detection of steady-state visual evoked potential (SSVEP) responses and indicate the next steps in our ongoing research.

The behavior of quantization spectra as a function of signal-to-noise ratio

NASA Technical Reports Server (NTRS)

Flanagan, M. J.

1991-01-01

An expression for the spectrum of quantization error in a discrete-time system whose input is a sinusoid plus white Gaussian noise is derived. This quantization spectrum consists of two components: a white-noise floor and spurious harmonics. The dithering effect of the input Gaussian noise in both components of the spectrum is considered. Quantitative results in a discrete Fourier transform (DFT) example show the behavior of spurious harmonics as a function of the signal-to-noise ratio (SNR). These results have strong implications for digital reception and signal analysis systems. At low SNRs, spurious harmonics decay exponentially on a log-log scale, and the resulting spectrum is white. As the SNR increases, the spurious harmonics figure prominently in the output spectrum. A useful expression is given that roughly bounds the magnitude of a spurious harmonic as a function of the SNR.

Low-noise front-end electronics for detection of intermediate-frequency weak light signals

NASA Astrophysics Data System (ADS)

Lin, Cunbao; Yan, Shuhua; Du, Zhiguang; Wei, Chunhua; Wang, Guochao

2015-02-01

A novel low-noise front-end electronics was proposed for detection of light signals with intensity about 10 μW and frequency above 2.7 MHz. The direct current (DC) power supply, pre-amplifier and main-amplifier were first designed, simulated and then realized. Small-size components were used to make the power supply small, and the pre-amplifier and main-amplifier were the least capacitors to avoid the phase shift of the signals. The performance of the developed front-end electronics was verified in cross-grating diffraction experiments. The results indicated that the output peak-topeak noise of the +/-5 V DC power supply was about 2 mV, and the total output current was 1.25 A. The signal-to-noise ratio (SNR) of the output signal of the pre-amplifier was about 50 dB, and it increased to nearly 60 dB after the mainamplifier, which means this front-end electronics was especially suitable for using in the phase-sensitive and integrated precision measurement systems.

Signal and noise extraction from analog memory elements for neuromorphic computing.

PubMed

Gong, N; Idé, T; Kim, S; Boybat, I; Sebastian, A; Narayanan, V; Ando, T

2018-05-29

Dense crossbar arrays of non-volatile memory (NVM) can potentially enable massively parallel and highly energy-efficient neuromorphic computing systems. The key requirements for the NVM elements are continuous (analog-like) conductance tuning capability and switching symmetry with acceptable noise levels. However, most NVM devices show non-linear and asymmetric switching behaviors. Such non-linear behaviors render separation of signal and noise extremely difficult with conventional characterization techniques. In this study, we establish a practical methodology based on Gaussian process regression to address this issue. The methodology is agnostic to switching mechanisms and applicable to various NVM devices. We show tradeoff between switching symmetry and signal-to-noise ratio for HfO 2 -based resistive random access memory. Then, we characterize 1000 phase-change memory devices based on Ge 2 Sb 2 Te 5 and separate total variability into device-to-device variability and inherent randomness from individual devices. These results highlight the usefulness of our methodology to realize ideal NVM devices for neuromorphic computing.

The dependence of signal-to-noise ratio on number of scans in covariance spectroscopy.

PubMed

Qian, Yi; Shen, Ming; Amoureux, Jean-Paul; Noda, Isao; Hu, Bingwen

2014-01-01

The dependence of signal-to-noise ratio on the number of scans in covariance spectroscopy has been systematically analyzed for the first time with the intriguing relationship of SNRcov∝n/2, which is different from that in FT2D spectrum with SNRFT∝n. This relationship guarantees the signal-to-noise ratio when increasing the number of scans. Copyright © 2014 Elsevier Inc. All rights reserved.

Demodulation of messages received with low signal to noise ratio

NASA Astrophysics Data System (ADS)

Marguinaud, A.; Quignon, T.; Romann, B.

The implementation of this all-digital demodulator is derived from maximum likelihood considerations applied to an analytical representation of the received signal. Traditional adapted filters and phase lock loops are replaced by minimum variance estimators and hypothesis tests. These statistical tests become very simple when working on phase signal. These methods, combined with rigorous control data representation allow significant computation savings as compared to conventional realizations. Nominal operation has been verified down to energetic signal over noise of -3 dB upon a QPSK demodulator.

Signals embedded in the radial velocity noise. Periodic variations in the τ Ceti velocities

NASA Astrophysics Data System (ADS)

Tuomi, M.; Jones, H. R. A.; Jenkins, J. S.; Tinney, C. G.; Butler, R. P.; Vogt, S. S.; Barnes, J. R.; Wittenmyer, R. A.; O'Toole, S.; Horner, J.; Bailey, J.; Carter, B. D.; Wright, D. J.; Salter, G. S.; Pinfield, D.

2013-03-01

Context. The abilities of radial velocity exoplanet surveys to detect the lowest-mass extra-solar planets are currently limited by a combination of instrument precision, lack of data, and "jitter". Jitter is a general term for any unknown features in the noise, and reflects a lack of detailed knowledge of stellar physics (asteroseismology, starspots, magnetic cycles, granulation, and other stellar surface phenomena), as well as the possible underestimation of instrument noise. Aims: We study an extensive set of radial velocities for the star HD 10700 (τ Ceti) to determine the properties of the jitter arising from stellar surface inhomogeneities, activity, and telescope-instrument systems, and perform a comprehensive search for planetary signals in the radial velocities. Methods: We performed Bayesian comparisons of statistical models describing the radial velocity data to quantify the number of significant signals and the magnitude and properties of the excess noise in the data. We reached our goal by adding artificial signals to the "flat" radial velocity data of HD 10700 and by seeing which one of our statistical noise models receives the greatest posterior probabilities while still being able to extract the artificial signals correctly from the data. We utilised various noise components to assess properties of the noise in the data and analyse the HARPS, AAPS, and HIRES data for HD 10700 to quantify these properties and search for previously unknown low-amplitude Keplerian signals. Results: According to our analyses, moving average components with an exponential decay with a timescale from a few hours to few days, and Gaussian white noise explains the jitter the best for all three data sets. Fitting the corresponding noise parameters results in significant improvements of the statistical models and enables the detection of very weak signals with amplitudes below 1 m s-1 level in our numerical experiments. We detect significant periodicities that have no

Characterization of transient noise in Advanced LIGO relevant to gravitational wave signal GW150914

NASA Astrophysics Data System (ADS)

Abbott, B. P.; Abbott, R.; Abbott, T. D.; Abernathy, M. R.; Acernese, F.; Ackley, K.; Adamo, M.; Adams, C.; Adams, T.; Addesso, P.; Adhikari, R. X.; Adya, V. B.; Affeldt, C.; Agathos, M.; Agatsuma, K.; Aggarwal, N.; Aguiar, O. D.; Aiello, L.; Ain, A.; Ajith, P.; Allen, B.; Allocca, A.; Altin, P. A.; Anderson, S. B.; Anderson, W. G.; Arai, K.; Araya, M. C.; Arceneaux, C. C.; Areeda, J. S.; Arnaud, N.; Arun, K. G.; Ascenzi, S.; Ashton, G.; Ast, M.; Aston, S. M.; Astone, P.; Aufmuth, P.; Aulbert, C.; Babak, S.; Bacon, P.; Bader, M. K. M.; Baker, P. T.; Baldaccini, F.; Ballardin, G.; Ballmer, S. W.; Barayoga, J. C.; Barclay, S. E.; Barish, B. C.; Barker, D.; Barone, F.; Barr, B.; Barsotti, L.; Barsuglia, M.; Barta, D.; Bartlett, J.; Bartos, I.; Bassiri, R.; Basti, A.; Batch, J. C.; Baune, C.; Bavigadda, V.; Bazzan, M.; Behnke, B.; Bejger, M.; Bell, A. S.; Bell, C. J.; Berger, B. K.; Bergman, J.; Bergmann, G.; Berry, C. P. L.; Bersanetti, D.; Bertolini, A.; Betzwieser, J.; Bhagwat, S.; Bhandare, R.; Bilenko, I. A.; Billingsley, G.; Birch, J.; Birney, R.; Biscans, S.; Bisht, A.; Bitossi, M.; Biwer, C.; Bizouard, M. A.; Blackburn, J. K.; Blackburn, L.; Blair, C. D.; Blair, D. G.; Blair, R. M.; Bloemen, S.; Bock, O.; Bodiya, T. P.; Boer, M.; Bogaert, G.; Bogan, C.; Bohe, A.; Bojtos, P.; Bond, C.; Bondu, F.; Bonnand, R.; Boom, B. A.; Bork, R.; Boschi, V.; Bose, S.; Bouffanais, Y.; Bozzi, A.; Bradaschia, C.; Brady, P. R.; Braginsky, V. B.; Branchesi, M.; Brau, J. E.; Briant, T.; Brillet, A.; Brinkmann, M.; Brisson, V.; Brockill, P.; Brooks, A. F.; Brown, D. A.; Brown, D. D.; Brown, N. M.; Buchanan, C. C.; Buikema, A.; Bulik, T.; Bulten, H. J.; Buonanno, A.; Buskulic, D.; Buy, C.; Byer, R. L.; Cadonati, L.; Cagnoli, G.; Cahillane, C.; Calderón Bustillo, J.; Callister, T.; Calloni, E.; Camp, J. B.; Cannon, K. C.; Cao, J.; Capano, C. D.; Capocasa, E.; Carbognani, F.; Caride, S.; Casanueva Diaz, J.; Casentini, C.; Caudill, S.; Cavaglià, M.; Cavalier, F.; Cavalieri, R.; Cella, G.; Cepeda, C. B.; Cerboni Baiardi, L.; Cerretani, G.; Cesarini, E.; Chakraborty, R.; Chalermsongsak, T.; Chamberlin, S. J.; Chan, M.; Chao, S.; Charlton, P.; Chassande-Mottin, E.; Chatterji, S.; Chen, H. Y.; Chen, Y.; Cheng, C.; Chincarini, A.; Chiummo, A.; Cho, H. S.; Cho, M.; Chow, J. H.; Christensen, N.; Chu, Q.; Chua, S.; Chung, S.; Ciani, G.; Clara, F.; Clark, J. A.; Cleva, F.; Coccia, E.; Cohadon, P.-F.; Colla, A.; Collette, C. G.; Cominsky, L.; Conte, A.; Conti, L.; Cook, D.; Corbitt, T. R.; Cornish, N.; Corsi, A.; Cortese, S.; Costa, C. A.; Coughlin, M. W.; Coughlin, S. B.; Coulon, J.-P.; Countryman, S. T.; Couvares, P.; Cowan, E. E.; Coward, D. M.; Cowart, M. J.; Coyne, D. C.; Coyne, R.; Craig, K.; Creighton, J. D. E.; Cripe, J.; Crowder, S. G.; Cumming, A.; Cunningham, L.; Cuoco, E.; Dal Canton, T.; Danilishin, S. L.; D'Antonio, S.; Danzmann, K.; Darman, N. S.; Dattilo, V.; Dave, I.; Daveloza, H. P.; Davier, M.; Davies, G. S.; Daw, E. J.; Day, R.; DeBra, D.; Debreczeni, G.; Degallaix, J.; De Laurentis, M.; Deléglise, S.; Del Pozzo, W.; Denker, T.; Dent, T.; Dereli, H.; Dergachev, V.; DeRosa, R. T.; De Rosa, R.; DeSalvo, R.; Dhurandhar, S.; Díaz, M. C.; Di Fiore, L.; Di Giovanni, M.; Di Lieto, A.; Di Pace, S.; Di Palma, I.; Di Virgilio, A.; Dojcinoski, G.; Dolique, V.; Donovan, F.; Dooley, K. L.; Doravari, S.; Douglas, R.; Downes, T. P.; Drago, M.; Drever, R. W. P.; Driggers, J. C.; Du, Z.; Ducrot, M.; Dwyer, S. E.; Edo, T. B.; Edwards, M. C.; Effler, A.; Eggenstein, H.-B.; Ehrens, P.; Eichholz, J.; Eikenberry, S. S.; Engels, W.; Essick, R. C.; Etzel, T.; Evans, M.; Evans, T. M.; Everett, R.; Factourovich, M.; Fafone, V.; Fair, H.; Fairhurst, S.; Fan, X.; Fang, Q.; Farinon, S.; Farr, B.; Farr, W. M.; Favata, M.; Fays, M.; Fehrmann, H.; Fejer, M. M.; Ferrante, I.; Ferreira, E. C.; Ferrini, F.; Fidecaro, F.; Fiori, I.; Fiorucci, D.; Fisher, R. P.; Flaminio, R.; Fletcher, M.; Fournier, J.-D.; Franco, S.; Frasca, S.; Frasconi, F.; Frei, Z.; Freise, A.; Frey, R.; Frey, V.; Fricke, T. T.; Fritschel, P.; Frolov, V. V.; Fulda, P.; Fyffe, M.; Gabbard, H. A. G.; Gair, J. R.; Gammaitoni, L.; Gaonkar, S. G.; Garufi, F.; Gatto, A.; Gaur, G.; Gehrels, N.; Gemme, G.; Gendre, B.; Genin, E.; Gennai, A.; George, J.; Gergely, L.; Germain, V.; Ghosh, Archisman; Ghosh, S.; Giaime, J. A.; Giardina, K. D.; Giazotto, A.; Gill, K.; Glaefke, A.; Goetz, E.; Goetz, R.; Gondan, L.; González, G.; Gonzalez Castro, J. M.; Gopakumar, A.; Gordon, N. A.; Gorodetsky, M. L.; Gossan, S. E.; Gosselin, M.; Gouaty, R.; Graef, C.; Graff, P. B.; Granata, M.; Grant, A.; Gras, S.; Gray, C.; Greco, G.; Green, A. C.; Groot, P.; Grote, H.; Grunewald, S.; Guidi, G. M.; Guo, X.; Gupta, A.; Gupta, M. K.; Gushwa, K. E.; Gustafson, E. K.; Gustafson, R.; Hacker, J. J.; Hall, B. R.; Hall, E. D.; Hammond, G.; Haney, M.; Hanke, M. M.; Hanks, J.; Hanna, C.; Hannam, M. D.; Hanson, J.; Hardwick, T.; Harms, J.; Harry, G. M.; Harry, I. W.; Hart, M. J.; Hartman, M. T.; Haster, C.-J.; Haughian, K.; Heidmann, A.; Heintze, M. C.; Heitmann, H.; Hello, P.; Hemming, G.; Hendry, M.; Heng, I. S.; Hennig, J.; Heptonstall, A. W.; Heurs, M.; Hild, S.; Hoak, D.; Hodge, K. A.; Hofman, D.; Hollitt, S. E.; Holt, K.; Holz, D. E.; Hopkins, P.; Hosken, D. J.; Hough, J.; Houston, E. A.; Howell, E. J.; Hu, Y. M.; Huang, S.; Huerta, E. A.; Huet, D.; Hughey, B.; Husa, S.; Huttner, S. H.; Huynh-Dinh, T.; Idrisy, A.; Indik, N.; Ingram, D. R.; Inta, R.; Isa, H. N.; Isac, J.-M.; Isi, M.; Islas, G.; Isogai, T.; Iyer, B. R.; Izumi, K.; Jacqmin, T.; Jang, H.; Jani, K.; Jaranowski, P.; Jawahar, S.; Jiménez-Forteza, F.; Johnson, W. W.; Jones, D. I.; Jones, R.; Jonker, R. J. G.; Ju, L.; K, Haris; Kalaghatgi, C. V.; Kalogera, V.; Kandhasamy, S.; Kang, G.; Kanner, J. B.; Karki, S.; Kasprzack, M.; Katsavounidis, E.; Katzman, W.; Kaufer, S.; Kaur, T.; Kawabe, K.; Kawazoe, F.; Kéfélian, F.; Kehl, M. S.; Keitel, D.; Kelley, D. B.; Kells, W.; Kennedy, R.; Key, J. S.; Khalaidovski, A.; Khalili, F. Y.; Khan, I.; Khan, S.; Khan, Z.; Khazanov, E. A.; Kijbunchoo, N.; Kim, C.; Kim, J.; Kim, K.; Kim, Nam-Gyu; Kim, Namjun; Kim, Y.-M.; King, E. J.; King, P. J.; Kinzel, D. L.; Kissel, J. S.; Kleybolte, L.; Klimenko, S.; Koehlenbeck, S. M.; Kokeyama, K.; Koley, S.; Kondrashov, V.; Kontos, A.; Korobko, M.; Korth, W. Z.; Kowalska, I.; Kozak, D. B.; Kringel, V.; Krishnan, B.; Królak, A.; Krueger, C.; Kuehn, G.; Kumar, P.; Kuo, L.; Kutynia, A.; Lackey, B. D.; Landry, M.; Lange, J.; Lantz, B.; Lasky, P. D.; Lazzarini, A.; Lazzaro, C.; Leaci, P.; Leavey, S.; Lebigot, E. O.; Lee, C. H.; Lee, H. K.; Lee, H. M.; Lee, K.; Lenon, A.; Leonardi, M.; Leong, J. R.; Leroy, N.; Letendre, N.; Levin, Y.; Levine, B. M.; Li, T. G. F.; Libson, A.; Littenberg, T. B.; Lockerbie, N. A.; Logue, J.; Lombardi, A. L.; Lord, J. E.; Lorenzini, M.; Loriette, V.; Lormand, M.; Losurdo, G.; Lough, J. D.; Lück, H.; Lundgren, A. P.; Luo, J.; Lynch, R.; Ma, Y.; MacDonald, T.; Machenschalk, B.; MacInnis, M.; Macleod, D. M.; Magaña-Sandoval, F.; Magee, R. M.; Mageswaran, M.; Majorana, E.; Maksimovic, I.; Malvezzi, V.; Man, N.; Mandel, I.; Mandic, V.; Mangano, V.; Mansell, G. L.; Manske, M.; Mantovani, M.; Marchesoni, F.; Marion, F.; Márka, S.; Márka, Z.; Markosyan, A. S.; Maros, E.; Martelli, F.; Martellini, L.; Martin, I. W.; Martin, R. M.; Martynov, D. V.; Marx, J. N.; Mason, K.; Masserot, A.; Massinger, T. J.; Masso-Reid, M.; Matichard, F.; Matone, L.; Mavalvala, N.; Mazumder, N.; Mazzolo, G.; McCarthy, R.; McClelland, D. E.; McCormick, S.; McGuire, S. C.; McIntyre, G.; McIver, J.; McManus, D. J.; McWilliams, S. T.; Meacher, D.; Meadors, G. D.; Meidam, J.; Melatos, A.; Mendell, G.; Mendoza-Gandara, D.; Mercer, R. A.; Merilh, E.; Merzougui, M.; Meshkov, S.; Messenger, C.; Messick, C.; Meyers, P. M.; Mezzani, F.; Miao, H.; Michel, C.; Middleton, H.; Mikhailov, E. E.; Milano, L.; Miller, J.; Millhouse, M.; Minenkov, Y.; Ming, J.; Mirshekari, S.; Mishra, C.; Mitra, S.; Mitrofanov, V. P.; Mitselmakher, G.; Mittleman, R.; Moggi, A.; Mohan, M.; Mohapatra, S. R. P.; Montani, M.; Moore, B. C.; Moore, C. J.; Moraru, D.; Moreno, G.; Morriss, S. R.; Mossavi, K.; Mours, B.; Mow-Lowry, C. M.; Mueller, C. L.; Mueller, G.; Muir, A. W.; Mukherjee, Arunava; Mukherjee, D.; Mukherjee, S.; Mukund, N.; Mullavey, A.; Munch, J.; Murphy, D. J.; Murray, P. G.; Mytidis, A.; Nardecchia, I.; Naticchioni, L.; Nayak, R. K.; Necula, V.; Nedkova, K.; Nelemans, G.; Neri, M.; Neunzert, A.; Newton, G.; Nguyen, T. T.; Nielsen, A. B.; Nissanke, S.; Nitz, A.; Nocera, F.; Nolting, D.; Normandin, M. E.; Nuttall, L. K.; Oberling, J.; Ochsner, E.; O'Dell, J.; Oelker, E.; Ogin, G. H.; Oh, J. J.; Oh, S. H.; Ohme, F.; Oliver, M.; Oppermann, P.; Oram, Richard J.; O'Reilly, B.; O'Shaughnessy, R.; Ottaway, D. J.; Ottens, R. S.; Overmier, H.; Owen, B. J.; Pai, A.; Pai, S. A.; Palamos, J. R.; Palashov, O.; Palomba, C.; Pal-Singh, A.; Pan, H.; Pankow, C.; Pannarale, F.; Pant, B. C.; Paoletti, F.; Paoli, A.; Papa, M. A.; Paris, H. R.; Parker, W.; Pascucci, D.; Pasqualetti, A.; Passaquieti, R.; Passuello, D.; Patricelli, B.; Patrick, Z.; Pearlstone, B. L.; Pedraza, M.; Pedurand, R.; Pekowsky, L.; Pele, A.; Penn, S.; Perreca, A.; Phelps, M.; Piccinni, O.; Pichot, M.; Piergiovanni, F.; Pierro, V.; Pillant, G.; Pinard, L.; Pinto, I. M.; Pitkin, M.; Poggiani, R.; Popolizio, P.; Post, A.; Powell, J.; Prasad, J.; Predoi, V.; Premachandra, S. S.; Prestegard, T.; Price, L. R.; Prijatelj, M.; Principe, M.; Privitera, S.; Prodi, G. A.; Prokhorov, L.; Puncken, O.; Punturo, M.; Puppo, P.; Pürrer, M.; Qi, H.; Qin, J.; Quetschke, V.; Quintero, E. A.; Quitzow-James, R.; Raab, F. J.; Rabeling, D. S.; Radkins, H.; Raffai, P.; Raja, S.; Rakhmanov, M.; Rapagnani, P.; Raymond, V.; Razzano, M.; Re, V.; Read, J.; Reed, C. M.; Regimbau, T.; Rei, L.; Reid, S.; Reitze, D. H.; Rew, H.; Reyes, S. D.; Ricci, F.; Riles, K.; Robertson, N. A.; Robie, R.; Robinet, F.; Rocchi, A.; Rolland, L.; Rollins, J. G.; Roma, V. J.; Romano, R.; Romanov, G.; Romie, J. H.; Rosińska, D.; Rowan, S.; Rüdiger, A.; Ruggi, P.; Ryan, K.; Sachdev, S.; Sadecki, T.; Sadeghian, L.; Salconi, L.; Saleem, M.; Salemi, F.; Samajdar, A.; Sammut, L.; Sanchez, E. J.; Sandberg, V.; Sandeen, B.; Sanders, J. R.; Sassolas, B.; Sathyaprakash, B. S.; Saulson, P. R.; Sauter, O.; Savage, R. L.; Sawadsky, A.; Schale, P.; Schilling, R.; Schmidt, J.; Schmidt, P.; Schnabel, R.; Schofield, R. M. S.; Schönbeck, A.; Schreiber, E.; Schuette, D.; Schutz, B. F.; Scott, J.; Scott, S. M.; Sellers, D.; Sengupta, A. S.; Sentenac, D.; Sequino, V.; Sergeev, A.; Serna, G.; Setyawati, Y.; Sevigny, A.; Shaddock, D. A.; Shah, S.; Shahriar, M. S.; Shaltev, M.; Shao, Z.; Shapiro, B.; Shawhan, P.; Sheperd, A.; Shoemaker, D. H.; Shoemaker, D. M.; Siellez, K.; Siemens, X.; Sigg, D.; Silva, A. D.; Simakov, D.; Singer, A.; Singer, L. P.; Singh, A.; Singh, R.; Singhal, A.; Sintes, A. M.; Slagmolen, B. J. J.; Slutsky, J.; Smith, J. R.; Smith, N. D.; Smith, R. J. E.; Son, E. J.; Sorazu, B.; Sorrentino, F.; Souradeep, T.; Srivastava, A. K.; Staley, A.; Steinke, M.; Steinlechner, J.; Steinlechner, S.; Steinmeyer, D.; Stephens, B. C.; Stone, R.; Strain, K. A.; Straniero, N.; Stratta, G.; Strauss, N. A.; Strigin, S.; Sturani, R.; Stuver, A. L.; Summerscales, T. Z.; Sun, L.; Sutton, P. J.; Swinkels, B. L.; Szczepańczyk, M. J.; Tacca, M.; Talukder, D.; Tanner, D. B.; Tápai, M.; Tarabrin, S. P.; Taracchini, A.; Taylor, R.; Theeg, T.; Thirugnanasambandam, M. P.; Thomas, E. G.; Thomas, M.; Thomas, P.; Thorne, K. A.; Thorne, K. S.; Thrane, E.; Tiwari, S.; Tiwari, V.; Tokmakov, K. V.; Tomlinson, C.; Tonelli, M.; Torres, C. V.; Torrie, C. I.; Töyrä, D.; Travasso, F.; Traylor, G.; Trifirò, D.; Tringali, M. C.; Trozzo, L.; Tse, M.; Turconi, M.; Tuyenbayev, D.; Ugolini, D.; Unnikrishnan, C. S.; Urban, A. L.; Usman, S. A.; Vahlbruch, H.; Vajente, G.; Valdes, G.; van Bakel, N.; van Beuzekom, M.; van den Brand, J. F. J.; Van Den Broeck, C.; Vander-Hyde, D. C.; van der Schaaf, L.; van Heijningen, J. V.; van Veggel, A. A.; Vardaro, M.; Vass, S.; Vasúth, M.; Vaulin, R.; Vecchio, A.; Vedovato, G.; Veitch, J.; Veitch, P. J.; Venkateswara, K.; Verkindt, D.; Vetrano, F.; Viceré, A.; Vinciguerra, S.; Vine, D. J.; Vinet, J.-Y.; Vitale, S.; Vo, T.; Vocca, H.; Vorvick, C.; Voss, D.; Vousden, W. D.; Vyatchanin, S. P.; Wade, A. R.; Wade, L. E.; Wade, M.; Walker, M.; Wallace, L.; Walsh, S.; Wang, G.; Wang, H.; Wang, M.; Wang, X.; Wang, Y.; Ward, R. L.; Warner, J.; Was, M.; Weaver, B.; Wei, L.-W.; Weinert, M.; Weinstein, A. J.; Weiss, R.; Welborn, T.; Wen, L.; Weßels, P.; Westphal, T.; Wette, K.; Whelan, J. T.; Whitcomb, S.; White, D. J.; Whiting, B. F.; Williams, R. D.; Williamson, A. R.; Willis, J. L.; Willke, B.; Wimmer, M. H.; Winkler, W.; Wipf, C. C.; Wittel, H.; Woan, G.; Worden, J.; Wright, J. L.; Wu, G.; Yablon, J.; Yam, W.; Yamamoto, H.; Yancey, C. C.; Yap, M. J.; Yu, H.; Yvert, M.; Zadrożny, A.; Zangrando, L.; Zanolin, M.; Zendri, J.-P.; Zevin, M.; Zhang, F.; Zhang, L.; Zhang, M.; Zhang, Y.; Zhao, C.; Zhou, M.; Zhou, Z.; Zhu, X. J.; Zotov, N.; Zucker, M. E.; Zuraw, S. E.; Zweizig, J.; LIGO Scientific Collaboration; Virgo Collaboration

2016-07-01

On 14 September 2015, a gravitational wave signal from a coalescing black hole binary system was observed by the Advanced LIGO detectors. This paper describes the transient noise backgrounds used to determine the significance of the event (designated GW150914) and presents the results of investigations into potential correlated or uncorrelated sources of transient noise in the detectors around the time of the event. The detectors were operating nominally at the time of GW150914. We have ruled out environmental influences and non-Gaussian instrument noise at either LIGO detector as the cause of the observed gravitational wave signal.

Characterization of Transient Noise in Advanced LIGO Relevant to Gravitational Wave Signal GW150914

NASA Technical Reports Server (NTRS)

Abbott, B. P.; Abbott, R.; Abbott, T. D.; Abernathy, M. R.; Acernese, F.; Ackley, K.; Adamo, M.; Adams, C.; Adams, T.; Camp, Jordan B.

2016-01-01

On 14 September 2015, a gravitational wave signal from a coalescing black hole binary system was observed by the Advanced LIGO detectors. This paper describes the transient noise backgrounds used to determine the significance of the event (designated GW150914) and presents the results of investigations into potential correlated or uncorrelated sources of transient noise in the detectors around the time of the event. The detectors were operating nominally at the time of GW150914. We have ruled out environmental influences and non-Gaussian instrument noise at either LIGO detector as the cause of the observed gravitational wave signal.

High-frequency signal and noise estimates of CSR GRACE RL04

NASA Astrophysics Data System (ADS)

Bonin, Jennifer A.; Bettadpur, Srinivas; Tapley, Byron D.

2012-12-01

A sliding window technique is used to create daily-sampled Gravity Recovery and Climate Experiment (GRACE) solutions with the same background processing as the official CSR RL04 monthly series. By estimating over shorter time spans, more frequent solutions are made using uncorrelated data, allowing for higher frequency resolution in addition to daily sampling. Using these data sets, high-frequency GRACE errors are computed using two different techniques: assuming the GRACE high-frequency signal in a quiet area of the ocean is the true error, and computing the variance of differences between multiple high-frequency GRACE series from different centers. While the signal-to-noise ratios prove to be sufficiently high for confidence at annual and lower frequencies, at frequencies above 3 cycles/year the signal-to-noise ratios in the large hydrological basins looked at here are near 1.0. Comparisons with the GLDAS hydrological model and high frequency GRACE series developed at other centers confirm CSR GRACE RL04's poor ability to accurately and reliably measure hydrological signal above 3-9 cycles/year, due to the low power of the large-scale hydrological signal typical at those frequencies compared to the GRACE errors.

Photoacoustic signal and noise analysis for Si thin plate: signal correction in frequency domain.

PubMed

Markushev, D D; Rabasović, M D; Todorović, D M; Galović, S; Bialkowski, S E

2015-03-01

Methods for photoacoustic signal measurement, rectification, and analysis for 85 μm thin Si samples in the 20-20 000 Hz modulation frequency range are presented. Methods for frequency-dependent amplitude and phase signal rectification in the presence of coherent and incoherent noise as well as distortion due to microphone characteristics are presented. Signal correction is accomplished using inverse system response functions deduced by comparing real to ideal signals for a sample with well-known bulk parameters and dimensions. The system response is a piece-wise construction, each component being due to a particular effect of the measurement system. Heat transfer and elastic effects are modeled using standard Rosencweig-Gersho and elastic-bending theories. Thermal diffusion, thermoelastic, and plasmaelastic signal components are calculated and compared to measurements. The differences between theory and experiment are used to detect and correct signal distortion and to determine detector and sound-card characteristics. Corrected signal analysis is found to faithfully reflect known sample parameters.

Study of improving signal-noise ratio for fluorescence channel

NASA Astrophysics Data System (ADS)

Wang, Guoqing; Li, Xin; Lou, Yue; Chen, Dong; Zhao, Xin; Wang, Ran; Yan, Debao; Zhao, Qi

2017-10-01

Laser-induced fluorescence(LIFS), which is one of most effective discrimination methods to identify the material at the molecular level by inducing fluorescence spectrum, has been popularized for its fast and accurate probe's results. According to the research, violet laser or ultraviolet laser is always used as excitation light source. While, There is no atmospheric window for violet laser and ultraviolet laser, causing laser attenuation along its propagation path. What's worse, as the laser reaching sample, part of the light is reflected. That is, excitation laser really react on sample to produce fluorescence is very poor, leading to weak fluorescence mingled with the background light collected by LIFS' processing unit, when it used outdoor. In order to spread LIFS to remote probing under the complex background, study of improving signal-noise ratio for fluorescence channel is a meaningful work. Enhancing the fluorescence intensity and inhibiting background light both can improve fluorescence' signal-noise ratio. In this article, three different approaches of inhibiting background light are discussed to improve the signal-noise ratio of LIFS. The first method is increasing fluorescence excitation area in the proportion of LIFS' collecting field by expanding laser beam, if the collecting filed is fixed. The second one is changing field angle base to accommodate laser divergence angle. The third one is setting a very narrow gating circuit to control acquisition circuit, which is shortly open only when fluorescence arriving. At some level, these methods all can reduce the background light. But after discussion, the third one is best with adding gating acquisition circuit to acquisition circuit instead of changing light path, which is effective and economic.

Analysis of signal-dependent sensor noise on JPEG 2000-compressed Sentinel-2 multi-spectral images

NASA Astrophysics Data System (ADS)

Uss, M.; Vozel, B.; Lukin, V.; Chehdi, K.

2017-10-01

The processing chain of Sentinel-2 MultiSpectral Instrument (MSI) data involves filtering and compression stages that modify MSI sensor noise. As a result, noise in Sentinel-2 Level-1C data distributed to users becomes processed. We demonstrate that processed noise variance model is bivariate: noise variance depends on image intensity (caused by signal-dependency of photon counting detectors) and signal-to-noise ratio (SNR; caused by filtering/compression). To provide information on processed noise parameters, which is missing in Sentinel-2 metadata, we propose to use blind noise parameter estimation approach. Existing methods are restricted to univariate noise model. Therefore, we propose extension of existing vcNI+fBm blind noise parameter estimation method to multivariate noise model, mvcNI+fBm, and apply it to each band of Sentinel-2A data. Obtained results clearly demonstrate that noise variance is affected by filtering/compression for SNR less than about 15. Processed noise variance is reduced by a factor of 2 - 5 in homogeneous areas as compared to noise variance for high SNR values. Estimate of noise variance model parameters are provided for each Sentinel-2A band. Sentinel-2A MSI Level-1C noise models obtained in this paper could be useful for end users and researchers working in a variety of remote sensing applications.

Few-Flakes Reduced Graphene Oxide Sensors for Organic Vapors with a High Signal-to-Noise Ratio

PubMed Central

Hasan, Nowzesh; Zhang, Wenli

2017-01-01

This paper reports our findings on how to prepare a graphene oxide-based gas sensor for sensing fast pulses of volatile organic compounds with a better signal-to-noise ratio. We use rapid acetone pulses of varying concentrations to test the sensors. First, we compare the effect of graphene oxide deposition method (dielectrophoresis versus solvent evaporation) on the sensor’s response. We find that dielectrophoresis yields films with uniform coverage and better sensor response. Second, we examine the effect of chemical reduction. Contrary to prior reports, we find that graphene oxide reduction leads to a reduction in sensor response and current noise, thus keeping the signal-to-noise ratio the same. We found that if we sonicated the sensor in acetone, we created a sensor with a few flakes of reduced graphene oxide. Such sensors provided a higher signal-to-noise ratio that could be correlated to the vapor concentration of acetone with better repeatability. Modeling shows that the sensor’s response is due to one-site Langmuir adsorption or an overall single exponent process. Further, the desorption of acetone as deduced from the sensor recovery signal follows a single exponent process. Thus, we show a simple way to improve the signal-to-noise ratio in reduced graphene oxide sensors. PMID:29065488

Noise reduction in Lidar signal using correlation-based EMD combined with soft thresholding and roughness penalty

NASA Astrophysics Data System (ADS)

Chang, Jianhua; Zhu, Lingyan; Li, Hongxu; Xu, Fan; Liu, Binggang; Yang, Zhenbo

2018-01-01

Empirical mode decomposition (EMD) is widely used to analyze the non-linear and non-stationary signals for noise reduction. In this study, a novel EMD-based denoising method, referred to as EMD with soft thresholding and roughness penalty (EMD-STRP), is proposed for the Lidar signal denoising. With the proposed method, the relevant and irrelevant intrinsic mode functions are first distinguished via a correlation coefficient. Then, the soft thresholding technique is applied to the irrelevant modes, and the roughness penalty technique is applied to the relevant modes to extract as much information as possible. The effectiveness of the proposed method was evaluated using three typical signals contaminated by white Gaussian noise. The denoising performance was then compared to the denoising capabilities of other techniques, such as correlation-based EMD partial reconstruction, correlation-based EMD hard thresholding, and wavelet transform. The use of EMD-STRP on the measured Lidar signal resulted in the noise being efficiently suppressed, with an improved signal to noise ratio of 22.25 dB and an extended detection range of 11 km.

An ion-gated bipolar amplifier for ion sensing with enhanced signal and improved noise performance

NASA Astrophysics Data System (ADS)

Zhang, Da; Gao, Xindong; Chen, Si; Norström, Hans; Smith, Ulf; Solomon, Paul; Zhang, Shi-Li; Zhang, Zhen

2014-08-01

This work presents a proof-of-concept ion-sensitive device operating in electrolytes. The device, i.e., an ion-gated bipolar amplifier (IGBA), consists of a modified ion-sensitive field-effect transistor (ISFET) intimately integrated with a vertical bipolar junction transistor for immediate current amplification without introducing additional noise. With the current non-optimized design, the IGBA is already characterized by a 70-fold internal amplification of the ISFET output signal. This signal amplification is retained when the IGBA is used for monitoring pH variations. The tight integration significantly suppresses the interference of the IGBA signal by external noise, which leads to an improvement in signal-to-noise performance compared to its ISFET reference. The IGBA concept is especially suitable for biochips with millions of electric sensors that are connected to peripheral readout circuitry via extensive metallization which may in turn invite external interferences leading to contamination of the signal before it reaches the first external amplification stage.

Noise performance of the multiwavelength sub/millimeter inductance camera (MUSIC) detectors

NASA Astrophysics Data System (ADS)

Siegel, S. R.

2015-07-01

MUSIC is a multi-band imaging camera that employs 2304 Microwave Kinetic Inductance Detectors (MKIDs) in 576 spatial pixels to cover a 14 arc-minute field of view, with each pixel simultaneously sensitive to 4 bands centered at 0.87, 1.04, 1.33, and 1.98 mm. In April 2012 the MUSIC instrument was commissioned at the Caltech Submillimeter Observatory with a subset of the full focal plane. We examine the noise present in the detector timestreams during observations taken in the first year of operation. We find that fluctuations in atmospheric emission dominate at long timescales (< 0.5 Hz), and fluctuations in the amplitude and phase of the probe signal due to readout electronics contribute significant 1/f-type noise at shorter timescales. We describe a method to remove the amplitude, phase, and atmospheric noise using the fact that they are correlated among carrier tones. After removal, the complex signal is decomposed, or projected, into dissipation and frequency components. White noise from the cryogenic HEMT amplifier dominates in the dissipation component. An excess noise is observed in the frequency component that is likely due to fluctuations in two-level system (TLS) defects in the device substrate. We compare the amplitude of the TLS noise with previous measurements.

The curious case of HD 41248. A pair of static signals buried behind red noise

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jenkins, J. S.; Tuomi, M., E-mail: jjenkins@das.uchile.cl

2014-10-20

Gaining a better understanding of the effects of stellar-induced radial velocity noise is critical for the future of exoplanet studies since the discovery of the lowest-mass planets using this method will require us to go below the intrinsic stellar noise limit. An interesting test case in this respect is that of the southern solar analog HD 41248. The radial velocity time series of this star has been proposed to contain either a pair of signals with periods of around 18 and 25 days, which could be due to a pair of resonant super-Earths, or a single and varying 25 daymore » signal that could arise due to a complex interplay between differential rotation and modulated activity. In this work, we build up more evidence for the former scenario, showing that the signals are still clearly significant, even after more than 10 yr of observations, and they likely do not change in period, amplitude, or phase as a function of time, the hallmarks of static Doppler signals. We show that over the last two observing seasons, this star was more intrinsically active and the noise reddened, highlighting why better noise models are needed to find the lowest amplitude signals, in particular, models that consider noise correlations. This analysis shows that there is still sufficient evidence for the existence of two super-Earths on the edge of, or locked into, a 7:5 mean motion resonance orbiting HD 41248.« less

Effect on signal-to-noise ratio of splitting the continuous contacts of cuff electrodes into smaller recording areas

PubMed Central

2013-01-01

Background Cuff electrodes have been widely used chronically in different clinical applications. This neural interface has been dominantly used for nerve stimulation while interfering noise is the major issue when employed for recording purposes. Advancements have been made in rejecting extra-neural interference by using continuous ring contacts in tripolar topologies. Ring contacts provide an average of the neural activity, and thus reduce the information retrieved. Splitting these contacts into smaller recording areas could potentially increase the information content. In this study, we investigate the impact of such discretization on the Signal-to-Noise Ratio (SNR). The effect of contacts positioning and an additional short circuited pair of electrodes were also addressed. Methods Different recording configurations using ring, dot, and a mixed of both contacts were studied in vitro in a frog model. An interfering signal was induced in the medium to simulate myoelectric noise. The experimental setup was design in such a way that the only difference between recordings was the configuration used. The inter-session experimental differences were taken care of by a common configuration that allowed normalization between electrode designs. Results It was found that splitting all contacts into small recording areas had negative effects on noise rejection. However, if this is only applied to the central contact creating a mixed tripole configuration, a considerable and statistically significant improvement was observed. Moreover, the signal to noise ratio was equal or larger than what can be achieved with the best known configuration, namely the short circuited tripole. This suggests that for recording purposes, any tripole topology would benefit from splitting the central contact into one or more discrete contacts. Conclusions Our results showed that a mixed tripole configuration performs better than the configuration including only ring contacts. Therefore, splitting

Predicting the effect of urban noise on the active space of avian vocal signals.

PubMed

Parris, Kirsten M; McCarthy, Michael A

2013-10-01

Urbanization changes the physical environment of nonhuman species but also markedly changes their acoustic environment. Urban noise interferes with acoustic communication in a range of animals, including birds, with potentially profound impacts on fitness. However, a mechanistic theory to predict which species of birds will be most affected by urban noise is lacking. We develop a mathematical model to predict the decrease in the active space of avian vocal signals after moving from quiet forest habitats to noisy urban habitats. We find that the magnitude of the decrease is largely a function of signal frequency. However, this relationship is not monotonic. A metaregression of observed increases in the frequency of birdsong in urban noise supports the model's predictions for signals with frequencies between 1.5 and 4 kHz. Using results of the metaregression and the model described above, we show that the expected gain in active space following observed frequency shifts is up to 12% and greatest for birds with signals at the lower end of this frequency range. Our generally applicable model, along with three predictions regarding the behavioral and population-level responses of birds to urban noise, represents an important step toward a theory of acoustic communication in urban habitats.

Theoretical and experimental signal-to-noise ratio assessment in new direction sensing continuous-wave Doppler lidar

NASA Astrophysics Data System (ADS)

Tegtmeier Pedersen, A.; Abari, C. F.; Mann, J.; Mikkelsen, T.

2014-06-01

A new direction sensing continuous-wave Doppler lidar based on an image-reject homodyne receiver has recently been demonstrated at DTU Wind Energy, Technical University of Denmark. In this contribution we analyse the signal-to-noise ratio resulting from two different data processing methods both leading to the direction sensing capability. It is found that using the auto spectrum of the complex signal to determine the wind speed leads to a signal-to-noise ratio equivalent to that of a standard self-heterodyne receiver. Using the imaginary part of the cross spectrum to estimate the Doppler shift has the benefit of a zero-mean background spectrum, but comes at the expense of a decrease in the signal-to noise ratio by a factor of √2.

Noise-assisted data processing with empirical mode decomposition in biomedical signals.

PubMed

Karagiannis, Alexandros; Constantinou, Philip

2011-01-01

In this paper, a methodology is described in order to investigate the performance of empirical mode decomposition (EMD) in biomedical signals, and especially in the case of electrocardiogram (ECG). Synthetic ECG signals corrupted with white Gaussian noise are employed and time series of various lengths are processed with EMD in order to extract the intrinsic mode functions (IMFs). A statistical significance test is implemented for the identification of IMFs with high-level noise components and their exclusion from denoising procedures. Simulation campaign results reveal that a decrease of processing time is accomplished with the introduction of preprocessing stage, prior to the application of EMD in biomedical time series. Furthermore, the variation in the number of IMFs according to the type of the preprocessing stage is studied as a function of SNR and time-series length. The application of the methodology in MIT-BIH ECG records is also presented in order to verify the findings in real ECG signals.

A method for discrimination of noise and EMG signal regions recorded during rhythmic behaviors.

PubMed

Ying, Rex; Wall, Christine E

2016-12-08

Analyses of muscular activity during rhythmic behaviors provide critical data for biomechanical studies. Electrical potentials measured from muscles using electromyography (EMG) require discrimination of noise regions as the first step in analysis. An experienced analyst can accurately identify the onset and offset of EMG but this process takes hours to analyze a short (10-15s) record of rhythmic EMG bursts. Existing computational techniques reduce this time but have limitations. These include a universal threshold for delimiting noise regions (i.e., a single signal value for identifying the EMG signal onset and offset), pre-processing using wide time intervals that dampen sensitivity for EMG signal characteristics, poor performance when a low frequency component (e.g., DC offset) is present, and high computational complexity leading to lack of time efficiency. We present a new statistical method and MATLAB script (EMG-Extractor) that includes an adaptive algorithm to discriminate noise regions from EMG that avoids these limitations and allows for multi-channel datasets to be processed. We evaluate the EMG-Extractor with EMG data on mammalian jaw-adductor muscles during mastication, a rhythmic behavior typified by low amplitude onsets/offsets and complex signal pattern. The EMG-Extractor consistently and accurately distinguishes noise from EMG in a manner similar to that of an experienced analyst. It outputs the raw EMG signal region in a form ready for further analysis. Copyright © 2016 Elsevier Ltd. All rights reserved.

Effects of spectrometer band pass, sampling, and signal-to-noise ratio on spectral identification using the Tetracorder algorithm

USGS Publications Warehouse

Swayze, G.A.; Clark, R.N.; Goetz, A.F.H.; Chrien, T.H.; Gorelick, N.S.

2003-01-01

Estimates of spectrometer band pass, sampling interval, and signal-to-noise ratio required for identification of pure minerals and plants were derived using reflectance spectra convolved to AVIRIS, HYDICE, MIVIS, VIMS, and other imaging spectrometers. For each spectral simulation, various levels of random noise were added to the reflectance spectra after convolution, and then each was analyzed with the Tetracorder spectra identification algorithm [Clark et al., 2003]. The outcome of each identification attempt was tabulated to provide an estimate of the signal-to-noise ratio at which a given percentage of the noisy spectra were identified correctly. Results show that spectral identification is most sensitive to the signal-to-noise ratio at narrow sampling interval values but is more sensitive to the sampling interval itself at broad sampling interval values because of spectral aliasing, a condition when absorption features of different materials can resemble one another. The band pass is less critical to spectral identification than the sampling interval or signal-to-noise ratio because broadening the band pass does not induce spectral aliasing. These conclusions are empirically corroborated by analysis of mineral maps of AVIRIS data collected at Cuprite, Nevada, between 1990 and 1995, a period during which the sensor signal-to-noise ratio increased up to sixfold. There are values of spectrometer sampling and band pass beyond which spectral identification of materials will require an abrupt increase in sensor signal-to-noise ratio due to the effects of spectral aliasing. Factors that control this threshold are the uniqueness of a material's diagnostic absorptions in terms of shape and wavelength isolation, and the spectral diversity of the materials found in nature and in the spectral library used for comparison. Array spectrometers provide the best data for identification when they critically sample spectra. The sampling interval should not be broadened to

Hearing Sensitivity to Shifts of Rippled-Spectrum Sound Signals in Masking Noise.

PubMed

Nechaev, Dmitry I; Milekhina, Olga N; Supin, Alexander Ya

2015-01-01

The goal of the study was to enlarge knowledge of discrimination of complex sound signals by the auditory system in masking noise. For that, influence of masking noise on detection of shift of rippled spectrum was studied in normal listeners. The signal was a shift of ripple phase within a 0.5-oct wide rippled spectrum centered at 2 kHz. The ripples were frequency-proportional (throughout the band, ripple spacing was a constant proportion of the ripple center frequency). Simultaneous masker was a 0.5-oct noise below-, on-, or above the signal band. Both the low-frequency (center frequency 1 kHz) and on-frequency (the same center frequency as for the signal) maskers increased the thresholds for detecting ripple phase shift. However, the threshold dependence on the masker level was different for these two maskers. For the on-frequency masker, the masking effect primarily depended on the masker/signal ratio: the threshold steeply increased at a ratio of 5 dB, and no shift was detectable at a ratio of 10 dB. For the low-frequency masker, the masking effect primarily depended on the masker level: the threshold increased at a masker level of 80 dB SPL, and no shift was detectable at a masker level of 90 dB (for a signal level of 50 dB) or 100 dB (for a signal level of 80 dB). The high-frequency masker had little effect. The data were successfully simulated using an excitation-pattern model. In this model, the effect of the on-frequency masker appeared to be primarily due to a decrease of ripple depth. The effect of the low-frequency masker appeared due to widening of the auditory filters at high sound levels.

Hearing Sensitivity to Shifts of Rippled-Spectrum Sound Signals in Masking Noise

PubMed Central

Nechaev, Dmitry I.; Milekhina, Olga N.; Supin, Alexander Ya.

2015-01-01

The goal of the study was to enlarge knowledge of discrimination of complex sound signals by the auditory system in masking noise. For that, influence of masking noise on detection of shift of rippled spectrum was studied in normal listeners. The signal was a shift of ripple phase within a 0.5-oct wide rippled spectrum centered at 2 kHz. The ripples were frequency-proportional (throughout the band, ripple spacing was a constant proportion of the ripple center frequency). Simultaneous masker was a 0.5-oct noise below-, on-, or above the signal band. Both the low-frequency (center frequency 1 kHz) and on-frequency (the same center frequency as for the signal) maskers increased the thresholds for detecting ripple phase shift. However, the threshold dependence on the masker level was different for these two maskers. For the on-frequency masker, the masking effect primarily depended on the masker/signal ratio: the threshold steeply increased at a ratio of 5 dB, and no shift was detectable at a ratio of 10 dB. For the low-frequency masker, the masking effect primarily depended on the masker level: the threshold increased at a masker level of 80 dB SPL, and no shift was detectable at a masker level of 90 dB (for a signal level of 50 dB) or 100 dB (for a signal level of 80 dB). The high-frequency masker had little effect. The data were successfully simulated using an excitation-pattern model. In this model, the effect of the on-frequency masker appeared to be primarily due to a decrease of ripple depth. The effect of the low-frequency masker appeared due to widening of the auditory filters at high sound levels. PMID:26462066

Noise source and reactor stability estimation in a boiling water reactor using a multivariate autoregressive model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kanemoto, S.; Andoh, Y.; Sandoz, S.A.

1984-10-01

A method for evaluating reactor stability in boiling water reactors has been developed. The method is based on multivariate autoregressive (M-AR) modeling of steady-state neutron and process noise signals. In this method, two kinds of power spectral densities (PSDs) for the measured neutron signal and the corresponding noise source signal are separately identified by the M-AR modeling. The closed- and open-loop stability parameters are evaluated from these PSDs. The method is applied to actual plant noise data that were measured together with artificial perturbation test data. Stability parameters identified from noise data are compared to those from perturbation test data,more » and it is shown that both results are in good agreement. In addition to these stability estimations, driving noise sources for the neutron signal are evaluated by the M-AR modeling. Contributions from void, core flow, and pressure noise sources are quantitatively evaluated, and the void noise source is shown to be the most dominant.« less

Geophysical Inversion with Adaptive Array Processing of Ambient Noise

NASA Astrophysics Data System (ADS)

Traer, James

2011-12-01

Land-based seismic observations of microseisms generated during Tropical Storms Ernesto and Florence are dominated by signals in the 0.15--0.5Hz band. Data from seafloor hydrophones in shallow water (70m depth, 130 km off the New Jersey coast) show dominant signals in the gravity-wave frequency band, 0.02--0.18Hz and low amplitudes from 0.18--0.3Hz, suggesting significant opposing wave components necessary for DF microseism generation were negligible at the site. Both storms produced similar spectra, despite differing sizes, suggesting near-coastal shallow water as the dominant region for observed microseism generation. A mathematical explanation for a sign-inversion induced to the passive fathometer response by minimum variance distortionless response (MVDR) beamforming is presented. This shows that, in the region containing the bottom reflection, the MVDR fathometer response is identical to that obtained with conventional processing multiplied by a negative factor. A model is presented for the complete passive fathometer response to ocean surface noise, interfering discrete noise sources, and locally uncorrelated noise in an ideal waveguide. The leading order term of the ocean surface noise produces the cross-correlation of vertical multipaths and yields the depth of sub-bottom reflectors. Discrete noise incident on the array via multipaths give multiple peaks in the fathometer response. These peaks may obscure the sub-bottom reflections but can be attenuated with use of Minimum Variance Distortionless Response (MVDR) steering vectors. A theory is presented for the Signal-to-Noise-Ratio (SNR) for the seabed reflection peak in the passive fathometer response as a function of seabed depth, seabed reflection coefficient, averaging time, bandwidth and spatial directivity of the noise field. The passive fathometer algorithm was applied to data from two drifting array experiments in the Mediterranean, Boundary 2003 and 2004, with 0.34s of averaging time. In the 2004

Signal analysis of voltage noise in welding arcs. [gas tungsten arc welding

NASA Technical Reports Server (NTRS)

Elis, E.; Eagar, T. W.

1982-01-01

Gas tungsten arc welds were made on low alloy steel plates to which intentional defects (discontinuities) were imposed. Disruption of shielding gas, welding over surface films, and tack welds produce changes in what is otherwise a relatively uniform voltage signal. The arc voltage was 15 volts + or - 2 volts with 300 mV ripple noise from the power supply. Changes in this steady noise voltage varied from 50 mV to less than one millivolt depending on the severity and the type of change experienced. In some instances the changes were easily detected by analysis of the signal in real time, while in other cases the signal had to transformed to the frequency domain in order to detect the changes. Discontinuities as small as 1.5 mm in length were detected. The ultimate sensitivity and reproducibility of the technique is still being investigated.

Detection of sub-threshold periodic signal by multiplicative and additive cross-correlated sine-Wiener noises in the FitzHugh-Nagumo neuron

NASA Astrophysics Data System (ADS)

Yao, Yuangen; Ma, Chengzhang; Wang, Canjun; Yi, Ming; Gui, Rong

2018-02-01

We study the effects of multiplicative and additive cross-correlated sine-Wiener (CCSW) noises on the performance of sub-threshold periodic signal detection in the FitzHugh-Nagumo (FHN) neuron by calculating Fourier coefficients Q for measuring synchronization between sub-threshold input signal and the response of system. CCSW noises-induced transitions of electrical activity in the FHN neuron model can be observed. Moreover, the performance of sub-threshold periodic signal detection is achieved at moderate noise strength, cross-correlation time and cross-correlation strength of CCSW noises, which indicate the occurrence of CCSW noises-induced stochastic resonance. Furthermore, the performance of sub-threshold signal detection is strongly sensitive to cross-correlation time of CCSW noises. Therefore, the performance can be effectively controlled by regulating cross-correlation time of CCSW noises. These results provide a possible mechanism for amplifying or detecting the sub-threshold signal in the nervous system.

Using Spatial Correlations of SPDC Sources for Increasing the Signal to Noise Ratio in Images

NASA Astrophysics Data System (ADS)

Ruíz, A. I.; Caudillo, R.; Velázquez, V. M.; Barrios, E.

2017-05-01

We experimentally show that, by using spatial correlations of photon pairs produced by Spontaneous Parametric Down-Conversion, it is possible to increase the Signal to Noise Ratio in images of objects illuminated with those photons; in comparison, objects illuminated with light from a laser present a minor ratio. Our simple experimental set-up was capable to produce an average improvement in signal to noise ratio of 11dB of Parametric Down-Converted light over laser light. This simple method can be easily implemented for obtaining high contrast images of faint objects and for transmitting information with low noise.

Direct bit detection receiver noise performance analysis for 32-PSK and 64-PSK modulated signals

NASA Astrophysics Data System (ADS)

Ahmed, Iftikhar

1987-12-01

Simple two channel receivers for 32-PSK and 64-PSK modulated signals have been proposed which allow digital data (namely bits), to be recovered directly instead of the traditional approach of symbol detection followed by symbol to bit mappings. This allows for binary rather than M-ary receiver decisions, reduces the amount of signal processing operations and permits parallel recovery of the bits. The noise performance of these receivers quantified by the Bit Error Rate (BER) assuming an Additive White Gaussian Noise interference model is evaluated as a function of Eb/No, the signal to noise ratio, and transmitted phase angles of the signals. The performance results of the direct bit detection receivers (DBDR) when compared to that of convectional phase measurement receivers demonstrate that DBDR's are optimum in BER sense. The simplicity of the receiver implementations and the BER of the delivered data make DBDR's attractive for high speed, spectrally efficient digital communication systems.

Adventitious sounds identification and extraction using temporal-spectral dominance-based features.

PubMed

Jin, Feng; Krishnan, Sridhar Sri; Sattar, Farook

2011-11-01

Respiratory sound (RS) signals carry significant information about the underlying functioning of the pulmonary system by the presence of adventitious sounds (ASs). Although many studies have addressed the problem of pathological RS classification, only a limited number of scientific works have focused on the analysis of the evolution of symptom-related signal components in joint time-frequency (TF) plane. This paper proposes a new signal identification and extraction method for various ASs based on instantaneous frequency (IF) analysis. The presented TF decomposition method produces a noise-resistant high definition TF representation of RS signals as compared to the conventional linear TF analysis methods, yet preserving the low computational complexity as compared to those quadratic TF analysis methods. The discarded phase information in conventional spectrogram has been adopted for the estimation of IF and group delay, and a temporal-spectral dominance spectrogram has subsequently been constructed by investigating the TF spreads of the computed time-corrected IF components. The proposed dominance measure enables the extraction of signal components correspond to ASs from noisy RS signal at high noise level. A new set of TF features has also been proposed to quantify the shapes of the obtained TF contours, and therefore strongly, enhances the identification of multicomponents signals such as polyphonic wheezes. An overall accuracy of 92.4±2.9% for the classification of real RS recordings shows the promising performance of the presented method.

Comparison of the signal-to-noise characteristics of quantum versus thermal ghost imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

O'Sullivan, Malcolm N.; Chan, Kam Wai Clifford; Boyd, Robert W.

2010-11-15

We present a theoretical comparison of the signal-to-noise characteristics of quantum versus thermal ghost imaging. We first calculate the signal-to-noise ratio of each process in terms of its controllable experimental conditions. We show that a key distinction is that a thermal ghost image always resides on top of a large background; the fluctuations in this background constitutes an intrinsic noise source for thermal ghost imaging. In contrast, there is a negligible intrinsic background to a quantum ghost image. However, for practical reasons involving achievable illumination levels, acquisition times for thermal ghost images are often much shorter than those for quantummore » ghost images. We provide quantitative predictions for the conditions under which each process provides superior performance. Our conclusion is that each process can provide useful functionality, although under complementary conditions.« less

Visual Motherese? Signal-to-Noise Ratios in Toddler-Directed Television

ERIC Educational Resources Information Center

Wass, Sam V.; Smith, Tim J.

2015-01-01

Younger brains are noisier information processing systems; this means that information for younger individuals has to allow clearer differentiation between those aspects that are required for the processing task in hand (the "signal") and those that are not (the "noise"). We compared toddler-directed and adult-directed TV…

Signal-to-noise enhancement techniques for quantum cascade absorption spectrometers employing optimal filtering and other approaches

NASA Astrophysics Data System (ADS)

Disselkamp, R. S.; Kelly, J. F.; Sams, R. L.; Anderson, G. A.

Optical feedback to the laser source in tunable diode laser spectroscopy (TDLS) is known to create intensity modulation noise due to elatoning and optical feedback (i.e. multiplicative technical noise) that usually limits spectral signal-to-noise (S/N). The large technical noise often limits absorption spectroscopy to noise floors 100-fold greater than the Poisson shot noise limit due to fluctuations in the laser intensity. The high output powers generated from quantum cascade (QC) lasers, along with their high gain, makes these injection laser systems especially susceptible to technical noise. In this article we discuss a method of using optimal filtering to reduce technical noise. We have observed S/N enhancements ranging from 20% to a factor of 50. The degree to which optimal filtering enhances S/N depends on the similarity between the Fourier components of the technical noise and those of the signal, with lower S/N enhancements observed for more similar Fourier decompositions of the signal and technical noise. We also examine the linearity of optimal filtered spectra in both time and intensity. This was accomplished by creating a synthetic spectrum for the species being studied (CH4, N2O, CO2 and H2O in ambient air) utilizing line positions and linewidths with an assumed Voigt profile from a commercial database (HITRAN). Agreement better than 0.036% in wavenumber and 1.64% in intensity (up to a 260-fold intensity ratio employed) was observed. Our results suggest that rapid ex post facto digital optimal filtering can be used to enhance S/N for routine trace gas detection.

Signal-to-noise limitations in white light holography.

PubMed

Ribak, E; Roddier, C; Roddier, F; Breckinridge, J B

1988-03-15

A simple derivation is given for the signal-to-noise ratio (SNR) in images reconstructed from incoherent holograms. Dependence is shown to be on the hologram SNR, object complexity, and the number of pixels in the detector. Reconstruction of involved objects becomes possible with high dynamic range detectors such as charge coupled devices. We have produced such white light holograms by means of a rotational shear interferometer combined with a chromatic corrector. A digital inverse transform recreated the object.

Analysis on frequency response of trans-impedance amplifier (TIA) for signal-to-noise ratio (SNR) enhancement in optical signal detection system using lock-in amplifier (LIA)

NASA Astrophysics Data System (ADS)

Kim, Ji-Hoon; Jeon, Su-Jin; Ji, Myung-Gi; Park, Jun-Hee; Choi, Young-Wan

2017-02-01

Lock-in amplifier (LIA) has been widely used in optical signal detection systems because it can measure small signal under high noise level. Generally, The LIA used in optical signal detection system is composed of transimpedance amplifier (TIA), phase sensitive detector (PSD) and low pass filter (LPF). But commercial LIA using LPF is affected by flicker noise. To avoid flicker noise, there is 2ω detection LIA using BPF. To improve the dynamic reserve (DR) of the 2ω LIA, the signal to noise ratio (SNR) of the TIA should be improved. According to the analysis of frequency response of the TIA, the noise gain can be minimized by proper choices of input capacitor (Ci) and feed-back network in the TIA in a specific frequency range. In this work, we have studied how the SNR of the TIA can be improved by a proper choice of frequency range. We have analyzed the way to control this frequency range through the change of passive component in the TIA. The result shows that the variance of the passive component in the TIA can change the specific frequency range where the noise gain is minimized in the uniform gain region of the TIA.

Enhanced signal-to-noise ratios in frog hearing can be achieved through amplitude death

PubMed Central

Ahn, Kang-Hun

2013-01-01

In the ear, hair cells transform mechanical stimuli into neuronal signals with great sensitivity, relying on certain active processes. Individual hair cell bundles of non-mammals such as frogs and turtles are known to show spontaneous oscillation. However, hair bundles in vivo must be quiet in the absence of stimuli, otherwise the signal is drowned in intrinsic noise. Thus, a certain mechanism is required in order to suppress intrinsic noise. Here, through a model study of elastically coupled hair bundles of bullfrog sacculi, we show that a low stimulus threshold and a high signal-to-noise ratio (SNR) can be achieved through the amplitude death phenomenon (the cessation of spontaneous oscillations by coupling). This phenomenon occurs only when the coupled hair bundles have inhomogeneous distribution, which is likely to be the case in biological systems. We show that the SNR has non-monotonic dependence on the mass of the overlying membrane, and find out that the SNR has maximum value in the region of amplitude death. The low threshold of stimulus through amplitude death may account for the experimentally observed high sensitivity of frog sacculi in detecting vibration. The hair bundles' amplitude death mechanism provides a smart engineering design for low-noise amplification. PMID:23883956

Discrimination of acoustic communication signals by grasshoppers (Chorthippus biguttulus): temporal resolution, temporal integration, and the impact of intrinsic noise.

PubMed

Ronacher, Bernhard; Wohlgemuth, Sandra; Vogel, Astrid; Krahe, Rüdiger

2008-08-01

A characteristic feature of hearing systems is their ability to resolve both fast and subtle amplitude modulations of acoustic signals. This applies also to grasshoppers, which for mate identification rely mainly on the characteristic temporal patterns of their communication signals. Usually the signals arriving at a receiver are contaminated by various kinds of noise. In addition to extrinsic noise, intrinsic noise caused by stochastic processes within the nervous system contributes to making signal recognition a difficult task. The authors asked to what degree intrinsic noise affects temporal resolution and, particularly, the discrimination of similar acoustic signals. This study aims at exploring the neuronal basis for sexual selection, which depends on exploiting subtle differences between basically similar signals. Applying a metric, by which the similarities of spike trains can be assessed, the authors investigated how well the communication signals of different individuals of the same species could be discriminated and correctly classified based on the responses of auditory neurons. This spike train metric yields clues to the optimal temporal resolution with which spike trains should be evaluated. (c) 2008 APA, all rights reserved

Noise-Source Separation Using Internal and Far-Field Sensors for a Full-Scale Turbofan Engine

NASA Technical Reports Server (NTRS)

Hultgren, Lennart S.; Miles, Jeffrey H.

2009-01-01

Noise-source separation techniques for the extraction of the sub-dominant combustion noise from the total noise signatures obtained in static-engine tests are described. Three methods are applied to data from a static, full-scale engine test. Both 1/3-octave and narrow-band results are discussed. The results are used to assess the combustion-noise prediction capability of the Aircraft Noise Prediction Program (ANOPP). A new additional phase-angle-based discriminator for the three-signal method is also introduced.

Multimachine data–based prediction of high-frequency sensor signal noise for resistive wall mode control in ITER

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Yueqiang; Sabbagh, S. A.; Chapman, I. T.

The high-frequency noise measured by magnetic sensors, at levels above the typical frequency of resistive wall modes, is analyzed across a range of present tokamak devices including DIII-D, JET, MAST, ASDEX Upgrade, JT-60U, and NSTX. A high-pass filter enables identification of the noise component with Gaussian-like statistics that shares certain common characteristics in all devices considered. A conservative prediction is made for ITER plasma operation of the high-frequency noise component of the sensor signals, to be used for resistive wall mode feedback stabilization, based on the multimachine database. The predicted root-mean-square n = 1 (n is the toroidal mode number)more » noise level is 10 4 to 10 5 G/s for the voltage signal, and 0.1 to 1 G for the perturbed magnetic field signal. The lower cutoff frequency of the Gaussian pickup noise scales linearly with the sampling frequency, with a scaling coefficient of about 0.1. As a result, these basic noise characteristics should be useful for the modeling-based design of the feedback control system for the resistive wall mode in ITER.« less

Multimachine data–based prediction of high-frequency sensor signal noise for resistive wall mode control in ITER

DOE PAGES

Liu, Yueqiang; Sabbagh, S. A.; Chapman, I. T.; ...

2017-03-27

The high-frequency noise measured by magnetic sensors, at levels above the typical frequency of resistive wall modes, is analyzed across a range of present tokamak devices including DIII-D, JET, MAST, ASDEX Upgrade, JT-60U, and NSTX. A high-pass filter enables identification of the noise component with Gaussian-like statistics that shares certain common characteristics in all devices considered. A conservative prediction is made for ITER plasma operation of the high-frequency noise component of the sensor signals, to be used for resistive wall mode feedback stabilization, based on the multimachine database. The predicted root-mean-square n = 1 (n is the toroidal mode number)more » noise level is 10 4 to 10 5 G/s for the voltage signal, and 0.1 to 1 G for the perturbed magnetic field signal. The lower cutoff frequency of the Gaussian pickup noise scales linearly with the sampling frequency, with a scaling coefficient of about 0.1. As a result, these basic noise characteristics should be useful for the modeling-based design of the feedback control system for the resistive wall mode in ITER.« less

Trichotomous noise controlled signal amplification in a generalized Verhulst model

NASA Astrophysics Data System (ADS)

Mankin, Romi; Soika, Erkki; Lumi, Neeme

2014-10-01

The long-time limit of the probability distribution and statistical moments for a population size are studied by means of a stochastic growth model with generalized Verhulst self-regulation. The effect of variable environment on the carrying capacity of a population is modeled by a multiplicative three-level Markovian noise and by a time periodic deterministic component. Exact expressions for the moments of the population size have been calculated. It is shown that an interplay of a small periodic forcing and colored noise can cause large oscillations of the mean population size. The conditions for the appearance of such a phenomenon are found and illustrated by graphs. Implications of the results on models of symbiotic metapopulations are also discussed. Particularly, it is demonstrated that the effect of noise-generated amplification of an input signal gets more pronounced as the intensity of symbiotic interaction increases.

Visual signal detection in structured backgrounds. II. Effects of contrast gain control, background variations, and white noise

NASA Technical Reports Server (NTRS)

Eckstein, M. P.; Ahumada, A. J. Jr; Watson, A. B.

1997-01-01

Studies of visual detection of a signal superimposed on one of two identical backgrounds show performance degradation when the background has high contrast and is similar in spatial frequency and/or orientation to the signal. To account for this finding, models include a contrast gain control mechanism that pools activity across spatial frequency, orientation and space to inhibit (divisively) the response of the receptor sensitive to the signal. In tasks in which the observer has to detect a known signal added to one of M different backgrounds grounds due to added visual noise, the main sources of degradation are the stochastic noise in the image and the suboptimal visual processing. We investigate how these two sources of degradation (contrast gain control and variations in the background) interact in a task in which the signal is embedded in one of M locations in a complex spatially varying background (structured background). We use backgrounds extracted from patient digital medical images. To isolate effects of the fixed deterministic background (the contrast gain control) from the effects of the background variations, we conduct detection experiments with three different background conditions: (1) uniform background, (2) a repeated sample of structured background, and (3) different samples of structured background. Results show that human visual detection degrades from the uniform background condition to the repeated background condition and degrades even further in the different backgrounds condition. These results suggest that both the contrast gain control mechanism and the background random variations degrade human performance in detection of a signal in a complex, spatially varying background. A filter model and added white noise are used to generate estimates of sampling efficiencies, an equivalent internal noise, an equivalent contrast-gain-control-induced noise, and an equivalent noise due to the variations in the structured background.

MEMS microphone innovations towards high signal to noise ratios (Conference Presentation) (Plenary Presentation)

NASA Astrophysics Data System (ADS)

Dehé, Alfons

2017-06-01

After decades of research and more than ten years of successful production in very high volumes Silicon MEMS microphones are mature and unbeatable in form factor and robustness. Audio applications such as video, noise cancellation and speech recognition are key differentiators in smart phones. Microphones with low self-noise enable those functions. Backplate-free microphones enter the signal to noise ratios above 70dB(A). This talk will describe state of the art MEMS technology of Infineon Technologies. An outlook on future technologies such as the comb sensor microphone will be given.

How to COAAD Images. II. A Coaddition Image that is Optimal for Any Purpose in the Background-dominated Noise Limit

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zackay, Barak; Ofek, Eran O.

Image coaddition is one of the most basic operations that astronomers perform. In Paper I, we presented the optimal ways to coadd images in order to detect faint sources and to perform flux measurements under the assumption that the noise is approximately Gaussian. Here, we build on these results and derive from first principles a coaddition technique that is optimal for any hypothesis testing and measurement (e.g., source detection, flux or shape measurements, and star/galaxy separation), in the background-noise-dominated case. This method has several important properties. The pixels of the resulting coadded image are uncorrelated. This image preserves all themore » information (from the original individual images) on all spatial frequencies. Any hypothesis testing or measurement that can be done on all the individual images simultaneously, can be done on the coadded image without any loss of information. The PSF of this image is typically as narrow, or narrower than the PSF of the best image in the ensemble. Moreover, this image is practically indistinguishable from a regular single image, meaning that any code that measures any property on a regular astronomical image can be applied to it unchanged. In particular, the optimal source detection statistic derived in Paper I is reproduced by matched filtering this image with its own PSF. This coaddition process, which we call proper coaddition, can be understood as the maximum signal-to-noise ratio measurement of the Fourier transform of the image, weighted in such a way that the noise in the entire Fourier domain is of equal variance. This method has important implications for multi-epoch seeing-limited deep surveys, weak lensing galaxy shape measurements, and diffraction-limited imaging via speckle observations. The last topic will be covered in depth in future papers. We provide an implementation of this algorithm in MATLAB.« less

Sources of signal-dependent noise during isometric force production.

PubMed

Jones, Kelvin E; Hamilton, Antonia F; Wolpert, Daniel M

2002-09-01

It has been proposed that the invariant kinematics observed during goal-directed movements result from reducing the consequences of signal-dependent noise (SDN) on motor output. The purpose of this study was to investigate the presence of SDN during isometric force production and determine how central and peripheral components contribute to this feature of motor control. Peripheral and central components were distinguished experimentally by comparing voluntary contractions to those elicited by electrical stimulation of the extensor pollicis longus muscle. To determine other factors of motor-unit physiology that may contribute to SDN, a model was constructed and its output compared with the empirical data. SDN was evident in voluntary isometric contractions as a linear scaling of force variability (SD) with respect to the mean force level. However, during electrically stimulated contractions to the same force levels, the variability remained constant over the same range of mean forces. When the subjects were asked to combine voluntary with stimulation-induced contractions, the linear scaling relationship between the SD and mean force returned. The modeling results highlight that much of the basic physiological organization of the motor-unit pool, such as range of twitch amplitudes and range of recruitment thresholds, biases force output to exhibit linearly scaled SDN. This is in contrast to the square root scaling of variability with mean force present in any individual motor-unit of the pool. Orderly recruitment by twitch amplitude was a necessary condition for producing linearly scaled SDN. Surprisingly, the scaling of SDN was independent of the variability of motoneuron firing and therefore by inference, independent of presynaptic noise in the motor command. We conclude that the linear scaling of SDN during voluntary isometric contractions is a natural by-product of the organization of the motor-unit pool that does not depend on signal-dependent noise in the

Compaction of rolling circle amplification products increases signal integrity and signal-to-noise ratio

PubMed Central

Clausson, Carl-Magnus; Arngården, Linda; Ishaq, Omer; Klaesson, Axel; Kühnemund, Malte; Grannas, Karin; Koos, Björn; Qian, Xiaoyan; Ranefall, Petter; Krzywkowski, Tomasz; Brismar, Hjalmar; Nilsson, Mats; Wählby, Carolina; Söderberg, Ola

2015-01-01

Rolling circle amplification (RCA) for generation of distinct fluorescent signals in situ relies upon the self-collapsing properties of single-stranded DNA in commonly used RCA-based methods. By introducing a cross-hybridizing DNA oligonucleotide during rolling circle amplification, we demonstrate that the fluorophore-labeled RCA products (RCPs) become smaller. The reduced size of RCPs increases the local concentration of fluorophores and as a result, the signal intensity increases together with the signal-to-noise ratio. Furthermore, we have found that RCPs sometimes tend to disintegrate and may be recorded as several RCPs, a trait that is prevented with our cross-hybridizing DNA oligonucleotide. These effects generated by compaction of RCPs improve accuracy of visual as well as automated in situ analysis for RCA based methods, such as proximity ligation assays (PLA) and padlock probes. PMID:26202090

An improved method based on wavelet coefficient correlation to filter noise in Doppler ultrasound blood flow signals

NASA Astrophysics Data System (ADS)

Wan, Renzhi; Zu, Yunxiao; Shao, Lin

2018-04-01

The blood echo signal maintained through Medical ultrasound Doppler devices would always include vascular wall pulsation signal .The traditional method to de-noise wall signal is using high-pass filter, which will also remove the lowfrequency part of the blood flow signal. Some scholars put forward a method based on region selective reduction, which at first estimates of the wall pulsation signals and then removes the wall signal from the mixed signal. Apparently, this method uses the correlation between wavelet coefficients to distinguish blood signal from wall signal, but in fact it is a kind of wavelet threshold de-noising method, whose effect is not so much ideal. In order to maintain a better effect, this paper proposes an improved method based on wavelet coefficient correlation to separate blood signal and wall signal, and simulates the algorithm by computer to verify its validity.

Multiplane wave imaging increases signal-to-noise ratio in ultrafast ultrasound imaging.

PubMed

Tiran, Elodie; Deffieux, Thomas; Correia, Mafalda; Maresca, David; Osmanski, Bruno-Felix; Sieu, Lim-Anna; Bergel, Antoine; Cohen, Ivan; Pernot, Mathieu; Tanter, Mickael

2015-11-07

Ultrafast imaging using plane or diverging waves has recently enabled new ultrasound imaging modes with improved sensitivity and very high frame rates. Some of these new imaging modalities include shear wave elastography, ultrafast Doppler, ultrafast contrast-enhanced imaging and functional ultrasound imaging. Even though ultrafast imaging already encounters clinical success, increasing even more its penetration depth and signal-to-noise ratio for dedicated applications would be valuable. Ultrafast imaging relies on the coherent compounding of backscattered echoes resulting from successive tilted plane waves emissions; this produces high-resolution ultrasound images with a trade-off between final frame rate, contrast and resolution. In this work, we introduce multiplane wave imaging, a new method that strongly improves ultrafast images signal-to-noise ratio by virtually increasing the emission signal amplitude without compromising the frame rate. This method relies on the successive transmissions of multiple plane waves with differently coded amplitudes and emission angles in a single transmit event. Data from each single plane wave of increased amplitude can then be obtained, by recombining the received data of successive events with the proper coefficients. The benefits of multiplane wave for B-mode, shear wave elastography and ultrafast Doppler imaging are experimentally demonstrated. Multiplane wave with 4 plane waves emissions yields a 5.8  ±  0.5 dB increase in signal-to-noise ratio and approximately 10 mm in penetration in a calibrated ultrasound phantom (0.7 d MHz(-1) cm(-1)). In shear wave elastography, the same multiplane wave configuration yields a 2.07  ±  0.05 fold reduction of the particle velocity standard deviation and a two-fold reduction of the shear wave velocity maps standard deviation. In functional ultrasound imaging, the mapping of cerebral blood volume results in a 3 to 6 dB increase of the contrast-to-noise ratio in deep

Substrate noise coupling: a pain for mixed-signal systems (Keynote Address)

NASA Astrophysics Data System (ADS)

Wambacq, Piet; Van der Plas, Geert; Donnay, Stephane; Badaroglu, Mustafa; Soens, Charlotte

2005-06-01

Crosstalk from digital to analog in mixed-signal ICs is recognized as one of the major roadblocks for systems-on-chip (SoC) in future CMOS technologies. This crosstalk mainly happens via the semiconducting silicon substrate, which is usually treated as a ground node by analog and RF designers. The substrate noise coupling problem leads more and more to malfunctioning or extra design iterations. One of the reasons is that the phenomenon of substrate noise coupling is difficult to model and hence difficult to understand. It can be caused by the switching of thousands or millions of gates and depends on layout details. From the generation side (the digital domain), coping with the large amount of noise generators can be solved by macromodeling. On the other hand, the impact of substrate noise on the analog circuits requires careful modeling at the level of transistors and parasitics of layout, power supply, package, PCB, Comparison to measurements of macromodeling at the digital side and careful modeling at the analog side, shows that both the generation and the impact of substrate noise can be predicted with an accuracy of a few dB. In addition, this combination of macromodeling at the digital side and careful modeling at the analog side leads to an understanding of the problem, which can be used for digital low-noise design techniques to minimize the generation of noise, and substrate noise immune design of analog/RF circuits.

Coherency of seismic noise, Green functions and site effects

NASA Astrophysics Data System (ADS)

Prieto, G. A.; Beroza, G. C.

2007-12-01

The newly rediscovered methodology of cross correlating seismic noise (or seismic coda) to retrieve the Green function takes advantage of the coherency of the signals across a set of stations. Only coherent signals are expected to emerge after stacking over a long enough time. Cross-correlation has a significant disadvantage for this purpose, in that the Green function recovered is convolved with the source-time function of the noise source. For seismic waves, this can mean that the microseism peak dominates the signal. We show how the use of the transfer function between sensors provides a better resolved Green function (after inverse Fourier transform), because the deconvolution process removes the effect of the noise source-time function. In addition, we compute the coherence of the seismic noise as a function of frequency and distance, providing information about the effective frequency band over which Green function retrieval is possible. The coherence may also be used in resolution analysis for time reversal as a constraint on the de-coherence length (the distance between sensors over which the signals become uncorrelated). We use the information from the transfer function and the coherence to examine wave propagation effects (attenuation and site effects) for closely spaced stations compared to a reference station.

A joint resonance frequency estimation and in-band noise reduction method for enhancing the detectability of bearing fault signals

NASA Astrophysics Data System (ADS)

Bozchalooi, I. Soltani; Liang, Ming

2008-05-01

The vibration signal measured from a bearing contains vital information for the prognostic and health assessment purposes. However, when bearings are installed as part of a complex mechanical system, the measured signal is often heavily clouded by various noises due to the compounded effect of interferences of other machine elements and background noises present in the measuring device. As such, reliable condition monitoring would not be possible without proper de-noising. This is particularly true for incipient bearing faults with very weak signature signals. A new de-noising scheme is proposed in this paper to enhance the vibration signals acquired from faulty bearings. This de-noising scheme features a spectral subtraction to trim down the in-band noise prior to wavelet filtering. The Gabor wavelet is used in the wavelet transform and its parameters, i.e., scale and shape factor are selected in separate steps. The proper scale is found based on a novel resonance estimation algorithm. This algorithm makes use of the information derived from the variable shaft rotational speed though such variation is highly undesirable in fault detection since it complicates the process substantially. The shape factor value is then selected by minimizing a smoothness index. This index is defined as the ratio of the geometric mean to the arithmetic mean of the wavelet coefficient moduli. De-noising results are presented for simulated signals and experimental data acquired from both normal and faulty bearings with defective outer race, inner race, and rolling element.

An artificial EMG generation model based on signal-dependent noise and related application to motion classification

PubMed Central

Hayashi, Hideaki; Nakamura, Go; Chin, Takaaki; Tsuji, Toshio

2017-01-01

This paper proposes an artificial electromyogram (EMG) signal generation model based on signal-dependent noise, which has been ignored in existing methods, by introducing the stochastic construction of the EMG signals. In the proposed model, an EMG signal variance value is first generated from a probability distribution with a shape determined by a commanded muscle force and signal-dependent noise. Artificial EMG signals are then generated from the associated Gaussian distribution with a zero mean and the generated variance. This facilitates representation of artificial EMG signals with signal-dependent noise superimposed according to the muscle activation levels. The frequency characteristics of the EMG signals are also simulated via a shaping filter with parameters determined by an autoregressive model. An estimation method to determine EMG variance distribution using rectified and smoothed EMG signals, thereby allowing model parameter estimation with a small number of samples, is also incorporated in the proposed model. Moreover, the prediction of variance distribution with strong muscle contraction from EMG signals with low muscle contraction and related artificial EMG generation are also described. The results of experiments conducted, in which the reproduction capability of the proposed model was evaluated through comparison with measured EMG signals in terms of amplitude, frequency content, and EMG distribution demonstrate that the proposed model can reproduce the features of measured EMG signals. Further, utilizing the generated EMG signals as training data for a neural network resulted in the classification of upper limb motion with a higher precision than by learning from only measured EMG signals. This indicates that the proposed model is also applicable to motion classification. PMID:28640883

Fractional Gaussian noise-enhanced information capacity of a nonlinear neuron model with binary signal input

NASA Astrophysics Data System (ADS)

Gao, Feng-Yin; Kang, Yan-Mei; Chen, Xi; Chen, Guanrong

2018-05-01

This paper reveals the effect of fractional Gaussian noise with Hurst exponent H ∈(1 /2 ,1 ) on the information capacity of a general nonlinear neuron model with binary signal input. The fGn and its corresponding fractional Brownian motion exhibit long-range, strong-dependent increments. It extends standard Brownian motion to many types of fractional processes found in nature, such as the synaptic noise. In the paper, for the subthreshold binary signal, sufficient conditions are given based on the "forbidden interval" theorem to guarantee the occurrence of stochastic resonance, while for the suprathreshold binary signal, the simulated results show that additive fGn with Hurst exponent H ∈(1 /2 ,1 ) could increase the mutual information or bits count. The investigation indicated that the synaptic noise with the characters of long-range dependence and self-similarity might be the driving factor for the efficient encoding and decoding of the nervous system.

Reducing Brain Signal Noise in the Prediction of Economic Choices: A Case Study in Neuroeconomics

PubMed Central

Sundararajan, Raanju R.; Palma, Marco A.; Pourahmadi, Mohsen

2017-01-01

In order to reduce the noise of brain signals, neuroeconomic experiments typically aggregate data from hundreds of trials collected from a few individuals. This contrasts with the principle of simple and controlled designs in experimental and behavioral economics. We use a frequency domain variant of the stationary subspace analysis (SSA) technique, denoted as DSSA, to filter out the noise (nonstationary sources) in EEG brain signals. The nonstationary sources in the brain signal are associated with variations in the mental state that are unrelated to the experimental task. DSSA is a powerful tool for reducing the number of trials needed from each participant in neuroeconomic experiments and also for improving the prediction performance of an economic choice task. For a single trial, when DSSA is used as a noise reduction technique, the prediction model in a food snack choice experiment has an increase in overall accuracy by around 10% and in sensitivity and specificity by around 20% and in AUC by around 30%, respectively. PMID:29311784

Reducing Brain Signal Noise in the Prediction of Economic Choices: A Case Study in Neuroeconomics.

PubMed

Sundararajan, Raanju R; Palma, Marco A; Pourahmadi, Mohsen

2017-01-01

In order to reduce the noise of brain signals, neuroeconomic experiments typically aggregate data from hundreds of trials collected from a few individuals. This contrasts with the principle of simple and controlled designs in experimental and behavioral economics. We use a frequency domain variant of the stationary subspace analysis (SSA) technique, denoted as DSSA, to filter out the noise (nonstationary sources) in EEG brain signals. The nonstationary sources in the brain signal are associated with variations in the mental state that are unrelated to the experimental task. DSSA is a powerful tool for reducing the number of trials needed from each participant in neuroeconomic experiments and also for improving the prediction performance of an economic choice task. For a single trial, when DSSA is used as a noise reduction technique, the prediction model in a food snack choice experiment has an increase in overall accuracy by around 10% and in sensitivity and specificity by around 20% and in AUC by around 30%, respectively.

The Signal Importance of Noise

ERIC Educational Resources Information Center

Macy, Michael; Tsvetkova, Milena

2015-01-01

Noise is widely regarded as a residual category--the unexplained variance in a linear model or the random disturbance of a predictable pattern. Accordingly, formal models often impose the simplifying assumption that the world is noise-free and social dynamics are deterministic. Where noise is assigned causal importance, it is often assumed to be a…

A measure of the signal-to-noise ratio of microarray samples and studies using gene correlations.

PubMed

Venet, David; Detours, Vincent; Bersini, Hugues

2012-01-01

The quality of gene expression data can vary dramatically from platform to platform, study to study, and sample to sample. As reliable statistical analysis rests on reliable data, determining such quality is of the utmost importance. Quality measures to spot problematic samples exist, but they are platform-specific, and cannot be used to compare studies. As a proxy for quality, we propose a signal-to-noise ratio for microarray data, the "Signal-to-Noise Applied to Gene Expression Experiments", or SNAGEE. SNAGEE is based on the consistency of gene-gene correlations. We applied SNAGEE to a compendium of 80 large datasets on 37 platforms, for a total of 24,380 samples, and assessed the signal-to-noise ratio of studies and samples. This allowed us to discover serious issues with three studies. We show that signal-to-noise ratios of both studies and samples are linked to the statistical significance of the biological results. We showed that SNAGEE is an effective way to measure data quality for most types of gene expression studies, and that it often outperforms existing techniques. Furthermore, SNAGEE is platform-independent and does not require raw data files. The SNAGEE R package is available in BioConductor.

Effects of traffic noise on tree frog stress levels, immunity, and color signaling.

PubMed

Troïanowski, Mathieu; Mondy, Nathalie; Dumet, Adeline; Arcanjo, Caroline; Lengagne, Thierry

2017-10-01

During the last decade, many studies have focused on the detrimental effects of noise pollution on acoustic communication. Surprisingly, although it is known that noise exposure strongly influences health in humans, studies on wildlife remain scarce. In order to gain insight into the consequences of traffic noise exposure, we experimentally manipulated traffic noise exposure as well as the endocrine status of animals to investigate physiological and phenotypic consequences of noise pollution in an anuran species. We showed that noise exposure increased stress hormone level and induced an immunosuppressive effect. In addition, both traffic noise exposure and stress hormone application negatively impacted H. arborea vocal sac coloration. Moreover, our results suggest profound changes in sexual selection processes because the best quality males with initial attractive vocal sac coloration were the most impacted by noise. Hence, our study suggests that the recent increases in anthropogenic noise worldwide might affect a broader range of animal species than previously thought, because of alteration of visual signals and immunity. Generalizing these results to other taxa is crucial for the conservation of biodiversity in an increasingly noisy world. © 2017 Society for Conservation Biology.

Signal detection with criterion noise: applications to recognition memory.

PubMed

Benjamin, Aaron S; Diaz, Michael; Wee, Serena

2009-01-01

A tacit but fundamental assumption of the theory of signal detection is that criterion placement is a noise-free process. This article challenges that assumption on theoretical and empirical grounds and presents the noisy decision theory of signal detection (ND-TSD). Generalized equations for the isosensitivity function and for measures of discrimination incorporating criterion variability are derived, and the model's relationship with extant models of decision making in discrimination tasks is examined. An experiment evaluating recognition memory for ensembles of word stimuli revealed that criterion noise is not trivial in magnitude and contributes substantially to variance in the slope of the isosensitivity function. The authors discuss how ND-TSD can help explain a number of current and historical puzzles in recognition memory, including the inconsistent relationship between manipulations of learning and the isosensitivity function's slope, the lack of invariance of the slope with manipulations of bias or payoffs, the effects of aging on the decision-making process in recognition, and the nature of responding in remember-know decision tasks. ND-TSD poses novel, theoretically meaningful constraints on theories of recognition and decision making more generally, and provides a mechanism for rapprochement between theories of decision making that employ deterministic response rules and those that postulate probabilistic response rules.

An approach to improving the signal-to-optical-noise ratio of pulsed magnetic field photonic sensors

NASA Astrophysics Data System (ADS)

Wang, Jiang-ping; Li, Yu-quan

2008-12-01

During last years, interest in pulsed magnetic field sensors has widely increased. In fact, magnetic field measurement has a critical part in various scientific and technical areas. In order to research on pulsed magnetic field characteristic and corresponding measuring and defending means, a sensor with high immunity to electrical noise, high sensitivity, high accuracy and wide dynamic range is needed. The conventional magnetic field measurement system currently use active metallic probes which can disturb the measuring magnetic field and make sensor very sensitive to electromagnetic noise. Photonic magnetic field sensor exhibit great advantages with respect to the electronic ones: a very good galvanic insulation, high sensitivity and very wide bandwidth. Photonic sensing technology is fit for demand of a measure pulsed magnetic field. A type of pulsed magnetic field photonic sensor has been designed, analyzed, and tested. The cross polarization angle in photonic sensor effect on the signal-to-optical-noise ratio is theoretically analyzed in this paper. A novel approach for improving the signal-to-optical-noise ratio of pulsed magnetic field sensors was proposed. The experiments have proved that this approach is practical. The theoretical analysis and simulation results show that the signal-to-optical-noise ratio can potentially be considerably improved by setup suitable for the cross polarization angle.

Efficient algorithm for baseline wander and powerline noise removal from ECG signals based on discrete Fourier series.

PubMed

Bahaz, Mohamed; Benzid, Redha

2018-03-01

Electrocardiogram (ECG) signals are often contaminated with artefacts and noises which can lead to incorrect diagnosis when they are visually inspected by cardiologists. In this paper, the well-known discrete Fourier series (DFS) is re-explored and an efficient DFS-based method is proposed to reduce contribution of both baseline wander (BW) and powerline interference (PLI) noises in ECG records. In the first step, the determination of the exact number of low frequency harmonics contributing in BW is achieved. Next, the baseline drift is estimated by the sum of all associated Fourier sinusoids components. Then, the baseline shift is discarded efficiently by a subtraction of its approximated version from the original biased ECG signal. Concerning the PLI, the subtraction of the contributing harmonics calculated in the same manner reduces efficiently such type of noise. In addition of visual quality results, the proposed algorithm shows superior performance in terms of higher signal-to-noise ratio and smaller mean square error when faced to the DCT-based algorithm.

Environment-specific noise suppression for improved speech intelligibility by cochlear implant users.

PubMed

Hu, Yi; Loizou, Philipos C

2010-06-01

Attempts to develop noise-suppression algorithms that can significantly improve speech intelligibility in noise by cochlear implant (CI) users have met with limited success. This is partly because algorithms were sought that would work equally well in all listening situations. Accomplishing this has been quite challenging given the variability in the temporal/spectral characteristics of real-world maskers. A different approach is taken in the present study focused on the development of environment-specific noise suppression algorithms. The proposed algorithm selects a subset of the envelope amplitudes for stimulation based on the signal-to-noise ratio (SNR) of each channel. Binary classifiers, trained using data collected from a particular noisy environment, are first used to classify the mixture envelopes of each channel as either target-dominated (SNR>or=0 dB) or masker-dominated (SNR<0 dB). Only target-dominated channels are subsequently selected for stimulation. Results with CI listeners indicated substantial improvements (by nearly 44 percentage points at 5 dB SNR) in intelligibility with the proposed algorithm when tested with sentences embedded in three real-world maskers. The present study demonstrated that the environment-specific approach to noise reduction has the potential to restore speech intelligibility in noise to a level near to that attained in quiet.

Amplitude-phase cross talk as a deterioration factor of signal-to-noise ratio in phase-detection noise-cancellation technique for spectral pump/probe measurements and compensation of the amplitude-phase cross talk

NASA Astrophysics Data System (ADS)

Seto, Keisuke; Tarumi, Takashi; Tokunaga, Eiji

2018-06-01

Noise cancellation of the light source is an important method to enhance the signal-to-noise ratio (SNR) and facilitate high-speed detection in pump/probe measurements. We developed a method to eliminate the noise for the multichannel spectral pump/probe measurements with a spectral dispersion of a white probe pulse light. In this method, the sample-induced intensity modulation is converted to the phase modulation of the pulse repetition irrespective of the intensity noise of the light source. The SNR is enhanced through the phase detection of the observed signal with the signal synchronized to the pulse repetition serving as the phase reference (synchronized signal). However, the shot-noise limited performance is not achieved with an intense probe light. In this work, we demonstrate that the performance limitation below the shot noise limit is caused by the amplitude-phase cross talk. It converts the amplitude noise into the phase noise and is caused by the space-charge effect in the photodetector, the reverse bias voltage drop across the load impedance, and the phase detection circuit. The phase delay occurs with an intense light at a PIN photodiode, whereas the phase is advanced in an avalanche photodiode. Although the amplitude distortion characteristics also reduce the performance, the distortion effect is equivalent to the amplitude-phase cross talk. We also propose possible ways to compensate the cross talk effect by using the phase modulation of the synchronized signal for the phase detection based on the instantaneous amplitude.

Investigation of signal models and methods for evaluating structures of processing telecommunication information exchange systems under acoustic noise conditions

NASA Astrophysics Data System (ADS)

Kropotov, Y. A.; Belov, A. A.; Proskuryakov, A. Y.; Kolpakov, A. A.

2018-05-01

The paper considers models and methods for estimating signals during the transmission of information messages in telecommunication systems of audio exchange. One-dimensional probability distribution functions that can be used to isolate useful signals, and acoustic noise interference are presented. An approach to the estimation of the correlation and spectral functions of the parameters of acoustic signals is proposed, based on the parametric representation of acoustic signals and the components of the noise components. The paper suggests an approach to improving the efficiency of interference cancellation and highlighting the necessary information when processing signals from telecommunications systems. In this case, the suppression of acoustic noise is based on the methods of adaptive filtering and adaptive compensation. The work also describes the models of echo signals and the structure of subscriber devices in operational command telecommunications systems.

Improving the signal-to-noise ratio in ultrasound-modulated optical tomography by a lock-in amplifier

NASA Astrophysics Data System (ADS)

Zhu, Lili; Wu, Jingping; Lin, Guimin; Hu, Liangjun; Li, Hui

2016-10-01

With high spatial resolution of ultrasonic location and high sensitivity of optical detection, ultrasound-modulated optical tomography (UOT) is a promising noninvasive biological tissue imaging technology. In biological tissue, the ultrasound-modulated light signals are very weak and are overwhelmed by the strong unmodulated light signals. It is a difficulty and key to efficiently pick out the weak modulated light from strong unmodulated light in UOT. Under the effect of an ultrasonic field, the scattering light intensity presents a periodic variation as the ultrasonic frequency changes. So the modulated light signals would be escape from the high unmodulated light signals, when the modulated light signals and the ultrasonic signal are processed cross correlation operation by a lock-in amplifier and without a chopper. Experimental results indicated that the signal-to-noise ratio of UOT is significantly improved by a lock-in amplifier, and the higher the repetition frequency of pulsed ultrasonic wave, the better the signal-to-noise ratio of UOT.

Signal transmission competing with noise in model excitable brains

NASA Astrophysics Data System (ADS)

Marro, J.; Mejias, J. F.; Pinamonti, G.; Torres, J. J.

2013-01-01

This is a short review of recent studies in our group on how weak signals may efficiently propagate in a system with noise-induced excitation-inhibition competition which adapts to the activity at short-time scales and thus induces excitable conditions. Our numerical results on simple mathematical models should hold for many complex networks in nature, including some brain cortical areas. In particular, they serve us here to interpret available psycho-technical data.

Point process analysis of noise in early invertebrate vision

PubMed Central

Vinnicombe, Glenn

2017-01-01

Noise is a prevalent and sometimes even dominant aspect of many biological processes. While many natural systems have adapted to attenuate or even usefully integrate noise, the variability it introduces often still delimits the achievable precision across biological functions. This is particularly so for visual phototransduction, the process responsible for converting photons of light into usable electrical signals (quantum bumps). Here, randomness of both the photon inputs (regarded as extrinsic noise) and the conversion process (intrinsic noise) are seen as two distinct, independent and significant limitations on visual reliability. Past research has attempted to quantify the relative effects of these noise sources by using approximate methods that do not fully account for the discrete, point process and time ordered nature of the problem. As a result the conclusions drawn from these different approaches have led to inconsistent expositions of phototransduction noise performance. This paper provides a fresh and complete analysis of the relative impact of intrinsic and extrinsic noise in invertebrate phototransduction using minimum mean squared error reconstruction techniques based on Bayesian point process (Snyder) filters. An integrate-fire based algorithm is developed to reliably estimate photon times from quantum bumps and Snyder filters are then used to causally estimate random light intensities both at the front and back end of the phototransduction cascade. Comparison of these estimates reveals that the dominant noise source transitions from extrinsic to intrinsic as light intensity increases. By extending the filtering techniques to account for delays, it is further found that among the intrinsic noise components, which include bump latency (mean delay and jitter) and shape (amplitude and width) variance, it is the mean delay that is critical to noise performance. As the timeliness of visual information is important for real-time action, this delay could

Measuring noise in microwave metamaterials

NASA Astrophysics Data System (ADS)

Wiltshire, M. C. K.; Syms, R. R. A.

2018-05-01

Electromagnetic metamaterials are artificially constructed media composed of arrays of electrical circuits that can exhibit electric and magnetic characteristics unlike those of any conventional materials. However, the materials are lossy and hence noisy, so that the signal-to-noise ratio in practical situations is greatly reduced. In particular, operating in the double negative region, where both the permittivity and the permeability are negative so that the refractive index is real but negative, incurs significant loss and noise penalties. In this work, we report noise measurements on a double negative metamaterial at microwave frequencies and compare them with the results of a simple model based on a transmission line loaded with lossy elements that mimic the split ring resonators and fine wires of the metamaterial. A noise source is associated with the resistive part of each element, and these are added incoherently to predict the total noise spectrum of the metamaterial. The theoretical results are in good agreement with the measurements. In particular, we find that the measured noise spectrum has contributions from both electric and magnetic noise, but is dominated by the magnetic noise. This limits possible applications, even with optimised materials, to functions that cannot be realised by conventional means.

Analysis for signal-to-noise ratio of hyper-spectral imaging FTIR interferometer

NASA Astrophysics Data System (ADS)

Li, Xun-niu; Zheng, Wei-jian; Lei, Zheng-gang; Wang, Hai-yang; Fu, Yan-peng

2013-08-01

Signal-to-noise Ratio of hyper-spectral imaging FTIR interferometer system plays a decisive role on the performance of the instrument. It is necessary to analyze them in the development process. Based on the simplified target/background model, the energy transfer model of the LWIR hyper-spectral imaging interferometer has been discussed. The noise equivalent spectral radiance (NESR) and its influencing factors of the interferometer system was analyzed, and the signal-to-noise（SNR） was calculated by using the properties of NESR and incident radiance. In a typical application environment, using standard atmospheric model of USA(1976 COESA) as a background, and set a reasonable target/background temperature difference, and take Michelson spatial modulation Fourier Transform interferometer as an example, the paper had calculated the NESR and the SNR of the interferometer system which using the commercially LWIR cooled FPA and UFPA detector. The system noise sources of the instrument were also analyzed in the paper. The results of those analyses can be used to optimize and pre-estimate the performance of the interferometer system, and analysis the applicable conditions of use different detectors. It has important guiding significance for the LWIR interferometer spectrometer design.

On signals faint and sparse: The ACICA algorithm for blind de-trending of exoplanetary transits with low signal-to-noise

DOE Office of Scientific and Technical Information (OSTI.GOV)

Waldmann, I. P., E-mail: ingo@star.ucl.ac.uk

2014-01-01

Independent component analysis (ICA) has recently been shown to be a promising new path in data analysis and de-trending of exoplanetary time series signals. Such approaches do not require or assume any prior or auxiliary knowledge about the data or instrument in order to de-convolve the astrophysical light curve signal from instrument or stellar systematic noise. These methods are often known as 'blind-source separation' (BSS) algorithms. Unfortunately, all BSS methods suffer from an amplitude and sign ambiguity of their de-convolved components, which severely limits these methods in low signal-to-noise (S/N) observations where their scalings cannot be determined otherwise. Here wemore » present a novel approach to calibrate ICA using sparse wavelet calibrators. The Amplitude Calibrated Independent Component Analysis (ACICA) allows for the direct retrieval of the independent components' scalings and the robust de-trending of low S/N data. Such an approach gives us an unique and unprecedented insight in the underlying morphology of a data set, which makes this method a powerful tool for exoplanetary data de-trending and signal diagnostics.« less

Improving the Signal-To-Noise Ratio When Monitoring Countermovement Jump Performance.

PubMed

Kennedy, Rodney A; Drake, David

2018-05-08

Kennedy, RA and Drake, D. Improving the signal-to-noise ratio when monitoring countermovement jump performance. J Strength Cond Res XX(X): 000-000, 2018-Countermovement jump (CMJ) performance has been routinely used to monitor neuromuscular status. However, the protocol used to establish the criterion score is not well documented. The purpose of this study was to examine how the protocol used would influence of the sensitivity of CMJ variables in rugby union players. Fifteen male (age: 19.7 ± 0.5 years) rugby union players performed 8 CMJs on 2 occasions, separated by 7 days. The between-session coefficient of variation (CV) was calculated using 2 techniques for treating multiple trials, the average, and the trial with the best jump height (JH), and then compared with the smallest worthwhile change (SWC). The signal-to-noise ratio was measured as the group mean change in a variable divided by the CV. Using the average value across multiple trials is superior to the best trial method, based on lower CVs for all variables. Only the average performance across 6 or more trials was classified as ideal (CV < 0.5 × SWC) for peak velocity (PV). In addition, the signal-to-noise ratio for peak concentric power (PCP), PV, and JH were classified as good, irrespective of the treatment method. Although increasing the number of trials can reduce the random error, it may be pragmatic to simply take the average from 2 to 3 trials, facilitating a CV < SWC for PV, PCP, and JH. Due to its simplicity, JH may be considered the principal variable to monitor neuromuscular fatigue.

The effect of hearing aid signal-processing schemes on acceptable noise levels: perception and prediction.

PubMed

Wu, Yu-Hsiang; Stangl, Elizabeth

2013-01-01

The acceptable noise level (ANL) test determines the maximum noise level that an individual is willing to accept while listening to speech. The first objective of the present study was to systematically investigate the effect of wide dynamic range compression processing (WDRC), and its combined effect with digital noise reduction (DNR) and directional processing (DIR), on ANL. Because ANL represents the lowest signal-to-noise ratio (SNR) that a listener is willing to accept, the second objective was to examine whether the hearing aid output SNR could predict aided ANL across different combinations of hearing aid signal-processing schemes. Twenty-five adults with sensorineural hearing loss participated in the study. ANL was measured monaurally in two unaided and seven aided conditions, in which the status of the hearing aid processing schemes (enabled or disabled) and the location of noise (front or rear) were manipulated. The hearing aid output SNR was measured for each listener in each condition using a phase-inversion technique. The aided ANL was predicted by unaided ANL and hearing aid output SNR, under the assumption that the lowest acceptable SNR at the listener's eardrum is a constant across different ANL test conditions. Study results revealed that, on average, WDRC increased (worsened) ANL by 1.5 dB, while DNR and DIR decreased (improved) ANL by 1.1 and 2.8 dB, respectively. Because the effects of WDRC and DNR on ANL were opposite in direction but similar in magnitude, the ANL of linear/DNR-off was not significantly different from that of WDRC/DNR-on. The results further indicated that the pattern of ANL change across different aided conditions was consistent with the pattern of hearing aid output SNR change created by processing schemes. Compared with linear processing, WDRC creates a noisier sound image and makes listeners less willing to accept noise. However, this negative effect on noise acceptance can be offset by DNR, regardless of microphone mode

Assessing signal-to-noise in quantitative proteomics: multivariate statistical analysis in DIGE experiments.

PubMed

Friedman, David B

2012-01-01

All quantitative proteomics experiments measure variation between samples. When performing large-scale experiments that involve multiple conditions or treatments, the experimental design should include the appropriate number of individual biological replicates from each condition to enable the distinction between a relevant biological signal from technical noise. Multivariate statistical analyses, such as principal component analysis (PCA), provide a global perspective on experimental variation, thereby enabling the assessment of whether the variation describes the expected biological signal or the unanticipated technical/biological noise inherent in the system. Examples will be shown from high-resolution multivariable DIGE experiments where PCA was instrumental in demonstrating biologically significant variation as well as sample outliers, fouled samples, and overriding technical variation that would not be readily observed using standard univariate tests.

Noise frame duration, masking potency and whiteness of temporal noise.

PubMed

Kukkonen, Heljä; Rovamo, Jyrki; Donner, Kristian; Tammikallio, Marja; Raninen, Antti

2002-09-01

Because of the limited contrast range, increasing the duration of the noise frame is often the only option for increasing the masking potency of external, white temporal noise. This, however, reduces the high-frequency cutoff beyond which noise is no longer white. This study was conducted to determine the longest noise frame duration that produces the strongest masking effect and still mimics white noise on the detection of sinusoidal flicker. Contrast energy thresholds (E(th)) were measured for flicker at 1.25 to 20 Hz in strong, purely temporal (spatially uniform), additive, external noise. The masking power of white external noise, characterized by its spectral density at zero frequency N0, increases with the duration of the noise frame. For short noise frame durations, E(th) increased in direct proportion to N0, keeping the nominal signal-to-noise ratio [SNR = (E(th)/N0)(0.5)] constant at threshold. The masking effect thus increased with the duration of the noise frame and the noise mimicked white noise. When noise frame duration and N0 increased further, the nominal SNR at threshold started to decrease, indicating that noise no longer mimicked white noise. The minimum number of noise frames per flicker cycle needed to mimic white noise decreased with increasing flicker frequency from 8.3 at 1.25 Hz to 1.6 at 20 Hz. The critical high-frequency cutoff of detection-limiting temporal noise in terms of noise frames per signal cycle depends on the temporal frequency of the signal. This is opposite to the situation in the spatial domain and must be taken into consideration when temporal signals are masked with temporal noise.

Communication system with adaptive noise suppression

NASA Technical Reports Server (NTRS)

Kozel, David (Inventor); Devault, James A. (Inventor); Birr, Richard B. (Inventor)

2007-01-01

A signal-to-noise ratio dependent adaptive spectral subtraction process eliminates noise from noise-corrupted speech signals. The process first pre-emphasizes the frequency components of the input sound signal which contain the consonant information in human speech. Next, a signal-to-noise ratio is determined and a spectral subtraction proportion adjusted appropriately. After spectral subtraction, low amplitude signals can be squelched. A single microphone is used to obtain both the noise-corrupted speech and the average noise estimate. This is done by determining if the frame of data being sampled is a voiced or unvoiced frame. During unvoiced frames an estimate of the noise is obtained. A running average of the noise is used to approximate the expected value of the noise. Spectral subtraction may be performed on a composite noise-corrupted signal, or upon individual sub-bands of the noise-corrupted signal. Pre-averaging of the input signal's magnitude spectrum over multiple time frames may be performed to reduce musical noise.

Telecoil-mode hearing aid compatibility performance requirements for wireless and cordless handsets: magnetic signal-to-noise.

PubMed

Julstrom, Stephen; Kozma-Spytek, Linda; Isabelle, Scott

2011-09-01

During the revision of the American National Standards Institute (ANSI) C63.19 and the development of the ANSI/Telecommunications Industry Association-1083 hearing aid compatibility standards, it became evident that additional data concerning user acceptance of interfering magnetic noises generated by wireless and cordless telephones were needed in order to determine the requirements for telecoil-coupling compatibility. Further insight was needed into the magnetic signal-to-noise (S/N) ratios required to achieve specific levels of telephone usability by hearing aid wearers. (A companion article addresses magnetic signal level requirements.) Test subjects used their own hearing aids. The magnetic signals were applied through large magnetic head-worn coils, selected for the field orientation appropriate for each hearing aid. After adjusting their aid's volume control to an acoustic speech reference, the subjects adjusted the applied magnetic signal level to find their Most Comfortable Level (MCL). Each subject then adjusted the levels of six of eight different representative interfering noises to three levels of subjective telephone usability: "usable for a brief call," "acceptable for normal use," and "excellent performance." Each subject's objective noise audibility threshold in the presence of speech was also obtained for the various noise types. The 57 test subjects covered an age range of 22 to 79 yr, with a self-reported hearing loss duration of 12 to 72 yr. All had telecoils that they used for at least some telecommunications needs. The self-reported degree of hearing loss ranged from moderate to profound. A guided intake questionnaire yielded general background information for each subject. A test control box fed by prepared speech and noise recordings from computer files enabled the subject or the tester, depending on the portion of the test, to select A-weighting-normalized noise interference levels in 1.25 dB steps relative to the selected MCL. For each

Background Noise Reduction Using Adaptive Noise Cancellation Determined by the Cross-Correlation

NASA Technical Reports Server (NTRS)

Spalt, Taylor B.; Brooks, Thomas F.; Fuller, Christopher R.

2012-01-01

Background noise due to flow in wind tunnels contaminates desired data by decreasing the Signal-to-Noise Ratio. The use of Adaptive Noise Cancellation to remove background noise at measurement microphones is compromised when the reference sensor measures both background and desired noise. The technique proposed modifies the classical processing configuration based on the cross-correlation between the reference and primary microphone. Background noise attenuation is achieved using a cross-correlation sample width that encompasses only the background noise and a matched delay for the adaptive processing. A present limitation of the method is that a minimum time delay between the background noise and desired signal must exist in order for the correlated parts of the desired signal to be separated from the background noise in the crosscorrelation. A simulation yields primary signal recovery which can be predicted from the coherence of the background noise between the channels. Results are compared with two existing methods.

Noise-Optimized Silicon Radiometers

PubMed Central

Eppeldauer, George P.

2000-01-01

This paper describes a new, experimentally verified, noise analysis and the design considerations of the dynamic characteristics of silicon radiometers. Transimpedance gain, loop gain, and voltage gain were optimized versus frequency for photodiode current meters measuring ac and dc optical radiation. Silicon radiometers with improved dynamic characteristics were built and tested. The frequency-dependent photocurrent gains were measured. The noise floor was optimized in an ac measurement mode using photodiodes of different shunt resistance and operational amplifiers with low 1/f voltage and current noise. In the dark (without any signal), the noise floor of the optimized silicon radiometers was dominated by the Johnson noise of the source resistance. The Johnson noise was decreased and equalized to the amplified 1/f input noise at a 9 Hz chopping frequency and 30 s integration time constant, resulting in an equivalent root-mean-square (rms) photocurrent noise of 8 × 10−17 A. The lowest noise floor of 5 × 10−17 A, equal to a noise equivalent power (NEP) of 1.4 × 10−16 W at the 730 nm peak responsivity, was obtained at a 100 s integration time constant. The radiometers, optimized for ac measurements, were tested in a dc measurement mode as well. Performances in ac and dc measurement modes were compared. In the ac mode, a ten times shorter (40 s) overall measurement time was needed than in the dc mode (400 s) to obtain the same 10−16 A noise floor. PMID:27551606

Application of the Radon-FCL approach to seismic random noise suppression and signal preservation

NASA Astrophysics Data System (ADS)

Meng, Fanlei; Li, Yue; Liu, Yanping; Tian, Yanan; Wu, Ning

2016-08-01

The fractal conservation law (FCL) is a linear partial differential equation that is modified by an anti-diffusive term of lower order. The analysis indicated that this algorithm could eliminate high frequencies and preserve or amplify low/medium-frequencies. Thus, this method is quite suitable for the simultaneous noise suppression and enhancement or preservation of seismic signals. However, the conventional FCL filters seismic data only along the time direction, thereby ignoring the spatial coherence between neighbouring traces, which leads to the loss of directional information. Therefore, we consider the development of the conventional FCL into the time-space domain and propose a Radon-FCL approach. We applied a Radon transform to implement the FCL method in this article; performing FCL filtering in the Radon domain achieves a higher level of noise attenuation. Using this method, seismic reflection events can be recovered with the sacrifice of fewer frequency components while effectively attenuating more random noise than conventional FCL filtering. Experiments using both synthetic and common shot point data demonstrate the advantages of the Radon-FCL approach versus the conventional FCL method with regard to both random noise attenuation and seismic signal preservation.

Computational Modelling and Children's Expressions of Signal and Noise

ERIC Educational Resources Information Center

Ainley, Janet; Pratt, Dave

2017-01-01

Previous research has demonstrated how young children can identify the signal in data. In this exploratory study we considered how they might also express meanings for noise when creating computational models using recent developments in software tools. We conducted extended clinical interviews with four groups of 11-year-olds and analysed the…

Micro-Pulse Lidar Signals: Uncertainty Analysis

NASA Technical Reports Server (NTRS)

Welton, Ellsworth J.; Campbell, James R.; Starr, David OC. (Technical Monitor)

2002-01-01

Micro-pulse lidar (MPL) systems are small, autonomous, eye-safe lidars used for continuous observations of the vertical distribution of cloud and aerosol layers. Since the construction of the first MPL in 1993, procedures have been developed to correct for various instrument effects present in MPL signals. The primary instrument effects include afterpulse, laser-detector cross-talk, and overlap, poor near-range (less than 6 km) focusing. The accurate correction of both afterpulse and overlap effects are required to study both clouds and aerosols. Furthermore, the outgoing energy of the laser pulses and the statistical uncertainty of the MPL detector must also be correctly determined in order to assess the accuracy of MPL observations. The uncertainties associated with the afterpulse, overlap, pulse energy, detector noise, and all remaining quantities affecting measured MPL signals, are determined in this study. The uncertainties are propagated through the entire MPL correction process to give a net uncertainty on the final corrected MPL signal. The results show that in the near range, the overlap uncertainty dominates. At altitudes above the overlap region, the dominant source of uncertainty is caused by uncertainty in the pulse energy. However, if the laser energy is low, then during mid-day, high solar background levels can significantly reduce the signal-to-noise of the detector. In such a case, the statistical uncertainty of the detector count rate becomes dominant at altitudes above the overlap region.

Signal to Noise Ratio for Different Gridded Rainfall Products of Indian Monsoon

NASA Astrophysics Data System (ADS)

Nehra, P.; Shastri, H. K.; Ghosh, S.; Mishra, V.; Murtugudde, R. G.

2014-12-01

Gridded rainfall datasets provide useful information of spatial and temporal distribution of precipitation over a region. For India, there are 3 gridded rainfall data products available from India Meteorological Department (IMD), Tropical Rainfall Measurement Mission (TRMM) and Asian Precipitation - Highly Resolved Observational Data Integration towards Evaluation of Water Resources (APHRODITE), these compile precipitation information obtained through satellite based measurement and ground station based data. The gridded rainfall data from IMD is available at spatial resolution of 1°, 0.5° and 0.25° where as TRMM and APHRODITE is available at 0.25°. Here, we employ 7 years (1998-2004) of common time period amongst the 3 data products for the south-west monsoon season, i.e., the months June to September. We examine temporal mean and standard deviation of these 3 products to observe substantial variation amongst them at 1° resolution whereas for 0.25° resolution, all the data types are nearly identical. We determine the Signal to Noise Ratio (SNR) of the 3 products at 1° and 0.25° resolution based on noise separation technique adopting horizontal separation of the power spectrum generated with the Fast Fourier Transformation (FFT). A methodology is developed for threshold based separation of signal and noise from the power spectrum, treating the noise as white. The variance of signal to that of noise is computed to obtain SNR. Determination of SNR for different regions over the country shows the highest SNR with APHRODITE at 0.25° resolution. It is observed that the eastern part of India has the highest SNR in all cases considered whereas the northern and southern most Indian regions have lowest SNR. An incremental linear trend is observed among the SNR values and the spatial variance of corresponding region. Relationship between the computed SNR values and the interpolation method used with the dataset is analyzed. The SNR analysis provides an effective

Comparison of reproduce signal and noise of conventional and keepered CoCrTa/Cr thin film media

NASA Astrophysics Data System (ADS)

Sin, Kyusik; Ding, Juren; Glijer, Pawel; Sivertsen, John M.; Judy, Jack H.; Zhu, Jian-Gang

1994-05-01

We studied keepered high coercivity CoCrTa/Cr thin film media with a Cr isolation layer between the CoCrTa storage and an overcoating of an isotropic NiFe soft magnetic layer. The influence of the thickness of the NiFe and Cr layers, and the effects of head bias current on the signal output and noise, were studied using a thin film head. The reproduced signal increased by 7.3 dB, but the signal-to-noise ratio decreased by 4 dB at a linear density of 2100 fr/mm (53.3 kfr/in.) with a 1000 Å thick NiFe keeper layer. The medium noise increased with increasing NiFe thickness and the signal output decreased with decreasing Cr thickness. A low output signal obtained with very thin Cr may be due to magnetic interactions between the keeper layer and magnetic media layer. It is observed that signal distortion and timing asymmetry of the output signals depend on the thickness of the keeper layer and the head bias current. The signal distortion increased and the timing asymmetry decreased as the head bias current was increased. These results may be associated with different permeability of the keeper under the poles of the thin film head due to the superposition of head bias and bit fields.

Signal and noise level estimation for narrow spectral width returns observed by the Indian MST radar

NASA Astrophysics Data System (ADS)

Hooper, D. A.

1999-07-01

Use is made of five sets of multibeam observations of the lower atmosphere made by the Indian mesosphere-stratosphere-troposphere (MST) radar. Two aspects of signal processing which can lead to serious underestimates of the signal-to-noise ratio are considered. First, a comparison is made of the effects of different data weighting windows applied to the inphase and quadrature components of the radar return samples prior to Fourier transformation. The relatively high degree of spectral leakage associated with the rectangular and Hamming windows can give rise to overestimates of the noise levels by up to 28 dB for the strongest signals. Use of the Hanning window is found to be the most appropriate for these particular data. Second, a technique for removing systematic dc biases from the data in the time domain is compared with the more well-known practice of correction in the frequency domain. The latter technique, which is often used to remove the effects of ground clutter, is shown to be particularly inappropriate for the characteristically narrow spectral width signals observed by the Indian MST radar. For cases of near-zero Doppler shift it can remove up to 30 dB of signal information. The consequences of noise and signal level discrepancies for studies of refractivity structures are discussed. It is shown that neither problem has a significant effect on Doppler shift or spectral width estimates.

Cancelation and its simulation using Matlab according to active noise control case study of automotive noise silencer

NASA Astrophysics Data System (ADS)

Alfisyahrin; Isranuri, I.

2018-02-01

Active Noise Control is a technique to overcome noisy with noise or sound countered with sound in scientific terminology i.e signal countered with signals. This technique can be used to dampen relevant noise in accordance with the wishes of the engineering task and reducing automotive muffler noise to a minimum. Objective of this study is to develop a Active Noise Control which should cancel the noise of automotive Exhaust (Silencer) through Signal Processing Simulation methods. Noise generator of Active Noise Control is to make the opponent signal amplitude and frequency of the automotive noise. The steps are: Firstly, the noise of automotive silencer was measured to characterize the automotive noise that its amplitude and frequency which intended to be expressed. The opposed sound which having similar character with the signal source should be generated by signal function. A comparison between the data which has been completed with simulation calculations Fourier transform field data is data that has been captured on the muffler (noise silencer) Toyota Kijang Capsule assembly 2009. MATLAB is used to simulate how the signal processing noise generated by exhaust (silencer) using FFT. This opponent is inverted phase signal from the signal source 180° conducted by Instruments of Signal Noise Generators. The process of noise cancelation examined through simulation using computer software simulation. The result is obtained that attenuation of sound (noise cancellation) has a difference of 33.7%. This value is obtained from the comparison of the value of the signal source and the signal value of the opponent. So it can be concluded that the noisy signal can be attenuated by 33.7%.

Understanding the amplitudes of noise correlation measurements

USGS Publications Warehouse

Tsai, Victor C.

2011-01-01

Cross correlation of ambient seismic noise is known to result in time series from which station-station travel-time measurements can be made. Part of the reason that these cross-correlation travel-time measurements are reliable is that there exists a theoretical framework that quantifies how these travel times depend on the features of the ambient noise. However, corresponding theoretical results do not currently exist to describe how the amplitudes of the cross correlation depend on such features. For example, currently it is not possible to take a given distribution of noise sources and calculate the cross correlation amplitudes one would expect from such a distribution. Here, we provide a ray-theoretical framework for calculating cross correlations. This framework differs from previous work in that it explicitly accounts for attenuation as well as the spatial distribution of sources and therefore can address the issue of quantifying amplitudes in noise correlation measurements. After introducing the general framework, we apply it to two specific problems. First, we show that we can quantify the amplitudes of coherency measurements, and find that the decay of coherency with station-station spacing depends crucially on the distribution of noise sources. We suggest that researchers interested in performing attenuation measurements from noise coherency should first determine how the dominant sources of noise are distributed. Second, we show that we can quantify the signal-to-noise ratio of noise correlations more precisely than previous work, and that these signal-to-noise ratios can be estimated for given situations prior to the deployment of seismometers. It is expected that there are applications of the theoretical framework beyond the two specific cases considered, but these applications await future work.

Failure of the precedence effect with a noise-band vocoder

PubMed Central

Seeber, Bernhard U.; Hafter, Ervin R.

2011-01-01

The precedence effect (PE) describes the ability to localize a direct, leading sound correctly when its delayed copy (lag) is present, though not separately audible. The relative contribution of binaural cues in the temporal fine structure (TFS) of lead–lag signals was compared to that of interaural level differences (ILDs) and interaural time differences (ITDs) carried in the envelope. In a localization dominance paradigm participants indicated the spatial location of lead–lag stimuli processed with a binaural noise-band vocoder whose noise carriers introduced random TFS. The PE appeared for noise bursts of 10 ms duration, indicating dominance of envelope information. However, for three test words the PE often failed even at short lead–lag delays, producing two images, one toward the lead and one toward the lag. When interaural correlation in the carrier was increased, the images appeared more centered, but often remained split. Although previous studies suggest dominance of TFS cues, no image is lateralized in accord with the ITD in the TFS. An interpretation in the context of auditory scene analysis is proposed: By replacing the TFS with that of noise the auditory system loses the ability to fuse lead and lag into one object, and thus to show the PE. PMID:21428515

TES Detector Noise Limited Readout Using SQUID Multiplexers

NASA Technical Reports Server (NTRS)

Staguhn, J. G.; Benford, D. J.; Chervenak, J. A.; Khan, S. A.; Moseley, S. H.; Shafer, R. A.; Deiker, S.; Grossman, E. N.; Hilton, G. C.; Irwin, K. D.

2004-01-01

The availability of superconducting Transition Edge Sensors (TES) with large numbers of individual detector pixels requires multiplexers for efficient readout. The use of multiplexers reduces the number of wires needed between the cryogenic electronics and the room temperature electronics and cuts the number of required cryogenic amplifiers. We are using an 8 channel SQUID multiplexer to read out one-dimensional TES arrays which are used for submillimeter astronomical observations. We present results from test measurements which show that the low noise level of the SQUID multiplexers allows accurate measurements of the TES Johnson noise, and that in operation, the readout noise is dominated by the detector noise. Multiplexers for large number of channels require a large bandwidth for the multiplexed readout signal. We discuss the resulting implications for the noise performance of these multiplexers which will be used for the readout of two dimensional TES arrays in next generation instruments.

Seismic signal and noise on Europa and how to use it

NASA Astrophysics Data System (ADS)

Panning, M. P.; Stähler, S. C.; Bills, B. G.; Castillo, J.; Huang, H. H.; Husker, A. L.; Kedar, S.; Lorenz, R. D.; Pike, W. T.; Schmerr, N. C.; Tsai, V. C.; Vance, S.

2017-12-01

Seismology is one of our best tools for detailing interior structure of planetary bodies, and a seismometer is included in the baseline and threshold mission design for a potential Europa lander mission. Guiding mission design and planning for adequate science return, though, requires modeling of both the anticipated signal and noise. Assuming ice seismicity on Europa behaves according to statistical properties observed in Earth catalogs and scaling cumulative seismic moment release to the moon, we simulate long seismic records and estimate background noise and peak signal amplitudes (Panning et al., 2017). This suggests a sensitive instrument comparable to many broadband terrestrial instruments or the SP instrument from the InSight mission to Mars will be able to record signals, while high frequency geophones are likely inadequate. We extend this analysis to also begin incorporation of spatial and temporal variation due to the tidal cycle, which can help inform landing site selection. We also begin exploration of how chaotic terrane at the bottom of the ice shell and inter-ice heterogeneities (i.e. internal melt structures) may affect predicted seismic observations using 2D numerical seismic simulations. We also show some of the key seismic observations to determine interior properties of Europa (Stähler et al., 2017). M. P. Panning, S. C. Stähler, H.-H. Huang, S. D. Vance, S. Kedar, V. C. Tsai, W. T. Pike, R. D. Lorenz, "Expected seismicity and the seismic noise environment of Europa," J. Geophys. Res., in revision, 2017. S. C. Stähler, M. P. Panning, S. D. Vance, R. D. Lorenz, M. van Driel, T. Nissen-Meyer, S. Kedar, "Seismic wave propagation in icy ocean worlds," J. Geophys. Res., in revision, 2017.

Application of 3-signal coherence to core noise transmission

NASA Technical Reports Server (NTRS)

Krejsa, E. A.

1983-01-01

A method for determining transfer functions across turbofan engine components and from the engine to the far-field is developed. The method is based on the three-signal coherence technique used previously to obtain far-field core noise levels. This method eliminates the bias error in transfer function measurements due to contamination of measured pressures by nonpropagating pressure fluctuations. Measured transfer functions from the engine to the far-field, across the tailpipe, and across the turbine are presented for three turbofan engines.

Speckle noise reduction technique for Lidar echo signal based on self-adaptive pulse-matching independent component analysis

NASA Astrophysics Data System (ADS)

Xu, Fan; Wang, Jiaxing; Zhu, Daiyin; Tu, Qi

2018-04-01

Speckle noise has always been a particularly tricky problem in improving the ranging capability and accuracy of Lidar system especially in harsh environment. Currently, effective speckle de-noising techniques are extremely scarce and should be further developed. In this study, a speckle noise reduction technique has been proposed based on independent component analysis (ICA). Since normally few changes happen in the shape of laser pulse itself, the authors employed the laser source as a reference pulse and executed the ICA decomposition to find the optimal matching position. In order to achieve the self-adaptability of algorithm, local Mean Square Error (MSE) has been defined as an appropriate criterion for investigating the iteration results. The obtained experimental results demonstrated that the self-adaptive pulse-matching ICA (PM-ICA) method could effectively decrease the speckle noise and recover the useful Lidar echo signal component with high quality. Especially, the proposed method achieves 4 dB more improvement of signal-to-noise ratio (SNR) than a traditional homomorphic wavelet method.

New technique for the direct measurement of core noise from aircraft engines

NASA Technical Reports Server (NTRS)

Krejsa, E. A.

1981-01-01

A new technique is presented for directly measuring the core noise levels from gas turbine aircraft engines. The technique requires that fluctuating pressures be measured in the far-field and at two locations within the engine core. The cross-spectra of these measurements are used to determine the levels of the far-field noise that propagated from the engine core. The technique makes it possible to measure core noise levels even when other noise sources dominate. The technique was applied to signals measured from an AVCO Lycoming YF102 turbofan engine. Core noise levels as a function of frequency and radiation angle were measured and are presented over a range of power settings.

Spectral analysis of fundamental signal and noise performances in photoconductors for mammography.

PubMed

Kim, Ho Kyung; Lim, Chang Hwy; Tanguay, Jesse; Yun, Seungman; Cunningham, Ian A

2012-05-01

This study investigates the fundamental signal and noise performance limitations imposed by the stochastic nature of x-ray interactions in selected photoconductor materials, such as Si, a-Se, CdZnTe, HgI(2), PbI(2), PbO, and TlBr, for x-ray spectra typically used in mammography. It is shown how Monte Carlo simulations can be combined with a cascaded model to determine the absorbed energy distribution for each combination of photoconductor and x-ray spectrum. The model is used to determine the quantum efficiency, mean energy absorption per interaction, Swank noise factor, secondary quantum noise, and zero-frequency detective quantum efficiency (DQE). The quantum efficiency of materials with higher atomic number and density demonstrates a larger dependence on convertor thickness than those with lower atomic number and density with the exception of a-Se. The mean deposited energy increases with increasing average energy of the incident x-ray spectrum. HgI(2), PbI(2), and CdZnTe demonstrate the largest increase in deposited energy with increasing mass loading and a-Se and Si the smallest. The best DQE performances are achieved with PbO and TlBr. For mass loading greater than 100 mg cm(-2), a-Se, HgI(2), and PbI(2) provide similar DQE values to PbO and TlBr. The quantum absorption efficiency, average deposited energy per interacting x-ray, Swank noise factor, and detective quantum efficiency are tabulated by means of graphs which may help with the design and selection of materials for photoconductor-based mammography detectors. Neglecting the electrical characteristics of photoconductor materials and taking into account only x-ray interactions, it is concluded that PbO shows the strongest signal-to-noise ratio performance of the materials investigated in this study.

Periodic variations in the signal-to-noise ratios of signals received from the ICE spacecraft

NASA Technical Reports Server (NTRS)

Nadeau, T.

1986-01-01

Data from the ICE probe to comet Giacobini-Zinner are analyzed to determine the effects of spacecraft rotation upon the signal to noise ratio (SNR) for the two channels of data. In addition, long-term variations from sources other than rotations are considered. Results include a pronounced SNR variation over a period of three seconds (one rotation) and a lesser effect over a two minute period (possibly due to the receiving antenna conscan).

Filter distortion effects on telemetry signal-to-noise ratio

NASA Technical Reports Server (NTRS)

Sadr, R.; Hurd, W.

1987-01-01

The effect of filtering on the Signal-to-Noise Ratio (SNR) of a coherently demodulated band-limited signal is determined in the presence of worse-case amplitude ripple. The problem is formulated mathematically as an optimization problem in the L2-Hilbert space. The form of the worst-cast amplitude ripple is specified, and the degradation in the SNR is derived in a closed form expression. It is shown that when the maximum passband amplitude ripple is 2 delta (peak to peak), the SNR is degraded by at most (1 - delta squared), even when the ripple is unknown or uncompensated. For example, an SNR loss of less than 0.01 dB due to amplitude ripple can be assured by keeping the amplitude ripple to under 0.42 dB.

Noise removal in extended depth of field microscope images through nonlinear signal processing.

PubMed

Zahreddine, Ramzi N; Cormack, Robert H; Cogswell, Carol J

2013-04-01

Extended depth of field (EDF) microscopy, achieved through computational optics, allows for real-time 3D imaging of live cell dynamics. EDF is achieved through a combination of point spread function engineering and digital image processing. A linear Wiener filter has been conventionally used to deconvolve the image, but it suffers from high frequency noise amplification and processing artifacts. A nonlinear processing scheme is proposed which extends the depth of field while minimizing background noise. The nonlinear filter is generated via a training algorithm and an iterative optimizer. Biological microscope images processed with the nonlinear filter show a significant improvement in image quality and signal-to-noise ratio over the conventional linear filter.

DOA-informed source extraction in the presence of competing talkers and background noise

NASA Astrophysics Data System (ADS)

Taseska, Maja; Habets, Emanuël A. P.

2017-12-01

A desired speech signal in hands-free communication systems is often degraded by noise and interfering speech. Even though the number and locations of the interferers are often unknown in practice, it is justified to assume in certain applications that the direction-of-arrival (DOA) of the desired source is approximately known. Using the known DOA, fixed spatial filters such as the delay-and-sum beamformer can be steered to extract the desired source. However, it is well-known that fixed data-independent spatial filters do not provide sufficient reduction of directional interferers. Instead, the DOA information can be used to estimate the statistics of the desired and the undesired signals and to compute optimal data-dependent spatial filters. One way the DOA is exploited for optimal spatial filtering in the literature, is by designing DOA-based narrowband detectors to determine whether a desired or an undesired signal is dominant at each time-frequency (TF) bin. Subsequently, the statistics of the desired and the undesired signals can be estimated during the TF bins where the respective signal is dominant. In a similar manner, a Gaussian signal model-based detector which does not incorporate DOA information has been used in scenarios where the undesired signal consists of stationary background noise. However, when the undesired signal is non-stationary, resulting for example from interfering speakers, such a Gaussian signal model-based detector is unable to robustly distinguish desired from undesired speech. To this end, we propose a DOA model-based detector to determine the dominant source at each TF bin and estimate the desired and undesired signal statistics. We demonstrate that data-dependent spatial filters that use the statistics estimated by the proposed framework achieve very good undesired signal reduction, even when using only three microphones.

A Signal to Noise Paradox in Climate Predictions

NASA Astrophysics Data System (ADS)

Eade, R.; Scaife, A. A.; Smith, D.; Dunstone, N. J.; MacLachlan, C.; Hermanson, L.; Ruth, C.

2017-12-01

Recent advances in climate modelling have resulted in the achievement of skilful long-range prediction, particular that associated with the winter circulation over the north Atlantic (e.g. Scaife et al 2014, Stockdale et al 2015, Dunstone et al 2016) including impacts over Europe and North America, and further afield. However, while highly significant and potentially useful skill exists, the signal-to-noise ratio of the ensemble mean to total variability in these ensemble predictions is anomalously small (Scaife et al 2014) and the correlation between the ensemble mean and historical observations exceeds the proportion of predictable variance in the ensemble (Eade et al 2014). This means the real world is more predictable than our climate models. Here we discuss a series of hypothesis tests that have been carried out to assess issues with model mechanisms compared to the observed world, and present the latest findings in our attempt to determine the cause of the anomalously weak predicted signals in our seasonal-to-decadal hindcasts.

On the signal-to-noise ratio in IUE high-dispersion spectra

NASA Technical Reports Server (NTRS)

Leckrone, David S.; Adelman, Saul J.

1989-01-01

An observational and data reduction technique for fixed pattern noise (FPN) and random noise (RN) in fully extracted IUE high-dispersion spectra is described in detail, along with actual empirical values of signal-to-noise ratio (S/N) achieved. A co-addition procedure, involving SWP and LWR cameras observations of the same spectrum at different positions in the image format, provides a basis to disentangle FPN from RN, allowing each average amplitude, within a given wavelength interval, to be estimated as a function of average flux number. Empirical curves, derived with the noise algorithm, make it possible to estimate the S/N in individual spectra at the wavelengths investigated. The average S/N at the continuum level in well-exposed stellar spectra varies from 10 to 20, for the orders analyzed, depending on position in the spectral format. The co-addition procedure yields an improvement in S/N by factors ranging from 2.3 to 2.9. Direct measurements of S/N in narrow, line-free wavelength intervals of individual and co-added spectra for weak-lined stars yield comparable, or in some cases somewhat higher, S/N values and improvement factors.

Active elimination of radio frequency interference for improved signal-to-noise ratio for in-situ NMR experiments in strong magnetic field gradients

NASA Astrophysics Data System (ADS)

Ibrahim, M.; Pardi, C. I.; Brown, T. W. C.; McDonald, P. J.

2018-02-01

Improvement in the signal-to-noise ratio of Nuclear Magnetic Resonance (NMR) systems may be achieved either by increasing the signal amplitude or by decreasing the noise. The noise has multiple origins - not all of which are strictly "noise": incoherent thermal noise originating in the probe and pre-amplifiers, probe ring down or acoustic noise and coherent externally broadcast radio frequency transmissions. The last cannot always be shielded in open access experiments. In this paper, we show that pulsed, low radio-frequency data communications are a significant source of broadcast interference. We explore two signal processing methods of de-noising short T2∗ NMR experiments corrupted by these communications: Linear Predictive Coding (LPC) and the Discrete Wavelet Transform (DWT). Results are shown for numerical simulations and experiments conducted under controlled conditions with pseudo radio frequency interference. We show that both the LPC and DWT methods have merit.

Signal-to-noise ratio of arbitrarily filtered spontaneous emission

NASA Astrophysics Data System (ADS)

Šprem, Marko; Bosiljevac, Marko; Babić, Dubravko

2018-02-01

The signal-to-noise ratio (SNR) of filtered incoherent light can be approximated from the product of the coherence time of the light and the equivalent (electrical) noise bandwidth of the detector. This approximation holds only for the light with very short coherence time, that is in the case where the optical bandwidth of the light is much larger than the electrical bandwidth. We present here an expression for accurate evaluation of the SNR of the filtered incoherent light, which computes SNR from arbitrary shapes of optical and electrical filter power spectral densities (PSD). The PSDs of the filters can be measured using optical and electrical spectrum analyzers. Using our expression, we show that the SNR reaches unity when the electrical filter bandwidth is becoming larger than the optical filter bandwidth. To prove the theory, we evaluate and directly measure SNR of an incoherent light source filtered with several optical filters with bandwidths larger and commensurate with the bandwidth of the detector. For later we used optical and electrical filters with 3-dB bandwidths of 15 GHz and 10 GHz, respectively. Using our expression to evaluate SNR we obtained results in a good agreement with directly measured SNR. The results also prove that the approximation for evaluating SNR does not provide accurate results. The PSD of the detector with large noise bandwidth is difficult to measure using spectrum analyzer. There- fore, we report here a method for measuring the electrical noise bandwidth of the detector using the heterodyne linewidth measurement technique with tunable laser.

An Infrared Camera Simulation for Estimating Spatial Temperature Profiles and Signal-to-Noise Ratios of an Airborne Laser-Illuminated Target

DTIC Science & Technology

2007-06-01

of SNR, she incorporated the effects that an InGaAs photovoltaic detector have in producing the signal along with the photon, Johnson, and shot noises ...the photovoltaic FPA detector modeled? • What detector noise sources limit the computed signal? 3.1 Modeling Methodology Two aspects in the IR camera...Another shot noise source in photovoltaic detectors is dark current. This current represents the current flowing in the detector when no optical radiation

Enhancement of Signal-to-noise Ratio in Natural-source Transient Magnetotelluric Data with Wavelet Transform

NASA Astrophysics Data System (ADS)

Zhang, Y.; Paulson, K. V.

For audio-frequency magnetotelluric surveys where the signals are lightning-stroke transients, the conventional Fourier transform method often fails to produce a high quality impedance tensor. An alternative approach is to use the wavelet transform method which is capable of localizing target information simultaneously in both the temporal and frequency domains. Unlike Fourier analysis that yields an average amplitude and phase, the wavelet transform produces an instantaneous estimate of the amplitude and phase of a signal. In this paper a complex well-localized wavelet, the Morlet wavelet, has been used to transform and analyze audio-frequency magnetotelluric data. With the Morlet wavelet, the magnetotelluric impedance tensor can be computed directly in the wavelet transform domain. The lightning-stroke transients are easily identified on the dilation-translation plane. Choosing those wavelet transform values where the signals are located, a higher signal-to-noise ratio estimation of the impedance tensor can be obtained. In a test using real data, the wavelet transform showed a significant improvement in the signal-to-noise ratio over the conventional Fourier transform.

Computational study of noise in a large signal transduction network.

PubMed

Intosalmi, Jukka; Manninen, Tiina; Ruohonen, Keijo; Linne, Marja-Leena

2011-06-21

Biochemical systems are inherently noisy due to the discrete reaction events that occur in a random manner. Although noise is often perceived as a disturbing factor, the system might actually benefit from it. In order to understand the role of noise better, its quality must be studied in a quantitative manner. Computational analysis and modeling play an essential role in this demanding endeavor. We implemented a large nonlinear signal transduction network combining protein kinase C, mitogen-activated protein kinase, phospholipase A2, and β isoform of phospholipase C networks. We simulated the network in 300 different cellular volumes using the exact Gillespie stochastic simulation algorithm and analyzed the results in both the time and frequency domain. In order to perform simulations in a reasonable time, we used modern parallel computing techniques. The analysis revealed that time and frequency domain characteristics depend on the system volume. The simulation results also indicated that there are several kinds of noise processes in the network, all of them representing different kinds of low-frequency fluctuations. In the simulations, the power of noise decreased on all frequencies when the system volume was increased. We concluded that basic frequency domain techniques can be applied to the analysis of simulation results produced by the Gillespie stochastic simulation algorithm. This approach is suited not only to the study of fluctuations but also to the study of pure noise processes. Noise seems to have an important role in biochemical systems and its properties can be numerically studied by simulating the reacting system in different cellular volumes. Parallel computing techniques make it possible to run massive simulations in hundreds of volumes and, as a result, accurate statistics can be obtained from computational studies. © 2011 Intosalmi et al; licensee BioMed Central Ltd.

Speech enhancement based on neural networks improves speech intelligibility in noise for cochlear implant users.

PubMed

Goehring, Tobias; Bolner, Federico; Monaghan, Jessica J M; van Dijk, Bas; Zarowski, Andrzej; Bleeck, Stefan

2017-02-01

Speech understanding in noisy environments is still one of the major challenges for cochlear implant (CI) users in everyday life. We evaluated a speech enhancement algorithm based on neural networks (NNSE) for improving speech intelligibility in noise for CI users. The algorithm decomposes the noisy speech signal into time-frequency units, extracts a set of auditory-inspired features and feeds them to the neural network to produce an estimation of which frequency channels contain more perceptually important information (higher signal-to-noise ratio, SNR). This estimate is used to attenuate noise-dominated and retain speech-dominated CI channels for electrical stimulation, as in traditional n-of-m CI coding strategies. The proposed algorithm was evaluated by measuring the speech-in-noise performance of 14 CI users using three types of background noise. Two NNSE algorithms were compared: a speaker-dependent algorithm, that was trained on the target speaker used for testing, and a speaker-independent algorithm, that was trained on different speakers. Significant improvements in the intelligibility of speech in stationary and fluctuating noises were found relative to the unprocessed condition for the speaker-dependent algorithm in all noise types and for the speaker-independent algorithm in 2 out of 3 noise types. The NNSE algorithms used noise-specific neural networks that generalized to novel segments of the same noise type and worked over a range of SNRs. The proposed algorithm has the potential to improve the intelligibility of speech in noise for CI users while meeting the requirements of low computational complexity and processing delay for application in CI devices. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Stochastic amplification and signaling in enzymatic futile cycles through noise-induced bistability with oscillations

NASA Astrophysics Data System (ADS)

Samoilov, Michael; Plyasunov, Sergey; Arkin, Adam P.

2005-02-01

Stochastic effects in biomolecular systems have now been recognized as a major physiologically and evolutionarily important factor in the development and function of many living organisms. Nevertheless, they are often thought of as providing only moderate refinements to the behaviors otherwise predicted by the classical deterministic system description. In this work we show by using both analytical and numerical investigation that at least in one ubiquitous class of (bio)chemical-reaction mechanisms, enzymatic futile cycles, the external noise may induce a bistable oscillatory (dynamic switching) behavior that is both quantitatively and qualitatively different from what is predicted or possible deterministically. We further demonstrate that the noise required to produce these distinct properties can itself be caused by a set of auxiliary chemical reactions, making it feasible for biological systems of sufficient complexity to generate such behavior internally. This new stochastic dynamics then serves to confer additional functional modalities on the enzymatic futile cycle mechanism that include stochastic amplification and signaling, the characteristics of which could be controlled by both the type and parameters of the driving noise. Hence, such noise-induced phenomena may, among other roles, potentially offer a novel type of control mechanism in pathways that contain these cycles and the like units. In particular, observations of endogenous or externally driven noise-induced dynamics in regulatory networks may thus provide additional insight into their topology, structure, and kinetics. network motif | signal transduction | chemical reaction | synthetic biology | systems biology

High power, high signal-to-noise ratio single-frequency 1μm Brillouin all-fiber laser

NASA Astrophysics Data System (ADS)

Wang, Jing; Hou, Yubin; Zhang, Qian; Jin, Dongchen; Sun, Ruoyu; Shi, Hongxing; Liu, Jiang; Wang, Pu

2016-03-01

We demonstrate a high-power, high signal-to-noise ratio single-frequency 1 μm Brillouin all-fiber laser with high slope efficiency. The Brillouin laser system consists of a high-power single-frequency fiber laser and a single-pass Brillouin ring cavity. The high-power single-frequency fiber laser is one-stage master-oscillator power amplifier with the maximum output power of 10.33 W, the signal-to-noise ratio of 50 dB and the slope efficiency of 46%. The Brillouin fiber laser is pumped by the amplified laser with a linewidth of 33 kHz and an output power of 2.61 W limited by the damage threshold of the optical isolator. By optimizing the length of the Brillouin ring cavity to 10 m, stable singlefrequency Brillouin fiber laser is obtained with 3 kHz linewidth owing to the linewidth narrowing effect. At the launched pump power of 2.15 W, the Brillouin fiber laser generates maximum output power of 1.4 W with a slope efficiency of 79% and the optical signal-to-noise ratio of 77 dB.

Gravitational wave searches with pulsar timing arrays: Cancellation of clock and ephemeris noises

NASA Astrophysics Data System (ADS)

Tinto, Massimo

2018-04-01

We propose a data processing technique to cancel monopole and dipole noise sources (such as clock and ephemeris noises, respectively) in pulsar timing array searches for gravitational radiation. These noises are the dominant sources of correlated timing fluctuations in the lower-part (≈10-9-10-8 Hz ) of the gravitational wave band accessible by pulsar timing experiments. After deriving the expressions that reconstruct these noises from the timing data, we estimate the gravitational wave sensitivity of our proposed processing technique to single-source signals to be at least one order of magnitude higher than that achievable by directly processing the timing data from an equal-size array. Since arrays can generate pairs of clock and ephemeris-free timing combinations that are no longer affected by correlated noises, we implement with them the cross-correlation statistic to search for an isotropic stochastic gravitational wave background. We find the resulting optimal signal-to-noise ratio to be more than one order of magnitude larger than that obtainable by correlating pairs of timing data from arrays of equal size.

Effect of signal to noise ratio on the speech perception ability of older adults

PubMed Central

Shojaei, Elahe; Ashayeri, Hassan; Jafari, Zahra; Zarrin Dast, Mohammad Reza; Kamali, Koorosh

2016-01-01

Background: Speech perception ability depends on auditory and extra-auditory elements. The signal- to-noise ratio (SNR) is an extra-auditory element that has an effect on the ability to normally follow speech and maintain a conversation. Speech in noise perception difficulty is a common complaint of the elderly. In this study, the importance of SNR magnitude as an extra-auditory effect on speech perception in noise was examined in the elderly. Methods: The speech perception in noise test (SPIN) was conducted on 25 elderly participants who had bilateral low–mid frequency normal hearing thresholds at three SNRs in the presence of ipsilateral white noise. These participants were selected by available sampling method. Cognitive screening was done using the Persian Mini Mental State Examination (MMSE) test. Results: Independent T- test, ANNOVA and Pearson Correlation Index were used for statistical analysis. There was a significant difference in word discrimination scores at silence and at three SNRs in both ears (p≤0.047). Moreover, there was a significant difference in word discrimination scores for paired SNRs (0 and +5, 0 and +10, and +5 and +10 (p≤0.04)). No significant correlation was found between age and word recognition scores at silence and at three SNRs in both ears (p≥0.386). Conclusion: Our results revealed that decreasing the signal level and increasing the competing noise considerably reduced the speech perception ability in normal hearing at low–mid thresholds in the elderly. These results support the critical role of SNRs for speech perception ability in the elderly. Furthermore, our results revealed that normal hearing elderly participants required compensatory strategies to maintain normal speech perception in challenging acoustic situations. PMID:27390712

Applying the Multiple Signal Classification Method to Silent Object Detection Using Ambient Noise

NASA Astrophysics Data System (ADS)

Mori, Kazuyoshi; Yokoyama, Tomoki; Hasegawa, Akio; Matsuda, Minoru

2004-05-01

The revolutionary concept of using ocean ambient noise positively to detect objects, called acoustic daylight imaging, has attracted much attention. The authors attempted the detection of a silent target object using ambient noise and a wide-band beam former consisting of an array of receivers. In experimental results obtained in air, using the wide-band beam former, we successfully applied the delay-sum array (DSA) method to detect a silent target object in an acoustic noise field generated by a large number of transducers. This paper reports some experimental results obtained by applying the multiple signal classification (MUSIC) method to a wide-band beam former to detect silent targets. The ocean ambient noise was simulated by transducers decentralized to many points in air. Both MUSIC and DSA detected a spherical target object in the noise field. The relative power levels near the target obtained with MUSIC were compared with those obtained by DSA. Then the effectiveness of the MUSIC method was evaluated according to the rate of increase in the maximum and minimum relative power levels.

Contralateral-noise effects on cochlear responses in anesthetized mice are dominated by feedback from an unknown pathway

PubMed Central

Usubuchi, Hajime; Vetter, Douglas E.; Elgoyhen, A. Bélen; Thomas, Steven A.; Liberman, M. Charles

2012-01-01

Suppression of ipsilateral distortion product otoacoustic emissions (DPOAEs) by contralateral noise is used in humans and animals to assay the strength of sound-evoked negative feedback from the medial olivocochlear (MOC) efferent pathway. However, depending on species and anesthesia, contributions of other feedback systems to the middle or inner ear can cloud the interpretation. Here, contributions of MOC and middle-ear muscle reflexes, as well as autonomic feedback, to contra-noise suppression in anesthetized mice are dissected by selectively eliminating each pathway by surgical transection, pharmacological blockade, or targeted gene deletion. When ipsilateral DPOAEs were evoked by low-level primaries, contra-noise suppression was typically ∼1 dB with contra-noise levels around 95 dB SPL, and it always disappeared upon contralateral cochlear destruction. Lack of middle-ear muscle contribution was suggested by persistence of contra-noise suppression after paralysis with curare, tensor tympani cauterization, or section of the facial nerve. Contribution of cochlear sympathetics was ruled out by studying mutant mice lacking adrenergic signaling (dopamine β-hydroxylase knockouts). Surprisingly, contra-noise effects on low-level DPOAEs were also not diminished by eliminating the MOC system pharmacologically (strychnine), surgically, or by deletion of relevant cholinergic receptors (α9/α10). In contrast, when ipsilateral DPOAEs were evoked by high-level primaries, the contra-noise suppression, although comparable in magnitude, was largely eliminated by MOC blockade or section. Possible alternate pathways are discussed for the source of contra-noise-evoked effects at low ipsilateral levels. PMID:22514298

Adaptive detection of noise signal according to Neumann-Pearson criterion

NASA Astrophysics Data System (ADS)

Padiryakov, Y. A.

1985-03-01

Optimum detection according to the Neumann-Pearson criterion is considered in the case of a random Gaussian noise signal, stationary during measurement, and a stationary random Gaussian background interference. Detection is based on two samples, their statistics characterized by estimates of their spectral densities, it being a priori known that sample A from the signal channel is either the sum of signal and interference or interference alone and sample B from the reference interference channel is an interference with the same spectral density as that of the interference in sample A for both hypotheses. The probability of correct detection is maximized on the average, first in the 2N-dimensional space of signal spectral density and interference spectral density readings, by fixing the probability of false alarm at each point so as to stabilize it at a constant level against variation of the interference spectral density. Deterministic decision rules are established. The algorithm is then reduced to equivalent detection in the N-dimensional space of the ratio of sample A readings to sample B readings.

Correcting speckle contrast at small speckle size to enhance signal to noise ratio for laser speckle contrast imaging.

PubMed

Qiu, Jianjun; Li, Yangyang; Huang, Qin; Wang, Yang; Li, Pengcheng

2013-11-18

In laser speckle contrast imaging, it was usually suggested that speckle size should exceed two camera pixels to eliminate the spatial averaging effect. In this work, we show the benefit of enhancing signal to noise ratio by correcting the speckle contrast at small speckle size. Through simulations and experiments, we demonstrated that local speckle contrast, even at speckle size much smaller than one pixel size, can be corrected through dividing the original speckle contrast by the static speckle contrast. Moreover, we show a 50% higher signal to noise ratio of the speckle contrast image at speckle size below 0.5 pixel size than that at speckle size of two pixels. These results indicate the possibility of selecting a relatively large aperture to simultaneously ensure sufficient light intensity and high accuracy and signal to noise ratio, making the laser speckle contrast imaging more flexible.

Hearing through the noise: Biologically inspired noise reduction

NASA Astrophysics Data System (ADS)

Lee, Tyler Paul

Vocal communication in the natural world demands that a listener perform a remarkably complicated task in real-time. Vocalizations mix with all other sounds in the environment as they travel to the listener, arriving as a jumbled low-dimensional signal. A listener must then use this signal to extract the structure corresponding to individual sound sources. How this computation is implemented in the brain remains poorly understood, yet an accurate description of such mechanisms would impact a variety of medical and technological applications of sound processing. In this thesis, I describe initial work on how neurons in the secondary auditory cortex of the Zebra Finch extract song from naturalistic background noise. I then build on our understanding of the function of these neurons by creating an algorithm that extracts speech from natural background noise using spectrotemporal modulations. The algorithm, implemented as an artificial neural network, can be flexibly applied to any class of signal or noise and performs better than an optimal frequency-based noise reduction algorithm for a variety of background noises and signal-to-noise ratios. One potential drawback to using spectrotemporal modulations for noise reduction, though, is that analyzing the modulations present in an ongoing sound requires a latency set by the slowest temporal modulation computed. The algorithm avoids this problem by reducing noise predictively, taking advantage of the large amount of temporal structure present in natural sounds. This predictive denoising has ties to recent work suggesting that the auditory system uses attention to focus on predicted regions of spectrotemporal space when performing auditory scene analysis.

Balanced ionotropic receptor dynamics support signal estimation via voltage-dependent membrane noise.

PubMed

Marcoux, Curtis M; Clarke, Stephen E; Nesse, William H; Longtin, Andre; Maler, Leonard

2016-01-01

Encoding behaviorally relevant stimuli in a noisy background is critical for animals to survive in their natural environment. We identify core biophysical and synaptic mechanisms that permit the encoding of low-frequency signals in pyramidal neurons of the weakly electric fish Apteronotus leptorhynchus, an animal that can accurately encode even miniscule amplitude modulations of its self-generated electric field. We demonstrate that slow NMDA receptor (NMDA-R)-mediated excitatory postsynaptic potentials (EPSPs) are able to summate over many interspike intervals (ISIs) of the primary electrosensory afferents (EAs), effectively eliminating the baseline EA ISI correlations from the pyramidal cell input. Together with a dynamic balance of NMDA-R and GABA-A-R currents, this permits stimulus-evoked changes in EA spiking to be transmitted efficiently to target electrosensory lobe (ELL) pyramidal cells, for encoding low-frequency signals. Interestingly, AMPA-R activity is depressed and appears to play a negligible role in the generation of action potentials. Instead, we hypothesize that cell-intrinsic voltage-dependent membrane noise supports the encoding of perithreshold sensory input; this noise drives a significant proportion of pyramidal cell spikes. Together, these mechanisms may be sufficient for the ELL to encode signals near the threshold of behavioral detection. Copyright © 2016 the American Physiological Society.

Enhancing scatterometry CD signal-to-noise ratio for 1x logic and memory challenges

NASA Astrophysics Data System (ADS)

Shaughnessy, Derrick; Krishnan, Shankar; Wei, Lanhua; Shchegrov, Andrei V.

2013-04-01

The ongoing transition from 2D to 3D structures in logic and memory has led to an increased adoption of scatterometry CD (SCD) for inline metrology. However, shrinking device dimensions in logic and high aspect ratios in memory represent primary challenges for SCD and require a significant breakthrough in improving signal-to-noise performance. We present a report on the new generation of SCD technology, enabled by a new laser-driven plasma source. The developed light source provides several key advantages over conventional arc lamps typically used in SCD applications. The plasma color temperature of the laser driven source is considerably higher than available with arc lamps resulting in >5X increase in radiance in the visible and >10X increase in radiance in the DUV when compared to sources on previous generation SCD tools while maintaining or improving source intensity noise. This high radiance across such a broad spectrum allows for the use of a single light source from 190-1700nm. When combined with other optical design changes, the higher source radiance enables reduction of measurement box size of our spectroscopic ellipsometer from 45×45um box to 25×25um box without compromising signal to noise ratio. The benefits for 1×nm SCD metrology of the additional photons across the DUV to IR spectrum have been found to be greater than the increase in source signal to noise ratio would suggest. Better light penetration in Si and poly-Si has resulted in improved sensitivity and correlation breaking for critical parameters in 1xnm FinFET and HAR flash memory structures.

Signal processing of aircraft flyover noise

NASA Technical Reports Server (NTRS)

Kelly, Jeffrey J.

1991-01-01

A detailed analysis of signal processing concerns for measuring aircraft flyover noise is presented. Development of a de-Dopplerization scheme for both corrected time history and spectral data is discussed along with an analysis of motion effects on measured spectra. A computer code was written to implement the de-Dopplerization scheme. Input to the code is the aircraft position data and the pressure time histories. To facilitate ensemble averaging, a uniform level flyover is considered but the code can accept more general flight profiles. The effects of spectral smearing and its removal is discussed. Using data acquired from XV-15 tilt rotor flyover test comparisons are made showing the measured and corrected spectra. Frequency shifts are accurately accounted for by the method. It is shown that correcting for spherical spreading, Doppler amplitude, and frequency can give some idea about source directivity. The analysis indicated that smearing increases with frequency and is more severe on approach than recession.

Simulation for noise cancellation using LMS adaptive filter

NASA Astrophysics Data System (ADS)

Lee, Jia-Haw; Ooi, Lu-Ean; Ko, Ying-Hao; Teoh, Choe-Yung

2017-06-01

In this paper, the fundamental algorithm of noise cancellation, Least Mean Square (LMS) algorithm is studied and enhanced with adaptive filter. The simulation of the noise cancellation using LMS adaptive filter algorithm is developed. The noise corrupted speech signal and the engine noise signal are used as inputs for LMS adaptive filter algorithm. The filtered signal is compared to the original noise-free speech signal in order to highlight the level of attenuation of the noise signal. The result shows that the noise signal is successfully canceled by the developed adaptive filter. The difference of the noise-free speech signal and filtered signal are calculated and the outcome implies that the filtered signal is approaching the noise-free speech signal upon the adaptive filtering. The frequency range of the successfully canceled noise by the LMS adaptive filter algorithm is determined by performing Fast Fourier Transform (FFT) on the signals. The LMS adaptive filter algorithm shows significant noise cancellation at lower frequency range.

Evaluation of the effectiveness of Gaussian filtering in distinguishing punctate synaptic signals from background noise during image analysis.

PubMed

Iwabuchi, Sadahiro; Kakazu, Yasuhiro; Koh, Jin-Young; Harata, N Charles

2014-02-15

Images in biomedical imaging research are often affected by non-specific background noise. This poses a serious problem when the noise overlaps with specific signals to be quantified, e.g. for their number and intensity. A simple and effective means of removing background noise is to prepare a filtered image that closely reflects background noise and to subtract it from the original unfiltered image. This approach is in common use, but its effectiveness in identifying and quantifying synaptic puncta has not been characterized in detail. We report on our assessment of the effectiveness of isolating punctate signals from diffusely distributed background noise using one variant of this approach, "Difference of Gaussian(s) (DoG)" which is based on a Gaussian filter. We evaluated immunocytochemically stained, cultured mouse hippocampal neurons as an example, and provided the rationale for choosing specific parameter values for individual steps in detecting glutamatergic nerve terminals. The intensity and width of the detected puncta were proportional to those obtained by manual fitting of two-dimensional Gaussian functions to the local information in the original image. DoG was compared with the rolling-ball method, using biological data and numerical simulations. Both methods removed background noise, but differed slightly with respect to their efficiency in discriminating neighboring peaks, as well as their susceptibility to high-frequency noise and variability in object size. DoG will be useful in detecting punctate signals, once its characteristics are examined quantitatively by experimenters. Copyright © 2013 Elsevier B.V. All rights reserved.

Comparison of noise reduction systems

NASA Astrophysics Data System (ADS)

Noel, S. D.; Whitaker, R. W.

1991-06-01

When using infrasound as a tool for verification, the most important measurement to determine yield has been the peak-to-peak pressure amplitude of the signal. Therefore, there is a need to operate at the most favorable signal-to-noise ratio (SNR) possible. Winds near the ground can degrade the SNR, thereby making accurate signal amplitude measurement difficult. Wind noise reduction techniques were developed to help alleviate this problem; however, a noise reducing system should reduce the noise, and should not introduce distortion of coherent signals. An experiment is described to study system response for a variety of noise reducing configurations to a signal generated by an underground test (UGT) at the Nevada Test Site (NTS). In addition to the signal, background noise reduction is examined through measurements of variance. Sensors using two particular geometries of noise reducing equipment, the spider and the cross appear to deliver the best SNR. Because the spider configuration is easier to deploy, it is now the most commonly used.

Signal-to-noise ratio estimation in digital computer simulation of lowpass and bandpass systems with applications to analog and digital communications, volume 3

NASA Technical Reports Server (NTRS)

Tranter, W. H.; Turner, M. D.

1977-01-01

Techniques are developed to estimate power gain, delay, signal-to-noise ratio, and mean square error in digital computer simulations of lowpass and bandpass systems. The techniques are applied to analog and digital communications. The signal-to-noise ratio estimates are shown to be maximum likelihood estimates in additive white Gaussian noise. The methods are seen to be especially useful for digital communication systems where the mapping from the signal-to-noise ratio to the error probability can be obtained. Simulation results show the techniques developed to be accurate and quite versatile in evaluating the performance of many systems through digital computer simulation.

Acceptance Noise Level: Effects of the Speech Signal, Babble, and Listener Language

ERIC Educational Resources Information Center

Shi, Lu-Feng; Azcona, Gabrielly; Buten, Lupe

2015-01-01

Purpose: The acceptable noise level (ANL) measure has gained much research/clinical interest in recent years. The present study examined how the characteristics of the speech signal and the babble used in the measure may affect the ANL in listeners with different native languages. Method: Fifteen English monolingual, 16 Russian-English bilingual,…

Signatures of nonlinearity in single cell noise-induced oscillations.

PubMed

Thomas, Philipp; Straube, Arthur V; Timmer, Jens; Fleck, Christian; Grima, Ramon

2013-10-21

A class of theoretical models seeks to explain rhythmic single cell data by postulating that they are generated by intrinsic noise in biochemical systems whose deterministic models exhibit only damped oscillations. The main features of such noise-induced oscillations are quantified by the power spectrum which measures the dependence of the oscillatory signal's power with frequency. In this paper we derive an approximate closed-form expression for the power spectrum of any monostable biochemical system close to a Hopf bifurcation, where noise-induced oscillations are most pronounced. Unlike the commonly used linear noise approximation which is valid in the macroscopic limit of large volumes, our theory is valid over a wide range of volumes and hence affords a more suitable description of single cell noise-induced oscillations. Our theory predicts that the spectra have three universal features: (i) a dominant peak at some frequency, (ii) a smaller peak at twice the frequency of the dominant peak and (iii) a peak at zero frequency. Of these, the linear noise approximation predicts only the first feature while the remaining two stem from the combination of intrinsic noise and nonlinearity in the law of mass action. The theoretical expressions are shown to accurately match the power spectra determined from stochastic simulations of mitotic and circadian oscillators. Furthermore it is shown how recently acquired single cell rhythmic fibroblast data displays all the features predicted by our theory and that the experimental spectrum is well described by our theory but not by the conventional linear noise approximation. © 2013 Elsevier Ltd. All rights reserved.

Propagation effects on radio range and noise in earth-space telecommunications

NASA Technical Reports Server (NTRS)

Flock, W. L.; Slobin, S. D.; Smith, E. K.

1982-01-01

Attention is given to the propagation effects on radio range and noise in earth-space telecommunications. The use of higher frequencies minimizes ionospheric effects on propagation, but tropospheric effects often increase or dominate. For paths of geostationary satellites, and beyond, the excess range delay caused by the ionosphere and plasmasphere is proportional to the total electron content along the path and inversely proportional to frequency squared. The delay due to dry air is usually of the order of a few meters while the delay due to water vapor (a few tens of centimeters) is responsible for most of the temporal variation in the range delay for clean air. For systems such as that of the Voyager spacecraft, and for attenuation values up to about 10 dB, increased sky noise degrades the received signal-to-noise ratio more than does the reduction in signal level due to attenuation.

Computation of the ensemble channelized Hotelling observer signal-to-noise ratio for ordered-subset image reconstruction using noisy data

NASA Astrophysics Data System (ADS)

Soares, Edward J.; Gifford, Howard C.; Glick, Stephen J.

2003-05-01

We investigated the estimation of the ensemble channelized Hotelling observer (CHO) signal-to-noise ratio (SNR) for ordered-subset (OS) image reconstruction using noisy projection data. Previously, we computed the ensemble CHO SNR using a method for approximating the channelized covariance of OS reconstruction, which requires knowledge of the noise-free projection data. Here, we use a "plug-in" approach, in which noisy data is used in place of the noise-free data in the aforementioned channelized covariance approximation. Additionally, we evaluated the use of smoothing of the noisy projections before use in the covariance approximation. Additionally, we evaluated the use of smoothing of the noisy projections before use in the covariance calculation. The task was detection of a 10% contrast Gaussian signal within a slice of the MCAT phantom. Simulated projections of the MCAT phantom were scaled and Poisson noise was added to create 100 noisy signal-absent data sets. Simulated projections of the scaled signal were then added to the noisy background projections to create 100 noisy signal-present data set. These noisy data sets were then used to generate 100 estimates of the ensemble CHO SNR for reconstructions at various iterates. For comparison purposes, the same calculation was repeated with the noise-free data. The results, reported as plots of the average CHO SNR generated in this fashion, along with 95% confidence intervals, demonstrate that this approach works very well, and would allow optimization of imaging systems and reconstruction methods using a more accurate object model (i.e., real patient data).

Spin noise amplification and giant noise in optical microcavity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ryzhov, I. I.; Poltavtsev, S. V.; Kozlov, G. G.

2015-06-14

When studying the spin-noise-induced fluctuations of Kerr rotation in a quantum-well microcavity, we have found a dramatic increase of the noise signal (by more than two orders of magnitude) in the vicinity of anti-crossing of the polariton branches. The effect is explained by nonlinear optical instability of the microcavity giving rise to the light-power-controlled amplification of the polarization noise signal. In the framework of the developed model of built-in amplifier, we also interpret the nontrivial spectral and intensity-related properties of the observed noise signal below the region of anti-crossing of polariton branches. The discovered effect of optically controllable amplification ofmore » broadband polarization signals in microcavities in the regime of optical instability may be of interest for detecting weak oscillations of optical anisotropy in fundamental research and for other applications in optical information processing.« less

Spectral reconstruction analysis for enhancing signal-to-noise in time-resolved spectroscopies

NASA Astrophysics Data System (ADS)

Wilhelm, Michael J.; Smith, Jonathan M.; Dai, Hai-Lung

2015-09-01

We demonstrate a new spectral analysis for the enhancement of the signal-to-noise ratio (SNR) in time-resolved spectroscopies. Unlike the simple linear average which produces a single representative spectrum with enhanced SNR, this Spectral Reconstruction analysis (SRa) improves the SNR (by a factor of ca. 0 . 6 √{ n } ) for all n experimentally recorded time-resolved spectra. SRa operates by eliminating noise in the temporal domain, thereby attenuating noise in the spectral domain, as follows: Temporal profiles at each measured frequency are fit to a generic mathematical function that best represents the temporal evolution; spectra at each time are then reconstructed with data points from the fitted profiles. The SRa method is validated with simulated control spectral data sets. Finally, we apply SRa to two distinct experimentally measured sets of time-resolved IR emission spectra: (1) UV photolysis of carbonyl cyanide and (2) UV photolysis of vinyl cyanide.

Measuring multielectron beam imaging fidelity with a signal-to-noise ratio analysis

NASA Astrophysics Data System (ADS)

Mukhtar, Maseeh; Bunday, Benjamin D.; Quoi, Kathy; Malloy, Matt; Thiel, Brad

2016-07-01

Java Monte Carlo Simulator for Secondary Electrons (JMONSEL) simulations are used to generate expected imaging responses of chosen test cases of patterns and defects with the ability to vary parameters for beam energy, spot size, pixel size, and/or defect material and form factor. The patterns are representative of the design rules for an aggressively scaled FinFET-type design. With these simulated images and resulting shot noise, a signal-to-noise framework is developed, which relates to defect detection probabilities. Additionally, with this infrastructure, the effect of detection chain noise and frequency-dependent system response can be made, allowing for targeting of best recipe parameters for multielectron beam inspection validation experiments. Ultimately, these results should lead to insights into how such parameters will impact tool design, including necessary doses for defect detection and estimations of scanning speeds for achieving high throughput for high-volume manufacturing.

Activation of parallel fiber feedback by spatially diffuse stimuli reduces signal and noise correlations via independent mechanisms in a cerebellum-like structure.

PubMed

Simmonds, Benjamin; Chacron, Maurice J

2015-01-01

Correlations between the activities of neighboring neurons are observed ubiquitously across systems and species and are dynamically regulated by several factors such as the stimulus' spatiotemporal extent as well as by the brain's internal state. Using the electrosensory system of gymnotiform weakly electric fish, we recorded the activities of pyramidal cell pairs within the electrosensory lateral line lobe (ELL) under spatially localized and diffuse stimulation. We found that both signal and noise correlations were markedly reduced (>40%) under the latter stimulation. Through a network model incorporating key anatomical features of the ELL, we reveal how activation of diffuse parallel fiber feedback from granule cells by spatially diffuse stimulation can explain both the reduction in signal as well as the reduction in noise correlations seen experimentally through independent mechanisms. First, we show that burst-timing dependent plasticity, which leads to a negative image of the stimulus and thereby reduces single neuron responses, decreases signal but not noise correlations. Second, we show trial-to-trial variability in the responses of single granule cells to sensory input reduces noise but not signal correlations. Thus, our model predicts that the same feedback pathway can simultaneously reduce both signal and noise correlations through independent mechanisms. To test this prediction experimentally, we pharmacologically inactivated parallel fiber feedback onto ELL pyramidal cells. In agreement with modeling predictions, we found that inactivation increased both signal and noise correlations but that there was no significant relationship between magnitude of the increase in signal correlations and the magnitude of the increase in noise correlations. The mechanisms reported in this study are expected to be generally applicable to the cerebellum as well as other cerebellum-like structures. We further discuss the implications of such decorrelation on the neural

Spectral analysis of fundamental signal and noise performances in photoconductors for mammography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Ho Kyung; Lim, Chang Hwy; Tanguay, Jesse

2012-05-15

Purpose: This study investigates the fundamental signal and noise performance limitations imposed by the stochastic nature of x-ray interactions in selected photoconductor materials, such as Si, a-Se, CdZnTe, HgI{sub 2}, PbI{sub 2}, PbO, and TlBr, for x-ray spectra typically used in mammography. Methods: It is shown how Monte Carlo simulations can be combined with a cascaded model to determine the absorbed energy distribution for each combination of photoconductor and x-ray spectrum. The model is used to determine the quantum efficiency, mean energy absorption per interaction, Swank noise factor, secondary quantum noise, and zero-frequency detective quantum efficiency (DQE). Results: The quantummore » efficiency of materials with higher atomic number and density demonstrates a larger dependence on convertor thickness than those with lower atomic number and density with the exception of a-Se. The mean deposited energy increases with increasing average energy of the incident x-ray spectrum. HgI{sub 2}, PbI{sub 2}, and CdZnTe demonstrate the largest increase in deposited energy with increasing mass loading and a-Se and Si the smallest. The best DQE performances are achieved with PbO and TlBr. For mass loading greater than 100 mg cm{sup -2}, a-Se, HgI{sub 2}, and PbI{sub 2} provide similar DQE values to PbO and TlBr. Conclusions: The quantum absorption efficiency, average deposited energy per interacting x-ray, Swank noise factor, and detective quantum efficiency are tabulated by means of graphs which may help with the design and selection of materials for photoconductor-based mammography detectors. Neglecting the electrical characteristics of photoconductor materials and taking into account only x-ray interactions, it is concluded that PbO shows the strongest signal-to-noise ratio performance of the materials investigated in this study.« less

Advanced study of video signal processing in low signal to noise environments

NASA Technical Reports Server (NTRS)

Carden, F.; Henry, R.

1972-01-01

A nonlinear analysis of a multifilter phase-lockloop (MPLL) by using the method of harmonic balance is presented. The particular MPLL considered has a low-pass filter and a band-pass filter in parallel. An analytic expression for the relationship between the input signal phase deviation and the phase error is determined for sinusoidal FM in the absence of noise. The expression is used to determine bounds on the proper operating region for the MPLL and to investigate the jump phenomenon previously observed. From these results the proper modulation index, modulating frequency, etc. used for the design of a MPLL are determined. Data for the loop unlock boundary obtained from the theoretical expression are compared to data obtained from analog computer simulations of the MPLL.

Noise and signal properties in PSF-based fully 3D PET image reconstruction: an experimental evaluation

NASA Astrophysics Data System (ADS)

Tong, S.; Alessio, A. M.; Kinahan, P. E.

2010-03-01

The addition of accurate system modeling in PET image reconstruction results in images with distinct noise texture and characteristics. In particular, the incorporation of point spread functions (PSF) into the system model has been shown to visually reduce image noise, but the noise properties have not been thoroughly studied. This work offers a systematic evaluation of noise and signal properties in different combinations of reconstruction methods and parameters. We evaluate two fully 3D PET reconstruction algorithms: (1) OSEM with exact scanner line of response modeled (OSEM+LOR), (2) OSEM with line of response and a measured point spread function incorporated (OSEM+LOR+PSF), in combination with the effects of four post-reconstruction filtering parameters and 1-10 iterations, representing a range of clinically acceptable settings. We used a modified NEMA image quality (IQ) phantom, which was filled with 68Ge and consisted of six hot spheres of different sizes with a target/background ratio of 4:1. The phantom was scanned 50 times in 3D mode on a clinical system to provide independent noise realizations. Data were reconstructed with OSEM+LOR and OSEM+LOR+PSF using different reconstruction parameters, and our implementations of the algorithms match the vendor's product algorithms. With access to multiple realizations, background noise characteristics were quantified with four metrics. Image roughness and the standard deviation image measured the pixel-to-pixel variation; background variability and ensemble noise quantified the region-to-region variation. Image roughness is the image noise perceived when viewing an individual image. At matched iterations, the addition of PSF leads to images with less noise defined as image roughness (reduced by 35% for unfiltered data) and as the standard deviation image, while it has no effect on background variability or ensemble noise. In terms of signal to noise performance, PSF-based reconstruction has a 7% improvement in

Early-warning signals of critical transition: Effect of extrinsic noise

NASA Astrophysics Data System (ADS)

Qin, Shanshan; Tang, Chao

2018-03-01

Complex dynamical systems often have tipping points and exhibit catastrophic regime shift. Despite the notorious difficulty of predicting such transitions, accumulating studies have suggested the existence of generic early-warning signals (EWSs) preceding upcoming transitions. However, previous theories and models were based on the effect of the intrinsic noise (IN) when a system is approaching a critical point, and did not consider the pervasive environmental fluctuations or the extrinsic noise (EN). Here, we extend previous theory to investigate how the interplay of EN and IN affects EWSs. Stochastic simulations of model systems subject to both IN and EN have verified our theory and demonstrated that EN can dramatically alter and diminish the EWS. This effect is stronger with increasing amplitude and correlation time scale of the EN. In the presence of EN, the EWS can fail to predict or even give a false alarm of critical transitions.

Allan Deviation Plot as a Tool for Quartz-Enhanced Photoacoustic Sensors Noise Analysis.

PubMed

Giglio, Marilena; Patimisco, Pietro; Sampaolo, Angelo; Scamarcio, Gaetano; Tittel, Frank K; Spagnolo, Vincenzo

2016-04-01

We report here on the use of the Allan deviation plot to analyze the long-term stability of a quartz-enhanced photoacoustic (QEPAS) gas sensor. The Allan plot provides information about the optimum averaging time for the QEPAS signal and allows the prediction of its ultimate detection limit. The Allan deviation can also be used to determine the main sources of noise coming from the individual components of the sensor. Quartz tuning fork thermal noise dominates for integration times up to 275 s, whereas at longer averaging times, the main contribution to the sensor noise originates from laser power instabilities.

Practical ranges of loudness levels of various types of environmental noise, including traffic noise, aircraft noise, and industrial noise.

PubMed

Salomons, Erik M; Janssen, Sabine A

2011-06-01

In environmental noise control one commonly employs the A-weighted sound level as an approximate measure of the effect of noise on people. A measure that is more closely related to direct human perception of noise is the loudness level. At constant A-weighted sound level, the loudness level of a noise signal varies considerably with the shape of the frequency spectrum of the noise signal. In particular the bandwidth of the spectrum has a large effect on the loudness level, due to the effect of critical bands in the human hearing system. The low-frequency content of the spectrum also has an effect on the loudness level. In this note the relation between loudness level and A-weighted sound level is analyzed for various environmental noise spectra, including spectra of traffic noise, aircraft noise, and industrial noise. From loudness levels calculated for these environmental noise spectra, diagrams are constructed that show the relation between loudness level, A-weighted sound level, and shape of the spectrum. The diagrams show that the upper limits of the loudness level for broadband environmental noise spectra are about 20 to 40 phon higher than the lower limits for narrowband spectra, which correspond to the loudness levels of pure tones. The diagrams are useful for assessing limitations and potential improvements of environmental noise control methods and policy based on A-weighted sound levels.

Vibration-induced electrical noise in a cryogen-free dilution refrigerator: Characterization, mitigation, and impact on qubit coherence

NASA Astrophysics Data System (ADS)

Kalra, Rachpon; Laucht, Arne; Dehollain, Juan Pablo; Bar, Daniel; Freer, Solomon; Simmons, Stephanie; Muhonen, Juha T.; Morello, Andrea

2016-07-01

Cryogen-free low-temperature setups are becoming more prominent in experimental science due to their convenience and reliability, and concern about the increasing scarcity of helium as a natural resource. Despite not having any moving parts at the cold end, pulse tube cryocoolers introduce vibrations that can be detrimental to the experiments. We characterize the coupling of these vibrations to the electrical signal observed on cables installed in a cryogen-free dilution refrigerator. The dominant electrical noise is in the 5-10 kHz range and its magnitude is found to be strongly temperature dependent. We test the performance of different cables designed to diagnose and tackle the noise, and find triboelectrics to be the dominant mechanism coupling the vibrations to the electrical signal. Flattening a semi-rigid cable or jacketing a flexible cable in order to restrict movement within the cable, successfully reduces the noise level by over an order of magnitude. Furthermore, we characterize the effect of the pulse tube vibrations on an electron spin qubit device in this setup. Coherence measurements are used to map out the spectrum of the noise experienced by the qubit, revealing spectral components matching the spectral signature of the pulse tube.

Vibration-induced electrical noise in a cryogen-free dilution refrigerator: Characterization, mitigation, and impact on qubit coherence.

PubMed

Kalra, Rachpon; Laucht, Arne; Dehollain, Juan Pablo; Bar, Daniel; Freer, Solomon; Simmons, Stephanie; Muhonen, Juha T; Morello, Andrea

2016-07-01

Cryogen-free low-temperature setups are becoming more prominent in experimental science due to their convenience and reliability, and concern about the increasing scarcity of helium as a natural resource. Despite not having any moving parts at the cold end, pulse tube cryocoolers introduce vibrations that can be detrimental to the experiments. We characterize the coupling of these vibrations to the electrical signal observed on cables installed in a cryogen-free dilution refrigerator. The dominant electrical noise is in the 5-10 kHz range and its magnitude is found to be strongly temperature dependent. We test the performance of different cables designed to diagnose and tackle the noise, and find triboelectrics to be the dominant mechanism coupling the vibrations to the electrical signal. Flattening a semi-rigid cable or jacketing a flexible cable in order to restrict movement within the cable, successfully reduces the noise level by over an order of magnitude. Furthermore, we characterize the effect of the pulse tube vibrations on an electron spin qubit device in this setup. Coherence measurements are used to map out the spectrum of the noise experienced by the qubit, revealing spectral components matching the spectral signature of the pulse tube.

Analysis of Vibration and Noise of Construction Machinery Based on Ensemble Empirical Mode Decomposition and Spectral Correlation Analysis Method

NASA Astrophysics Data System (ADS)

Chen, Yuebiao; Zhou, Yiqi; Yu, Gang; Lu, Dan

In order to analyze the effect of engine vibration on cab noise of construction machinery in multi-frequency bands, a new method based on ensemble empirical mode decomposition (EEMD) and spectral correlation analysis is proposed. Firstly, the intrinsic mode functions (IMFs) of vibration and noise signals were obtained by EEMD method, and then the IMFs which have the same frequency bands were selected. Secondly, we calculated the spectral correlation coefficients between the selected IMFs, getting the main frequency bands in which engine vibration has significant impact on cab noise. Thirdly, the dominated frequencies were picked out and analyzed by spectral analysis method. The study result shows that the main frequency bands and dominated frequencies in which engine vibration have serious impact on cab noise can be identified effectively by the proposed method, which provides effective guidance to noise reduction of construction machinery.

A de-noising method using the improved wavelet threshold function based on noise variance estimation

NASA Astrophysics Data System (ADS)

Liu, Hui; Wang, Weida; Xiang, Changle; Han, Lijin; Nie, Haizhao

2018-01-01

The precise and efficient noise variance estimation is very important for the processing of all kinds of signals while using the wavelet transform to analyze signals and extract signal features. In view of the problem that the accuracy of traditional noise variance estimation is greatly affected by the fluctuation of noise values, this study puts forward the strategy of using the two-state Gaussian mixture model to classify the high-frequency wavelet coefficients in the minimum scale, which takes both the efficiency and accuracy into account. According to the noise variance estimation, a novel improved wavelet threshold function is proposed by combining the advantages of hard and soft threshold functions, and on the basis of the noise variance estimation algorithm and the improved wavelet threshold function, the research puts forth a novel wavelet threshold de-noising method. The method is tested and validated using random signals and bench test data of an electro-mechanical transmission system. The test results indicate that the wavelet threshold de-noising method based on the noise variance estimation shows preferable performance in processing the testing signals of the electro-mechanical transmission system: it can effectively eliminate the interference of transient signals including voltage, current, and oil pressure and maintain the dynamic characteristics of the signals favorably.

Optimum Boundaries of Signal-to-Noise Ratio for Adaptive Code Modulations

DTIC Science & Technology

2017-11-14

1510–1521, Feb. 2015. [2]. Pursley, M. B. and Royster, T. C., “Adaptive-rate nonbinary LDPC coding for frequency - hop communications ,” IEEE...and this can cause a very narrowband noise near the center frequency during USRP signal acquisition and generation. This can cause a high BER...Final Report APPROVED FOR PUBLIC RELEASE; DISTRIBUTION IS UNLIMITED. AIR FORCE RESEARCH LABORATORY Space Vehicles Directorate 3550 Aberdeen Ave

Novel active signal compression in low-noise analog readout at future X-ray FEL facilities

NASA Astrophysics Data System (ADS)

Manghisoni, M.; Comotti, D.; Gaioni, L.; Lodola, L.; Ratti, L.; Re, V.; Traversi, G.; Vacchi, C.

2015-04-01

This work presents the design of a low-noise front-end implementing a novel active signal compression technique. This feature can be exploited in the design of analog readout channels for application to the next generation free electron laser (FEL) experiments. The readout architecture includes the low-noise charge sensitive amplifier (CSA) with dynamic signal compression, a time variant shaper used to process the signal at the preamplifier output and a 10-bit successive approximation register (SAR) analog-to-digital converter (ADC). The channel will be operated in such a way to cope with the high frame rate (exceeding 1 MHz) foreseen for future XFEL machines. The choice of a 65 nm CMOS technology has been made in order to include all the building blocks in the target pixel pitch of 100 μm. This work has been carried out in the frame of the PixFEL Project funded by the Istituto Nazionale di Fisica Nucleare (INFN), Italy.

Stature signals status: The association of stature, status and perceived dominance - a thought experiment.

PubMed

Hermanussen, Michael; Scheffler, Christiane

2016-11-01

Background: There is a common perception that tall stature results in social dominance. Evidence in meerkats suggests that social dominance itself may be a strong stimulus for growth. Relative size serves as the signal for individuals to induce strategic growth adjustments . Aim: We construct a thought experiment to explore the potential consequences of the question: is stature a social signal also in humans? We hypothesize that (1) upward trends in height in the lower social strata are perceived as social challenges yielding similar though attenuated upward trends in the dominant strata, and that (2) democratization, but also periods of political turmoil that facilitate upward mobility of the lower strata, are accompanied by upward trends in height. Material and methods: We reanalyzed large sets of height data of European conscripts born between 1856-1860 and 1976-1980; and annual data of German military conscripts, born between 1965 and 1985, with information on height and school education. Results: Taller stature is associated with higher socioeconomic status. Historic populations show larger height differences between social strata that tend to diminish in the more recent populations. German height data suggest that both democratization, and periods of political turmoil facilitating upward mobility of the lower social strata are accompanied by a general upward height spiral that captures the whole population. Discussion: We consider stature as a signal. Nutrition, health, general living conditions and care giving are essential prerequisites for growth, yet not to maximize stature, but to allow for its function as a lifelong social signal. Considering stature as a social signal provides an elegant explanation of the rapid height adjustments observed in migrants, of the hitherto unexplained clustering of body height in modern and historic cohorts of military conscripts, and of the parallelism between changes in political conditions, and secular trends in adult

Signal-to-noise ratio estimation on SEM images using cubic spline interpolation with Savitzky-Golay smoothing.

PubMed

Sim, K S; Kiani, M A; Nia, M E; Tso, C P

2014-01-01

A new technique based on cubic spline interpolation with Savitzky-Golay noise reduction filtering is designed to estimate signal-to-noise ratio of scanning electron microscopy (SEM) images. This approach is found to present better result when compared with two existing techniques: nearest neighbourhood and first-order interpolation. When applied to evaluate the quality of SEM images, noise can be eliminated efficiently with optimal choice of scan rate from real-time SEM images, without generating corruption or increasing scanning time. © 2013 The Authors Journal of Microscopy © 2013 Royal Microscopical Society.

Comprehensive quantification of signal-to-noise ratio and g-factor for image-based and k-space-based parallel imaging reconstructions.

PubMed

Robson, Philip M; Grant, Aaron K; Madhuranthakam, Ananth J; Lattanzi, Riccardo; Sodickson, Daniel K; McKenzie, Charles A

2008-10-01

Parallel imaging reconstructions result in spatially varying noise amplification characterized by the g-factor, precluding conventional measurements of noise from the final image. A simple Monte Carlo based method is proposed for all linear image reconstruction algorithms, which allows measurement of signal-to-noise ratio and g-factor and is demonstrated for SENSE and GRAPPA reconstructions for accelerated acquisitions that have not previously been amenable to such assessment. Only a simple "prescan" measurement of noise amplitude and correlation in the phased-array receiver, and a single accelerated image acquisition are required, allowing robust assessment of signal-to-noise ratio and g-factor. The "pseudo multiple replica" method has been rigorously validated in phantoms and in vivo, showing excellent agreement with true multiple replica and analytical methods. This method is universally applicable to the parallel imaging reconstruction techniques used in clinical applications and will allow pixel-by-pixel image noise measurements for all parallel imaging strategies, allowing quantitative comparison between arbitrary k-space trajectories, image reconstruction, or noise conditioning techniques. (c) 2008 Wiley-Liss, Inc.

Anthropogenic noise disrupts use of vocal information about predation risk.

PubMed

Kern, Julie M; Radford, Andrew N

2016-11-01

Anthropogenic noise is rapidly becoming a universal environmental feature. While the impacts of such additional noise on avian sexual signals are well documented, our understanding of its effect in other terrestrial taxa, on other vocalisations, and on receivers is more limited. Little is known, for example, about the influence of anthropogenic noise on responses to vocalisations relating to predation risk, despite the potential fitness consequences. We use playback experiments to investigate the impact of traffic noise on the responses of foraging dwarf mongooses (Helogale parvula) to surveillance calls produced by sentinels, individuals scanning for danger from a raised position whose presence usually results in reduced vigilance by foragers. Foragers exhibited a lessened response to surveillance calls in traffic-noise compared to ambient-sound playback, increasing personal vigilance. A second playback experiment, using noise playbacks without surveillance calls, suggests that the increased vigilance could arise in part from the direct influence of additional noise as there was an increase in response to traffic-noise playback alone. Acoustic masking could also play a role. Foragers maintained the ability to distinguish between sentinels of different dominance class, increasing personal vigilance when presented with subordinate surveillance calls compared to calls of a dominant groupmate in both noise treatments, suggesting complete masking was not occurring. However, an acoustic-transmission experiment showed that while surveillance calls were potentially audible during approaching traffic noise, they were probably inaudible during peak traffic intensity noise. While recent work has demonstrated detrimental effects of anthropogenic noise on defensive responses to actual predatory attacks, which are relatively rare, our results provide evidence of a potentially more widespread influence since animals should constantly assess background risk to optimise the

Noise characteristics of CT perfusion imaging: how does noise propagate from source images to final perfusion maps?

NASA Astrophysics Data System (ADS)

Li, Ke; Chen, Guang-Hong

2016-03-01

Cerebral CT perfusion (CTP) imaging is playing an important role in the diagnosis and treatment of acute ischemic strokes. Meanwhile, the reliability of CTP-based ischemic lesion detection has been challenged due to the noisy appearance and low signal-to-noise ratio of CTP maps. To reduce noise and improve image quality, a rigorous study on the noise transfer properties of CTP systems is highly desirable to provide the needed scientific guidance. This paper concerns how noise in the CTP source images propagates to the final CTP maps. Both theoretical deviations and subsequent validation experiments demonstrated that, the noise level of background frames plays a dominant role in the noise of the cerebral blood volume (CBV) maps. This is in direct contradiction with the general belief that noise of non-background image frames is of greater importance in CTP imaging. The study found that when radiation doses delivered to the background frames and to all non-background frames are equal, lowest noise variance is achieved in the final CBV maps. This novel equality condition provides a practical means to optimize radiation dose delivery in CTP data acquisition: radiation exposures should be modulated between background frames and non-background frames so that the above equality condition is satisïnAed. For several typical CTP acquisition protocols, numerical simulations and in vivo canine experiment demonstrated that noise of CBV can be effectively reduced using the proposed exposure modulation method.

Signal-to-noise ratio analysis and evaluation of the Hadamard imaging technique

NASA Technical Reports Server (NTRS)

Jobson, D. J.; Katzberg, S. J.; Spiers, R. B., Jr.

1977-01-01

The signal-to-noise ratio performance of the Hadamard imaging technique is analyzed and an experimental evaluation of a laboratory Hadamard imager is presented. A comparison between the performances of Hadamard and conventional imaging techniques shows that the Hadamard technique is superior only when the imaging objective lens is required to have an effective F (focus) number of about 2 or slower.

Increasing signal-to-noise ratio of reconstructed digital holograms by using light spatial noise portrait of camera's photosensor

NASA Astrophysics Data System (ADS)

Cheremkhin, Pavel A.; Evtikhiev, Nikolay N.; Krasnov, Vitaly V.; Rodin, Vladislav G.; Starikov, Sergey N.

2015-01-01

Digital holography is technique which includes recording of interference pattern with digital photosensor, processing of obtained holographic data and reconstruction of object wavefront. Increase of signal-to-noise ratio (SNR) of reconstructed digital holograms is especially important in such fields as image encryption, pattern recognition, static and dynamic display of 3D scenes, and etc. In this paper compensation of photosensor light spatial noise portrait (LSNP) for increase of SNR of reconstructed digital holograms is proposed. To verify the proposed method, numerical experiments with computer generated Fresnel holograms with resolution equal to 512×512 elements were performed. Simulation of shots registration with digital camera Canon EOS 400D was performed. It is shown that solo use of the averaging over frames method allows to increase SNR only up to 4 times, and further increase of SNR is limited by spatial noise. Application of the LSNP compensation method in conjunction with the averaging over frames method allows for 10 times SNR increase. This value was obtained for LSNP measured with 20 % error. In case of using more accurate LSNP, SNR can be increased up to 20 times.

A Background Noise Reduction Technique Using Adaptive Noise Cancellation for Microphone Arrays

NASA Technical Reports Server (NTRS)

Spalt, Taylor B.; Fuller, Christopher R.; Brooks, Thomas F.; Humphreys, William M., Jr.; Brooks, Thomas F.

2011-01-01

Background noise in wind tunnel environments poses a challenge to acoustic measurements due to possible low or negative Signal to Noise Ratios (SNRs) present in the testing environment. This paper overviews the application of time domain Adaptive Noise Cancellation (ANC) to microphone array signals with an intended application of background noise reduction in wind tunnels. An experiment was conducted to simulate background noise from a wind tunnel circuit measured by an out-of-flow microphone array in the tunnel test section. A reference microphone was used to acquire a background noise signal which interfered with the desired primary noise source signal at the array. The technique s efficacy was investigated using frequency spectra from the array microphones, array beamforming of the point source region, and subsequent deconvolution using the Deconvolution Approach for the Mapping of Acoustic Sources (DAMAS) algorithm. Comparisons were made with the conventional techniques for improving SNR of spectral and Cross-Spectral Matrix subtraction. The method was seen to recover the primary signal level in SNRs as low as -29 dB and outperform the conventional methods. A second processing approach using the center array microphone as the noise reference was investigated for more general applicability of the ANC technique. It outperformed the conventional methods at the -29 dB SNR but yielded less accurate results when coherence over the array dropped. This approach could possibly improve conventional testing methodology but must be investigated further under more realistic testing conditions.

NONLINEAR AND FIBER OPTICS: Analysis of the mode noise in interference fiber channels used for the distribution of microwave signals

NASA Astrophysics Data System (ADS)

Bratchikov, A. N.; Glukhov, I. P.

1991-03-01

The results are given of a statistical theory of the speckle generalized to interference channels used for the distribution of microwave signals using multimode fiber waveguides with step and graded refractive-index profiles. A method is described for estimating the mode noise level in the open and closed regimes with one longitudinal speckle. The influence of the degree of mode filtering, losses at microbends, and spectral properties of a laser source on the statistical properties and the mode noise level is demonstrated. Numerical estimates are obtained of the ratio of the powers of the signal and mode noise for interference channels with typical parameters of fiber waveguides and a qualitative description is given of the effect of the mode noise.

Active noise control using noise source having adaptive resonant frequency tuning through stress variation

NASA Technical Reports Server (NTRS)

Pla, Frederic G. (Inventor); Renshaw, Anthony A. (Inventor); Rajiyah, Harindra (Inventor); Hedeen, Robert A. (Inventor)

1995-01-01

A noise source for an aircraft engine active noise cancellation system in which the resonant frequency of a noise radiating element is tuned to permit noise cancellation over a wide range of frequencies. The resonant frequency of the noise radiating element is tuned by an expandable ring embedded in the noise radiating element. Excitation of the ring causes expansion or contraction of the ring, thereby varying the stress in the noise radiating element. The ring is actuated by a controller which receives input of a feedback signal proportional to displacement of the noise radiating element and a signal corresponding to the blade passage frequency of the engine's fan. In response, the controller determines a control signal which is sent to the ring, causing the ring to expand or contract. Instead of a single ring embedded in the noise radiating panel, a first expandable ring can be bonded to one side of the noise radiating element, and a second expandable ring can be bonded to the other side.

Separating the signal from the noise: Expanding flow cytometry into the sub-micron range.

EPA Science Inventory

Cytometry Part A Special Section: Separating the signal from the noise: Expanding flow cytometry into the sub-micron range. The current Cytometry Part A Special Section presents three studies that utilize cytometers to study sub-micron particles. The three studies involve the 1...

Indirect estimation of signal-dependent noise with nonadaptive heterogeneous samples.

PubMed

Azzari, Lucio; Foi, Alessandro

2014-08-01

We consider the estimation of signal-dependent noise from a single image. Unlike conventional algorithms that build a scatterplot of local mean-variance pairs from either small or adaptively selected homogeneous data samples, our proposed approach relies on arbitrarily large patches of heterogeneous data extracted at random from the image. We demonstrate the feasibility of our approach through an extensive theoretical analysis based on mixture of Gaussian distributions. A prototype algorithm is also developed in order to validate the approach on simulated data as well as on real camera raw images.

FPGA implementation of ICA algorithm for blind signal separation and adaptive noise canceling.

PubMed

Kim, Chang-Min; Park, Hyung-Min; Kim, Taesu; Choi, Yoon-Kyung; Lee, Soo-Young

2003-01-01

An field programmable gate array (FPGA) implementation of independent component analysis (ICA) algorithm is reported for blind signal separation (BSS) and adaptive noise canceling (ANC) in real time. In order to provide enormous computing power for ICA-based algorithms with multipath reverberation, a special digital processor is designed and implemented in FPGA. The chip design fully utilizes modular concept and several chips may be put together for complex applications with a large number of noise sources. Experimental results with a fabricated test board are reported for ANC only, BSS only, and simultaneous ANC/BSS, which demonstrates successful speech enhancement in real environments in real time.

Correlated cone noise decreases rod signal contributions to the post-receptoral pathways.

PubMed

Hathibelagal, Amithavikram R; Feigl, Beatrix; Zele, Andrew J

2018-04-01

This study investigated how invisible extrinsic temporal white noise that correlates with the activity of one of the three [magnocellular (MC), parvocellular (PC), or koniocellular (KC)] post-receptoral pathways alters mesopic rod signaling. A four-primary photostimulator provided independent control of the rod and three cone photoreceptor excitations. The rod contributions to the three post-receptoral pathways were estimated by perceptually matching a 20% contrast rod pulse by independently varying the LMS (MC pathway), +L-M (PC pathway), and S-cone (KC pathway) excitations. We show that extrinsic cone noise caused a predominant decrease in the overall magnitude and ratio of the rod contributions to each pathway. Thus, the relative cone activity in the post-receptoral pathways determines the relative mesopic rod inputs to each pathway.

Signal-to-noise ratio application to seismic marker analysis and fracture detection

NASA Astrophysics Data System (ADS)

Xu, Hui-Qun; Gui, Zhi-Xian

2014-03-01

Seismic data with high signal-to-noise ratios (SNRs) are useful in reservoir exploration. To obtain high SNR seismic data, significant effort is required to achieve noise attenuation in seismic data processing, which is costly in materials, and human and financial resources. We introduce a method for improving the SNR of seismic data. The SNR is calculated by using the frequency domain method. Furthermore, we optimize and discuss the critical parameters and calculation procedure. We applied the proposed method on real data and found that the SNR is high in the seismic marker and low in the fracture zone. Consequently, this can be used to extract detailed information about fracture zones that are inferred by structural analysis but not observed in conventional seismic data.

Active noise control in a duct to cancel broadband noise

NASA Astrophysics Data System (ADS)

Chen, Kuan-Chun; Chang, Cheng-Yuan; Kuo, Sen M.

2017-09-01

The paper presents cancelling duct noises by using the active noise control (ANC) techniques. We use the single channel feed forward algorithm with feedback neutralization to realize ANC. Several kinds of ducts noises including tonal noises, sweep tonal signals, and white noise had investigated. Experimental results show that the proposed ANC system can cancel these noises in a PVC duct very well. The noise reduction of white noise can be up to 20 dB.

Stimulation of the Locus Ceruleus Modulates Signal-to-Noise Ratio in the Olfactory Bulb.

PubMed

Manella, Laura C; Petersen, Nicholas; Linster, Christiane

2017-11-29

Norepinephrine (NE) has been shown to influence sensory, and specifically olfactory processing at the behavioral and physiological levels, potentially by regulating signal-to-noise ratio (S/N). The present study is the first to look at NE modulation of olfactory bulb (OB) in regards to S/N in vivo We show, in male rats, that locus ceruleus stimulation and pharmacological infusions of NE into the OB modulate both spontaneous and odor-evoked neural responses. NE in the OB generated a non-monotonic dose-response relationship, suppressing mitral cell activity at high and low, but not intermediate, NE levels. We propose that NE enhances odor responses not through direct potentiation of the afferent signal per se, but rather by reducing the intrinsic noise of the system. This has important implications for the ways in which an animal interacts with its olfactory environment, particularly as the animal shifts from a relaxed to an alert behavioral state. SIGNIFICANCE STATEMENT Sensory perception can be modulated by behavioral states such as hunger, fear, stress, or a change in environmental context. Behavioral state often affects neural processing via the release of circulating neurochemicals such as hormones or neuromodulators. We here show that the neuromodulator norepinephrine modulates olfactory bulb spontaneous activity and odor responses so as to generate an increased signal-to-noise ratio at the output of the olfactory bulb. Our results help interpret and improve existing ideas for neural network mechanisms underlying behaviorally observed improvements in near-threshold odor detection and discrimination. Copyright © 2017 the authors 0270-6474/17/3711605-11$15.00/0.

Core Noise Diagnostics of Turbofan Engine Noise Using Correlation and Coherence Functions

NASA Technical Reports Server (NTRS)

Miles, Jeffrey H.

2009-01-01

Cross-correlation and coherence functions are used to look for periodic acoustic components in turbofan engine combustor time histories, to investigate direct and indirect combustion noise source separation based on signal propagation time delays, and to provide information on combustor acoustics. Using the cross-correlation function, time delays were identified in all cases, clearly indicating the combustor is the source of the noise. In addition, unfiltered and low-pass filtered at 400 Hz signals had a cross-correlation time delay near 90 ms, while the low-pass filtered at less than 400 Hz signals had a cross-correlation time delay longer than 90 ms. Low-pass filtering at frequencies less than 400 Hz partially removes the direct combustion noise signals. The remainder includes the indirect combustion noise signal, which travels more slowly because of the dependence on the entropy convection velocity in the combustor. Source separation of direct and indirect combustion noise is demonstrated by proper use of low-pass filters with the cross-correlation function for a range of operating conditions. The results may lead to a better idea about the acoustics in the combustor and may help develop and validate improved reduced-order physics-based methods for predicting direct and indirect combustion noise.

Active noise control using noise source having adaptive resonant frequency tuning through stiffness variation

NASA Technical Reports Server (NTRS)

Rajiyah, Harindra (Inventor); Hedeen, Robert A. (Inventor); Pla, Frederic G. (Inventor); Renshaw, Anthony A. (Inventor)

1995-01-01

A noise source for an aircraft engine active noise cancellation system in which the resonant frequency of a noise radiating element is tuned to permit noise cancellation over a wide range of frequencies. The resonant frequency of the noise radiating element is tuned by a plurality of force transmitting mechanisms which contact the noise radiating element. Each one of the force transmitting mechanisms includes an expandable element and a spring in contact with the noise radiating element so that excitation of the element varies the spring force applied to the noise radiating element. The elements are actuated by a controller which receives input of a signal proportional to displacement of the noise radiating element and a signal corresponding to the blade passage frequency of the engine's fan. In response, the controller determines a control signal which is sent to the elements and causes the spring force applied to the noise radiating element to be varied. The force transmitting mechanisms can be arranged to either produce bending or linear stiffness variations in the noise radiating element.

Polarization-discrimination technique to maximize the lidar signal-to-noise ratio for daylight operations.

PubMed

Hassebo, Yasser Y; Gross, Barry; Oo, Min; Moshary, Fred; Ahmed, Samir

2006-08-01

The impact and potential of a polarization-selection technique to reduce the sky background signal for linearly polarized monostatic elastic backscatter lidar measurements are examined. Taking advantage of naturally occurring polarization properties in scattered skylight, we devised a polarization-discrimination technique in which both the lidar transmitter and the receiver track and minimize detected sky background noise while maintaining maximum lidar signal throughput. Lidar elastic backscatter measurements, carried out continuously during daylight hours at 532 nm, show as much as a factor of square root 10 improvement in the signal-to-noise ratio (SNR) over conventional unpolarized schemes. For vertically pointing lidars, the largest improvements are limited to the early morning and late afternoon hours, while for lidars scanning azimuthally and in elevation at angles other than vertical, significant improvements are achievable over more extended time periods with the specific times and improvement factors depending on the specific angle between the lidar and the solar axes. The resulting diurnal variations in SNR improvement sometimes show an asymmetry with the solar angle that analysis indicates can be attributed to changes in observed relative humidity that modifies the underlying aerosol microphysics and observed optical depth.

Polarization-discrimination technique to maximize the lidar signal-to-noise ratio for daylight operations

NASA Astrophysics Data System (ADS)

Hassebo, Yasser Y.; Gross, Barry; Oo, Min; Moshary, Fred; Ahmed, Samir

2006-08-01

The impact and potential of a polarization-selection technique to reduce the sky background signal for linearly polarized monostatic elastic backscatter lidar measurements are examined. Taking advantage of naturally occurring polarization properties in scattered skylight, we devised a polarization-discrimination technique in which both the lidar transmitter and the receiver track and minimize detected sky background noise while maintaining maximum lidar signal throughput. Lidar elastic backscatter measurements, carried out continuously during daylight hours at 532 nm, show as much as a factor of square root 10 improvement in the signal-to-noise ratio (SNR) over conventional unpolarized schemes. For vertically pointing lidars, the largest improvements are limited to the early morning and late afternoon hours, while for lidars scanning azimuthally and in elevation at angles other than vertical, significant improvements are achievable over more extended time periods with the specific times and improvement factors depending on the specific angle between the lidar and the solar axes. The resulting diurnal variations in SNR improvement sometimes show an asymmetry with the solar angle that analysis indicates can be attributed to changes in observed relative humidity that modifies the underlying aerosol microphysics and observed optical depth.

Statistical characteristics of the sequential detection of signals in correlated noise

NASA Astrophysics Data System (ADS)

Averochkin, V. A.; Baranov, P. E.

1985-10-01

A solution is given to the problem of determining the distribution of the duration of the sequential two-threshold Wald rule for the time-discrete detection of determinate and Gaussian correlated signals on a background of Gaussian correlated noise. Expressions are obtained for the joint probability densities of the likelihood ratio logarithms, and an analysis is made of the effect of correlation and SNR on the duration distribution and the detection efficiency. Comparison is made with Neumann-Pearson detection.

Adaptive noise reduction circuit for a sound reproduction system

NASA Technical Reports Server (NTRS)

Engebretson, A. Maynard (Inventor); O'Connell, Michael P. (Inventor)

1995-01-01

A noise reduction circuit for a hearing aid having an adaptive filter for producing a signal which estimates the noise components present in an input signal. The circuit includes a second filter for receiving the noise-estimating signal and modifying it as a function of a user's preference or as a function of an expected noise environment. The circuit also includes a gain control for adjusting the magnitude of the modified noise-estimating signal, thereby allowing for the adjustment of the magnitude of the circuit response. The circuit also includes a signal combiner for combining the input signal with the adjusted noise-estimating signal to produce a noise reduced output signal.

Aircraft Noise Prediction Program (ANOPP) Fan Noise Prediction for Small Engines

NASA Technical Reports Server (NTRS)

Hough, Joe W.; Weir, Donald S.

1996-01-01

The Fan Noise Module of ANOPP is used to predict the broadband noise and pure tones for axial flow compressors or fans. The module, based on the method developed by M. F. Heidmann, uses empirical functions to predict fan noise spectra as a function of frequency and polar directivity. Previous studies have determined the need to modify the module to better correlate measurements of fan noise from engines in the 3000- to 6000-pound thrust class. Additional measurements made by AlliedSignal have confirmed the need to revise the ANOPP fan noise method for smaller engines. This report describes the revisions to the fan noise method which have been verified with measured data from three separate AlliedSignal fan engines. Comparisons of the revised prediction show a significant improvement in overall and spectral noise predictions.

Evaluation of piezoceramic actuators for control of aircraft interior noise

NASA Technical Reports Server (NTRS)

Silcox, Richard J.; Lefebvre, Sylvie; Metcalf, Vern L.; Beyer, Todd B.; Fuller, Chris R.

1992-01-01

Results of an experiment to evaluate piezoceramic actuators as the control actuator for active control of interior noise in a large-scale fuselage model are presented. Control was demonstrated for tonal excitation using a time domain least mean squares algorithm. A maximum of four actuator channels and six error signals were used. The actuators were employed for control of noise at frequencies where interior cavity modes were the dominant response and for driven acoustic responses where a structure resonance was dominant. Global reductions of 9 to 12 dB were obtained for the cases examined. The most effective configuration of skin-mounted actuators was found to be a pure in-plane forcing function as opposed to a bending excitation. The frame-mounted actuators were found to be equally effective as the skin-mounted actuators. However, both configurations resulted in local regions of unacceptably high vibration response in the structure.

Techniques and software tools for estimating ultrasonic signal-to-noise ratios

NASA Astrophysics Data System (ADS)

Chiou, Chien-Ping; Margetan, Frank J.; McKillip, Matthew; Engle, Brady J.; Roberts, Ronald A.

2016-02-01

At Iowa State University's Center for Nondestructive Evaluation (ISU CNDE), the use of models to simulate ultrasonic inspections has played a key role in R&D efforts for over 30 years. To this end a series of wave propagation models, flaw response models, and microstructural backscatter models have been developed to address inspection problems of interest. One use of the combined models is the estimation of signal-to-noise ratios (S/N) in circumstances where backscatter from the microstructure (grain noise) acts to mask sonic echoes from internal defects. Such S/N models have been used in the past to address questions of inspection optimization and reliability. Under the sponsorship of the National Science Foundation's Industry/University Cooperative Research Center at ISU, an effort was recently initiated to improve existing research-grade software by adding graphical user interface (GUI) to become user friendly tools for the rapid estimation of S/N for ultrasonic inspections of metals. The software combines: (1) a Python-based GUI for specifying an inspection scenario and displaying results; and (2) a Fortran-based engine for computing defect signal and backscattered grain noise characteristics. The latter makes use of several models including: the Multi-Gaussian Beam Model for computing sonic fields radiated by commercial transducers; the Thompson-Gray Model for the response from an internal defect; the Independent Scatterer Model for backscattered grain noise; and the Stanke-Kino Unified Model for attenuation. The initial emphasis was on reformulating the research-grade code into a suitable modular form, adding the graphical user interface and performing computations rapidly and robustly. Thus the initial inspection problem being addressed is relatively simple. A normal-incidence pulse/echo immersion inspection is simulated for a curved metal component having a non-uniform microstructure, specifically an equiaxed, untextured microstructure in which the average

Estimating the frequency interval of a regularly spaced multicomponent harmonic line signal in colored noise

NASA Astrophysics Data System (ADS)

Frazer, Gordon J.; Anderson, Stuart J.

1997-10-01

The radar returns from some classes of time-varying point targets can be represented by the discrete-time signal plus noise model: xt equals st plus [vt plus (eta) t] equals (summation)i equals o P minus 1 Aiej2(pi f(i)/f(s)t) plus vt plus (eta) t, t (epsilon) 0, . . ., N minus 1, fi equals kfI plus fo where the received signal xt corresponds to the radar return from the target of interest from one azimuth-range cell. The signal has an unknown number of components, P, unknown complex amplitudes Ai and frequencies fi. The frequency parameters fo and fI are unknown, although constrained such that fo less than fI/2 and parameter k (epsilon) {minus u, . . ., minus 2, minus 1, 0, 1, 2, . . ., v} is constrained such that the component frequencies fi are bound by (minus fs/2, fs/2). The noise term vt, is typically colored, and represents clutter, interference and various noise sources. It is unknown, except that (summation)tvt2 less than infinity; in general, vt is not well modelled as an auto-regressive process of known order. The additional noise term (eta) t represents time-invariant point targets in the same azimuth-range cell. An important characteristic of the target is the unknown parameter, fI, representing the frequency interval between harmonic lines. It is desired to determine an estimate of fI from N samples of xt. We propose an algorithm to estimate fI based on Thomson's harmonic line F-Test, which is part of the multi-window spectrum estimation method and demonstrate the proposed estimator applied to target echo time series collected using an experimental HF skywave radar.

A de-noising algorithm based on wavelet threshold-exponential adaptive window width-fitting for ground electrical source airborne transient electromagnetic signal

NASA Astrophysics Data System (ADS)

Ji, Yanju; Li, Dongsheng; Yu, Mingmei; Wang, Yuan; Wu, Qiong; Lin, Jun

2016-05-01

The ground electrical source airborne transient electromagnetic system (GREATEM) on an unmanned aircraft enjoys considerable prospecting depth, lateral resolution and detection efficiency, etc. In recent years it has become an important technical means of rapid resources exploration. However, GREATEM data are extremely vulnerable to stationary white noise and non-stationary electromagnetic noise (sferics noise, aircraft engine noise and other human electromagnetic noises). These noises will cause degradation of the imaging quality for data interpretation. Based on the characteristics of the GREATEM data and major noises, we propose a de-noising algorithm utilizing wavelet threshold method and exponential adaptive window width-fitting. Firstly, the white noise is filtered in the measured data using the wavelet threshold method. Then, the data are segmented using data window whose step length is even logarithmic intervals. The data polluted by electromagnetic noise are identified within each window based on the discriminating principle of energy detection, and the attenuation characteristics of the data slope are extracted. Eventually, an exponential fitting algorithm is adopted to fit the attenuation curve of each window, and the data polluted by non-stationary electromagnetic noise are replaced with their fitting results. Thus the non-stationary electromagnetic noise can be effectively removed. The proposed algorithm is verified by the synthetic and real GREATEM signals. The results show that in GREATEM signal, stationary white noise and non-stationary electromagnetic noise can be effectively filtered using the wavelet threshold-exponential adaptive window width-fitting algorithm, which enhances the imaging quality.

Signal-to-noise ratio of Singer product apertures

NASA Astrophysics Data System (ADS)

Shutler, Paul M. E.; Byard, Kevin

2017-09-01

Formulae for the signal-to-noise ratio (SNR) of Singer product apertures are derived, allowing optimal Singer product apertures to be identified, and the CPU time required to decode them is quantified. This allows a systematic comparison to be made of the performance of Singer product apertures against both conventionally wrapped Singer apertures, and also conventional product apertures such as square uniformly redundant arrays. For very large images, equivalently for images at very high resolution, the SNR of Singer product apertures is asymptotically as good as the best conventional apertures, but Singer product apertures decode faster than any conventional aperture by at least a factor of ten for image sizes up to several megapixels. These theoretical predictions are verified using numerical simulations, demonstrating that coded aperture video is for the first time a realistic possibility.

Vibration-induced electrical noise in a cryogen-free dilution refrigerator: Characterization, mitigation, and impact on qubit coherence

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kalra, Rachpon; Laucht, Arne; Dehollain, Juan Pablo

Cryogen-free low-temperature setups are becoming more prominent in experimental science due to their convenience and reliability, and concern about the increasing scarcity of helium as a natural resource. Despite not having any moving parts at the cold end, pulse tube cryocoolers introduce vibrations that can be detrimental to the experiments. We characterize the coupling of these vibrations to the electrical signal observed on cables installed in a cryogen-free dilution refrigerator. The dominant electrical noise is in the 5–10 kHz range and its magnitude is found to be strongly temperature dependent. We test the performance of different cables designed to diagnosemore » and tackle the noise, and find triboelectrics to be the dominant mechanism coupling the vibrations to the electrical signal. Flattening a semi-rigid cable or jacketing a flexible cable in order to restrict movement within the cable, successfully reduces the noise level by over an order of magnitude. Furthermore, we characterize the effect of the pulse tube vibrations on an electron spin qubit device in this setup. Coherence measurements are used to map out the spectrum of the noise experienced by the qubit, revealing spectral components matching the spectral signature of the pulse tube.« less

Shielded multi-stage EMI noise filter

DOEpatents

Kisner, Roger Allen; Fugate, David Lee

2016-11-08

Electromagnetic interference (EMI) noise filter embodiments and methods for filtering are provided herein. EMI noise filters include multiple signal exclusion enclosures. The multiple signal exclusion enclosures contain filter circuit stages. The signal exclusion enclosures can attenuate noise generated external to the enclosures and/or isolate noise currents generated by the corresponding filter circuits within the enclosures. In certain embodiments, an output of one filter circuit stage is connected to an input of the next filter circuit stage. The multiple signal exclusion enclosures can be chambers formed using conductive partitions to divide an outer signal exclusion enclosure. EMI noise filters can also include mechanisms to maintain the components of the filter circuit stages at a consistent temperature. For example, a metal base plate can distribute heat among filter components, and an insulating material can be positioned inside signal exclusion enclosures.

On the measurement of criterion noise in signal detection theory: the case of recognition memory.

PubMed

Kellen, David; Klauer, Karl Christoph; Singmann, Henrik

2012-07-01

Traditional approaches within the framework of signal detection theory (SDT; Green & Swets, 1966), especially in the field of recognition memory, assume that the positioning of response criteria is not a noisy process. Recent work (Benjamin, Diaz, & Wee, 2009; Mueller & Weidemann, 2008) has challenged this assumption, arguing not only for the existence of criterion noise but also for its large magnitude and substantive contribution to individuals' performance. A review of these recent approaches for the measurement of criterion noise in SDT identifies several shortcomings and confoundings. A reanalysis of Benjamin et al.'s (2009) data sets as well as the results from a new experimental method indicate that the different forms of criterion noise proposed in the recognition memory literature are of very low magnitudes, and they do not provide a significant improvement over the account already given by traditional SDT without criterion noise. Copyright 2012 APA, all rights reserved.

The Effect of Classroom Amplification on the Signal-to-Noise Ratio in Classrooms while Class Is in Session

ERIC Educational Resources Information Center

Larsen, Jeffery B.; Blair, James C.

2008-01-01

Purpose: The purpose of this study was to measure the signal-to-noise ratios in classrooms while class was in session and students were interacting with the teacher and each other. Method: Measurements of noise and reverberation were collected for 5 different classrooms in 3 different schools while class was in session. Activities taking place…

Circadian Rhythm of Ambient Noise Off the Southeast Coast of India

NASA Astrophysics Data System (ADS)

Kannan, R.; Latha, G.; Prashanthi Devi, M.

An ambient noise system consisting of a vertical linear hydrophone array was deployed in the shallow waters off Chennai, southeast coast of India from 1 August to 16 September 2013 to record ambient ocean noise of frequencies up to 10kHz. Biological sounds, which are broadband, short duration signals resulting from Terapon theraps, a native species, are a prominent feature of the ocean soundscape. Terapon activity peaks at 8pm and 11pm, and its presence is not observed after 12 midnight in both the months. In the other period, the ambient noise fluctuation is due to wind and vessel traffic. Hence, the present study focuses on the description of the ambient noise fluctuation over two 12h periods, i.e., 12 midnight-12 noon considered as period I, and 12 noon-12 midnight as period II in order to show the circadian rhythm of ambient noise. In this study area, Terapon vocalization reached 25dB above the ambient noise level and it dominates the short-term spectra records in the 0.4-4kHz range. All Terapon signals had daily patterns of sound production with highest levels of activity after dusk during the study period. The result shows that the circadian rhythm of ambient noise is mainly of biological sound generated by Terapon and it is reported first time in the shallow waters off the southeast coast of India.

Active noise control using noise source having adaptive resonant frequency tuning through variable ring loading

NASA Technical Reports Server (NTRS)

Rajiyah, Harindra (Inventor); Pla, Frederic G. (Inventor); Hedeen, Robert A. (Inventor); Renshaw, Anthony A. (Inventor)

1995-01-01

A noise source for an aircraft engine active noise cancellation system in which the resonant frequency of noise radiating structure is tuned to permit noise cancellation over a wide range of frequencies. The resonant frequency of the noise radiating structure is tuned by a plurality of drivers arranged to contact the noise radiating structure. Excitation of the drivers causes expansion or contraction of the drivers, thereby varying the edge loading applied to the noise radiating structure. The drivers are actuated by a controller which receives input of a feedback signal proportional to displacement of the noise radiating element and a signal corresponding to the blade passage frequency of the engine's fan. In response, the controller determines a control signal which is sent to the drivers, causing them to expand or contract. The noise radiating structure may be either the outer shroud of the engine or a ring mounted flush with an inner wall of the shroud or disposed in the interior of the shroud.

Immersive audiomotor game play enhances neural and perceptual salience of weak signals in noise

PubMed Central

Whitton, Jonathon P.; Hancock, Kenneth E.; Polley, Daniel B.

2014-01-01

All sensory systems face the fundamental challenge of encoding weak signals in noisy backgrounds. Although discrimination abilities can improve with practice, these benefits rarely generalize to untrained stimulus dimensions. Inspired by recent findings that action video game training can impart a broader spectrum of benefits than traditional perceptual learning paradigms, we trained adult humans and mice in an immersive audio game that challenged them to forage for hidden auditory targets in a 2D soundscape. Both species learned to modulate their angular search vectors and target approach velocities based on real-time changes in the level of a weak tone embedded in broadband noise. In humans, mastery of this tone in noise task generalized to an improved ability to comprehend spoken sentences in speech babble noise. Neural plasticity in the auditory cortex of trained mice supported improved decoding of low-intensity sounds at the training frequency and an enhanced resistance to interference from background masking noise. These findings highlight the potential to improve the neural and perceptual salience of degraded sensory stimuli through immersive computerized games. PMID:24927596

Immersive audiomotor game play enhances neural and perceptual salience of weak signals in noise.

PubMed

Whitton, Jonathon P; Hancock, Kenneth E; Polley, Daniel B

2014-06-24

All sensory systems face the fundamental challenge of encoding weak signals in noisy backgrounds. Although discrimination abilities can improve with practice, these benefits rarely generalize to untrained stimulus dimensions. Inspired by recent findings that action video game training can impart a broader spectrum of benefits than traditional perceptual learning paradigms, we trained adult humans and mice in an immersive audio game that challenged them to forage for hidden auditory targets in a 2D soundscape. Both species learned to modulate their angular search vectors and target approach velocities based on real-time changes in the level of a weak tone embedded in broadband noise. In humans, mastery of this tone in noise task generalized to an improved ability to comprehend spoken sentences in speech babble noise. Neural plasticity in the auditory cortex of trained mice supported improved decoding of low-intensity sounds at the training frequency and an enhanced resistance to interference from background masking noise. These findings highlight the potential to improve the neural and perceptual salience of degraded sensory stimuli through immersive computerized games.

Ceilometer signal performance with height in high aerosol loads

NASA Astrophysics Data System (ADS)

Bachour, D.; Perez-Astudillo, D.

2016-02-01

This paper is dedicated to the study of the Vaisala CL51 ceilometer backscatter signals during a one-year period, in particular the study of the noise embedded in the signals measured by the ceilometer, under cloudless conditions. The noise analysis is done to provide indication about the maximum atmospheric height up to which the ceilometer signal is still reliable enough in clear-sky conditions, for the detection of changing aerosol contents. The experiment was carried out in Doha, Qatar, for a period of 12 months, from December 2012 to November 2013. 214 clear days were selected during this year. Several tests were performed in order to assess the variability of the backscatter signals from day to day and between different heights in the atmosphere. To the authors' knowledge, it is the first time that the signal performance of a ceilometer is studied in a highly aerosol-loaded region, and for a relatively extended period of time. Considering the whole year, it is found that a height of 5 or 6 km represents a good compromise between including the signals arising from the dynamicity of the atmosphere and removing as much as possible the signal dominated by noise at higher heights. In winter months, however, this limit can be extended up to a height of 7 km.

Chronic anthropogenic noise disrupts glucocorticoid signaling and has multiple effects on fitness in an avian community.

PubMed

Kleist, Nathan J; Guralnick, Robert P; Cruz, Alexander; Lowry, Christopher A; Francis, Clinton D

2018-01-23

Anthropogenic noise is a pervasive pollutant that decreases environmental quality by disrupting a suite of behaviors vital to perception and communication. However, even within populations of noise-sensitive species, individuals still select breeding sites located within areas exposed to high noise levels, with largely unknown physiological and fitness consequences. We use a study system in the natural gas fields of northern New Mexico to test the prediction that exposure to noise causes glucocorticoid-signaling dysfunction and decreases fitness in a community of secondary cavity-nesting birds. In accordance with these predictions, and across all species, we find strong support for noise exposure decreasing baseline corticosterone in adults and nestlings and, conversely, increasing acute stressor-induced corticosterone in nestlings. We also document fitness consequences with increased noise in the form of reduced hatching success in the western bluebird ( Sialia mexicana ), the species most likely to nest in noisiest environments. Nestlings of all three species exhibited accelerated growth of both feathers and body size at intermediate noise amplitudes compared with lower or higher amplitudes. Our results are consistent with recent experimental laboratory studies and show that noise functions as a chronic, inescapable stressor. Anthropogenic noise likely impairs environmental risk perception by species relying on acoustic cues and ultimately leads to impacts on fitness. Our work, when taken together with recent efforts to document noise across the landscape, implies potential widespread, noise-induced chronic stress coupled with reduced fitness for many species reliant on acoustic cues.

Noise Reduction in Brainwaves by Using Both EEG Signals and Frontal Viewing Camera Images

PubMed Central

Bang, Jae Won; Choi, Jong-Suk; Park, Kang Ryoung

2013-01-01

Electroencephalogram (EEG)-based brain-computer interfaces (BCIs) have been used in various applications, including human–computer interfaces, diagnosis of brain diseases, and measurement of cognitive status. However, EEG signals can be contaminated with noise caused by user's head movements. Therefore, we propose a new method that combines an EEG acquisition device and a frontal viewing camera to isolate and exclude the sections of EEG data containing these noises. This method is novel in the following three ways. First, we compare the accuracies of detecting head movements based on the features of EEG signals in the frequency and time domains and on the motion features of images captured by the frontal viewing camera. Second, the features of EEG signals in the frequency domain and the motion features captured by the frontal viewing camera are selected as optimal ones. The dimension reduction of the features and feature selection are performed using linear discriminant analysis. Third, the combined features are used as inputs to support vector machine (SVM), which improves the accuracy in detecting head movements. The experimental results show that the proposed method can detect head movements with an average error rate of approximately 3.22%, which is smaller than that of other methods. PMID:23669713

Seismic noise frequency dependent P and S wave sources

NASA Astrophysics Data System (ADS)

Stutzmann, E.; Schimmel, M.; Gualtieri, L.; Farra, V.; Ardhuin, F.

2013-12-01

Seismic noise in the period band 3-10 sec is generated in the oceans by the interaction of ocean waves. Noise signal is dominated by Rayleigh waves but body waves can be extracted using a beamforming approach. We select the TAPAS array deployed in South Spain between June 2008 and September 2009 and we use the vertical and horizontal components to extract noise P and S waves, respectively. Data are filtered in narrow frequency bands and we select beam azimuths and slownesses that correspond to the largest continuous sources per day. Our procedure automatically discard earthquakes which are localized during short time durations. Using this approach, we detect many more noise P-waves than S-waves. Source locations are determined by back-projecting the detected slowness/azimuth. P and S waves are generated in nearby areas and both source locations are frequency dependent. Long period sources are dominantly in the South Atlantic and Indian Ocean whereas shorter period sources are rather in the North Atlantic Ocean. We further show that the detected S-waves are dominantly Sv-waves. We model the observed body waves using an ocean wave model that takes into account all possible wave interactions including coastal reflection. We use the wave model to separate direct and multiply reflected phases for P and S waves respectively. We show that in the South Atlantic the complex source pattern can be explained by the existence of both coastal and pelagic sources whereas in the North Atlantic most body wave sources are pelagic. For each detected source, we determine the equivalent source magnitude which is compared to the model.

Real-time photonic sampling with improved signal-to-noise and distortion ratio using polarization-dependent modulators

NASA Astrophysics Data System (ADS)

Liang, Dong; Zhang, Zhiyao; Liu, Yong; Li, Xiaojun; Jiang, Wei; Tan, Qinggui

2018-04-01

A real-time photonic sampling structure with effective nonlinearity suppression and excellent signal-to-noise ratio (SNR) performance is proposed. The key points of this scheme are the polarization-dependent modulators (P-DMZMs) and the sagnac loop structure. Thanks to the polarization sensitive characteristic of P-DMZMs, the differences between transfer functions of the fundamental signal and the distortion become visible. Meanwhile, the selection of specific biases in P-DMZMs is helpful to achieve a preferable linearized performance with a low noise level for real-time photonic sampling. Compared with the quadrature-biased scheme, the proposed scheme is capable of valid nonlinearity suppression and is able to provide a better SNR performance even in a large frequency range. The proposed scheme is proved to be effective and easily implemented for real time photonic applications.

Analysis and suppression of passive noise in surface microseismic data

NASA Astrophysics Data System (ADS)

Forghani-Arani, Farnoush

Surface microseismic surveys are gaining popularity in monitoring the hydraulic fracturing process. The effectiveness of these surveys, however, is strongly dependent on the signal-to-noise ratio of the acquired data. Cultural and industrial noise generated during hydraulic fracturing operations usually dominate the data, thereby decreasing the effectiveness of using these data in identifying and locating microseismic events. Hence, noise suppression is a critical step in surface microseismic monitoring. In this thesis, I focus on two important aspects in using surface-recorded microseismic seismic data: first, I take advantage of the unwanted surface noise to understand the characteristics of these noise and extract information about the propagation medium from the noise; second, I propose effective techniques to suppress the surface noise while preserving the waveforms that contain information about the source of microseisms. Automated event identification on passive seismic data using only a few receivers is challenging especially when the record lengths span over long durations of time. I introduce an automatic event identification algorithm that is designed specifically for detecting events in passive data acquired with a small number of receivers. I demonstrate that the conventional STA/LTA (Short-term Average/Long-term Average) algorithm is not sufficiently effective in event detection in the common case of low signal-to-noise ratio. With a cross-correlation based method as an extension of the STA/LTA algorithm, even low signal-to-noise events (that were not detectable with conventional STA/LTA) were revealed. Surface microseismic data contains surface-waves (generated primarily from hydraulic fracturing activities) and body-waves in the form of microseismic events. It is challenging to analyze the surface-waves on the recorded data directly because of the randomness of their source and their unknown source signatures. I use seismic interferometry to extract

Noise reduction experience at Hughes Helicopter, Inc.

NASA Technical Reports Server (NTRS)

Janakiram, D. S.

1982-01-01

Noise reduction is mostly limited to light helicopters whose noise signature is dominated by their tail rotors. It is primarily hardware oriented. Well known noise reduction techniques such as reduction of rotor speeds with an accompanying increase in solidity to maintain performance, engine noise reduction with the use of exhaust mufflers, and acoustic blanketing of transmission and engine compartment are used. The concept of blade phasing as a means of reducing tail rotor noise is also used. Engine noise (exhaust noise), power train noise and airframe noise becomes important at low rotor tip speeds and means must be found to reduce these noise sources if further noise reductions are desired. The use of a special test rig aids in isolating the various noise sources and arriving at the penalties (performance or payload) involved in quieting them. Significant noise reduction are achieved for the light helicopter with minimum performance or weight penalties because of the dominance of a single noise source (the tail rotor).

Noise reduction experience at Hughes Helicopter, Inc.

NASA Astrophysics Data System (ADS)

Janakiram, D. S.

1982-07-01

Noise reduction is mostly limited to light helicopters whose noise signature is dominated by their tail rotors. It is primarily hardware oriented. Well known noise reduction techniques such as reduction of rotor speeds with an accompanying increase in solidity to maintain performance, engine noise reduction with the use of exhaust mufflers, and acoustic blanketing of transmission and engine compartment are used. The concept of blade phasing as a means of reducing tail rotor noise is also used. Engine noise (exhaust noise), power train noise and airframe noise becomes important at low rotor tip speeds and means must be found to reduce these noise sources if further noise reductions are desired. The use of a special test rig aids in isolating the various noise sources and arriving at the penalties (performance or payload) involved in quieting them. Significant noise reduction are achieved for the light helicopter with minimum performance or weight penalties because of the dominance of a single noise source (the tail rotor).

Design of Flow Systems for Improved Networking and Reduced Noise in Biomolecular Signal Processing in Biocomputing and Biosensing Applications

PubMed Central

Verma, Arjun; Fratto, Brian E.; Privman, Vladimir; Katz, Evgeny

2016-01-01

We consider flow systems that have been utilized for small-scale biomolecular computing and digital signal processing in binary-operating biosensors. Signal measurement is optimized by designing a flow-reversal cuvette and analyzing the experimental data to theoretically extract the pulse shape, as well as reveal the level of noise it possesses. Noise reduction is then carried out numerically. We conclude that this can be accomplished physically via the addition of properly designed well-mixing flow-reversal cell(s) as an integral part of the flow system. This approach should enable improved networking capabilities and potentially not only digital but analog signal-processing in such systems. Possible applications in complex biocomputing networks and various sense-and-act systems are discussed. PMID:27399702

Photon noise from chaotic and coherent millimeter-wave sources measured with horn-coupled, aluminum lumped-element kinetic inductance detectors

NASA Astrophysics Data System (ADS)

Flanigan, D.; McCarrick, H.; Jones, G.; Johnson, B. R.; Abitbol, M. H.; Ade, P.; Araujo, D.; Bradford, K.; Cantor, R.; Che, G.; Day, P.; Doyle, S.; Kjellstrand, C. B.; Leduc, H.; Limon, M.; Luu, V.; Mauskopf, P.; Miller, A.; Mroczkowski, T.; Tucker, C.; Zmuidzinas, J.

2016-02-01

We report photon-noise limited performance of horn-coupled, aluminum lumped-element kinetic inductance detectors at millimeter wavelengths. The detectors are illuminated by a millimeter-wave source that uses an active multiplier chain to produce radiation between 140 and 160 GHz. We feed the multiplier with either amplified broadband noise or a continuous-wave tone from a microwave signal generator. We demonstrate that the detector response over a 40 dB range of source power is well-described by a simple model that considers the number of quasiparticles. The detector noise-equivalent power (NEP) is dominated by photon noise when the absorbed power is greater than approximately 1 pW, which corresponds to NEP≈2 ×10-17 W Hz-1 /2 , referenced to absorbed power. At higher source power levels, we observe the relationships between noise and power expected from the photon statistics of the source signal: NEP∝P for broadband (chaotic) illumination and NEP∝P1 /2 for continuous-wave (coherent) illumination.

A complex symbol signal-to-noise ratio estimator and its performance

NASA Technical Reports Server (NTRS)

Feria, Y.

1994-01-01

This article presents an algorithm for estimating the signal-to-noise ratio (SNR) of signals that contain data on a downconverted suppressed carrier or the first harmonic of a square-wave subcarrier. This algorithm can be used to determine the performance of the full-spectrum combiner for the Galileo S-band (2.2- to 2.3-GHz) mission by measuring the input and output symbol SNR. A performance analysis of the algorithm shows that the estimator can estimate the complex symbol SNR using 10,000 symbols at a true symbol SNR of -5 dB with a mean of -4.9985 dB and a standard deviation of 0.2454 dB, and these analytical results are checked by simulations of 100 runs with a mean of -5.06 dB and a standard deviation of 0.2506 dB.

Assessment of the Dominant Path Model and Field Measurements for NLOS DTV Signal Propagation

NASA Astrophysics Data System (ADS)

Adonias, Geoflly L.; Carvalho, Joabson N.

2018-03-01

In Brazil, one of the most important telecommunications systems is broadcast television. Such relevance demands an extensive analysis to be performed chasing technical excellence in order to offer a better digital transmission to the user. Therefore, it is mandatory to evaluate the quality and strength of the Digital TV signal, through studies of coverage predictions models, allowing stations to be projected in a way that their respective signals are harmoniously distributed. The purpose of this study is to appraise measurements of digital television signal obtained in the field and to compare them with numerical results from the simulation of the Dominant Path Model. The outcomes indicate possible blocking zones and a low accumulated probability index above the reception threshold, as well as characterise the gain level of the receiving antenna, which would prevent signal blocking.

How is spatial context learning integrated over signal versus noise? A primacy effect in contextual cueing.

PubMed

Jungé, Justin A; Scholl, Brian J; Chun, Marvin M

2007-01-01

Over repeated exposure to particular visual search displays, subjects are able to implicitly extract regularities that then make search more efficient-a phenomenon known as contextual cueing. Here we explore how the learning involved in contextual cueing is formed, maintained, and updated over experience. During an initial training phase, a group of signal first subjects searched through a series of predictive displays (where distractor locations were perfectly correlated with the target location), followed with no overt break by a series of unpredictive displays (where repeated contexts were uncorrelated with target locations). A second noise first group of subjects encountered the unpredictive displays followed by the predictive displays. Despite the fact that both groups had the same overall exposure to signal and noise, only the signal first group demonstrated subsequent contextual cueing. This primacy effect indicates that initial experience can result in hypotheses about regularities in displays-or the lack thereof-which then become resistant to updating. The absence of regularities in early stages of training even blocked observers from learning predictive regularities later on.

How is spatial context learning integrated over signal versus noise? A primacy effect in contextual cueing

PubMed Central

Jungé, Justin A.; Scholl, Brian J.; Chun, Marvin M.

2008-01-01

Over repeated exposure to particular visual search displays, subjects are able to implicitly extract regularities that then make search more efficient—a phenomenon known as contextual cueing. Here we explore how the learning involved in contextual cueing is formed, maintained, and updated over experience. During an initial training phase, a group of signal first subjects searched through a series of predictive displays (where distractor locations were perfectly correlated with the target location), followed with no overt break by a series of unpredictive displays (where repeated contexts were uncorrelated with target locations). A second noise first group of subjects encountered the unpredictive displays followed by the predictive displays. Despite the fact that both groups had the same overall exposure to signal and noise, only the signal first group demonstrated subsequent contextual cueing. This primacy effect indicates that initial experience can result in hypotheses about regularities in displays—or the lack thereof—which then become resistant to updating. The absence of regularities in early stages of training even blocked observers from learning predictive regularities later on. PMID:18725966

Noise screen for attitude control system

NASA Technical Reports Server (NTRS)

Rodden, John J. (Inventor); Stevens, Homer D. (Inventor); Hong, David P. (Inventor); Hirschberg, Philip C. (Inventor)

2002-01-01

An attitude control system comprising a controller and a noise screen device coupled to the controller. The controller is adapted to control an attitude of a vehicle carrying an actuator system that is adapted to pulse in metered bursts in order to generate a control torque to control the attitude of the vehicle in response to a control pulse. The noise screen device is adapted to generate a noise screen signal in response to the control pulse that is generated when an input attitude error signal exceeds a predetermined deadband attitude level. The noise screen signal comprises a decaying offset signal that when combined with the attitude error input signal results in a net attitude error input signal away from the predetermined deadband level to reduce further control pulse generation.

Analysis and control of computer cooling fan noise

NASA Astrophysics Data System (ADS)

Wong, Kam

This thesis is divided into three parts: the study of the source mechanisms and their separation, passive noise control, and active noise control. The mechanisms of noise radiated by a typical computer cooling fan is investigated both theoretically and experimentally focusing on the dominant rotor-stator interaction. The unsteady force generated by the aerodynamic interaction between the rotor blades and struts is phase locked with the blade rotation and radiates tonal noise. Experimentally, synchronous averaging with the rotation signal extracts the tones made by the deterministic part of the rotor-strut interaction mechanism. This averaged signal is called the rotary noise. The difference between the overall noise and rotary noise is defined as random noise which is broadband in the spectrum. The deterministic tonal peaks are certainly more annoying than the broadband, so the suppression of the tones is the focus of this study. Based on the theoretical study of point force formulation, methods are devised to separate the noise radiated by the two components of drag and thrust forces on blades and struts. The source separation is also extended to the leading and higher order modes of the spinning pressure pattern. By using the original fan rotor and installing it in various casings, the noise sources of the original fan are decomposed into elementary sources through directivity measurements. Details of the acoustical directivity for the original fan and its various modifications are interpreted. For the sample fan, two common features account for most of the tonal noise radiated. The two features are the inlet flow distortion caused by the square fan casing, and the large strut carrying the electric wires for the motor. When the inlet bellmouth is installed and the large strut is trimmed down to size, a significant reduction of 12 dB in tonal sound power is achieved. These structural corrections constitute the passive noise control. However, the end product still

An all digital phase locked loop for synchronization of a sinusoidal signal embedded in white Gaussian noise

NASA Technical Reports Server (NTRS)

Reddy, C. P.; Gupta, S. C.

1973-01-01

An all digital phase locked loop which tracks the phase of the incoming sinusoidal signal once per carrier cycle is proposed. The different elements and their functions and the phase lock operation are explained in detail. The nonlinear difference equations which govern the operation of the digital loop when the incoming signal is embedded in white Gaussian noise are derived, and a suitable model is specified. The performance of the digital loop is considered for the synchronization of a sinusoidal signal. For this, the noise term is suitably modelled which allows specification of the output probabilities for the two level quantizer in the loop at any given phase error. The loop filter considered increases the probability of proper phase correction. The phase error states in modulo two-pi forms a finite state Markov chain which enables the calculation of steady state probabilities, RMS phase error, transient response and mean time for cycle skipping.

Performance of signal-to-noise ratio estimation for scanning electron microscope using autocorrelation Levinson-Durbin recursion model.

PubMed

Sim, K S; Lim, M S; Yeap, Z X

2016-07-01

A new technique to quantify signal-to-noise ratio (SNR) value of the scanning electron microscope (SEM) images is proposed. This technique is known as autocorrelation Levinson-Durbin recursion (ACLDR) model. To test the performance of this technique, the SEM image is corrupted with noise. The autocorrelation function of the original image and the noisy image are formed. The signal spectrum based on the autocorrelation function of image is formed. ACLDR is then used as an SNR estimator to quantify the signal spectrum of noisy image. The SNR values of the original image and the quantified image are calculated. The ACLDR is then compared with the three existing techniques, which are nearest neighbourhood, first-order linear interpolation and nearest neighbourhood combined with first-order linear interpolation. It is shown that ACLDR model is able to achieve higher accuracy in SNR estimation. © 2016 The Authors Journal of Microscopy © 2016 Royal Microscopical Society.

Masking potency and whiteness of noise at various noise check sizes.

PubMed

Kukkonen, H; Rovamo, J; Näsänen, R

1995-02-01

The masking effect of spatial noise can be increased by increasing either the rms contrast or check size of noise. In this study, the authors investigated the largest noise check size that still mimics the effect of white noise in grating detection and how it depends on the bandwidth and spatial frequency of a grating. The authors measured contrast energy thresholds, E, for vertical cosine gratings at various spatial frequencies and bandwidths. Gratings were embedded in two-dimensional spatial noise. The side length of the square noise checks was varied in the experiments. The spectral density, N(0,0), of white spatial noise at zero frequency was calculated by multiplying the noise check area by the rms contrast of noise squared. The physical signal-to-noise ratio at threshold [E/N(0,0)]0.5 was initially constant but then started to decrease. The largest noise check that still produced a constant physical signal-to-noise ratio at threshold was directly proportional to the spatial frequency. When expressed as a fraction of grating cycle, the largest noise check size depended only on stimulus bandwidth. The smallest number of noise checks per grating cycle needed to mimic the effect of white noise decreased from 4.2 to 2.6 when the number of grating cycles increased from 1 to 64. Spatial noise can be regarded as white in grating detection if there are at least four square noise checks per grating cycle at all spatial frequencies.

LIMPIC: a computational method for the separation of protein MALDI-TOF-MS signals from noise.

PubMed

Mantini, Dante; Petrucci, Francesca; Pieragostino, Damiana; Del Boccio, Piero; Di Nicola, Marta; Di Ilio, Carmine; Federici, Giorgio; Sacchetta, Paolo; Comani, Silvia; Urbani, Andrea

2007-03-26

Mass spectrometry protein profiling is a promising tool for biomarker discovery in clinical proteomics. However, the development of a reliable approach for the separation of protein signals from noise is required. In this paper, LIMPIC, a computational method for the detection of protein peaks from linear-mode MALDI-TOF data is proposed. LIMPIC is based on novel techniques for background noise reduction and baseline removal. Peak detection is performed considering the presence of a non-homogeneous noise level in the mass spectrum. A comparison of the peaks collected from multiple spectra is used to classify them on the basis of a detection rate parameter, and hence to separate the protein signals from other disturbances. LIMPIC preprocessing proves to be superior than other classical preprocessing techniques, allowing for a reliable decomposition of the background noise and the baseline drift from the MALDI-TOF mass spectra. It provides lower coefficient of variation associated with the peak intensity, improving the reliability of the information that can be extracted from single spectra. Our results show that LIMPIC peak-picking is effective even in low protein concentration regimes. The analytical comparison with commercial and freeware peak-picking algorithms demonstrates its superior performances in terms of sensitivity and specificity, both on in-vitro purified protein samples and human plasma samples. The quantitative information on the peak intensity extracted with LIMPIC could be used for the recognition of significant protein profiles by means of advanced statistic tools: LIMPIC might be valuable in the perspective of biomarker discovery.

Systematic analysis of the contributions of stochastic voltage gated channels to neuronal noise

PubMed Central

O'Donnell, Cian; van Rossum, Mark C. W.

2014-01-01

Electrical signaling in neurons is mediated by the opening and closing of large numbers of individual ion channels. The ion channels' state transitions are stochastic and introduce fluctuations in the macroscopic current through ion channel populations. This creates an unavoidable source of intrinsic electrical noise for the neuron, leading to fluctuations in the membrane potential and spontaneous spikes. While this effect is well known, the impact of channel noise on single neuron dynamics remains poorly understood. Most results are based on numerical simulations. There is no agreement, even in theoretical studies, on which ion channel type is the dominant noise source, nor how inclusion of additional ion channel types affects voltage noise. Here we describe a framework to calculate voltage noise directly from an arbitrary set of ion channel models, and discuss how this can be use to estimate spontaneous spike rates. PMID:25360105

Improving signal-to-noise ratios of liquid chromatography-tandem mass spectrometry peaks using noise frequency spectrum modification between two consecutive matched-filtering procedures.

PubMed

Wang, Shau-Chun; Huang, Chih-Min; Chiang, Shu-Min

2007-08-17

This paper reports a simple chemometric technique to alter the noise spectrum of liquid chromatography-tandem mass spectrometry (LC-MS-MS) chromatogram between two consecutive matched filter procedures to improve the peak signal-to-noise (S/N) ratio enhancement. This technique is to multiply one match-filtered LC-MS-MS chromatogram with another artificial chromatogram added with thermal noises prior to the second matched filter. Because matched filter cannot eliminate low-frequency components inherent in the flicker noises of spike-like sharp peaks randomly riding on LC-MS-MS chromatograms, efficient peak S/N ratio improvement cannot be accomplished using one-step or consecutive matched filter procedures to process LC-MS-MS chromatograms. In contrast, when the match-filtered LC-MS-MS chromatogram is conditioned with the multiplication alteration prior to the second matched filter, much better efficient ratio improvement is achieved. The noise frequency spectrum of match-filtered chromatogram, which originally contains only low-frequency components, is altered to span a boarder range with multiplication operation. When the frequency range of this modified noise spectrum shifts toward higher frequency regime, the second matched filter, working as a low-pass filter, is able to provide better filtering efficiency to obtain higher peak S/N ratios. Real LC-MS-MS chromatograms containing random spike-like peaks, of which peak S/N ratio improvement is less than four times with two consecutive matched filters typically, are remedied to accomplish much better ratio enhancement approximately 16-folds when the noise frequency spectrum is modified between two matched filters.

Optimization of wide-angle seismic signal-to-noise ratios and P-wave transmission in Kenya

USGS Publications Warehouse

Jacob, A.W.B.; Vees, R.; Braile, L.W.; Criley, E.

1994-01-01

In previous refraction and wide-angle reflection experiments in the Kenya Rift there were problems with poor signal-noise ratios which made good seismic interpretation difficult. Careful planning and preparation for KRISP 90 has substantially overcome these problems and produced excellent seismic sections in a difficult environment. Noise levels were minimized by working, as far as possible, at times of the day when conditions were quiet, while source signals were optimized by using dispersed charges in water where it was available and waterfilled boreholes in most cases where it was not. Seismic coupling at optimum depth in water has been found to be more than 100 times greater than it is in a borehole in dry loosely compacted material. Allowing for the source coupling, a very marked difference has been found between the observation ranges in the rift and those on the flanks, where the observation ranges are greater. These appear to indicate a significant difference in seismic transmission through the two types of crust. ?? 1994.

Vibration-induced electrical noise in a cryogen-free dilution refrigerator: Characterization, mitigation, and impact on qubit coherence

NASA Astrophysics Data System (ADS)

Laucht, Arne; Kalra, Rachpon; Dehollain, Juan P.; Bar, Daniel; Freer, Solomon; Simmons, Stephanie; Muhonen, Juha T.; Morello, Andrea

Cryogen-free low-temperature setups are becoming more prominent in experimental science due to their convenience and reliability, and concern about the increasing scarcity of helium as a natural resource. Despite not having any moving parts at the cold end, pulse tube cryocoolers introduce vibrations that can be detrimental to the experiments. We characterize the coupling of these vibrations to the electrical signal observed on cables installed in a cryogen-free dilution refrigerator. The dominant electrical noise is in the 5-10 kHz range and its magnitude is found to be strongly temperature dependent. We test the performance of different cables designed to diagnose and tackle the noise, and find triboelectrics to be the dominant mechanism coupling the vibrations to the electrical signal. Flattening a semi-rigid cable or jacketing a flexible cable in order to restrict movement within the cable, successfully reduces the noise level by over an order of magnitude. Furthermore, we characterize the effect of the pulse tube vibrations on an electron spin qubit device in this setup. Coherence measurements are used to map out the spectrum of the noise experienced by the qubit, revealing spectral components matching the spectral signature of the pulse tube. This research was funded by the Australian Research Council (CE110001027) and the US Army Research Office (W911NF-13-1-0024).

The effect of classroom amplification on the signal-to-noise ratio in classrooms while class is in session.

PubMed

Larsen, Jeffery B; Blair, James C

2008-10-01

The purpose of this study was to measure the signal-to-noise ratios in classrooms while class was in session and students were interacting with the teacher and each other. Measurements of noise and reverberation were collected for 5 different classrooms in 3 different schools while class was in session. Activities taking place during the measurements were recorded to compare with sound level measures. The use of infrared classroom amplification was compared with no amplification. The results revealed that when classroom amplification was used, students heard the teacher's voice at a level that was an average of 13 dB above the noise floor as compared to an average of +2 dB above the noise floor without amplification.

Noise Gating Solar Images

NASA Astrophysics Data System (ADS)

DeForest, Craig; Seaton, Daniel B.; Darnell, John A.

2017-08-01

I present and demonstrate a new, general purpose post-processing technique, "3D noise gating", that can reduce image noise by an order of magnitude or more without effective loss of spatial or temporal resolution in typical solar applications.Nearly all scientific images are, ultimately, limited by noise. Noise can be direct Poisson "shot noise" from photon counting effects, or introduced by other means such as detector read noise. Noise is typically represented as a random variable (perhaps with location- or image-dependent characteristics) that is sampled once per pixel or once per resolution element of an image sequence. Noise limits many aspects of image analysis, including photometry, spatiotemporal resolution, feature identification, morphology extraction, and background modeling and separation.Identifying and separating noise from image signal is difficult. The common practice of blurring in space and/or time works because most image "signal" is concentrated in the low Fourier components of an image, while noise is evenly distributed. Blurring in space and/or time attenuates the high spatial and temporal frequencies, reducing noise at the expense of also attenuating image detail. Noise-gating exploits the same property -- "coherence" -- that we use to identify features in images, to separate image features from noise.Processing image sequences through 3-D noise gating results in spectacular (more than 10x) improvements in signal-to-noise ratio, while not blurring bright, resolved features in either space or time. This improves most types of image analysis, including feature identification, time sequence extraction, absolute and relative photometry (including differential emission measure analysis), feature tracking, computer vision, correlation tracking, background modeling, cross-scale analysis, visual display/presentation, and image compression.I will introduce noise gating, describe the method, and show examples from several instruments (including SDO

Extending the impulse response in order to reduce errors due to impulse noise and signal fading

NASA Technical Reports Server (NTRS)

Webb, Joseph A.; Rolls, Andrew J.; Sirisena, H. R.

1988-01-01

A finite impulse response (FIR) digital smearing filter was designed to produce maximum intersymbol interference and maximum extension of the impulse response of the signal in a noiseless binary channel. A matched FIR desmearing filter at the receiver then reduced the intersymbol interference to zero. Signal fades were simulated by means of 100 percent signal blockage in the channel. Smearing and desmearing filters of length 256, 512, and 1024 were used for these simulations. Results indicate that impulse response extension by means of bit smearing appears to be a useful technique for correcting errors due to impulse noise or signal fading in a binary channel.

Stochastic resonance in a piecewise nonlinear model driven by multiplicative non-Gaussian noise and additive white noise

NASA Astrophysics Data System (ADS)

Guo, Yongfeng; Shen, Yajun; Tan, Jianguo

2016-09-01

The phenomenon of stochastic resonance (SR) in a piecewise nonlinear model driven by a periodic signal and correlated noises for the cases of a multiplicative non-Gaussian noise and an additive Gaussian white noise is investigated. Applying the path integral approach, the unified colored noise approximation and the two-state model theory, the analytical expression of the signal-to-noise ratio (SNR) is derived. It is found that conventional stochastic resonance exists in this system. From numerical computations we obtain that: (i) As a function of the non-Gaussian noise intensity, the SNR is increased when the non-Gaussian noise deviation parameter q is increased. (ii) As a function of the Gaussian noise intensity, the SNR is decreased when q is increased. This demonstrates that the effect of the non-Gaussian noise on SNR is different from that of the Gaussian noise in this system. Moreover, we further discuss the effect of the correlation time of the non-Gaussian noise, cross-correlation strength, the amplitude and frequency of the periodic signal on SR.

Intrinsic low pass filtering improves signal-to-noise ratio in critical-point flexure biosensors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jain, Ankit; Alam, Muhammad Ashraful, E-mail: alam@purdue.edu

2014-08-25

A flexure biosensor consists of a suspended beam and a fixed bottom electrode. The adsorption of the target biomolecules on the beam changes its stiffness and results in change of beam's deflection. It is now well established that the sensitivity of sensor is maximized close to the pull-in instability point, where effective stiffness of the beam vanishes. The question: “Do the signal-to-noise ratio (SNR) and the limit-of-detection (LOD) also improve close to the instability point?”, however remains unanswered. In this article, we systematically analyze the noise response to evaluate SNR and establish LOD of critical-point flexure sensors. We find thatmore » a flexure sensor acts like an effective low pass filter close to the instability point due to its relatively small resonance frequency, and rejects high frequency noise, leading to improved SNR and LOD. We believe that our conclusions should establish the uniqueness and the technological relevance of critical-point biosensors.« less

Channel noise enhances signal detectability in a model of acoustic neuron through the stochastic resonance paradigm.

PubMed

Liberti, M; Paffi, A; Maggio, F; De Angelis, A; Apollonio, F; d'Inzeo, G

2009-01-01

A number of experimental investigations have evidenced the extraordinary sensitivity of neuronal cells to weak input stimulations, including electromagnetic (EM) fields. Moreover, it has been shown that biological noise, due to random channels gating, acts as a tuning factor in neuronal processing, according to the stochastic resonant (SR) paradigm. In this work the attention is focused on noise arising from the stochastic gating of ionic channels in a model of Ranvier node of acoustic fibers. The small number of channels gives rise to a high noise level, which is able to cause a spike train generation even in the absence of stimulations. A SR behavior has been observed in the model for the detection of sinusoidal signals at frequencies typical of the speech.

Airframe noise

NASA Astrophysics Data System (ADS)

Crighton, David G.

1991-08-01

Current understanding of airframe noise was reviewed as represented by experiment at model and full scale, by theoretical modeling, and by empirical correlation models. The principal component sources are associated with the trailing edges of wing and tail, deflected trailing edge flaps, flap side edges, leading edge flaps or slats, undercarriage gear elements, gear wheel wells, fuselage and wing boundary layers, and panel vibration, together with many minor protrusions like radio antennas and air conditioning intakes which may contribute significantly to perceived noise. There are also possibilities for interactions between the various mechanisms. With current engine technology, the principal airframe noise mechanisms dominate only at low frequencies, typically less than 1 kHz and often much lower, but further reduction of turbomachinery noise in particular may make airframe noise the principal element of approach noise at frequencies in the sensitive range.

Impact of physiological noise correction on detecting blood oxygenation level-dependent contrast in the breast

NASA Astrophysics Data System (ADS)

Wallace, Tess E.; Manavaki, Roido; Graves, Martin J.; Patterson, Andrew J.; Gilbert, Fiona J.

2017-01-01

Physiological fluctuations are expected to be a dominant source of noise in blood oxygenation level-dependent (BOLD) magnetic resonance imaging (MRI) experiments to assess tumour oxygenation and angiogenesis. This work investigates the impact of various physiological noise regressors: retrospective image correction (RETROICOR), heart rate (HR) and respiratory volume per unit time (RVT), on signal variance and the detection of BOLD contrast in the breast in response to a modulated respiratory stimulus. BOLD MRI was performed at 3 T in ten volunteers at rest and during cycles of oxygen and carbogen gas breathing. RETROICOR was optimized using F-tests to determine which cardiac and respiratory phase terms accounted for a significant amount of signal variance. A nested regression analysis was performed to assess the effect of RETROICOR, HR and RVT on the model fit residuals, temporal signal-to-noise ratio, and BOLD activation parameters. The optimized RETROICOR model accounted for the largest amount of signal variance ( Δ R\\text{adj}2   =  3.3  ±  2.1%) and improved the detection of BOLD activation (P  =  0.002). Inclusion of HR and RVT regressors explained additional signal variance, but had a negative impact on activation parameter estimation (P  <  0.001). Fluctuations in HR and RVT appeared to be correlated with the stimulus and may contribute to apparent BOLD signal reactivity.

Spin noise spectroscopy of ZnO

NASA Astrophysics Data System (ADS)

Horn, H.; Berski, F.; Balocchi, A.; Marie, X.; Mansur-Al-Suleiman, M.; Bakin, A.; Waag, A.; Hübner, J.; Oestreich, M.

2013-12-01

We investigate the thermal equilibrium dynamics of electron spins bound to donors in nanoporous ZnO by optical spin noise spectroscopy. The spin noise spectra reveal two noise contributions: A weak spin noise signal from undisturbed localized donor electrons with a dephasing time of 24 ns due to hyperfine interaction and a strong spin noise signal with a spin dephasing time of 5 ns which we attribute to localized donor electrons which interact with lattice defects.

Direct Signal-to-Noise Quality Comparison between an Electronic and Conventional Stethoscope aboard the International Space Station

NASA Technical Reports Server (NTRS)

Marshburn, Thomas; Cole, Richard; Ebert, Doug; Bauer, Pete

2014-01-01

Introduction: Evaluation of heart, lung, and bowel sounds is routinely performed with the use of a stethoscope to help detect a broad range of medical conditions. Stethoscope acquired information is even more valuable in a resource limited environments such as the International Space Station (ISS) where additional testing is not available. The high ambient noise level aboard the ISS poses a specific challenge to auscultation by stethoscope. An electronic stethoscope's ambient noise-reduction, greater sound amplification, recording capabilities, and sound visualization software may be an advantage to a conventional stethoscope in this environment. Methods: A single operator rated signal-to-noise quality from a conventional stethoscope (Littman 2218BE) and an electronic stethoscope (Litmann 3200). Borborygmi, pulmonic, and cardiac sound quality was ranked with both stethoscopes. Signal-to-noise rankings were preformed on a 1 to 10 subjective scale with 1 being inaudible, 6 the expected quality in an emergency department, 8 the expected quality in a clinic, and 10 the clearest possible quality. Testing took place in the Japanese Pressurized Module (JPM), Unity (Node 2), Destiny (US Lab), Tranquility (Node 3), and the Cupola of the International Space Station. All examinations were conducted at a single point in time. Results: The electronic stethoscope's performance ranked higher than the conventional stethoscope for each body sound in all modules tested. The electronic stethoscope's sound quality was rated between 7 and 10 in all modules tested. In comparison, the traditional stethoscope's sound quality was rated between 4 and 7. The signal to noise ratio of borborygmi showed the biggest difference between stethoscopes. In the modules tested, the auscultation of borborygmi was rated between 5 and 7 by the conventional stethoscope and consistently 10 by the electronic stethoscope. Discussion: This stethoscope comparison was limited to a single operator. However, we

Influence of signals length and noise in power spectral densities computation using Hilbert-Huang Transform in synthetic HRV

NASA Astrophysics Data System (ADS)

Rodríguez, María. G.; Altuve, Miguel; Lollett, Carlos; Wong, Sara

2013-11-01

Among non-invasive techniques, heart rate variability (HRV) analysis has become widely used for assessing the balance of the autonomic nervous system. Research in this area has not stopped and alternative tools for the study and interpretation of HRV, are still being proposed. Nevertheless, frequency-domain analysis of HRV is controversial when the heartbeat sequence is non-stationary. The Hilbert-Huang Transform (HHT) is a relative new technique for timefrequency analyses of non-linear and non-stationary signals. The main purpose of this work is to investigate the influence of time serieś length and noise in HRV from synthetic signals, using HHT and to compare it with Welch method. Synthetic heartbeat time series with different sizes and levels of signal to noise ratio (SNR) were investigated. Results shows i) sequencés length did not affect the estimation of HRV spectral parameter, ii) favorable performance for HHT for different SNR. Additionally, HHT can be applied to non-stationary signals from nonlinear systems and it will be useful to HRV analysis to interpret autonomic activity when acute and transient phenomena are assessed.

Signal-to-noise contribution of principal component loads in reconstructed near-infrared Raman tissue spectra.

PubMed

Grimbergen, M C M; van Swol, C F P; Kendall, C; Verdaasdonk, R M; Stone, N; Bosch, J L H R

2010-01-01

The overall quality of Raman spectra in the near-infrared region, where biological samples are often studied, has benefited from various improvements to optical instrumentation over the past decade. However, obtaining ample spectral quality for analysis is still challenging due to device requirements and short integration times required for (in vivo) clinical applications of Raman spectroscopy. Multivariate analytical methods, such as principal component analysis (PCA) and linear discriminant analysis (LDA), are routinely applied to Raman spectral datasets to develop classification models. Data compression is necessary prior to discriminant analysis to prevent or decrease the degree of over-fitting. The logical threshold for the selection of principal components (PCs) to be used in discriminant analysis is likely to be at a point before the PCs begin to introduce equivalent signal and noise and, hence, include no additional value. Assessment of the signal-to-noise ratio (SNR) at a certain peak or over a specific spectral region will depend on the sample measured. Therefore, the mean SNR over the whole spectral region (SNR(msr)) is determined in the original spectrum as well as for spectra reconstructed from an increasing number of principal components. This paper introduces a method of assessing the influence of signal and noise from individual PC loads and indicates a method of selection of PCs for LDA. To evaluate this method, two data sets with different SNRs were used. The sets were obtained with the same Raman system and the same measurement parameters on bladder tissue collected during white light cystoscopy (set A) and fluorescence-guided cystoscopy (set B). This method shows that the mean SNR over the spectral range in the original Raman spectra of these two data sets is related to the signal and noise contribution of principal component loads. The difference in mean SNR over the spectral range can also be appreciated since fewer principal components can

Estimation of signal-dependent noise level function in transform domain via a sparse recovery model.

PubMed

Yang, Jingyu; Gan, Ziqiao; Wu, Zhaoyang; Hou, Chunping

2015-05-01

This paper proposes a novel algorithm to estimate the noise level function (NLF) of signal-dependent noise (SDN) from a single image based on the sparse representation of NLFs. Noise level samples are estimated from the high-frequency discrete cosine transform (DCT) coefficients of nonlocal-grouped low-variation image patches. Then, an NLF recovery model based on the sparse representation of NLFs under a trained basis is constructed to recover NLF from the incomplete noise level samples. Confidence levels of the NLF samples are incorporated into the proposed model to promote reliable samples and weaken unreliable ones. We investigate the behavior of the estimation performance with respect to the block size, sampling rate, and confidence weighting. Simulation results on synthetic noisy images show that our method outperforms existing state-of-the-art schemes. The proposed method is evaluated on real noisy images captured by three types of commodity imaging devices, and shows consistently excellent SDN estimation performance. The estimated NLFs are incorporated into two well-known denoising schemes, nonlocal means and BM3D, and show significant improvements in denoising SDN-polluted images.

A laboratory study of the subjective response to helicopter blade-slap noise

NASA Technical Reports Server (NTRS)

Shepherd, K. P.

1978-01-01

The test stimuli recorded during a recent field study consisted of 16 sounds, each presented at 4 peak noise levels. Two helicopters and a fixed-wing aircraft were used. The impulsive characteristics of one helicopter were varied by operating at different rotor speeds, whereas the other helicopter, the noise of which was dominated by the tail rotor, displayed little variation in blade-slap noise. Thirty-two subjects made noisiness judgments on a continuous, 11 point, numerical scale. Preliminary results indicate that proposed impulsiveness corrections provide no significant improvement in the noisiness predictive ability of Effective Perceived Noise Levels (EPNL). For equal EPNL, the two categories of helicopter stimuli, one of which was far more impulsive than the other, showed no difference in judged noisiness. Examination of the physical characteristics of the sounds presented in the laboratory highlighted the difficulty of reproducing acoustical signals with high-crest factors.

Photoswitching Near-Infrared Fluorescence from Polymer Nanoparticles Catapults Signals over the Region of Noises and Interferences for Enhanced Sensitivity.

PubMed

Wang, Jie; Lv, Yanlin; Wan, Wei; Wang, Xuefei; Li, Alexander D Q; Tian, Zhiyuan

2016-02-01

As a very sensitive technique, photoswitchable fluorescence not only gains ultrasensitivity but also imparts many novel and unexpected applications. Applications of near-infrared (NIR) fluorescence have demonstrated low background noises, high tissue-penetrating ability, and an ability to reduce photodamage to live cells. Because of these desired features, NIR-fluorescent dyes have been the premium among fluorescent dyes, and probes with photoswitchable NIR fluorescence are even more desirable for enhanced signal quality in the emerging optical imaging modalities but rarely used because they are extremely challenging to design and construct. Using a spiropyran derivative functioning as both a photoswitch and a fluorophore to launch its periodically modulated red fluorescence excitation energy into a NIR acceptor, we fabricated core-shell polymer nanoparticles exhibiting a photoswitchable fluorescence signal within the biological window (∼700-1000 nm) with a peak maximum of 776 nm. Live cells constantly synthesize new molecules, including fluorescent molecules, and also endocytose exogenous particles, including fluorescent particles. Upon excitation at different wavelengths, these fluorescent species bring about background noises and interferences covering nearly the whole visible region and therefore render many intracellular targets unaddressable. The oscillating NIR fluorescence signal with an on/off ratio of up to 67 that the polymer nanoparticles display is beyond the typical background noises and interferences, thus producing superior sharpness, reliability, and signal-to-noise ratios in cellular imaging. Taking these salient features, we anticipate that these types of nanoparticles will be useful for in vivo imaging of biological tissue and other complex specimens, where two-photon activation and excitation are used in combination with NIR-fluorescence photoswitching.

The threshold signal:noise ratio in the perception of fragmented figures.

PubMed

Merkul'ev, A V; Pronin, S V; Semenov, L A; Foreman, N; Chikhman, V N; Shelepin, Yu E

2006-01-01

Perception thresholds were measured for fragmented outline figures (the Gollin test). A new approach to the question of the perception of incomplete images was developed. In this approach, figure fragmentation consisted of masking with multiplicative texture-like noise--this interference was termed "invisible" masking. The first series of studies established that the "similarity" between the amplitude-frequency spectra of test figures and "invisible" masks, expressed as a linear correlation coefficient, had significant effects on the recognition thresholds of these figures. The second series of experiments showed that progressing formation of the figures was accompanied by increases in the correlation between their spatial-frequency characteristics and the corresponding characteristics of the incomplete figure, while the correlation with the "invisible" mask decreased. It is suggested that the ratio of the correlation coefficients, characterizing the "similarity" of the fragmented figure with the intact figure and the "invisible" mask, corresponds to the signal:noise ratio. The psychophysical recognition threshold for figures for naive subjects not familiar with the test image alphabet was reached after the particular level of fragmentation at which this ratio was unity.

On measurement noise in the European TWSTFT network.

PubMed

Piester, Dirk; Bauch, Andreas; Becker, Jürgen; Staliuniene, Egle; Schlunegger, Christian

2008-09-01

Two-way satellite time and frequency transfer (TWSTFT) using geostationary telecommunication satellites is widely used in the timing community today and has also been chosen as the primary means to effect synchronization of elements of the ground segment of the European satellite navigation system Galileo. We investigated the link performance in a multistation network based on operational parameters such as the number of simultaneously transmitting stations, transmit and receive power, and chip rates of the pseudorandom noise modulation of the transmitted signals. Our work revealed that TWSTFT through a "quiet" transponder channel (2 stations transmitting only) leads to a measurement noise, expressed by the 1 pps jitter, reduced by a factor of 1.4 compared with a busy transponder carrying signals of 12 stations. The frequency transfer capability expressed by the Allan deviation is reduced at short averaging times by the same amount. At averaging times of >1 d, no such reduction could be observed, which points to the fact that other noise sources dominate at such averaging times. We also found that higher transmit power increases the carrier-to-noise density ratio at the receive station and thus entails lower jitter but causes interference with other station's signals. In addition, the use of lower chip rates, which could be accommodated by a reduced assigned bandwidth on the satellite transponder, is not recommended. The 1 pps jitter would go up by a factor of 2.5 when going from 2.5 MCh/s to 1 MCh/s. The 2 Galileo precise timing facilities (PTFs) can be included in the currently operated network of 12 stations in Europe and all requirements on the TWSTFT performance can be met, provided that suitable ground equipment will be installed in the Galileo ground segment.

Approximations to camera sensor noise

NASA Astrophysics Data System (ADS)

Jin, Xiaodan; Hirakawa, Keigo

2013-02-01

Noise is present in all image sensor data. Poisson distribution is said to model the stochastic nature of the photon arrival process, while it is common to approximate readout/thermal noise by additive white Gaussian noise (AWGN). Other sources of signal-dependent noise such as Fano and quantization also contribute to the overall noise profile. Question remains, however, about how best to model the combined sensor noise. Though additive Gaussian noise with signal-dependent noise variance (SD-AWGN) and Poisson corruption are two widely used models to approximate the actual sensor noise distribution, the justification given to these types of models are based on limited evidence. The goal of this paper is to provide a more comprehensive characterization of random noise. We concluded by presenting concrete evidence that Poisson model is a better approximation to real camera model than SD-AWGN. We suggest further modification to Poisson that may improve the noise model.

A Noise Removal Method for Uniform Circular Arrays in Complex Underwater Noise Environments with Low SNR

PubMed Central

Xia, Huijun; Yang, Kunde; Ma, Yuanliang; Wang, Yong; Liu, Yaxiong

2017-01-01

Generally, many beamforming methods are derived under the assumption of white noise. In practice, the actual underwater ambient noise is complex. As a result, the noise removal capacity of the beamforming method may be deteriorated considerably. Furthermore, in underwater environment with extremely low signal-to-noise ratio (SNR), the performances of the beamforming method may be deteriorated. To tackle these problems, a noise removal method for uniform circular array (UCA) is proposed to remove the received noise and improve the SNR in complex noise environments with low SNR. First, the symmetrical noise sources are defined and the spatial correlation of the symmetrical noise sources is calculated. Then, based on the preceding results, the noise covariance matrix is decomposed into symmetrical and asymmetrical components. Analysis indicates that the symmetrical component only affect the real part of the noise covariance matrix. Consequently, the delay-and-sum (DAS) beamforming is performed by using the imaginary part of the covariance matrix to remove the symmetrical component. However, the noise removal method causes two problems. First, the proposed method produces a false target. Second, the proposed method would seriously suppress the signal when it is located in some directions. To solve the first problem, two methods to reconstruct the signal covariance matrix are presented: based on the estimation of signal variance and based on the constrained optimization algorithm. To solve the second problem, we can design the array configuration and select the suitable working frequency. Theoretical analysis and experimental results are included to demonstrate that the proposed methods are particularly effective in complex noise environments with low SNR. The proposed method can be extended to any array. PMID:28598386

Magnetotellurics with long distance remote reference to reject DC railway noise