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.
Ultimate capacity of linear time-invariant bosonic channels with additive Gaussian noise
NASA Astrophysics Data System (ADS)
Roy Bardhan, Bhaskar; Shapiro, Jeffrey H.
2016-03-01
Fiber-optic communications are moving to coherent detection in order to increase their spectral efficiency, i.e., their channel capacity per unit bandwidth. At power levels below the threshold for significant nonlinear effects, the channel model for such operation a linear time-invariant filter followed by additive Gaussian noise is one whose channel capacity is well known from Shannon's noisy channel coding theorem. The fiber channel, however, is really a bosonic channel, meaning that its ultimate classical information capacity must be determined from quantum-mechanical analysis, viz. from the Holevo-Schumacher-Westmoreland (HSW) theorem. Based on recent results establishing the HSW capacity of a linear (lossy or amplifying) channel with additive Gaussian noise, we provide a general continuous-time result, namely the HSW capacity of a linear time-invariant (LTI) bosonic channel with additive Gaussian noise arising from a thermal environment. In particular, we treat quasi-monochromatic communication under an average power constraint through a channel comprised of a stable LTI filter that may be attenuating at all frequencies or amplifying at some frequencies and attenuating at others. Phase-insensitive additive Gaussian noise-associated with the continuous-time Langevin noise operator needed to preserve free-field commutator brackets is included at the filter output. We compare the resulting spectral efficiencies with corresponding results for heterodyne and homodyne detection over the same channel to assess the increased spectral efficiency that might be realized with optimum quantum reception.
Additive non-Gaussian noise attacks on the scalar Costa scheme (SCS)
NASA Astrophysics Data System (ADS)
Tzschoppe, Roman; Bauml, Robert; Fischer, Robert; Huber, Johannes; Kaup, Andre
2005-03-01
The additive attack public mutual information game is explicitly solved for one of the simplest quantization based watermarking schemes, the scalar Costa scheme (SCS). It is a zero-sum game played between the embedder and the attacker, and the payoff function is the mutual information. The solution of the game, a subgame perfect nash equilibrium, is found by backward induction. Therefore, the Blahut-Arimoto algorithm is employed for numerically optimizing the mutual information over noise distributions. Although the worst case distribution is in general strongly non-Gaussian, the capacity degradation compared to a suboptimal Gaussian noise attack is quite small. The loss, if the embedder optimizes SCS for a Gaussian attack but the worst case attack is employed, is negligible.
On estimating the phase of periodic waveform in additive Gaussian noise, part 2
NASA Astrophysics Data System (ADS)
Rauch, L. L.
1984-11-01
Motivated by advances in signal processing technology that support more complex algorithms, a new look is taken at the problem of estimating the phase and other parameters of a periodic waveform in additive Gaussian noise. The general problem was introduced and the maximum a posteriori probability criterion with signal space interpretation was used to obtain the structures of optimum and some suboptimum phase estimators for known constant frequency and unknown constant phase with an a priori distribution. Optimal algorithms are obtained for some cases where the frequency is a parameterized function of time with the unknown parameters and phase having a joint a priori distribution. In the last section, the intrinsic and extrinsic geometry of hypersurfaces is introduced to provide insight to the estimation problem for the small noise and large noise cases.
NASA Technical Reports Server (NTRS)
Painter, J. H.; Gupta, S. C.
1973-01-01
This paper presents the derivation of the recursive algorithms necessary for real-time digital detection of M-ary known signals that are subject to independent multiplicative and additive Gaussian noises. The motivating application is minimum probability of error detection of digital data-link messages aboard civil aircraft in the earth reflection multipath environment. For each known signal, the detector contains one Kalman filter and one probability computer. The filters estimate the multipath disturbance. The estimates and the received signal drive the probability computers. Outputs of all the computers are compared in amplitude to give the signal decision. The practicality and usefulness of the detector are extensively discussed.
Performance of peaky template matching under additive white Gaussian noise and uniform quantization
NASA Astrophysics Data System (ADS)
Horvath, Matthew S.; Rigling, Brian D.
2015-05-01
Peaky template matching (PTM) is a special case of a general algorithm known as multinomial pattern matching originally developed for automatic target recognition of synthetic aperture radar data. The algorithm is a model- based approach that first quantizes pixel values into Nq = 2 discrete values yielding generative Beta-Bernoulli models as class-conditional templates. Here, we consider the case of classification of target chips in AWGN and develop approximations to image-to-template classification performance as a function of the noise power. We focus specifically on the case of a uniform quantization" scheme, where a fixed number of the largest pixels are quantized high as opposed to using a fixed threshold. This quantization method reduces sensitivity to the scaling of pixel intensities and quantization in general reduces sensitivity to various nuisance parameters difficult to account for a priori. Our performance expressions are verified using forward-looking infrared imagery from the Army Research Laboratory Comanche dataset.
The properties of the anti-tumor model with coupling non-Gaussian noise and Gaussian colored noise
NASA Astrophysics Data System (ADS)
Guo, Qin; Sun, Zhongkui; Xu, Wei
2016-05-01
The anti-tumor model with correlation between multiplicative non-Gaussian noise and additive Gaussian-colored noise has been investigated in this paper. The behaviors of the stationary probability distribution demonstrate that the multiplicative non-Gaussian noise plays a dual role in the development of tumor and an appropriate additive Gaussian colored noise can lead to a minimum of the mean value of tumor cell population. The mean first passage time is calculated to quantify the effects of noises on the transition time of tumors between the stable states. An increase in both the non-Gaussian noise intensity and the departure from the Gaussian noise can accelerate the transition from the disease state to the healthy state. On the contrary, an increase in cross-correlated degree will slow down the transition. Moreover, the correlation time can enhance the stability of the disease state.
NASA Astrophysics Data System (ADS)
Hamdi, Mazda; Kenari, Masoumeh Nasiri
2013-06-01
We consider a time-hopping based multiple access scheme introduced in [1] for communication over dispersive infrared links, and evaluate its performance for correlator and matched filter receivers. In the investigated time-hopping code division multiple access (TH-CDMA) method, the transmitter benefits a low rate convolutional encoder. In this method, the bit interval is divided into Nc chips and the output of the encoder along with a PN sequence assigned to the user determines the position of the chip in which the optical pulse is transmitted. We evaluate the multiple access performance of the system for correlation receiver considering background noise which is modeled as White Gaussian noise due to its large intensity. For the correlation receiver, the results show that for a fixed processing gain, at high transmit power, where the multiple access interference has the dominant effect, the performance improves by the coding gain. But at low transmit power, in which the increase of coding gain leads to the decrease of the chip time, and consequently, to more corruption due to the channel dispersion, there exists an optimum value for the coding gain. However, for the matched filter, the performance always improves by the coding gain. The results show that the matched filter receiver outperforms the correlation receiver in the considered cases. Our results show that, for the same bandwidth and bit rate, the proposed system excels other multiple access techniques, like conventional CDMA and time hopping scheme.
NASA Astrophysics Data System (ADS)
Kleine, Achim
Models were developed to investigate the tracking behavior of combined Costas/AFC (Automatic Frequency Control) feedback loops under Rayleigh/Rician fading conditions with additive Gaussian noise jamming. A general linearized tracking model was developed for land-mobile channels. The model can be used for the nonlinearized case with sinusoidal phase detection characteristic using a standard solution of the Fokker-Planck equation. A tracking analysis for Costas/AFC loops with coherent automatic gain control, and an accuracy analysis for interferometers equipped with Costas/AFC loops are treated as examples. The tracking model is the most inaccurate in the case of quasistationary channels.
NASA Astrophysics Data System (ADS)
Ranjha, Bilal; Zhou, Zhou; Kavehrad, Mohsen
2014-08-01
We have compared the bit error rate (BER) performance of precoding-based asymmetrically clipped optical orthogonal frequency division multiplexing (ACO-OFDM) and pulse amplitude modulated discrete multitone (PAM-DMT) optical wireless (OW) systems in additive white Gaussian noise (AWGN) and indoor multipath frequency selective channel. Simulation and analytical results show that precoding schemes such as discrete Fourier transform, discrete cosine transform, and Zadoff-Chu sequences do not affect the performance of the OW systems in the AWGN channel while they do reduce the peak-to-average power ratio (PAPR) of the OFDM output signal. However, in a multipath indoor channel, using zero forcing frequency domain equalization precoding-based systems give better BER performance than their conventional counterparts. With additional clipping to further reduce the PAPR, precoding-based systems also show better BER performance compared to nonprecoded systems when clipped relative to the peak of nonprecoded systems. Therefore, precoding-based ACO-OFDM and PAM-DMT systems offer better BER performance, zero signaling overhead, and low PAPR compared to conventional systems.
A Gaussian measure of quantum phase noise
NASA Technical Reports Server (NTRS)
Schleich, Wolfgang P.; Dowling, Jonathan P.
1992-01-01
We study the width of the semiclassical phase distribution of a quantum state in its dependence on the average number of photons (m) in this state. As a measure of phase noise, we choose the width, delta phi, of the best Gaussian approximation to the dominant peak of this probability curve. For a coherent state, this width decreases with the square root of (m), whereas for a truncated phase state it decreases linearly with increasing (m). For an optimal phase state, delta phi decreases exponentially but so does the area caught underneath the peak: all the probability is stored in the broad wings of the distribution.
Characterization of non-Gaussianity in gravitational wave detector noise
NASA Astrophysics Data System (ADS)
Yamamoto, Takahiro; Hayama, Kazuhiro; Mano, Shuhei; Itoh, Yousuke; Kanda, Nobuyuki
2016-04-01
The first detection of a gravitational wave (GW) has been achieved by two detectors of the advanced LIGO. Routine detections of GW events from various GW sources are expected in the coming decades. Although the first signal was statistically significant, we expect to see numerous low signal-to-noise ratio (SNR) events with which we may be able to learn various aspects of the Universe that have yet to be unveiled. On the other hand, instrumental glitches due to nonstationarity and/or a non-Gaussian tail of detector noise distribution prevent us from confidently identifying true but low SNR GW signals out of instrumental noise. Thus, to make the best use of data from GW detectors, it is important to establish a method to safely distinguish true GW signals from false signals due to instrumental noises. For this purpose, we urgently need to understand characteristics of detector noises, since the nonstationarity and non-Gaussianity inherent in detector outputs are known to increase false detections of signals. Focusing on identifying the non-Gaussian noise components, this paper introduces a new measure for characterizing the non-Gaussian noise components using the parameter ν which characterizes the weight of tail in a Student-t distribution. A confidence interval is reported on the extent to which detector noise deviates from Gaussianity. Our method revealed stationary and transient deterioration of Gaussianity in LIGO S5 data.
Measuring Gaussian noise using a lock-in amplifier
NASA Astrophysics Data System (ADS)
Kouh, T.; Kemiktarak, U.; Basarir, O.; Lissandrello, C.; Ekinci, K. L.
2014-08-01
Gaussian fluctuations (or Gaussian noise) appear in almost all measurements in physics. Here, a concise and self-contained introduction to thermal Gaussian noise is presented. Our analysis in the frequency domain centers on thermal fluctuations of the position of a particle bound in a one-dimensional harmonic potential, which in this case is a microcantilever immersed in a bath of room-temperature gas. Position fluctuations of the microcantilever, detected by the optical beam deflection technique, are then fed into a lock-in amplifier to measure the probability distribution and spectral properties of the fluctuations. The lock-in amplifier measurement is designed to emphasize the frequency-domain properties of Gaussian noise. The discussion here can be complementary to a discussion of Gaussian fluctuations in the time domain.
Theory of Mesoscopic Threshold Detectors of non-Gaussian Noise
NASA Astrophysics Data System (ADS)
Jordan, Andrew
2009-03-01
Recently, measurements of current fluctuations arising from the charge discreteness (shot noise) have become an invaluable tool in mesoscopic physics, the most noticeable achievement being the measurement of quasi-particle charge in the fractional quantum Hall state. Typically, shot noise experiments report measurements of the zero-frequency noise power, which is a characteristic of the Gaussian component of current fluctuations. A natural generalization of the noise power, the counting statistics of charge transmitted through a system, is interesting in itself, because it contains complete information about the electron transport on a long time scale. However, the measurement of non-Gaussian noise effects presents an experimental challenge because of the limitations imposed by the central limit theorem. This difficulty can be partly overcome by placing an auxiliary mesoscopic system (detector) very close to the noise source and arranging strong coupling to the noise. This leads to the idea of a threshold detector, which is able to measure rare current fluctuations. Its basic principle is analogous to a pole vault: A detection event occurs when the measured system variable exceeds a given threshold value. A natural candidate for such a threshold detector is a metastable system operating on an activation principle. By measuring the rate of switching out of the metastable state, information about the statistical properties of the noise driving the system may be extracted. This requires solving the Kramers' problem of noise-activated escape from a metastable state beyond the Gaussian noise approximation and investigating how the measurement circuit affects threshold detection.
Continuous-variable quantum key distribution with Gaussian source noise
Shen Yujie; Peng Xiang; Yang Jian; Guo Hong
2011-05-15
Source noise affects the security of continuous-variable quantum key distribution (CV QKD) and is difficult to analyze. We propose a model to characterize Gaussian source noise through introducing a neutral party (Fred) who induces the noise with a general unitary transformation. Without knowing Fred's exact state, we derive the security bounds for both reverse and direct reconciliations and show that the bound for reverse reconciliation is tight.
Making tensor factorizations robust to non-gaussian noise.
Chi, Eric C.; Kolda, Tamara Gibson
2011-03-01
Tensors are multi-way arrays, and the CANDECOMP/PARAFAC (CP) tensor factorization has found application in many different domains. The CP model is typically fit using a least squares objective function, which is a maximum likelihood estimate under the assumption of independent and identically distributed (i.i.d.) Gaussian noise. We demonstrate that this loss function can be highly sensitive to non-Gaussian noise. Therefore, we propose a loss function based on the 1-norm because it can accommodate both Gaussian and grossly non-Gaussian perturbations. We also present an alternating majorization-minimization (MM) algorithm for fitting a CP model using our proposed loss function (CPAL1) and compare its performance to the workhorse algorithm for fitting CP models, CP alternating least squares (CPALS).
Oscillator strength of impurity doped quantum dots: Influence of Gaussian white noise
NASA Astrophysics Data System (ADS)
Pal, Suvajit; Ganguly, Jayanta; Saha, Surajit; Ghosh, Manas
2015-10-01
We make a rigorous analysis of profiles of oscillator strength of a doped quantum dot in the presence and absence of noise. The noise employed here is a Gaussian white noise. The quantum dot is doped with repulsive Gaussian impurity. Noise has been administered additively and multiplicatively to the system. A perpendicular magnetic field is also present and a static external electric field has been applied. Profile of OS has been minutely monitored with variation of several important quantities such as confinement energy, electric field strength, dopant location, magnetic field strength, dopant potential, noise strength, Al concentration, and mode of application of noise. The profiles are enriched with significant subtleties and often reveal enhancement and maximization of oscillator strength in the presence of noise. These observations are indeed useful in the study of linear and nonlinear optical properties of doped QD systems which bear sufficient technological importance.
Ballistic diffusion induced by non-Gaussian noise
NASA Astrophysics Data System (ADS)
Qin, Li; Li, Qiang
2013-03-01
In this letter, we have analyzed the diffusive behavior of a Brownian particle subject to both internal Gaussian thermal and external non-Gaussian noise sources. We discuss two time correlation functions C(t) of the non-Gaussian stochastic process, and find that they depend on the parameter q, indicating the departure of the non-Gaussian noise from Gaussian behavior: for q <= 1, C(t) is fitted very well by the first-order exponentially decaying curve and approaches zero in the long-time limit, whereas for q > 1, C(t) can be approximated by a second-order exponentially decaying function and converges to a non-zero constant. Due to the properties of C(t), the particle exhibits a normal diffusion for q <= 1, while for q > 1 the non-Gaussian noise induces a ballistic diffusion, i.e., the long-time mean square displacement of the free particle reads <[x(t) -
Qubit Noise Spectroscopy for Non-Gaussian Dephasing Environments
NASA Astrophysics Data System (ADS)
Norris, Leigh M.; Paz-Silva, Gerardo A.; Viola, Lorenza
2016-04-01
We introduce open-loop quantum control protocols for characterizing the spectral properties of non-Gaussian noise, applicable to both classical and quantum dephasing environments. By engineering a multidimensional frequency comb via repetition of suitably designed pulse sequences, the desired high-order spectra may be related to observable properties of the qubit probe. We prove that access to a high time resolution is key to achieving spectral reconstruction over an extended bandwidth, overcoming the limitations of existing schemes. Non-Gaussian spectroscopy is demonstrated for a classical noise model describing quadratic dephasing at an optimal point, as well as a quantum spin-boson model out of equilibrium. In both cases, we obtain spectral reconstructions that accurately predict the qubit dynamics in the non-Gaussian regime.
Qubit Noise Spectroscopy for Non-Gaussian Dephasing Environments.
Norris, Leigh M; Paz-Silva, Gerardo A; Viola, Lorenza
2016-04-15
We introduce open-loop quantum control protocols for characterizing the spectral properties of non-Gaussian noise, applicable to both classical and quantum dephasing environments. By engineering a multidimensional frequency comb via repetition of suitably designed pulse sequences, the desired high-order spectra may be related to observable properties of the qubit probe. We prove that access to a high time resolution is key to achieving spectral reconstruction over an extended bandwidth, overcoming the limitations of existing schemes. Non-Gaussian spectroscopy is demonstrated for a classical noise model describing quadratic dephasing at an optimal point, as well as a quantum spin-boson model out of equilibrium. In both cases, we obtain spectral reconstructions that accurately predict the qubit dynamics in the non-Gaussian regime. PMID:27127947
Stochastic Schroedinger equations with general complex Gaussian noises
Bassi, Angelo
2003-06-01
Within the framework of non-Markovian stochastic Schroedinger equations, we generalize the results of [W. T. Strunz, Phys. Lett. A 224, 25 (1996)] to the case of general complex Gaussian noises; we analyze the two important cases of purely real and purely imaginary stochastic processes.
Cochlear toughening, protection, and potentiation of noise-induced trauma by non-Gaussian noise
NASA Astrophysics Data System (ADS)
Hamernik, Roger P.; Qiu, Wei; Davis, Bob
2003-02-01
An interrupted noise exposure of sufficient intensity, presented on a daily repeating cycle, produces a threshold shift (TS) following the first day of exposure. TSs measured on subsequent days of the exposure sequence have been shown to decrease relative to the initial TS. This reduction of TS, despite the continuing daily exposure regime, has been called a cochlear toughening effect and the exposures referred to as toughening exposures. Four groups of chinchillas were exposed to one of four different noises presented on an interrupted (6 h/day for 20 days) or noninterrupted (24 h/day for 5 days) schedule. The exposures had equivalent total energy, an overall level of 100 dB(A) SPL, and approximately the same flat, broadband long-term spectrum. The noises differed primarily in their temporal structures; two were Gaussian and two were non-Gausssian, nonstationary. Brainstem auditory evoked potentials were used to estimate hearing thresholds and surface preparation histology was used to determine sensory cell loss. The experimental results presented here show that: (1) Exposures to interrupted high-level, non-Gaussian signals produce a toughening effect comparable to that produced by an equivalent interrupted Gaussian noise. (2) Toughening, whether produced by Gaussian or non-Gaussian noise, results in reduced trauma compared to the equivalent uninterrupted noise, and (3) that both continuous and interrupted non-Gaussian exposures produce more trauma than do energy and spectrally equivalent Gaussian noises. Over the course of the 20-day exposure, the pattern of TS following each day's exposure could exhibit a variety of configurations. These results do not support the equal energy hypothesis as a unifying principal for estimating the potential of a noise exposure to produce hearing loss.
Masking and scrambling in the auditory thalamus of awake rats by Gaussian and modulated noises.
Martin, Eugene M; West, Morris F; Bedenbaugh, Purvis H
2004-10-12
This paper provides a look at how modulated broad-band noises modulate the thalamic response evoked by brief probe sounds in the awake animal. We demonstrate that noise not only attenuates the response to probe sounds (masking) but also changes the temporal response pattern (scrambling). Two brief probe sounds, a Gaussian noise burst and a brief sinusoidal tone, were presented in silence and in three ongoing noises. The three noises were targeted at activating the auditory system in qualitatively distinct ways. Dynamic ripple noise, containing many random tone-like elements, is targeted at those parts of the auditory system that respond well to tones. International Collegium of Rehabilitative Audiology noise, comprised of the sum of several simultaneous streams of Schroeder-phase speech, is targeted at those parts of the auditory system that respond well to modulated sounds but lack a well defined response to tones. Gaussian noise is targeted at those parts of the auditory system that respond to acoustic energy regardless of modulation. All noises both attenuated and decreased the precise temporal repeatability of the onset response to probe sounds. In addition, the modulated noises induced context-specific changes in the temporal pattern of the response to probe sounds. Scrambling of the temporal response pattern may be a direct neural correlate of the unfortunate experience of being able to hear, but not understand, speech sounds in noisy environments. PMID:15452349
Nonlinear Bayesian estimation of BOLD signal under non-Gaussian noise.
Khan, Ali Fahim; Younis, Muhammad Shahzad; Bajwa, Khalid Bashir
2015-01-01
Modeling the blood oxygenation level dependent (BOLD) signal has been a subject of study for over a decade in the neuroimaging community. Inspired from fluid dynamics, the hemodynamic model provides a plausible yet convincing interpretation of the BOLD signal by amalgamating effects of dynamic physiological changes in blood oxygenation, cerebral blood flow and volume. The nonautonomous, nonlinear set of differential equations of the hemodynamic model constitutes the process model while the weighted nonlinear sum of the physiological variables forms the measurement model. Plagued by various noise sources, the time series fMRI measurement data is mostly assumed to be affected by additive Gaussian noise. Though more feasible, the assumption may cause the designed filter to perform poorly if made to work under non-Gaussian environment. In this paper, we present a data assimilation scheme that assumes additive non-Gaussian noise, namely, the e-mixture noise, affecting the measurements. The proposed filter MAGSF and the celebrated EKF are put to test by performing joint optimal Bayesian filtering to estimate both the states and parameters governing the hemodynamic model under non-Gaussian environment. Analyses using both the synthetic and real data reveal superior performance of the MAGSF as compared to EKF. PMID:25691911
Gaussian white noise analysis and its application to Feynman path integral
NASA Astrophysics Data System (ADS)
Suryawan, Herry Pribawanto
2016-02-01
In applied science, Gaussian white noise (the time derivative of Brownian motion) is often chosen as a mathematical idealization of phenomena involving sudden and extremely large fluctuations. It is also possible to define and study Gaussian white noise in a mathematically rigorous framework. In this survey paper we review the Gaussian white noise as an object in an infinite dimensional topological vector space. A brief construction of Gaussian white noise space and Gaussian white noise distributions will be presented. Gaussian white noise analysis provides a framework which offers various generalization of concept known from finite dimensional analysis to the infinite dimensional case, among them are differential operators, Fourier transform, and distribution theory. We will also present some recent developments and results on the application of Gaussian white noise theory to Feynman's path integral approach for quantum mechanics.
NASA Astrophysics Data System (ADS)
Basin, M.; Maldonado, J. J.; Zendejo, O.
2016-07-01
This paper proposes new mean-square filter and parameter estimator design for linear stochastic systems with unknown parameters over linear observations, where unknown parameters are considered as combinations of Gaussian and Poisson white noises. The problem is treated by reducing the original problem to a filtering problem for an extended state vector that includes parameters as additional states, modelled as combinations of independent Gaussian and Poisson processes. The solution to this filtering problem is based on the mean-square filtering equations for incompletely polynomial states confused with Gaussian and Poisson noises over linear observations. The resulting mean-square filter serves as an identifier for the unknown parameters. Finally, a simulation example shows effectiveness of the proposed mean-square filter and parameter estimator.
Exploring electro-optic effect of impurity doped quantum dots in presence of Gaussian white noise
NASA Astrophysics Data System (ADS)
Pal, Suvajit; Ganguly, Jayanta; Saha, Surajit; Ghosh, Manas
2016-01-01
We explore the profiles of electro-optic effect (EOE) of impurity doped quantum dots (QDs) in presence and absence of noise. We have invoked Gaussian white noise in the present study. The quantum dot is doped with Gaussian impurity. Noise has been administered to the system additively and multiplicatively. A perpendicular magnetic field acts as a confinement source and a static external electric field has been applied. The EOE profiles have been followed as a function of incident photon energy when several important parameters such as electric field strength, magnetic field strength, confinement energy, dopant location, relaxation time, Al concentration, dopant potential, and noise strength possess different values. In addition, the role of mode of application of noise (additive/multiplicative) on the EOE profiles has also been scrutinized. The EOE profiles are found to be adorned with interesting observations such as shift of peak position and maximization/minimization of peak intensity. However, the presence of noise and also the pathway of its application bring about rich variety in the features of EOE profiles through some noticeable manifestations. The observations indicate possibilities of harnessing the EOE susceptibility of doped QD systems in presence of noise.
Numeric Solutions of Dirac-Gursey Spinor Field Equation Under External Gaussian White Noise
NASA Astrophysics Data System (ADS)
Aydogmus, Fatma
2016-06-01
In this paper, we consider the Dirac-Gursey spinor field equation that has particle-like solutions derived classical field equations so-called instantons, formed by using Heisenberg ansatz, under the effect of an additional Gaussian white noise term. Our purpose is to understand how the behavior of spinor-type excited instantons in four dimensions can be affected by noise. Thus, we simulate the phase portraits and Poincaré sections of the obtained system numerically both with and without noise. Recurrence plots are also given for more detailed information regarding the system.
NASA Astrophysics Data System (ADS)
Ganguly, Jayanta; Ghosh, Manas
2014-05-01
We investigate the profiles of diagonal components of frequency-dependent first nonlinear (βxxx and βyyy) optical response of repulsive impurity doped quantum dots. We have assumed a Gaussian function to represent the dopant impurity potential. This study primarily addresses the role of noise on the polarizability components. We have invoked Gaussian white noise consisting of additive and multiplicative characteristics (in Stratonovich sense). The doped system has been subjected to an oscillating electric field of given intensity, and the frequency-dependent first nonlinear polarizabilities are computed. The noise characteristics are manifested in an interesting way in the nonlinear polarizability components. In case of additive noise, the noise strength remains practically ineffective in influencing the optical responses. The situation completely changes with the replacement of additive noise by its multiplicative analog. The replacement enhances the nonlinear optical response dramatically and also causes their maximization at some typical value of noise strength that depends on oscillation frequency.
Ganguly, Jayanta; Ghosh, Manas
2014-05-07
We investigate the profiles of diagonal components of frequency-dependent first nonlinear (β{sub xxx} and β{sub yyy}) optical response of repulsive impurity doped quantum dots. We have assumed a Gaussian function to represent the dopant impurity potential. This study primarily addresses the role of noise on the polarizability components. We have invoked Gaussian white noise consisting of additive and multiplicative characteristics (in Stratonovich sense). The doped system has been subjected to an oscillating electric field of given intensity, and the frequency-dependent first nonlinear polarizabilities are computed. The noise characteristics are manifested in an interesting way in the nonlinear polarizability components. In case of additive noise, the noise strength remains practically ineffective in influencing the optical responses. The situation completely changes with the replacement of additive noise by its multiplicative analog. The replacement enhances the nonlinear optical response dramatically and also causes their maximization at some typical value of noise strength that depends on oscillation frequency.
Response of MDOF strongly nonlinear systems to fractional Gaussian noises.
Deng, Mao-Lin; Zhu, Wei-Qiu
2016-08-01
In the present paper, multi-degree-of-freedom strongly nonlinear systems are modeled as quasi-Hamiltonian systems and the stochastic averaging method for quasi-Hamiltonian systems (including quasi-non-integrable, completely integrable and non-resonant, completely integrable and resonant, partially integrable and non-resonant, and partially integrable and resonant Hamiltonian systems) driven by fractional Gaussian noise is introduced. The averaged fractional stochastic differential equations (SDEs) are derived. The simulation results for some examples show that the averaged SDEs can be used to predict the response of the original systems and the simulation time for the averaged SDEs is less than that for the original systems. PMID:27586630
Broad-band Gaussian noise is most effective in improving motor performance and is most pleasant.
Trenado, Carlos; Mikulić, Areh; Manjarrez, Elias; Mendez-Balbuena, Ignacio; Schulte-Mönting, Jürgen; Huethe, Frank; Hepp-Reymond, Marie-Claude; Kristeva, Rumyana
2014-01-01
Modern attempts to improve human performance focus on stochastic resonance (SR). SR is a phenomenon in non-linear systems characterized by a response increase of the system induced by a particular level of input noise. Recently, we reported that an optimum level of 0-15 Hz Gaussian noise applied to the human index finger improved static isometric force compensation. A possible explanation was a better sensorimotor integration caused by increase in sensitivity of peripheral receptors and/or of internal SR. The present study in 10 subjects compares SR effects in the performance of the same motor task and on pleasantness, by applying three Gaussian noises chosen on the sensitivity of the fingertip receptors (0-15 Hz mostly for Merkel receptors, 250-300 Hz for Pacini corpuscles and 0-300 Hz for all). We document that only the 0-300 Hz noise induced SR effect during the transitory phase of the task. In contrast, the motor performance was improved during the stationary phase for all three noise frequency bandwidths. This improvement was stronger for 0-300 Hz and 250-300 Hz than for 0-15 Hz noise. Further, we found higher degree of pleasantness for 0-300 Hz and 250-300 Hz noise bandwidths than for 0-15 Hz. Thus, we show that the most appropriate Gaussian noise that could be used in haptic gloves is the 0-300 Hz, as it improved motor performance during both stationary and transitory phases. In addition, this noise had the highest degree of pleasantness and thus reveals that the glabrous skin can also forward pleasant sensations. PMID:24550806
Broad-band Gaussian noise is most effective in improving motor performance and is most pleasant
Trenado, Carlos; Mikulić, Areh; Manjarrez, Elias; Mendez-Balbuena, Ignacio; Schulte-Mönting, Jürgen; Huethe, Frank; Hepp-Reymond, Marie-Claude; Kristeva, Rumyana
2014-01-01
Modern attempts to improve human performance focus on stochastic resonance (SR). SR is a phenomenon in non-linear systems characterized by a response increase of the system induced by a particular level of input noise. Recently, we reported that an optimum level of 0–15 Hz Gaussian noise applied to the human index finger improved static isometric force compensation. A possible explanation was a better sensorimotor integration caused by increase in sensitivity of peripheral receptors and/or of internal SR. The present study in 10 subjects compares SR effects in the performance of the same motor task and on pleasantness, by applying three Gaussian noises chosen on the sensitivity of the fingertip receptors (0–15 Hz mostly for Merkel receptors, 250–300 Hz for Pacini corpuscles and 0–300 Hz for all). We document that only the 0–300 Hz noise induced SR effect during the transitory phase of the task. In contrast, the motor performance was improved during the stationary phase for all three noise frequency bandwidths. This improvement was stronger for 0–300 Hz and 250–300 Hz than for 0–15 Hz noise. Further, we found higher degree of pleasantness for 0–300 Hz and 250–300 Hz noise bandwidths than for 0–15 Hz. Thus, we show that the most appropriate Gaussian noise that could be used in haptic gloves is the 0–300 Hz, as it improved motor performance during both stationary and transitory phases. In addition, this noise had the highest degree of pleasantness and thus reveals that the glabrous skin can also forward pleasant sensations. PMID:24550806
Toward the detection of gravitational waves under non-Gaussian noises I. Locally optimal statistic.
Yokoyama, Jun'ichi
2014-01-01
After reviewing the standard hypothesis test and the matched filter technique to identify gravitational waves under Gaussian noises, we introduce two methods to deal with non-Gaussian stationary noises. We formulate the likelihood ratio function under weakly non-Gaussian noises through the Edgeworth expansion and strongly non-Gaussian noises in terms of a new method we call Gaussian mapping where the observed marginal distribution and the two-body correlation function are fully taken into account. We then apply these two approaches to Student's t-distribution which has a larger tails than Gaussian. It is shown that while both methods work well in the case the non-Gaussianity is small, only the latter method works well for highly non-Gaussian case. PMID:25504231
Toward the detection of gravitational waves under non-Gaussian noises I. Locally optimal statistic
YOKOYAMA, Jun’ichi
2014-01-01
After reviewing the standard hypothesis test and the matched filter technique to identify gravitational waves under Gaussian noises, we introduce two methods to deal with non-Gaussian stationary noises. We formulate the likelihood ratio function under weakly non-Gaussian noises through the Edgeworth expansion and strongly non-Gaussian noises in terms of a new method we call Gaussian mapping where the observed marginal distribution and the two-body correlation function are fully taken into account. We then apply these two approaches to Student’s t-distribution which has a larger tails than Gaussian. It is shown that while both methods work well in the case the non-Gaussianity is small, only the latter method works well for highly non-Gaussian case. PMID:25504231
NASA Astrophysics Data System (ADS)
Ganguly, Jayanta; Ghosh, Manas
2015-07-01
We investigate the modulation of diagonal components of static linear (αxx, αyy) and first nonlinear (βxxx, βyyy) polarizabilities of quantum dots by Gaussian white noise. Quantum dot is doped with impurity represented by a Gaussian potential and repulsive in nature. The study reveals the importance of mode of application of noise (additive/multiplicative) on the polarizability components. The doped system is further exposed to a static external electric field of given intensity. As important observation we have found that the strength of additive noise becomes unable to influence the polarizability components. However, the multiplicative noise influences them conspicuously and gives rise to additional interesting features. Multiplicative noise even enhances the magnitude of the polarizability components immensely. The present investigation deems importance in view of the fact that noise seriously affects the optical properties of doped quantum dot devices.
Optimal configurations of full-Stokes polarimeter with immunity to both Poisson and Gaussian noise
NASA Astrophysics Data System (ADS)
Mu, Tingkui; Chen, Zeyu; Zhang, Chunmin; Liang, Rongguang
2016-05-01
For a full-Stokes polarimeter (FSP), generally there are two types of noise, signal-dependent Poisson shot noise and signal-independent additive Gaussian noise, which will degrade the signal-to-noise ratio on the measured Stokes parameters. The relation between the immunity to Gaussian noise and the condition of the measurement matrix has been widely studied in the recent literature. In this paper, we present a new merit function and use it to achieve optimal configurations with immunity to both types of noise. The numerical results show that, for the FSP consisting of variable retarders followed by a fixed polarizer, the four measurement channels immune to these two types of noise can be optimally composed by a 102.2° retardance with a pair of azimuths ±71.9° and a 142.1° retardance with a pair of azimuths ±34.95°, or by two quarter-wave plates with four pairs of azimuths (±70.15°, ±87.84°) and (±42.82°, ±19.14°). The tolerances of the retardances or azimuths in the optimized configurations are evaluated for practical manufacturing, assembling and alignment.
Analysis of regularized inversion of data corrupted by white Gaussian noise
NASA Astrophysics Data System (ADS)
Kekkonen, Hanne; Lassas, Matti; Siltanen, Samuli
2014-04-01
Tikhonov regularization is studied in the case of linear pseudodifferential operator as the forward map and additive white Gaussian noise as the measurement error. The measurement model for an unknown function u(x) is \\begin{eqnarray*} m(x) = Au(x) + \\delta \\varepsilon (x), \\end{eqnarray*} where δ > 0 is the noise magnitude. If ɛ was an L2-function, Tikhonov regularization gives an estimate \\begin{eqnarray*} T_\\alpha (m) = \\mathop {{arg\\, min}}_{u\\in H^r} \\big \\lbrace \\Vert A u-m\\Vert _{L^2}^2+ \\alpha \\Vert u\\Vert _{H^r}^2 \\big \\rbrace \\end{eqnarray*} for u where α = α(δ) is the regularization parameter. Here penalization of the Sobolev norm \\Vert u\\Vert _{H^r} covers the cases of standard Tikhonov regularization (r = 0) and first derivative penalty (r = 1). Realizations of white Gaussian noise are almost never in L2, but do belong to Hs with probability one if s < 0 is small enough. A modification of Tikhonov regularization theory is presented, covering the case of white Gaussian measurement noise. Furthermore, the convergence of regularized reconstructions to the correct solution as δ → 0 is proven in appropriate function spaces using microlocal analysis. The convergence of the related finite-dimensional problems to the infinite-dimensional problem is also analysed.
NASA Astrophysics Data System (ADS)
Tuzlukov, Vyacheslav
2011-06-01
In this paper, we consider the problem of M-ary signal detection based on the generalized approach to signal processing (GASP) in noise over a single-input multiple-output (SIMO) channel affected by frequency-dispersive Rayleigh distributed fading and corrupted by additive non-Gaussian noise modeled as spherically invariant random process. We derive both the optimum generalized detector (GD) structure based on GASP and a suboptimal reduced-complexity GD applying the low energy coherence approach jointly with the GASP in noise. Both GD structures are independent of the actual noise statistics. We also carry out a performance analysis of both GDs and compare with the conventional receivers. The performance analysis is carried out with reference to the case that the channel is affected by a frequency-selective fading and for a binary frequency-shift keying (BFSK) signaling format. The results obtained through both a Chernoff-bounding technique and Monte Carlo simulations reveal that the adoption of diversity also represents a suitable means to restore performance in the presence of dispersive fading and impulsive non-Gaussian noise. It is also shown that the suboptimal GD incurs a limited loss with respect to the optimum GD and this loss is less in comparison with the conventional receiver.
Non-stationary noise estimation using dictionary learning and Gaussian mixture models
NASA Astrophysics Data System (ADS)
Hughes, James M.; Rockmore, Daniel N.; Wang, Yang
2014-02-01
Stationarity of the noise distribution is a common assumption in image processing. This assumption greatly simplifies denoising estimators and other model parameters and consequently assuming stationarity is often a matter of convenience rather than an accurate model of noise characteristics. The problematic nature of this assumption is exacerbated in real-world contexts, where noise is often highly non-stationary and can possess time- and space-varying characteristics. Regardless of model complexity, estimating the parameters of noise dis- tributions in digital images is a difficult task, and estimates are often based on heuristic assumptions. Recently, sparse Bayesian dictionary learning methods were shown to produce accurate estimates of the level of additive white Gaussian noise in images with minimal assumptions. We show that a similar model is capable of accu- rately modeling certain kinds of non-stationary noise processes, allowing for space-varying noise in images to be estimated, detected, and removed. We apply this modeling concept to several types of non-stationary noise and demonstrate the model's effectiveness on real-world problems, including denoising and segmentation of images according to noise characteristics, which has applications in image forensics.
Image denoising in mixed Poisson-Gaussian noise.
Luisier, Florian; Blu, Thierry; Unser, Michael
2011-03-01
We propose a general methodology (PURE-LET) to design and optimize a wide class of transform-domain thresholding algorithms for denoising images corrupted by mixed Poisson-Gaussian noise. We express the denoising process as a linear expansion of thresholds (LET) that we optimize by relying on a purely data-adaptive unbiased estimate of the mean-squared error (MSE), derived in a non-Bayesian framework (PURE: Poisson-Gaussian unbiased risk estimate). We provide a practical approximation of this theoretical MSE estimate for the tractable optimization of arbitrary transform-domain thresholding. We then propose a pointwise estimator for undecimated filterbank transforms, which consists of subband-adaptive thresholding functions with signal-dependent thresholds that are globally optimized in the image domain. We finally demonstrate the potential of the proposed approach through extensive comparisons with state-of-the-art techniques that are specifically tailored to the estimation of Poisson intensities. We also present denoising results obtained on real images of low-count fluorescence microscopy. PMID:20840902
Coherence resonance in the two-dimensional neural map driven by non-Gaussian colored noise
NASA Astrophysics Data System (ADS)
Li, Dongxi; Hu, Bing; Wang, Jia; Jing, Yingchuan; Hou, Fangmei
2016-01-01
Based on the two-dimensional (2D) neural map, we investigate the impacts of non-Gaussian colored noise on the firing activity of discrete system. Taking the coherence parameter R to measure the regularity of firing behavior, it is demonstrated that coherence parameter R has a pronounced minimum value with the noise intensity and the correlation time of non-Gaussian colored noise, which is the so-called phenomenon of coherence resonance (CR). Besides, the firing activity is not sensitive to the non-Gaussian parameter which determines the departure from the Gaussian distribution when the correlation time is large enough.
Lifting primordial non-Gaussianity above the noise
NASA Astrophysics Data System (ADS)
Welling, Yvette; van der Woude, Drian; Pajer, Enrico
2016-08-01
Primordial non-Gaussianity (PNG) in Large Scale Structures is obfuscated by the many additional sources of non-linearity. Within the Effective Field Theory approach to Standard Perturbation Theory, we show that matter non-linearities in the bispectrum can be modeled sufficiently well to strengthen current bounds with near future surveys, such as Euclid. We find that the EFT corrections are crucial to this improvement in sensitivity. Yet, our understanding of non-linearities is still insufficient to reach important theoretical benchmarks for equilateral PNG, while, for local PNG, our forecast is more optimistic. We consistently account for the theoretical error intrinsic to the perturbative approach and discuss the details of its implementation in Fisher forecasts.
Analytic expressions for rate and CV of a type I neuron driven by white gaussian noise.
Lindner, Benjamin; Longtin, André; Bulsara, Adi
2003-08-01
We study the one-dimensional normal form of a saddle-node system under the influence of additive gaussian white noise and a static "bias current" input parameter, a model that can be looked upon as the simplest version of a type I neuron with stochastic input. This is in contrast with the numerous studies devoted to the noise-driven leaky integrate-and-fire neuron. We focus on the firing rate and coefficient of variation (CV) of the interspike interval density, for which scaling relations with respect to the input parameter and noise intensity are derived. Quadrature formulas for rate and CV are numerically evaluated and compared to numerical simulations of the system and to various approximation formulas obtained in different limiting cases of the model. We also show that caution must be used to extend these results to the Theta neuron model with multiplicative gaussian white noise. The correspondence between the first passage time statistics for the saddle-node model and the Theta neuron model is obtained only in the Stratonovich interpretation of the stochastic Theta neuron model, while previous results have focused only on the Ito interpretation. The correct Stratonovich interpretation yields CVs that are still relatively high, although smaller than in the Ito interpretation; it also produces certain qualitative differences, especially at larger noise intensities. Our analysis provides useful relations for assessing the distance to threshold and the level of synaptic noise in real type I neurons from their firing statistics. We also briefly discuss the effect of finite boundaries (finite values of threshold and reset) on the firing statistics. PMID:14511512
NASA Astrophysics Data System (ADS)
Ganguly, Jayanta; Saha, Surajit; Pal, Suvajit; Ghosh, Manas
2016-03-01
We perform a meticulous analysis of profiles of third-order nonlinear optical susceptibility (TONOS) of impurity doped quantum dots (QDs) in the presence and absence of noise. We have invoked Gaussian white noise in the present study and noise has been introduced to the system additively and multiplicatively. The QD is doped with a Gaussian impurity. A magnetic field applied perpendicularly serves as a confinement source and the doped system has been exposed to a static external electric field. The TONOS profiles have been monitored against a continuous variation of incident photon energy when several important parameters such as electric field strength, magnetic field strength, confinement energy, dopant location, Al concentration, dopant potential, relaxation time, anisotropy, and noise strength assume different values. Moreover, the influence of mode of introduction of noise (additive/multiplicative) on the TONOS profiles has also been addressed. The said profiles are found to be consisting of interesting observations such as shift of TONOS peak position and maximization/minimization of TONOS peak intensity. The presence of noise alters the features of TONOS profiles and sometimes enhances the TONOS peak intensity from that of noise-free state. Furthermore, the mode of application of noise also often tailors the TONOS profiles in diverse fashions. The observations accentuate the possibility of tuning the TONOS of doped QD systems in the presence of noise.
Quantum error correction of continuous-variable states against Gaussian noise
Ralph, T. C.
2011-08-15
We describe a continuous-variable error correction protocol that can correct the Gaussian noise induced by linear loss on Gaussian states. The protocol can be implemented using linear optics and photon counting. We explore the theoretical bounds of the protocol as well as the expected performance given current knowledge and technology.
On stochastic differential equations driven by the renormalized square of the Gaussian white noise
NASA Astrophysics Data System (ADS)
Ben Ammou, Bilel Kacem; Lanconelli, Alberto
2015-11-01
We investigate the properties of the Wick square of Gaussian white noises through a new method to perform nonlinear operations on Hida distributions. This method lays in between the Wick product interpretation and the usual definition of nonlinear functions. We prove an Itô-type formula and solve stochastic differential equations driven by the renormalized square of the Gaussian white noise. Our approach works with standard assumptions on the coefficients of the equations, global Lipschitz continuity, and produces existence and uniqueness results in the space where the noise lives. The linear case is studied in details and positivity of the solution is proved.
Sonka, Milan; Abramoff, Michael D.
2013-01-01
In this paper, MMSE estimator is employed for noise-free 3D OCT data recovery in 3D complex wavelet domain. Since the proposed distribution for noise-free data plays a key role in the performance of MMSE estimator, a priori distribution for the pdf of noise-free 3D complex wavelet coefficients is proposed which is able to model the main statistical properties of wavelets. We model the coefficients with a mixture of two bivariate Gaussian pdfs with local parameters which are able to capture the heavy-tailed property and inter- and intrascale dependencies of coefficients. In addition, based on the special structure of OCT images, we use an anisotropic windowing procedure for local parameters estimation that results in visual quality improvement. On this base, several OCT despeckling algorithms are obtained based on using Gaussian/two-sided Rayleigh noise distribution and homomorphic/nonhomomorphic model. In order to evaluate the performance of the proposed algorithm, we use 156 selected ROIs from 650 × 512 × 128 OCT dataset in the presence of wet AMD pathology. Our simulations show that the best MMSE estimator using local bivariate mixture prior is for the nonhomomorphic model in the presence of Gaussian noise which results in an improvement of 7.8 ± 1.7 in CNR. PMID:24222760
Separation of components from a scale mixture of Gaussian white noises
NASA Astrophysics Data System (ADS)
Vamoş, Călin; Crăciun, Maria
2010-05-01
The time evolution of a physical quantity associated with a thermodynamic system whose equilibrium fluctuations are modulated in amplitude by a slowly varying phenomenon can be modeled as the product of a Gaussian white noise {Zt} and a stochastic process with strictly positive values {Vt} referred to as volatility. The probability density function (pdf) of the process Xt=VtZt is a scale mixture of Gaussian white noises expressed as a time average of Gaussian distributions weighted by the pdf of the volatility. The separation of the two components of {Xt} can be achieved by imposing the condition that the absolute values of the estimated white noise be uncorrelated. We apply this method to the time series of the returns of the daily S&P500 index, which has also been analyzed by means of the superstatistics method that imposes the condition that the estimated white noise be Gaussian. The advantage of our method is that this financial time series is processed without partitioning or removal of the extreme events and the estimated white noise becomes almost Gaussian only as result of the uncorrelation condition.
A feedback control strategy for the airfoil system under non-Gaussian colored noise excitation
Huang, Yong E-mail: taogang@njust.edu.cn; Tao, Gang E-mail: taogang@njust.edu.cn
2014-09-01
The stability of a binary airfoil with feedback control under stochastic disturbances, a non-Gaussian colored noise, is studied in this paper. First, based on some approximated theories and methods the non-Gaussian colored noise is simplified to an Ornstein-Uhlenbeck process. Furthermore, via the stochastic averaging method and the logarithmic polar transformation, one dimensional diffusion process can be obtained. At last by applying the boundary conditions, the largest Lyapunov exponent which can determine the almost-sure stability of the system and the effective region of control parameters is calculated.
A feedback control strategy for the airfoil system under non-Gaussian colored noise excitation.
Huang, Yong; Tao, Gang
2014-09-01
The stability of a binary airfoil with feedback control under stochastic disturbances, a non-Gaussian colored noise, is studied in this paper. First, based on some approximated theories and methods the non-Gaussian colored noise is simplified to an Ornstein-Uhlenbeck process. Furthermore, via the stochastic averaging method and the logarithmic polar transformation, one dimensional diffusion process can be obtained. At last by applying the boundary conditions, the largest Lyapunov exponent which can determine the almost-sure stability of the system and the effective region of control parameters is calculated. PMID:25273197
NASA Technical Reports Server (NTRS)
Cheung, K. M.; Vilnrotter, V.
1996-01-01
A closed-form expression for the capacity of an array of correlated Gaussian channels is derived. It is shown that when signal and noise are independent, the array of observables can be replaced with a single observable without diminishing the capacity of the array channel. Examples are provided to illustrate the dependence of channel capacity on noise correlation for two- and three-channel arrays.
NASA Technical Reports Server (NTRS)
Cheung, K.-M.; Vilnrotter, V.
1996-01-01
A closed-form expression for the capacity of an array of correlated Gaussian channels is derived. It is shown that when signal and noise are independent, the array of observables can be replaced with a single observable without diminishing the capacity of the array channel. Examples are provided to illustrate the dependence of channel capacity on noise correlation for two- and three-channel arrays.
Time jitter versus additive noise in a game theory context
NASA Astrophysics Data System (ADS)
Zaidi, Abdellatif; Boyer, Remy; Duhamel, Pierre
2005-03-01
Imperfectly synchronized watermark communication is almost the most hostile watermark channel. A desynchronization attack can yield a very high probability of bit error rate by simply moving the watermark from elements it has been embedded in, inhibiting hence its reliable retrieval from the original. In this paper, we adress attacks that can be modelled by an Additive White Gaussian Noise and Jitter (AWGN&J) channel in a game theory context. The AWGN&J channel was initially introduced to model local time fluctuations in the context of magnetic recording media. This channel is first briefly presented and characterized in terms of induced objective and perceptual distorsions. Also, performance loss of the one-bit watermarking Spread-Spectrum based scheme over an AWGN&J channel is derived. Then, results are applied in a game theoretic context to answer some questions such as: (i) for a given distortion budget, and from the attacker point of view, what part should be allocated to the desynchronization, and what part should be allocated to the additive noise?, (ii) from the defender point of view, what is the worst distortion? and (iii) is there means to countermeasure the attacker (limit the amount of objective distorsion)?
Minimal Model of Stochastic Athermal Systems: Origin of Non-Gaussian Noise
NASA Astrophysics Data System (ADS)
Kanazawa, Kiyoshi; Sano, Tomohiko G.; Sagawa, Takahiro; Hayakawa, Hisao
2015-03-01
For a wide class of stochastic athermal systems, we derive Langevin-like equations driven by non-Gaussian noise, starting from master equations and developing a new asymptotic expansion. We found an explicit condition whereby the non-Gaussian properties of the athermal noise become dominant for tracer particles associated with both thermal and athermal environments. Furthermore, we derive an inverse formula to infer microscopic properties of the athermal bath from the statistics of the tracer particle. We apply our formulation to a granular motor under viscous friction and analytically obtain the angular velocity distribution function. Our theory demonstrates that the non-Gaussian Langevin equation is the minimal model of athermal systems.
Optimum receivers for pattern recognition in the presence of Gaussian noise with unknown statistics.
Towghi, N; Javidi, B
2001-08-01
We develop algorithms to detect a known pattern or a reference signal in the presence of additive, disjoint background, and multiplicative white Gaussian noise with unknown statistics. The presence of three different types of noise processes with unknown statistics presents difficulties in estimating the unknown parameters. The standard methods such as expected-maximization-type algorithms are iterative, and in the framework of hypothesis testing they are time-consuming, because corresponding to each hypothesis one must estimate a set of parameters. Other standard methods such as setting the gradient of the likelihood function with respect to the unknown parameters will lead to a nonlinear system of equations that do not have a closed-form solution and require iterative methods. We develop an approach to overcome these handicaps and derive algorithms to detect a known object. We present new methods to estimate unknown parameters within the framework of hypothesis testing. The methods that we present are direct and provide closed-form estimates of the unknown parameters. Computer simulations are used to show that for the images tested, the receivers that we have designed perform better than existing receivers. PMID:11488488
Adaptive subspace detection of extended target in white Gaussian noise using sinc basis
NASA Astrophysics Data System (ADS)
Zhang, Xiao-Wei; Li, Ming; Qu, Jian-She; Yang, Hui
2016-01-01
For the high resolution radar (HRR), the problem of detecting the extended target is considered in this paper. Based on a single observation, a new two-step detection based on sparse representation (TSDSR) method is proposed to detect the extended target in the presence of Gaussian noise with unknown covariance. In the new method, the Sinc dictionary is introduced to sparsely represent the high resolution range profile (HRRP). Meanwhile, adaptive subspace pursuit (ASP) is presented to recover the HRRP embedded in the Gaussian noise and estimate the noise covariance matrix. Based on the Sinc dictionary and the estimated noise covariance matrix, one step subspace detector (OSSD) for the first-order Gaussian (FOG) model without secondary data is adopted to realise the extended target detection. Finally, the proposed TSDSR method is applied to raw HRR data. Experimental results demonstrate that HRRPs of different targets can be sparsely represented very well with the Sinc dictionary. Moreover, the new method can estimate the noise power with tiny errors and have a good detection performance.
NASA Technical Reports Server (NTRS)
Blasche, P. R.
1980-01-01
Specific configurations of first and second order all digital phase locked loops are analyzed for both ideal and additive white gaussian noise inputs. In addition, a design for a hardware digital phase locked loop capable of either first or second order operation is presented along with appropriate experimental data obtained from testing of the hardware loop. All parameters chosen for the analysis and the design of the digital phase locked loop are consistent with an application to an Omega navigation receiver although neither the analysis nor the design are limited to this application.
NASA Astrophysics Data System (ADS)
Sun, Xiaojuan; Perc, Matjaž; Lu, Qishao; Kurths, Jürgen
2010-09-01
In this paper, we examine the effects of correlated Gaussian noise on a two-dimensional neuronal network that is locally modeled by the Rulkov map. More precisely, we study the effects of the noise correlation on the variations of the mean firing rate and the correlations among neurons versus the noise intensity. Via numerical simulations, we show that the mean firing rate can always be optimized at an intermediate noise intensity, irrespective of the noise correlation. On the other hand, variations of the population coherence with respect to the noise intensity are strongly influenced by the ratio between local and global Gaussian noisy inputs. Biological implications of our findings are also discussed.
Detection of continuous-time quaternion signals in additive noise
NASA Astrophysics Data System (ADS)
Navarro-Moreno, Jesús; Ruiz-Molina, Juan Carlos; Oya, Antonia; Quesada-Rubio, José M.
2012-12-01
Different kinds of quaternion signal detection problems in continuous-time by using a widely linear processing are dealt with. The suggested solutions are based on an extension of the Karhunen-Loève expansion to the quaternion domain which provides uncorrelated scalar real-valued random coefficients. This expansion presents the notable advantage of transforming the original four-dimensional eigen problem to a one-dimensional problem. Firstly, we address the problem of detecting a quaternion deterministic signal in quaternion Gaussian noise and a version of Pitcher's Theorem is given. Also the particular case of a general quaternion Wiener noise is studied and an extension of the Cameron-Martin formula is presented. Finally, the problem of detecting a quaternion random signal in quaternion white Gaussian noise is tackled. In such a case, it is shown that the detector depends on the quaternion widely linear estimator of the signal.
Absolute judgment for one- and two-dimensional stimuli embedded in Gaussian noise
NASA Technical Reports Server (NTRS)
Kvalseth, T. O.
1977-01-01
This study examines the effect on human performance of adding Gaussian noise or disturbance to the stimuli in absolute judgment tasks involving both one- and two-dimensional stimuli. For each selected stimulus value (both an X-value and a Y-value were generated in the two-dimensional case), 10 values (or 10 pairs of values in the two-dimensional case) were generated from a zero-mean Gaussian variate, added to the selected stimulus value and then served as the coordinate values for the 10 points that were displayed sequentially on a CRT. The results show that human performance, in terms of the information transmitted and rms error as functions of stimulus uncertainty, was significantly reduced as the noise variance increased.
Canales-Rodríguez, Erick J; Daducci, Alessandro; Sotiropoulos, Stamatios N; Caruyer, Emmanuel; Aja-Fernández, Santiago; Radua, Joaquim; Yurramendi Mendizabal, Jesús M; Iturria-Medina, Yasser; Melie-García, Lester; Alemán-Gómez, Yasser; Thiran, Jean-Philippe; Sarró, Salvador; Pomarol-Clotet, Edith; Salvador, Raymond
2015-01-01
Spherical deconvolution (SD) methods are widely used to estimate the intra-voxel white-matter fiber orientations from diffusion MRI data. However, while some of these methods assume a zero-mean Gaussian distribution for the underlying noise, its real distribution is known to be non-Gaussian and to depend on many factors such as the number of coils and the methodology used to combine multichannel MRI signals. Indeed, the two prevailing methods for multichannel signal combination lead to noise patterns better described by Rician and noncentral Chi distributions. Here we develop a Robust and Unbiased Model-BAsed Spherical Deconvolution (RUMBA-SD) technique, intended to deal with realistic MRI noise, based on a Richardson-Lucy (RL) algorithm adapted to Rician and noncentral Chi likelihood models. To quantify the benefits of using proper noise models, RUMBA-SD was compared with dRL-SD, a well-established method based on the RL algorithm for Gaussian noise. Another aim of the study was to quantify the impact of including a total variation (TV) spatial regularization term in the estimation framework. To do this, we developed TV spatially-regularized versions of both RUMBA-SD and dRL-SD algorithms. The evaluation was performed by comparing various quality metrics on 132 three-dimensional synthetic phantoms involving different inter-fiber angles and volume fractions, which were contaminated with noise mimicking patterns generated by data processing in multichannel scanners. The results demonstrate that the inclusion of proper likelihood models leads to an increased ability to resolve fiber crossings with smaller inter-fiber angles and to better detect non-dominant fibers. The inclusion of TV regularization dramatically improved the resolution power of both techniques. The above findings were also verified in human brain data. PMID:26470024
Canales-Rodríguez, Erick J.; Caruyer, Emmanuel; Aja-Fernández, Santiago; Radua, Joaquim; Yurramendi Mendizabal, Jesús M.; Iturria-Medina, Yasser; Melie-García, Lester; Alemán-Gómez, Yasser; Thiran, Jean-Philippe; Sarró, Salvador; Pomarol-Clotet, Edith; Salvador, Raymond
2015-01-01
Spherical deconvolution (SD) methods are widely used to estimate the intra-voxel white-matter fiber orientations from diffusion MRI data. However, while some of these methods assume a zero-mean Gaussian distribution for the underlying noise, its real distribution is known to be non-Gaussian and to depend on many factors such as the number of coils and the methodology used to combine multichannel MRI signals. Indeed, the two prevailing methods for multichannel signal combination lead to noise patterns better described by Rician and noncentral Chi distributions. Here we develop a Robust and Unbiased Model-BAsed Spherical Deconvolution (RUMBA-SD) technique, intended to deal with realistic MRI noise, based on a Richardson-Lucy (RL) algorithm adapted to Rician and noncentral Chi likelihood models. To quantify the benefits of using proper noise models, RUMBA-SD was compared with dRL-SD, a well-established method based on the RL algorithm for Gaussian noise. Another aim of the study was to quantify the impact of including a total variation (TV) spatial regularization term in the estimation framework. To do this, we developed TV spatially-regularized versions of both RUMBA-SD and dRL-SD algorithms. The evaluation was performed by comparing various quality metrics on 132 three-dimensional synthetic phantoms involving different inter-fiber angles and volume fractions, which were contaminated with noise mimicking patterns generated by data processing in multichannel scanners. The results demonstrate that the inclusion of proper likelihood models leads to an increased ability to resolve fiber crossings with smaller inter-fiber angles and to better detect non-dominant fibers. The inclusion of TV regularization dramatically improved the resolution power of both techniques. The above findings were also verified in human brain data. PMID:26470024
NASA Astrophysics Data System (ADS)
Saha, Surajit; Ganguly, Jayanta; Pal, Suvajit; Ghosh, Manas
2016-08-01
We study the modulation of electro-optic effect (EOE) of impurity doped QD under the influence of geometrical anisotropy and position-dependent effective mass (PDEM) in presence of Gaussian white noise. Always a comparison has been made between fixed effective mass (FEM) and PDEM to understand the role of the latter. In addition, the role of mode of application of noise (additive/multiplicative) has also been analyzed. The EOE profiles are found to be enriched with shift of peak position and maximization of peak intensity. The observations reveal sensitive interplay between noise and anisotropy/PDEM to fine-tune the features of EOE profiles.
Forensic detection of noise addition in digital images
NASA Astrophysics Data System (ADS)
Cao, Gang; Zhao, Yao; Ni, Rongrong; Ou, Bo; Wang, Yongbin
2014-03-01
We proposed a technique to detect the global addition of noise to a digital image. As an anti-forensics tool, noise addition is typically used to disguise the visual traces of image tampering or to remove the statistical artifacts left behind by other operations. As such, the blind detection of noise addition has become imperative as well as beneficial to authenticate the image content and recover the image processing history, which is the goal of general forensics techniques. Specifically, the special image blocks, including constant and strip ones, are used to construct the features for identifying noise addition manipulation. The influence of noising on blockwise pixel value distribution is formulated and analyzed formally. The methodology of detectability recognition followed by binary decision is proposed to ensure the applicability and reliability of noising detection. Extensive experimental results demonstrate the efficacy of our proposed noising detector.
NASA Astrophysics Data System (ADS)
Rubel, Aleksey S.; Lukin, Vladimir V.; Egiazarian, Karen O.
2015-03-01
Results of denoising based on discrete cosine transform for a wide class of images corrupted by additive noise are obtained. Three types of noise are analyzed: additive white Gaussian noise and additive spatially correlated Gaussian noise with middle and high correlation levels. TID2013 image database and some additional images are taken as test images. Conventional DCT filter and BM3D are used as denoising techniques. Denoising efficiency is described by PSNR and PSNR-HVS-M metrics. Within hard-thresholding denoising mechanism, DCT-spectrum coefficient statistics are used to characterize images and, subsequently, denoising efficiency for them. Results of denoising efficiency are fitted for such statistics and efficient approximations are obtained. It is shown that the obtained approximations provide high accuracy of prediction of denoising efficiency.
Non-Gaussian resistance noise in misfit layer compounds: Bi-Se-Cr
NASA Astrophysics Data System (ADS)
Peng, Lintao; Freedman, Alex; Clarke, Samantha; Freedman, Danna; Grayson, M.
Misfit layer ternary compounds Bi-Se-Cr have been synthesized and structurally and magnetically characterized. However, the nature of the magnetic ordering below the transition temperature remains debatable between ferromagnetic and spin-glass. These misfit layer compounds consist of two alternating chalcogenide layers of CrSe2 and BiSe along the c-axis. Whereas the a-axis is lattice matched, the lattice mismatch along the b-axis introduces non-periodic modulation of atomic position leading to quasi-crystalline order along the b-axis alone. We explore unconventional electrical transport properties in the noise spectrum of these compounds. After thinning down the compounds to nanoscale, Van der Pauw devices are fabricated with standard electron beam lithography process. Large resistance noise was observed at temperature below the Cure temperature. The magnitude of resistance noise is much greater than trivial intrinsic noises like thermal Johnson noise and increases as temperature decreases. The probability density function of the relative noise shows 2-4 peaks among different observations which indicate strong non-Gaussian statistic property suggesting glassy behaviors in this material.
Optimal inversion of the generalized Anscombe transformation for Poisson-Gaussian noise.
Mäkitalo, Markku; Foi, Alessandro
2013-01-01
Many digital imaging devices operate by successive photon-to-electron, electron-to-voltage, and voltage-to-digit conversions. These processes are subject to various signal-dependent errors, which are typically modeled as Poisson-Gaussian noise. The removal of such noise can be effected indirectly by applying a variance-stabilizing transformation (VST) to the noisy data, denoising the stabilized data with a Gaussian denoising algorithm, and finally applying an inverse VST to the denoised data. The generalized Anscombe transformation (GAT) is often used for variance stabilization, but its unbiased inverse transformation has not been rigorously studied in the past. We introduce the exact unbiased inverse of the GAT and show that it plays an integral part in ensuring accurate denoising results. We demonstrate that this exact inverse leads to state-of-the-art results without any notable increase in the computational complexity compared to the other inverses. We also show that this inverse is optimal in the sense that it can be interpreted as a maximum likelihood inverse. Moreover, we thoroughly analyze the behavior of the proposed inverse, which also enables us to derive a closed-form approximation for it. This paper generalizes our work on the exact unbiased inverse of the Anscombe transformation, which we have presented earlier for the removal of pure Poisson noise. PMID:22692910
NASA Astrophysics Data System (ADS)
Li, Ming; Zhao, Wei
2012-12-01
We suggest that there exists a critical point H=0.70 of the local Hölder exponent H(t) for describing the weak stationary (stationary for short) property of the modified multifractional Gaussian noise (mmGn) from the point of view of engineering. More precisely, when H(t)>0.70 for t∈[0,∞], the stationarity of mmGn is conditional, relying on the variation ranges of H(t). When H(t)≤0.70, on the other side, mmGn is unconditionally stationary, yielding a consequence that short-memory mmGn is stationary. In addition, for H(t)>0.70, we introduce the concept of stationary range denoted by (H,H). It means that Corr[r(τ;H(t1)),r(τ;H(t2))]≥0.70 if H(t1), H(t2)∈(H,H), where r(τ;H(t1)) and r(τ;H(t2)) are the autocorrelation functions of mmGn with H(t1) and H(t2) for t1≠t2, respectively, and Corr[r(τ;H(t1)),r(τ;H(t2))] is the correlation coefficient between r(τ;H(t1)) and r(τ;H(t2)). We present a set of stationary ranges, which may be used for a quantitative description of the local stationarity of mmGn. A case study is demonstrated for applying the present method to testing the stationarity of a real-traffic trace.
Raghunathan, Shesha; Brun, Todd A.; Goan, Hsi-Sheng
2010-11-15
A promising technique for measuring single electron spins is magnetic resonance force microscopy (MRFM), in which a microcantilever with a permanent magnetic tip is resonantly driven by a single oscillating spin. The most effective experimental technique is the oscillating cantilever-driven adiabatic reversals (OSCAR) protocol, in which the signal takes the form of a frequency shift. If the quality factor of the cantilever is high enough, this signal will be amplified over time to the point where it can be detected by optical or other techniques. An important requirement, however, is that this measurement process occurs on a time scale that is short compared to any noise which disturbs the orientation of the measured spin. We describe a model of spin noise for the MRFM system and show how this noise is transformed to become time dependent in going to the usual rotating frame. We simplify the description of the cantilever-spin system by approximating the cantilever wave function as a Gaussian wave packet and show that the resulting approximation closely matches the full quantum behavior. We then examine the problem of detecting the signal for a cantilever with thermal noise and spin with spin noise, deriving a condition for this to be a useful measurement.
Quality parameter for coherent transmissions with Gaussian-distributed nonlinear noise.
Grellier, Edouard; Bononi, Alberto
2011-06-20
By assuming the nonlinear noise as a signal-independent circular gaussian noise, a typical case in non-dispersion managed links with coherent multilevel modulation formats, we provide several analytical properties of a new quality parameter--playing the role of the signal to noise ratio (SNR) at the sampling gate in the coherent receiver--which carry over to the Q-factor versus power (or "bell") curves. We show that the maximum Q is reached at an optimal power, the nonlinear threshold, at which the amplified spontaneous emission (ASE) noise power is twice the nonlinear noise power, and the SNR penalty with respect to linear propagation is 10Log(3/2) ≃ 1.76 dB,, although the Q-penalty is somewhat larger and increases at lower Q-factors, as we verify for the polarization-division multiplexing quadrature phase shift keying (PDM-QPSK) format. As we vary the ASE power, the maxima of the SNR vs. power curves are shown to slide along a straight-line with slope ≃-2 dB/dB. A similar behavior is followed by the Q-factor maxima, although for PDM-QPSK the local slope is around -2.7 dB/dB for Q-values of practical interest. PMID:21716520
Watanabe, Ryo; Ogawa, Masato; Mituzono, Hiroki; Aoki, Takahiro; Hayano, Mizuho; Watanabe, Yuka
2010-08-20
In optimizing exposures, it is very important to evaluate the impact of image noise on image quality. To realize this, there is a need to evaluate how much image noise will make the subject disease invisible. But generally it is very difficult to shoot images of different quality in a clinical examination. Thus, a method to create a noise addition image by adding the image noise to raw data has been reported. However, this approach requires a special system, so it is difficult to implement in many facilities. We have invented a method to easily create a noise addition image by using the water phantom and image add-subtract software that accompanies the device. To create a noise addition image, first we made a noise image by subtracting the water phantom with different SD. A noise addition image was then created by adding the noise image to the original image. By using this method, a simulation image with intergraded SD can be created from the original. Moreover, the noise frequency component of the created noise addition image is as same as the real image. Thus, the relationship of image quality to SD in the clinical image can be evaluated. Although this method is an easy method of LDSI creation on image data, a noise addition image can be easily created by using image addition and subtraction software and water phantom, and this can be implemented in many facilities. PMID:20953102
NASA Astrophysics Data System (ADS)
Pesquera, L.; Blanco, R.
1987-04-01
The anharmonic oscillator driven by Gaussian noise is studied in the limit of weak damping using the direct perturbation (DPM) and Markov approximation (MAM) methods. Mean values are obtained to first order in the anharmonic coupling constant g. From a careful treatment of the high-frequency behavior it is concluded that to first order in g the DPM takes high-frequency contributions into account whereas the MAM does not, while both agree if high-frequency contributions are not important. It is also shown that both methods give the same results to second order in g for the quartic anharmonic oscillator. The spectral density of the noise used in stochastic electrodynamics is considered as a particular example.
Reduction of Additive Colored Noise Using Coupled Dynamics
NASA Astrophysics Data System (ADS)
Kohar, Vivek; Kia, Behnam; Lindner, John F.; Ditto, William L.
We study the effect of additive colored noise on the evolution of maps and demonstrate that the deviations caused by such noise can be reduced using coupled dynamics. We consider both Ornstein-Uhlenbeck process as well as 1/fα noise in our numerical simulations. We observe that though the variance of deviations caused by noise depends on the correlations in the noise, under optimal coupling strength, it decreases by a factor equal to the number of coupled elements in the array as compared to the variance of deviations in a single isolated map. This reduction in noise levels occurs in chaotic as well as periodic regime of the maps. Lastly, we examine the effect of colored noise in chaos computing and find that coupling the chaos computing elements enhances the robustness of chaos computing.
Multiplicative noise effects on electroconvection in controlling additive noise by a magnetic field
NASA Astrophysics Data System (ADS)
Huh, Jong-Hoon
2015-12-01
We report multiplicative noise-induced threshold shift of electroconvection (EC) in the presence of a magnetic field H . Controlling the thermal fluctuation (i.e., additive noise) of the rodlike molecules of nematic liquid crystals by H , the EC threshold is examined at various noise levels [characterized by their intensity and cutoff frequency (fc) ]. For a sufficiently strong H (i.e., ignorable additive noise), a modified noise sensitivity characterizing the shift problem is in good agreement with experimental results for colored as well as white noise (fc→∞ ) ; until now, there was a large deviation for (sufficiently) colored noises. The present study shows that H provides us with ideal conditions for studying the corresponding Carr-Helfrich theory considering pure multiplicative noise.
Multiplicative noise effects on electroconvection in controlling additive noise by a magnetic field.
Huh, Jong-Hoon
2015-12-01
We report multiplicative noise-induced threshold shift of electroconvection (EC) in the presence of a magnetic field H. Controlling the thermal fluctuation (i.e., additive noise) of the rodlike molecules of nematic liquid crystals by H, the EC threshold is examined at various noise levels [characterized by their intensity and cutoff frequency (f(c))]. For a sufficiently strong H (i.e., ignorable additive noise), a modified noise sensitivity characterizing the shift problem is in good agreement with experimental results for colored as well as white noise (f(c)→∞); until now, there was a large deviation for (sufficiently) colored noises. The present study shows that H provides us with ideal conditions for studying the corresponding Carr-Helfrich theory considering pure multiplicative noise. PMID:26764708
NASA Technical Reports Server (NTRS)
Simon, M. K.; Huth, G. K.; Polydoros, A.
1982-01-01
Bandwidth-conserving modulation techniques, which trade average power for bandwidth in a favorable exchange, have recently found widespread application in digital radio and satellite communication systems. Quadrature amplitude-shift-keying (QASK) is a particular type of the considered techniques. QASK makes use of multilevel signals to amplitude modulate the in-phase and quadrature components of a carrier. Frequency hopping (FH) is used to protect a conventional communication system from radio frequency interference (RFI) or jamming. Differentially coherent detection provides a possible solution to the effect of phase discontinuities introduced by FH. The application of such a detection technique to QASK signals is discussed. A receiver structure is proposed and its symbol error probability performance for an additive white Gaussian noise (AWGN) background is investigated.
Yang, Sejung; Lee, Byung-Uk
2015-01-01
In certain image acquisitions processes, like in fluorescence microscopy or astronomy, only a limited number of photons can be collected due to various physical constraints. The resulting images suffer from signal dependent noise, which can be modeled as a Poisson distribution, and a low signal-to-noise ratio. However, the majority of research on noise reduction algorithms focuses on signal independent Gaussian noise. In this paper, we model noise as a combination of Poisson and Gaussian probability distributions to construct a more accurate model and adopt the contourlet transform which provides a sparse representation of the directional components in images. We also apply hidden Markov models with a framework that neatly describes the spatial and interscale dependencies which are the properties of transformation coefficients of natural images. In this paper, an effective denoising algorithm for Poisson-Gaussian noise is proposed using the contourlet transform, hidden Markov models and noise estimation in the transform domain. We supplement the algorithm by cycle spinning and Wiener filtering for further improvements. We finally show experimental results with simulations and fluorescence microscopy images which demonstrate the improved performance of the proposed approach. PMID:26352138
Type-A Worst-Case Uncertainty for Gaussian noise instruments
NASA Astrophysics Data System (ADS)
Arpaia, P.; Baccigalupi, C.; Martino, M.
2015-07-01
An analytical type-A approach is proposed for predicting the Worst-Case Uncertainty of a measurement system. In a set of independent observations of the same measurand, modelled as independent- and identically-distributed random variables, the upcoming extreme values (e.g. peaks) can be forecast by only characterizing the measurement system noise level, assumed to be white and Gaussian. Simulation and experimental results are presented to validate the model for a case study on the worst-case repeatability of a pulsed power supply for the klystron modulators of the Compact LInear Collider at CERN. The experimental validation highlights satisfying results for an acquisition system repeatable in the order of ±25 ppm over a bandwidth of 5 MHz.
NASA Astrophysics Data System (ADS)
Jin, X. L.; Huang, Z. L.
The nonstationary probability densities of system responses are obtained for nonlinear multi-degree-of-freedom systems subject to stochastic parametric and external excitations. First, the stochastic averaging method is used to obtain the averaged Itô equation for amplitude envelopes of the system response. Then, the corresponding Fokker-Planck-Kolmogorov equation governing the nonstationary probability density of the amplitude envelopes is deduced. By applying the Galerkin method, the nonstationary probability density can be expressed as a series expansion in terms of a set of orthogonal base functions with time-dependent coefficients. Finally, the nonstationary probability densities for the amplitude response, as well as those for the state-space response, are solved approximately. To illustrate the applicability, the proposed method is applied to a two-degree-of-freedom van der Pol oscillator subject to external excitations of Gaussian white noises.
NASA Astrophysics Data System (ADS)
Er, Guo-Kang
2014-04-01
In this paper, the state-space-split method is extended for the dimension reduction of some high-dimensional Fokker-Planck-Kolmogorov equations or the nonlinear stochastic dynamical systems in high dimensions subject to external excitation which is the filtered Gaussian white noise governed by the second order stochastic differential equation. The selection of sub state variables and then the dimension-reduction procedure for a class of nonlinear stochastic dynamical systems is given when the external excitation is the filtered Gaussian white noise. The stretched Euler-Bernoulli beam with hinge support at two ends, point-spring supports, and excited by uniformly distributed load being filtered Gaussian white noise governed by the second-order stochastic differential equation is analyzed and numerical results are presented. The results obtained with the presented procedure are compared with those obtained with the Monte Carlo simulation and equivalent linearization method to show the effectiveness and advantage of the state-space-split method and exponential polynomial closure method in analyzing the stationary probabilistic solutions of the multi-degree-of-freedom nonlinear stochastic dynamical systems excited by filtered Gaussian white noise.
On stochastic complex beam beam interaction models with Gaussian colored noise
NASA Astrophysics Data System (ADS)
Xu, Yong; Zhang, Huiqing; Xu, Wei
2007-10-01
This paper is to continue our study on complex beam-beam interaction models in particle accelerators with random excitations Y. Xu, W. Xu, G.M. Mahmoud, On a complex beam-beam interaction model with random forcing [Physica A 336 (2004) 347-360]. The random noise is taken as the form of exponentially correlated Gaussian colored noise, and the transition probability density function is obtained in terms of a perturbation expansion of the parameter. Then the method of stochastic averaging based on perturbation technique is used to derive a Fokker-Planck equation for the transition probability density function. The solvability condition and the general transforms using the method of characteristics are proposed to obtain the approximate expressions of probability density function to order ε. Also the exact stationary probability density and the first and second moments of the amplitude are obtained, and one can find when the correlation time equals to zero, the result is identical to that derived from the Stratonovich-Khasminskii theorem for the same model under a broad-band excitation in our previous work.
Modular design and implementation of field-programmable-gate-array-based Gaussian noise generator
NASA Astrophysics Data System (ADS)
Li, Yuan-Ping; Lee, Ta-Sung; Hwang, Jeng-Kuang
2016-05-01
The modular design of a Gaussian noise generator (GNG) based on field-programmable gate array (FPGA) technology was studied. A new range reduction architecture was included in a series of elementary function evaluation modules and was integrated into the GNG system. The approximation and quantisation errors for the square root module with a first polynomial approximation were high; therefore, we used the central limit theorem (CLT) to improve the noise quality. This resulted in an output rate of one sample per clock cycle. We subsequently applied Newton's method for the square root module, thus eliminating the need for the use of the CLT because applying the CLT resulted in an output rate of two samples per clock cycle (>200 million samples per second). Two statistical tests confirmed that our GNG is of high quality. Furthermore, the range reduction, which is used to solve a limited interval of the function approximation algorithms of the System Generator platform using Xilinx FPGAs, appeared to have a higher numerical accuracy, was operated at >350 MHz, and can be suitably applied for any function evaluation.
Xiao, Yanwen; Xu, Wei; Wang, Liang
2016-03-01
This paper focuses on the study of the stochastic Van der Pol vibro-impact system with fractional derivative damping under Gaussian white noise excitation. The equations of the original system are simplified by non-smooth transformation. For the simplified equation, the stochastic averaging approach is applied to solve it. Then, the fractional derivative damping term is facilitated by a numerical scheme, therewith the fourth-order Runge-Kutta method is used to obtain the numerical results. And the numerical simulation results fit the analytical solutions. Therefore, the proposed analytical means to study this system are proved to be feasible. In this context, the effects on the response stationary probability density functions (PDFs) caused by noise excitation, restitution condition, and fractional derivative damping are considered, in addition the stochastic P-bifurcation is also explored in this paper through varying the value of the coefficient of fractional derivative damping and the restitution coefficient. These system parameters not only influence the response PDFs of this system but also can cause the stochastic P-bifurcation. PMID:27036188
NASA Astrophysics Data System (ADS)
Xiao, Yanwen; Xu, Wei; Wang, Liang
2016-03-01
This paper focuses on the study of the stochastic Van der Pol vibro-impact system with fractional derivative damping under Gaussian white noise excitation. The equations of the original system are simplified by non-smooth transformation. For the simplified equation, the stochastic averaging approach is applied to solve it. Then, the fractional derivative damping term is facilitated by a numerical scheme, therewith the fourth-order Runge-Kutta method is used to obtain the numerical results. And the numerical simulation results fit the analytical solutions. Therefore, the proposed analytical means to study this system are proved to be feasible. In this context, the effects on the response stationary probability density functions (PDFs) caused by noise excitation, restitution condition, and fractional derivative damping are considered, in addition the stochastic P-bifurcation is also explored in this paper through varying the value of the coefficient of fractional derivative damping and the restitution coefficient. These system parameters not only influence the response PDFs of this system but also can cause the stochastic P-bifurcation.
Meng, Fan; Yang, Xiaomei; Zhou, Chenghu
2014-01-01
This paper studies the problem of the restoration of images corrupted by mixed Gaussian-impulse noise. In recent years, low-rank matrix reconstruction has become a research hotspot in many scientific and engineering domains such as machine learning, image processing, computer vision and bioinformatics, which mainly involves the problem of matrix completion and robust principal component analysis, namely recovering a low-rank matrix from an incomplete but accurate sampling subset of its entries and from an observed data matrix with an unknown fraction of its entries being arbitrarily corrupted, respectively. Inspired by these ideas, we consider the problem of recovering a low-rank matrix from an incomplete sampling subset of its entries with an unknown fraction of the samplings contaminated by arbitrary errors, which is defined as the problem of matrix completion from corrupted samplings and modeled as a convex optimization problem that minimizes a combination of the nuclear norm and the l(1)-norm in this paper. Meanwhile, we put forward a novel and effective algorithm called augmented Lagrange multipliers to exactly solve the problem. For mixed Gaussian-impulse noise removal, we regard it as the problem of matrix completion from corrupted samplings, and restore the noisy image following an impulse-detecting procedure. Compared with some existing methods for mixed noise removal, the recovery quality performance of our method is dominant if images possess low-rank features such as geometrically regular textures and similar structured contents; especially when the density of impulse noise is relatively high and the variance of Gaussian noise is small, our method can outperform the traditional methods significantly not only in the simultaneous removal of Gaussian noise and impulse noise, and the restoration ability for a low-rank image matrix, but also in the preservation of textures and details in the image. PMID:25248103
Threshold detection in generalized non-additive signals and noise
Middleton, D., LLNL
1997-12-22
The classical theory of optimum (binary-on-off) threshold detection for additive signals and generalized (i.e. nongaussian) noise is extended to the canonical nonadditive threshold situation. In the important (and usual) applications where the noise is sampled independently, a canonical threshold optimum theory is outlined here, which is found formally to parallel the earlier additive theory, including the critical properties of locally optimum Bayes detection algorithms, which are asymptotically normal and optimum as well. The important Class A clutter model provides an explicit example of optimal threshold envelope detection, for the non-additive cases of signal and noise. Various extensions are noted in the concluding section, as are selected references.
NASA Astrophysics Data System (ADS)
Hao, Meng-Li; Xu, Wei; Li, Dong-Xi; Liu, Di
2014-05-01
The extinction phenomenon induced by multiplicative non-Gaussian Lévy noise in a tumor growth model with immune response is discussed. Under the influence of the stochastic immune rate, the model is analyzed in terms of a stochastic differential equation with multiplicative noise. By means of the theory of the infinitesimal generator of Hunt processes, the escape probability, which is used to measure the noise-induced extinction probability of tumor cells, is explicitly expressed as a function of initial tumor cell density, stability index and noise intensity. Based on the numerical calculations, it is found that for different initial densities of tumor cells, noise parameters play opposite roles on the escape probability. The optimally selected values of the multiplicative noise intensity and the stability index are found to maximize the escape probability.
Role of time delay on intracellular calcium dynamics driven by non-Gaussian noises
Duan, Wei-Long; Zeng, Chunhua
2016-01-01
Effect of time delay (τ) on intracellular calcium dynamics with non-Gaussian noises in transmission processes of intracellular Ca2+ is studied by means of second-order stochastic Runge-Kutta type algorithm. By simulating and analyzing time series, normalized autocorrelation function, and characteristic correlation time of cytosolic and calcium store’s Ca2+ concentration, the results exhibit: (i) intracellular calcium dynamics’s time coherence disappears and stability strengthens as τ → 0.1s; (ii) for the case of τ < 0.1s, the normalized autocorrelation functions of cytosolic and calcium store’s Ca2+ concentration show damped motion when τ is very short, but they trend to a level line as τ → 0.1s, and for the case of τ > 0.1s, they show different variation as τ increases, the former changes from underdamped motion to a level line, but the latter changes from damped motion to underdamped motion; and (iii) at the moderate value of time delay, reverse resonance occurs both in cytosol and calcium store. PMID:27121687
Role of time delay on intracellular calcium dynamics driven by non-Gaussian noises.
Duan, Wei-Long; Zeng, Chunhua
2016-01-01
Effect of time delay (τ) on intracellular calcium dynamics with non-Gaussian noises in transmission processes of intracellular Ca(2+) is studied by means of second-order stochastic Runge-Kutta type algorithm. By simulating and analyzing time series, normalized autocorrelation function, and characteristic correlation time of cytosolic and calcium store's Ca(2+) concentration, the results exhibit: (i) intracellular calcium dynamics's time coherence disappears and stability strengthens as τ → 0.1s; (ii) for the case of τ < 0.1s, the normalized autocorrelation functions of cytosolic and calcium store's Ca(2+) concentration show damped motion when τ is very short, but they trend to a level line as τ → 0.1s, and for the case of τ > 0.1s, they show different variation as τ increases, the former changes from underdamped motion to a level line, but the latter changes from damped motion to underdamped motion; and (iii) at the moderate value of time delay, reverse resonance occurs both in cytosol and calcium store. PMID:27121687
Role of time delay on intracellular calcium dynamics driven by non-Gaussian noises
NASA Astrophysics Data System (ADS)
Duan, Wei-Long; Zeng, Chunhua
2016-04-01
Effect of time delay (τ) on intracellular calcium dynamics with non-Gaussian noises in transmission processes of intracellular Ca2+ is studied by means of second-order stochastic Runge-Kutta type algorithm. By simulating and analyzing time series, normalized autocorrelation function, and characteristic correlation time of cytosolic and calcium store’s Ca2+ concentration, the results exhibit: (i) intracellular calcium dynamics’s time coherence disappears and stability strengthens as τ → 0.1s (ii) for the case of τ < 0.1s, the normalized autocorrelation functions of cytosolic and calcium store’s Ca2+ concentration show damped motion when τ is very short, but they trend to a level line as τ → 0.1s, and for the case of τ > 0.1s, they show different variation as τ increases, the former changes from underdamped motion to a level line, but the latter changes from damped motion to underdamped motion; and (iii) at the moderate value of time delay, reverse resonance occurs both in cytosol and calcium store.
NASA Astrophysics Data System (ADS)
Kishan, Harini; Seelamantula, Chandra Sekhar
2015-09-01
We propose optimal bilateral filtering techniques for Gaussian noise suppression in images. To achieve maximum denoising performance via optimal filter parameter selection, we adopt Stein's unbiased risk estimate (SURE)-an unbiased estimate of the mean-squared error (MSE). Unlike MSE, SURE is independent of the ground truth and can be used in practical scenarios where the ground truth is unavailable. In our recent work, we derived SURE expressions in the context of the bilateral filter and proposed SURE-optimal bilateral filter (SOBF). We selected the optimal parameters of SOBF using the SURE criterion. To further improve the denoising performance of SOBF, we propose variants of SOBF, namely, SURE-optimal multiresolution bilateral filter (SMBF), which involves optimal bilateral filtering in a wavelet framework, and SURE-optimal patch-based bilateral filter (SPBF), where the bilateral filter parameters are optimized on small image patches. Using SURE guarantees automated parameter selection. The multiresolution and localized denoising in SMBF and SPBF, respectively, yield superior denoising performance when compared with the globally optimal SOBF. Experimental validations and comparisons show that the proposed denoisers perform on par with some state-of-the-art denoising techniques.
NASA Astrophysics Data System (ADS)
Ryu, Ji-Woo; Lee, Seon-Oh; Sim, Dong-Gyu; Han, Jong-Ki
2012-02-01
We present a no-reference peak signal to noise ratio (PSNR) estimation algorithm based on discrete cosine transform (DCT) coefficient distributions from H.264/MPEG-4 part 10 advanced video codec (H.264/AVC) bitstreams. To estimate the PSNR of a compressed picture without the original picture on the decoder side, it is important to model the distribution of transform coefficients obtained from quantized coefficients accurately. Whereas several conventional algorithms use the Laplacian or Cauchy distribution to model the DCT coefficient distribution, the proposed algorithm uses a generalized Gaussian distribution. Pearson's χ2 (chi-square) test was applied to show that the generalized Gaussian distribution is more appropriate than the other models for modeling the transform coefficients. The χ2 test was also used to find optimum parameters for the generalized Gaussian model. It was found that the generalized Gaussian model improves the accuracy of the DCT coefficient distribution, thus reducing the mean squared error between the real and the estimated PSNR.
NASA Astrophysics Data System (ADS)
Coelho, A. S.; Barbosa, F. A. S.; Cassemiro, K. N.; Martinelli, M.; Villar, A. S.; Nussenzveig, P.
2015-07-01
Gaussian quantum states hold special importance in the continuous variable regime. In quantum information science, the understanding and characterization of central resources such as entanglement may strongly rely on the knowledge of the Gaussian or non-Gaussian character of the quantum state. However, the quantum measurement associated with the spectral photocurrent of light modes consists of a mixture of quadrature observables. Within the framework of two recent papers [Phys. Rev. A 88, 052113 (2013), 10.1103/PhysRevA.88.052113 and Phys. Rev. Lett. 111, 200402 (2013), 10.1103/PhysRevLett.111.200402], we address here how the statistics of the spectral photocurrent relates to the character of the Wigner function describing those modes. We show that a Gaussian state can be misidentified as non-Gaussian and vice versa, a conclusion that forces the adoption of tacit a priori assumptions to perform quantum state reconstruction. We experimentally analyze the light beams generated by the optical parametric oscillator operating above threshold to show that the data strongly supports the generation of Gaussian states of the field, validating the use of necessary and sufficient criteria to characterize entanglement in this system.
Non-Gaussian noise in x-ray and γ-ray detectors
NASA Astrophysics Data System (ADS)
Chen, Liying; Barrett, Harrison H.
2005-04-01
Image statistics are usually modeled as Poisson in γ-ray imaging and as Gaussian in x-ray imaging. In nuclear medicine, event-driven detectors analyze the pulses from every absorbed gamma photon individually; the resulting images rigorously obey Poisson statistics but are approximately Gaussian when the mean number of counts per pixel is large. With integrating detectors, as in digital radiography, each x-ray photon makes a contribution to the image proportional to its pulse height. One pixel senses many photons in long exposures, so the image statistics approach Gaussian by the central limit theorem (CLT). If the exposure time is short enough, however, each pixel will usually respond to no more than one photon, and we can separate individual photons for position estimation. Integrating detectors are therefore event-driven when we use many short-exposure frames rather than one long exposure. In intermediate exposures, the number of photons in one pixel is too small to invoke CLT and apply Gaussian statistics, yet too large to identify individual photons and apply Poisson statistics. In this paper, we analyze the image quality in this intermediate case. Image quality is defined for detection tasks performed by the ideal observer. Because the frames in a data set are independent of each other, the probability density function (PDF) of the whole data set is a product of the frame PDFs. The log-likelihood ratio λ of the ideal observer is thus a sum across the frames and has Gaussian statistics even with non-Gaussian images. We compare the ideal observer's performance with the Hotelling observer's performance under this approximation. A data-thresholding technique to improve Hotelling observer's performance is also discussed.
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.
NASA Astrophysics Data System (ADS)
Pratim Ghosh, Arghya; Mandal, Arkajit; Sarkar, Sucharita; Ghosh, Manas
2016-05-01
We examine the influence of position-dependent effective mass (PDEM) on a few nonlinear optical (NLO) properties of impurity doped quantum dots (QDs) in presence and absence of noise. The said properties include total optical absorption coefficient (TOAC), nonlinear optical rectification (NOR), second harmonic generation (SHG) and third harmonic generation (THG). The impurity potential is modeled by a Gaussian function and the noise applied being Gaussian white noise. The profiles of above NLO properties have been pursued as a function of incident photon energy for different values of PDEM. Using PDEM the said profiles exhibit considerable departure from that of fixed effective mass (FEM). Presence of noise almost invariably amplifies the NLO properties with a few exceptions. A change in the mode of application of noise also sometimes affects the above profiles. The investigation furnishes us with a detailed picture of the subtle interplay between noise and PDEM through which the said NLO properties of doped QD systems can be tailored.
NASA Astrophysics Data System (ADS)
Yong-Ge, Yang; Wei, Xu; Ya-Hui, Sun; Xu-Dong, Gu
2016-02-01
This paper aims to investigate the stochastic response of the van der Pol (VDP) oscillator with two kinds of fractional derivatives under Gaussian white noise excitation. First, the fractional VDP oscillator is replaced by an equivalent VDP oscillator without fractional derivative terms by using the generalized harmonic balance technique. Then, the stochastic averaging method is applied to the equivalent VDP oscillator to obtain the analytical solution. Finally, the analytical solutions are validated by numerical results from the Monte Carlo simulation of the original fractional VDP oscillator. The numerical results not only demonstrate the accuracy of the proposed approach but also show that the fractional order, the fractional coefficient and the intensity of Gaussian white noise play important roles in the responses of the fractional VDP oscillator. An interesting phenomenon we found is that the effects of the fractional order of two kinds of fractional derivative items on the fractional stochastic systems are totally contrary. Project supported by the National Natural Science Foundation of China (Grant Nos. 11472212, 11532011, and 11502201).
An Improved Edge Detection Method for Image Corrupted by Gaussian Noise
NASA Astrophysics Data System (ADS)
Wang, Xiao; Xue, Hui
Due to the difficulty with extracting edge points and eliminating noise points from images, an improved maximizing objective function algorithm was proposed. More directions were added to relocate the edge points, at the same time, edge and noise characteristics were analyzed to separate and the noise points were eliminated by a proper threshold T. The comparison based on principle of the improved method, classical methods and the references methods is done, the simulation results indicated that the performance of the improved edge detection method was better than that of other compared algorithms.
NASA Technical Reports Server (NTRS)
Dembo, Amir
1989-01-01
Pinsker and Ebert (1970) proved that in channels with additive Gaussian noise, feedback at most doubles the capacity. Cover and Pombra (1989) proved that feedback at most adds half a bit per transmission. Following their approach, the author proves that in the limit as signal power approaches either zero (very low SNR) or infinity (very high SNR), feedback does not increase the finite block-length capacity (which for nonstationary Gaussian channels replaces the standard notion of capacity that may not exist). Tighter upper bounds on the capacity are obtained in the process. Specializing these results to stationary channels, the author recovers some of the bounds recently obtained by Ozarow.
NASA Astrophysics Data System (ADS)
Jia, Wantao; Zhu, Weiqiu
2014-03-01
A stochastic averaging method for predicting the response of quasi-partially integrable and non-resonant Hamiltonian systems to combined Gaussian and Poisson white noise excitations is proposed. For the case with r (1
Hirata, Christopher M.; Cutler, Curt
2010-06-15
Gravitational wave sources are a promising cosmological standard candle because their intrinsic luminosities are determined by fundamental physics (and are insensitive to dust extinction). They are, however, affected by weak lensing magnification due to the gravitational lensing from structures along the line of sight. This lensing is a source of uncertainty in the distance determination, even in the limit of perfect standard candle measurements. It is commonly believed that the uncertainty in the distance to an ensemble of gravitational wave sources is limited by the standard deviation of the lensing magnification distribution divided by the square root of the number of sources. Here we show that by exploiting the non-Gaussian nature of the lensing magnification distribution, we can improve this distance determination, typically by a factor of 2-3; we provide a fitting formula for the effective distance accuracy as a function of redshift for sources where the lensing noise dominates.
NASA Astrophysics Data System (ADS)
Ramon, Guy
2015-10-01
The effects of a collection of classical two-level charge fluctuators on the coherence of a dynamically decoupled qubit are studied. Distinct dynamics is found at different qubit working positions. Exact analytical formulas are derived at pure dephasing and approximate solutions are found at the general working position, for weakly and strongly coupled fluctuators. Analysis of these solutions, combined with numerical simulations of the multiple random telegraph processes, reveal the scaling of the noise with the number of fluctuators and the number of control pulses, as well as dependence on other parameters of the qubit-fluctuators system. These results can be used to determine potential microscopic models for the charge environment by performing noise spectroscopy.
Effect of multiplicative and additive noise on genetic transcriptional regulatory mechanism
NASA Astrophysics Data System (ADS)
Liu, Xue-Mei; Xie, Hui-Zhang; Liu, Liang-Gang; Li, Zhi-Bing
2009-02-01
A multiplicative noise and an additive noise are introduced in the kinetic model of Smolen-Baxter-Byrne [P. Smolen, D.A. Baxter, J.H. Byrne, Amer. J. Physiol. Cell. Physiol. 274 (1998) 531], in which the expression of gene is controlled by protein concentration of transcriptional activator. The Fokker-Planck equation is solved and the steady-state probability distribution is obtained numerically. It is found that the multiplicative noise converts the bistability to monostability that can be regarded as a noise-induced transition. The additive noise reduces the transcription efficiency. The correlation between the multiplicative noise and the additive noise works as a genetic switch and regulates the gene transcription effectively.
NASA Astrophysics Data System (ADS)
Barillec, Remi; Ingram, Ben; Cornford, Dan; Csató, Lehel
2011-03-01
Heterogeneous datasets arise naturally in most applications due to the use of a variety of sensors and measuring platforms. Such datasets can be heterogeneous in terms of the error characteristics and sensor models. Treating such data is most naturally accomplished using a Bayesian or model-based geostatistical approach; however, such methods generally scale rather badly with the size of dataset, and require computationally expensive Monte Carlo based inference. Recently within the machine learning and spatial statistics communities many papers have explored the potential of reduced rank representations of the covariance matrix, often referred to as projected or fixed rank approaches. In such methods the covariance function of the posterior process is represented by a reduced rank approximation which is chosen such that there is minimal information loss. In this paper a sequential Bayesian framework for inference in such projected processes is presented. The observations are considered one at a time which avoids the need for high dimensional integrals typically required in a Bayesian approach. A C++ library, gptk, which is part of the INTAMAP web service, is introduced which implements projected, sequential estimation and adds several novel features. In particular the library includes the ability to use a generic observation operator, or sensor model, to permit data fusion. It is also possible to cope with a range of observation error characteristics, including non-Gaussian observation errors. Inference for the covariance parameters is explored, including the impact of the projected process approximation on likelihood profiles. We illustrate the projected sequential method in application to synthetic and real datasets. Limitations and extensions are discussed.
NASA Astrophysics Data System (ADS)
Martellini, Lionel; Regimbau, Tania
2015-11-01
Under standard assumptions including stationary and serially uncorrelated Gaussian gravitational wave stochastic background signal and noise distributions, as well as homogenous detector sensitivities, the standard cross-correlation detection statistic is known to be optimal in the sense of minimizing the probability of a false dismissal at a fixed value of the probability of a false alarm. The focus of this paper is to analyze the comparative efficiency of this statistic, vs a simple alternative statistic obtained by cross-correlating the squared measurements, in situations that deviate from such standard assumptions. We find that differences in detector sensitivities have a large impact on the comparative efficiency of the cross-correlation detection statistic, which is dominated by the alternative statistic when these differences reach 1 order of magnitude. This effect holds even when both the signal and noise distributions are Gaussian. While the presence of non-Gaussian signals has no material impact for reasonable parameter values, the relative inefficiency of the cross-correlation statistic is less prominent for fat-tailed noise distributions, but it is magnified in case noise distributions have skewness parameters of opposite signs. Our results suggest that introducing an alternative detection statistic can lead to noticeable sensitivity gains when noise distributions are possibly non-Gaussian and/or when detector sensitivities exhibit substantial differences, a situation that is expected to hold in joint detections from Advanced LIGO and Advanced Virgo, in particular in the early phases of development of the detectors, or in joint detections from Advanced LIGO and the Einstein Telescope.
NASA Astrophysics Data System (ADS)
Almeida, Telmo P.; Drummond, Miguel V.; Pavlović, Natasa B.; André, Paulo S.; Nogueira, Rogério N.
2014-08-01
Of all the non-linear fiber propagation models proposed over the years, the Gaussian Noise (GN) model is growing in popularity due to its simplicity and yet reliability when it comes to predict performance of uncompensated coherent transmission (UT) systems that rely on state-of-the art digital-signal processing (DSP) for dispersion compensation. However, many of the systems currently deployed rely on optical CD compensation. Overhauling or upgrading these systems with the most recent DSP is not always feasible. In this context, it is important to broad the range of the GNmodel to dispersion managed (DM) systems, so both scenarios can benefit from a low complexity, fast and reliable performance prediction tool. In this paper, we validate the first results comparing the performance in both accuracy and simulation time of the GN model simulating a realistic DM scenario that relies on periodical spans of non-dispersion shifted fiber (NDSF) to perform the dispersion compensation. The same realistic scenarios were modeled with commercial software and the GN model. The objective was to predict the optimal launch power for different link lengths, central wavelengths and channel spacing values. Preliminary results obtained with the GN model are in good agreement with the ones from the commercial software for several link distances tested up to 2400 Km.
Schäfer, Joachim; Karpov, Evgueni; Cerf, Nicolas J.
2014-12-04
We seek for a realistic implementation of multimode Gaussian entangled states that can realize the optimal encoding for quantum bosonic Gaussian channels with memory. For a Gaussian channel with classical additive Markovian correlated noise and a lossy channel with non-Markovian correlated noise, we demonstrate the usefulness using Gaussian matrix-product states (GMPS). These states can be generated sequentially, and may, in principle, approximate well any Gaussian state. We show that we can achieve up to 99.9% of the classical Gaussian capacity with GMPS requiring squeezing parameters that are reachable with current technology. This may offer a way towards an experimental realization.
Gaussian Decomposition of Laser Altimeter Waveforms
NASA Technical Reports Server (NTRS)
Hofton, Michelle A.; Minster, J. Bernard; Blair, J. Bryan
1999-01-01
We develop a method to decompose a laser altimeter return waveform into its Gaussian components assuming that the position of each Gaussian within the waveform can be used to calculate the mean elevation of a specific reflecting surface within the laser footprint. We estimate the number of Gaussian components from the number of inflection points of a smoothed copy of the laser waveform, and obtain initial estimates of the Gaussian half-widths and positions from the positions of its consecutive inflection points. Initial amplitude estimates are obtained using a non-negative least-squares method. To reduce the likelihood of fitting the background noise within the waveform and to minimize the number of Gaussians needed in the approximation, we rank the "importance" of each Gaussian in the decomposition using its initial half-width and amplitude estimates. The initial parameter estimates of all Gaussians ranked "important" are optimized using the Levenburg-Marquardt method. If the sum of the Gaussians does not approximate the return waveform to a prescribed accuracy, then additional Gaussians are included in the optimization procedure. The Gaussian decomposition method is demonstrated on data collected by the airborne Laser Vegetation Imaging Sensor (LVIS) in October 1997 over the Sequoia National Forest, California.
A laboratory study of the perceived benefit of additional noise attenuation by houses
NASA Technical Reports Server (NTRS)
Flindell, I. H.
1983-01-01
Two Experiments were conducted to investigate the perceived benefit of additional house attenuation against aircraft flyover noise. First, subjects made annoyance judgments in a simulated living room while an operative window with real and dummy storm windows was manipulated in full view of those subjects. Second, subjects made annoyance judgments in an anechoic audiometric test chamber of frequency shaped noise signals having spectra closely matched to those of the aircraft flyover noises reproduced in the first experiment. These stimuli represented the aircraft flyover noises in levels and spectra but without the situational and visual cues present in the simulated living room. Perceptual constancy theory implies that annoyance tends to remain constant despite reductions in noise level caused by additional attenuation of which the subjects are fully aware. This theory was supported when account was taken for a reported annoyance overestimation for certain spectra and for a simulated condition cue overreaction.
Kastelein, Ronald A; Wensveen, Paul J; Hoek, Lean; Au, Whitlow W L; Terhune, John M; de Jong, Christ A F
2009-09-01
A psychoacoustic behavioral technique was used to determine the critical ratios (CRs) of two harbor porpoises for tonal signals with frequencies between 0.315 and 150 kHz, in random Gaussian white noise. The masked 50% detection hearing thresholds were measured using a "go/no-go" response paradigm and an up-down staircase psychometric method. CRs were determined at one masking noise level for each test frequency and were similar in both animals. For signals between 0.315 and 4 kHz, the CRs were relatively constant at around 18 dB. Between 4 and 150 kHz the CR increased gradually from 18 to 39 dB ( approximately 3.3 dB/octave). Generally harbor porpoises can detect tonal signals in Gaussian white noise slightly better than most odontocetes tested so far. By combining the mean CRs found in the present study with the spectrum level of the background noise levels at sea, the basic audiogram, and the directivity index, the detection threshold levels of harbor porpoises for tonal signals in various sea states can be calculated. PMID:19739772
Himemoto, Yoshiaki; Hiramatsu, Takashi; Taruya, Atsushi; Kudoh, Hideaki
2007-01-15
We discuss a robust data analysis method to detect a stochastic background of gravitational waves in the presence of non-Gaussian noise. In contrast to the standard cross-correlation (SCC) statistic frequently used in the stochastic background searches, we consider a generalized cross-correlation (GCC) statistic, which is nearly optimal even in the presence of non-Gaussian noise. The detection efficiency of the GCC statistic is investigated analytically, particularly focusing on the statistical relation between the false-alarm and the false-dismissal probabilities, and the minimum detectable amplitude of gravitational-wave signals. We derive simple analytic formulas for these statistical quantities. The robustness of the GCC statistic is clarified based on these formulas, and one finds that the detection efficiency of the GCC statistic roughly corresponds to the one of the SCC statistic neglecting the contribution of non-Gaussian tails. This remarkable property is checked by performing the Monte Carlo simulations and successful agreement between analytic and simulation results was found.
NASA Technical Reports Server (NTRS)
Lokshin, A.; Olsen, E. T.
1984-01-01
The scalloping problem for the case of Gaussian noise statistics is analyzed. The optimal weighting strategy for linearly combining two observations in adjacent beam areas is derived, and the sensitivity and scalloping for this weighting strategy are compared with those realized using a single observation or using equal weighting of two observations. The variation of the probability for detecting ETI signals with scan separation are calculated for the various weighting strategies, assuming that the transmitters are of equal strength and are uniformly distributed throughout space.
George: Gaussian Process regression
NASA Astrophysics Data System (ADS)
Foreman-Mackey, Daniel
2015-11-01
George is a fast and flexible library, implemented in C++ with Python bindings, for Gaussian Process regression useful for accounting for correlated noise in astronomical datasets, including those for transiting exoplanet discovery and characterization and stellar population modeling.
Equivalence of time and aperture domain additive noise in ultrasound coherence
Bottenus, Nick B.; Trahey, Gregg E.
2015-01-01
Ultrasonic echoes backscattered from diffuse media, recorded by an array transducer and appropriately focused, demonstrate coherence predicted by the van Cittert–Zernike theorem. Additive noise signals from off-axis scattering, reverberation, phase aberration, and electronic (thermal) noise can all superimpose incoherent or partially coherent signals onto the recorded echoes, altering the measured coherence. An expression is derived to describe the effect of uncorrelated random channel noise in terms of the noise-to-signal ratio. Equivalent descriptions are made in the aperture dimension to describe uncorrelated magnitude and phase apodizations of the array. Binary apodization is specifically described as an example of magnitude apodization and adjustments are presented to minimize the artifacts caused by finite signal length. The effects of additive noise are explored in short-lag spatial coherence imaging, an image formation technique that integrates the calculated coherence curve of acquired signals up to a small fraction of the array length for each lateral and axial location. A derivation of the expected contrast as a function of noise-to-signal ratio is provided and validation is performed in simulation. PMID:25618045
A stochastic multi-symplectic scheme for stochastic Maxwell equations with additive noise
Hong, Jialin; Zhang, Liying
2014-07-01
In this paper we investigate a stochastic multi-symplectic method for stochastic Maxwell equations with additive noise. Based on the stochastic version of variational principle, we find a way to obtain the stochastic multi-symplectic structure of three-dimensional (3-D) stochastic Maxwell equations with additive noise. We propose a stochastic multi-symplectic scheme and show that it preserves the stochastic multi-symplectic conservation law and the local and global stochastic energy dissipative properties, which the equations themselves possess. Numerical experiments are performed to verify the numerical behaviors of the stochastic multi-symplectic scheme.
NB-PLC channel modelling with cyclostationary noise addition & OFDM implementation for smart grid
NASA Astrophysics Data System (ADS)
Thomas, Togis; Gupta, K. K.
2016-03-01
Power line communication (PLC) technology can be a viable solution for the future ubiquitous networks because it provides a cheaper alternative to other wired technology currently being used for communication. In smart grid Power Line Communication (PLC) is used to support communication with low rate on low voltage (LV) distribution network. In this paper, we propose the channel modelling of narrowband (NB) PLC in the frequency range 5 KHz to 500 KHz by using ABCD parameter with cyclostationary noise addition. Behaviour of the channel was studied by the addition of 11KV/230V transformer, by varying load location and load. Bit error rate (BER) Vs signal to noise ratio SNR) was plotted for the proposed model by employing OFDM. Our simulation results based on the proposed channel model show an acceptable performance in terms of bit error rate versus signal to noise ratio, which enables communication required for smart grid applications.
Random attractors for the stochastic coupled fractional Ginzburg-Landau equation with additive noise
Shu, Ji E-mail: 530282863@qq.com; Li, Ping E-mail: 530282863@qq.com; Zhang, Jia; Liao, Ou
2015-10-15
This paper is concerned with the stochastic coupled fractional Ginzburg-Landau equation with additive noise. We first transform the stochastic coupled fractional Ginzburg-Landau equation into random equations whose solutions generate a random dynamical system. Then we prove the existence of random attractor for random dynamical system.
Adjustment on subjective annoyance of low frequency noise by adding additional sound
NASA Astrophysics Data System (ADS)
Di, Guo-qing; Li, Zheng-guang; Zhang, Bang-jun; Shi, Yao
2011-11-01
Structure-borne noise originating from a heat pump unit was selected to study the influence on subjective annoyance of low frequency noise (LFN) combined with additional sound. Paired comparison test was used for evaluating the subjective annoyance of LFN combined with different sound pressure levels (SPL) of pink noise, frequency-modulated pure tones (FM pure tones) and natural sounds. The results showed that, with pink noise of 250-1000 Hz combined with the original LFN, the subjective annoyance value (SAV) first dropped then rose with increasing SPL. When SPL of the pink noise was 15-25 dB, SAV was lower than that of the original LFN. With pink noise of frequency 250-20,000 Hz added to LFN, SAV increased linearly with increasing SPL. SAV and the psychoacoustic annoyance value (PAV) obtained by semi-theoretical formulas were well correlated. The determination coefficient ( R2) was 0.966 and 0.881, respectively, when the frequency range of the pink noise was 250-1000 and 250-20,000 Hz. When FM pure tones with central frequencies of 500, 2000 and 8000 Hz, or natural sounds (including the sound of singing birds, flowing water, wind or ticking clock) were, respectively, added to the original sound, the SAV increased as the SPL of the added sound increased. However, when a FM pure tone of 15 dB with a central frequency of 2000 Hz and a modulation frequency of 10 Hz was added, the SAV was lower than that of the original LFN. With SPL and central frequency held invariable, the SAV declined primarily when modulation frequency increased. With SPL and modulation frequency held invariable, the SAV became lowest when the central frequency was 2000 Hz. This showed a preferable correlation between SAV and fluctuation extent of FM pure tones.
Yang Kai; Huang, Shih-Ying; Packard, Nathan J.; Boone, John M.
2010-07-15
Purpose: A simplified linear model approach was proposed to accurately model the response of a flat panel detector used for breast CT (bCT). Methods: Individual detector pixel mean and variance were measured from bCT projection images acquired both in air and with a polyethylene cylinder, with the detector operating in both fixed low gain and dynamic gain mode. Once the coefficients of the linear model are determined, the fractional additive noise can be used as a quantitative metric to evaluate the system's efficiency in utilizing x-ray photons, including the performance of different gain modes of the detector. Results: Fractional additive noise increases as the object thickness increases or as the radiation dose to the detector decreases. For bCT scan techniques on the UC Davis prototype scanner (80 kVp, 500 views total, 30 frames/s), in the low gain mode, additive noise contributes 21% of the total pixel noise variance for a 10 cm object and 44% for a 17 cm object. With the dynamic gain mode, additive noise only represents approximately 2.6% of the total pixel noise variance for a 10 cm object and 7.3% for a 17 cm object. Conclusions: The existence of the signal-independent additive noise is the primary cause for a quadratic relationship between bCT noise variance and the inverse of radiation dose at the detector. With the knowledge of the additive noise contribution to experimentally acquired images, system modifications can be made to reduce the impact of additive noise and improve the quantum noise efficiency of the bCT system.
NASA Astrophysics Data System (ADS)
Azad, Nasser L.; Mozaffari, Ahmad
2015-12-01
The main scope of the current study is to develop a systematic stochastic model to capture the undesired uncertainty and random noises on the key parameters affecting the catalyst temperature over the coldstart operation of automotive engine systems. In the recent years, a number of articles have been published which aim at the modeling and analysis of automotive engines' behavior during coldstart operations by using regression modeling methods. Regarding highly nonlinear and uncertain nature of the coldstart operation, calibration of the engine system's variables, for instance the catalyst temperature, is deemed to be an intricate task, and it is unlikely to develop an exact physics-based nonlinear model. This encourages automotive engineers to take advantage of knowledge-based modeling tools and regression approaches. However, there exist rare reports which propose an efficient tool for coping with the uncertainty associated with the collected database. Here, the authors introduce a random noise to experimentally derived data and simulate an uncertain database as a representative of the engine system's behavior over coldstart operations. Then, by using a Gaussian process regression machine (GPRM), a reliable model is used for the sake of analysis of the engine's behavior. The simulation results attest the efficacy of GPRM for the considered case study. The research outcomes confirm that it is possible to develop a practical calibration tool which can be reliably used for modeling the catalyst temperature.
Mohamed Salleh, Faridah Hani; Arif, Shereena Mohd; Zainudin, Suhaila; Firdaus-Raih, Mohd
2015-12-01
A gene regulatory network (GRN) is a large and complex network consisting of interacting elements that, over time, affect each other's state. The dynamics of complex gene regulatory processes are difficult to understand using intuitive approaches alone. To overcome this problem, we propose an algorithm for inferring the regulatory interactions from knock-out data using a Gaussian model combines with Pearson Correlation Coefficient (PCC). There are several problems relating to GRN construction that have been outlined in this paper. We demonstrated the ability of our proposed method to (1) predict the presence of regulatory interactions between genes, (2) their directionality and (3) their states (activation or suppression). The algorithm was applied to network sizes of 10 and 50 genes from DREAM3 datasets and network sizes of 10 from DREAM4 datasets. The predicted networks were evaluated based on AUROC and AUPR. We discovered that high false positive values were generated by our GRN prediction methods because the indirect regulations have been wrongly predicted as true relationships. We achieved satisfactory results as the majority of sub-networks achieved AUROC values above 0.5. PMID:26278974
Gaussian entanglement of formation
Wolf, M.M.; Giedke, G.; Krueger, O.; Werner, R. F.; Cirac, J.I.
2004-05-01
We introduce a Gaussian version of the entanglement of formation adapted to bipartite Gaussian states by considering decompositions into pure Gaussian states only. We show that this quantity is an entanglement monotone under Gaussian operations and provide a simplified computation for states of arbitrary many modes. For the case of one mode per site the remaining variational problem can be solved analytically. If the considered state is in addition symmetric with respect to interchanging the two modes, we prove additivity of the considered entanglement measure. Moreover, in this case and considering only a single copy, our entanglement measure coincides with the true entanglement of formation.
NASA Astrophysics Data System (ADS)
Lankinen, Juho; Lyyra, Henri; Sokolov, Boris; Teittinen, Jose; Ziaei, Babak; Maniscalco, Sabrina
2016-05-01
We present a general model of qubit dynamics which entails pure dephasing and dissipative time-local master equations. This allows us to describe the combined effect of thermalization and dephasing beyond the usual Markovian approximation. We investigate the complete positivity conditions and introduce a heuristic model that is always physical and provides the correct Markovian limit. We study the effects of temperature on the non-Markovian behavior of the system and show that the noise additivity property discussed by Yu and Eberly [Phys. Rev. Lett. 97, 140403 (2006), 10.1103/PhysRevLett.97.140403] holds beyond the Markovian limit.
Noise is all around you, from televisions and radios to lawn mowers and washing machines. Normally, you ... sensitive structures of the inner ear and cause noise-induced hearing loss. More than 30 million Americans ...
Breaking Gaussian incompatibility on continuous variable quantum systems
Heinosaari, Teiko; Kiukas, Jukka; Schultz, Jussi
2015-08-15
We characterise Gaussian quantum channels that are Gaussian incompatibility breaking, that is, transform every set of Gaussian measurements into a set obtainable from a joint Gaussian observable via Gaussian postprocessing. Such channels represent local noise which renders measurements useless for Gaussian EPR-steering, providing the appropriate generalisation of entanglement breaking channels for this scenario. Understanding the structure of Gaussian incompatibility breaking channels contributes to the resource theory of noisy continuous variable quantum information protocols.
NASA Astrophysics Data System (ADS)
Yang, Kai; Huang, Shih-Ying C.; Packard, Nathan J.; Boone, John M.
2009-02-01
Cone-beam systems designed for breast cancer detection bear a unique radiation dose limitation and are vulnerable to the additive noise from the detector. Additive noise is the signal fluctuation from detector elements and is independent of the incident exposure level. In this study, two different approaches (single pixel based and region of interest based) to measure the additive noise were explored using continuously acquired air images at different exposure levels, with both raw images and flat-field corrected images. The influence from two major factors, inter-pixel variance and image lag, were studied. The pixel variance measured from dark images was used as the gold standard (for the entire detector 15.12+/-1.3 ADU2) for comparison. Image noise propagation through reconstruction procedures was also investigated and a mathematically derived quadratic relationship between the image noise and the inverse of the radiation dose was confirmed with experiment data. The additive noise level was proved to affect the CT image noise as the second order coefficient and thus determines the lower limit of the scan radiation dose, above which the scanner operates at quantum limited region and utilizes the x-ray photon most efficiently.
The conditional entropy power inequality for Gaussian quantum states
Koenig, Robert
2015-02-15
We propose a generalization of the quantum entropy power inequality involving conditional entropies. For the special case of Gaussian states, we give a proof based on perturbation theory for symplectic spectra. We discuss some implications for entanglement-assisted classical communication over additive bosonic noise channels.
Addition of visual noise boosts evoked potential-based brain-computer interface.
Xie, Jun; Xu, Guanghua; Wang, Jing; Zhang, Sicong; Zhang, Feng; Li, Yeping; Han, Chengcheng; Li, Lili
2014-01-01
Although noise has a proven beneficial role in brain functions, there have not been any attempts on the dedication of stochastic resonance effect in neural engineering applications, especially in researches of brain-computer interfaces (BCIs). In our study, a steady-state motion visual evoked potential (SSMVEP)-based BCI with periodic visual stimulation plus moderate spatiotemporal noise can achieve better offline and online performance due to enhancement of periodic components in brain responses, which was accompanied by suppression of high harmonics. Offline results behaved with a bell-shaped resonance-like functionality and 7-36% online performance improvements can be achieved when identical visual noise was adopted for different stimulation frequencies. Using neural encoding modeling, these phenomena can be explained as noise-induced input-output synchronization in human sensory systems which commonly possess a low-pass property. Our work demonstrated that noise could boost BCIs in addressing human needs. PMID:24828128
3D filtering technique in presence of additive noise in color videos implemented on DSP
NASA Astrophysics Data System (ADS)
Ponomaryov, Volodymyr I.; Montenegro-Monroy, Hector; Palacios, Alfredo
2014-05-01
A filtering method for color videos contaminated by additive noise is presented. The proposed framework employs three filtering stages: spatial similarity filtering, neighboring frame denoising, and spatial post-processing smoothing. The difference with other state-of- the-art filtering methods, is that this approach, based on fuzzy logic, analyses basic and related gradient values between neighboring pixels into a 7 fi 7 sliding window in the vicinity of a central pixel in each of the RGB channels. Following, the similarity measures between the analogous pixels in the color bands are taken into account during the denoising. Next, two neighboring video frames are analyzed together estimating local motions between the frames using block matching procedure. In the final stage, the edges and smoothed areas are processed differently in a current frame during the post-processing filtering. Numerous simulations results confirm that this 3D fuzzy filter perform better than other state-of-the- art methods, such as: 3D-LLMMSE, WMVCE, RFMDAF, FDARTF G, VBM3D and NLM, in terms of objective criteria (PSNR, MAE, NCD and SSIM) as well as subjective perception via human vision system in the different color videos. An efficiency analysis of the designed and other mentioned filters have been performed on the DSPs TMS320 DM642 and TMS320DM648 by Texas Instruments through MATLAB and Simulink module showing that the novel 3D fuzzy filter can be used in real-time processing applications.
Underwater Noise Modeling and Direction-Finding Based on Heteroscedastic Time Series
NASA Astrophysics Data System (ADS)
Amiri, Hadi; Amindavar, Hamidreza; Kamarei, Mahmoud
2006-12-01
We propose a new method for practical non-Gaussian and nonstationary underwater noise modeling. This model is very useful for passive sonar in shallow waters. In this application, measurement of additive noise in natural environment and exhibits shows that noise can sometimes be significantly non-Gaussian and a time-varying feature especially in the variance. Therefore, signal processing algorithms such as direction-finding that is optimized for Gaussian noise may degrade significantly in this environment. Generalized autoregressive conditional heteroscedasticity (GARCH) models are suitable for heavy tailed PDFs and time-varying variances of stochastic process. We use a more realistic GARCH-based noise model in the maximum-likelihood approach for the estimation of direction-of-arrivals (DOAs) of impinging sources onto a linear array, and demonstrate using measured noise that this approach is feasible for the additive noise and direction finding in an underwater environment.
Gaussian Multipole Model (GMM)
Elking, Dennis M.; Cisneros, G. Andrés; Piquemal, Jean-Philip; Darden, Thomas A.; Pedersen, Lee G.
2009-01-01
An electrostatic model based on charge density is proposed as a model for future force fields. The model is composed of a nucleus and a single Slater-type contracted Gaussian multipole charge density on each atom. The Gaussian multipoles are fit to the electrostatic potential (ESP) calculated at the B3LYP/6-31G* and HF/aug-cc-pVTZ levels of theory and tested by comparing electrostatic dimer energies, inter-molecular density overlap integrals, and permanent molecular multipole moments with their respective ab initio values. For the case of water, the atomic Gaussian multipole moments Qlm are shown to be a smooth function of internal geometry (bond length and bond angle), which can be approximated by a truncated linear Taylor series. In addition, results are given when the Gaussian multipole charge density is applied to a model for exchange-repulsion energy based on the inter-molecular density overlap. PMID:20209077
[Denoising and assessing method of additive noise in the ultraviolet spectrum of SO2 in flue gas].
Zhou, Tao; Sun, Chang-Ku; Liu, Bin; Zhao, Yu-Mei
2009-11-01
The problem of denoising and assessing method of the spectrum of SO2 in flue gas was studied based on DOAS. The denoising procedure of the additive noise in the spectrum was divided into two parts: reducing the additive noise and enhancing the useful signal. When obtaining the absorption feature of measured gas, a multi-resolution preprocessing method of original spectrum was adopted for denoising by DWT (discrete wavelet transform). The signal energy operators in different scales were used to choose the denoising threshold and separate the useful signal from the noise. On the other hand, because there was no sudden change in the spectra of flue gas in time series, the useful signal component was enhanced according to the signal time dependence. And the standard absorption cross section was used to build the ideal absorption spectrum with the measured gas temperature and pressure. This ideal spectrum was used as the desired signal instead of the original spectrum in the assessing method to modify the SNR (signal-noise ratio). There were two different environments to do the proof test-in the lab and at the scene. In the lab, SO2 was measured several times with the system using this method mentioned above. The average deviation was less than 1.5%, while the repeatability was less than 1%. And the short range experiment data were better than the large range. In the scene of a power plant whose concentration of flue gas had a large variation range, the maximum deviation of this method was 2.31% in the 18 groups of contrast data. The experimental results show that the denoising effect of the scene spectrum was better than that of the lab spectrum. This means that this method can improve the SNR of the spectrum effectively, which is seriously polluted by additive noise. PMID:20101989
NASA Astrophysics Data System (ADS)
Ludescher, Josef; Bogachev, Mikhail I.; Kantelhardt, Jan W.; Schumann, Aicko Y.; Bunde, Armin
2011-07-01
We study the performance of multifractal detrended fluctuation analysis (MF-DFA) applied to long-term correlated and multifractal data records in the presence of additive white noise, short-term memory and periodicities. Such additions and disturbances that can be typically found in the observational records of various complex systems ranging from climate dynamics to physiology, network traffic, and finance. In monofractal records, we find that (i) additive white noise hardly results in spurious multifractality, but causes underestimated generalized Hurst exponents h(q) for all q values; (ii) short-range correlations lead to pronounced crossovers in the generalized fluctuation functions Fq(s) at positions that decrease with increasing moment q, thus causing significantly overestimated h(q) for small q and spurious multifractality; (iii) periodicities like seasonal trends (with standard deviations comparable with the one of the studied process) result in spurious “reversed” multifractality where h(q) increases with increasing q (except for very short time windows). We also show that in multifractal cascades moderate additions of noise, short-range memory, or periodic trends cause flawed results for h(q) with q<2, while h(q) with q>2 remains nearly unchanged.
NASA Astrophysics Data System (ADS)
Chen, Chuchu; Hong, Jialin; Zhang, Liying
2016-02-01
Stochastic Maxwell equations with additive noise are a system of stochastic Hamiltonian partial differential equations intrinsically, possessing the stochastic multi-symplectic conservation law. It is shown that the averaged energy increases linearly with respect to the evolution of time and the flow of stochastic Maxwell equations with additive noise preserves the divergence in the sense of expectation. Moreover, we propose three novel stochastic multi-symplectic methods to discretize stochastic Maxwell equations in order to investigate the preservation of these properties numerically. We make theoretical discussions and comparisons on all of the three methods to observe that all of them preserve the corresponding discrete version of the averaged divergence. Meanwhile, we obtain the corresponding dissipative property of the discrete averaged energy satisfied by each method. Especially, the evolution rates of the averaged energies for all of the three methods are derived which are in accordance with the continuous case. Numerical experiments are performed to verify our theoretical results.
Autonomous Gaussian Decomposition
NASA Astrophysics Data System (ADS)
Lindner, Robert R.; Vera-Ciro, Carlos; Murray, Claire E.; Stanimirović, Snežana; Babler, Brian; Heiles, Carl; Hennebelle, Patrick; Goss, W. M.; Dickey, John
2015-04-01
We present a new algorithm, named Autonomous Gaussian Decomposition (AGD), for automatically decomposing spectra into Gaussian components. AGD uses derivative spectroscopy and machine learning to provide optimized guesses for the number of Gaussian components in the data, and also their locations, widths, and amplitudes. We test AGD and find that it produces results comparable to human-derived solutions on 21 cm absorption spectra from the 21 cm SPectral line Observations of Neutral Gas with the EVLA (21-SPONGE) survey. We use AGD with Monte Carlo methods to derive the H i line completeness as a function of peak optical depth and velocity width for the 21-SPONGE data, and also show that the results of AGD are stable against varying observational noise intensity. The autonomy and computational efficiency of the method over traditional manual Gaussian fits allow for truly unbiased comparisons between observations and simulations, and for the ability to scale up and interpret the very large data volumes from the upcoming Square Kilometer Array and pathfinder telescopes.
Searching for primordial non-Gaussianity in Planck CMB maps using a combined estimator
Novaes, C.P.; Wuensche, C.A.; Bernui, A.; Ferreira, I.S. E-mail: bernui@on.br E-mail: ca.wuensche@inpe.br
2014-01-01
The extensive search for deviations from Gaussianity in cosmic microwave background radiation (CMB) data is very important due to the information about the very early moments of the universe encoded there. Recent analyses from Planck CMB data do not exclude the presence of non-Gaussianity of small amplitude, although they are consistent with the Gaussian hypothesis. The use of different techniques is essential to provide information about types and amplitudes of non-Gaussianities in the CMB data. In particular, we find interesting to construct an estimator based upon the combination of two powerful statistical tools that appears to be sensitive enough to detect tiny deviations from Gaussianity in CMB maps. This estimator combines the Minkowski functionals with a Neural Network, maximizing a tool widely used to study non-Gaussian signals with a reinforcement of another tool designed to identify patterns in a data set. We test our estimator by analyzing simulated CMB maps contaminated with different amounts of local primordial non-Gaussianity quantified by the dimensionless parameter f{sub NL}. We apply it to these sets of CMB maps and find ∼> 98% of chance of positive detection, even for small intensity local non-Gaussianity like f{sub NL} = 38±18, the current limit from Planck data for large angular scales. Additionally, we test the suitability to distinguish between primary and secondary non-Gaussianities: first we train the Neural Network with two sets, one of nearly Gaussian CMB maps (|f{sub NL}| ≤ 10) but contaminated with realistic inhomogeneous Planck noise (i.e., secondary non-Gaussianity) and the other of non-Gaussian CMB maps, that is, maps endowed with weak primordial non-Gaussianity (28 ≤ f{sub NL} ≤ 48); after that we test an ensemble composed of CMB maps either with one of these non-Gaussian contaminations, and find out that our method successfully classifies ∼ 95% of the tested maps as being CMB maps containing primordial or
Searching for primordial non-Gaussianity in Planck CMB maps using a combined estimator
NASA Astrophysics Data System (ADS)
Novaes, C. P.; Bernui, A.; Ferreira, I. S.; Wuensche, C. A.
2014-01-01
The extensive search for deviations from Gaussianity in cosmic microwave background radiation (CMB) data is very important due to the information about the very early moments of the universe encoded there. Recent analyses from Planck CMB data do not exclude the presence of non-Gaussianity of small amplitude, although they are consistent with the Gaussian hypothesis. The use of different techniques is essential to provide information about types and amplitudes of non-Gaussianities in the CMB data. In particular, we find interesting to construct an estimator based upon the combination of two powerful statistical tools that appears to be sensitive enough to detect tiny deviations from Gaussianity in CMB maps. This estimator combines the Minkowski functionals with a Neural Network, maximizing a tool widely used to study non-Gaussian signals with a reinforcement of another tool designed to identify patterns in a data set. We test our estimator by analyzing simulated CMB maps contaminated with different amounts of local primordial non-Gaussianity quantified by the dimensionless parameter f NL. We apply it to these sets of CMB maps and find gtrsim 98% of chance of positive detection, even for small intensity local non-Gaussianity like f NL = 38±18, the current limit from Planck data for large angular scales. Additionally, we test the suitability to distinguish between primary and secondary non-Gaussianities: first we train the Neural Network with two sets, one of nearly Gaussian CMB maps (|f NL| <= 10) but contaminated with realistic inhomogeneous Planck noise (i.e., secondary non-Gaussianity) and the other of non-Gaussian CMB maps, that is, maps endowed with weak primordial non-Gaussianity (28 <= f NL <= 48); after that we test an ensemble composed of CMB maps either with one of these non-Gaussian contaminations, and find out that our method successfully classifies ~ 95% of the tested maps as being CMB maps containing primordial or secondary non-Gaussianity. Furthermore
NASA Astrophysics Data System (ADS)
Saha, Surajit; Pal, Suvajit; Ganguly, Jayanta; Ghosh, Manas
2016-03-01
We inspect the influence of position-dependent effective mass (PDEM) on the third-order nonlinear optical susceptibility (TONOS) of impurity doped quantum dots (QDs) in the presence and absence of noise. The TONOS profiles have been followed as a function of incident photon energy for different values of PDEM. Using PDEM the said profile considerably deviates from that of fixed effective mass (FEM). However, a switch from one mode of application of noise to another primarily alters the TONOS peak intensity. The observations highlight the possibility of tuning the TONOS profiles of doped QD systems exploiting noise and PDEM.
Differential detection of Gaussian MSK in a mobile radio environment
NASA Technical Reports Server (NTRS)
Simon, M. K.; Wang, C. C.
1984-01-01
Minimum shift keying with Gaussian shaped transmit pulses is a strong candidate for a modulation technique that satisfies the stringent out-of-band radiated power requirements of the mobil radio application. Numerous studies and field experiments have been conducted by the Japanese on urban and suburban mobile radio channels with systems employing Gaussian minimum-shift keying (GMSK) transmission and differentially coherent reception. A comprehensive analytical treatment is presented of the performance of such systems emphasizing the important trade-offs among the various system design parameters such as transmit and receiver filter bandwidths and detection threshold level. It is shown that two-bit differential detection of GMSK is capable of offering far superior performance to the more conventional one-bit detection method both in the presence of an additive Gaussian noise background and Rician fading.
NASA Technical Reports Server (NTRS)
Smalheer, C. V.
1973-01-01
The chemistry of lubricant additives is discussed to show what the additives are chemically and what functions they perform in the lubrication of various kinds of equipment. Current theories regarding the mode of action of lubricant additives are presented. The additive groups discussed include the following: (1) detergents and dispersants, (2) corrosion inhibitors, (3) antioxidants, (4) viscosity index improvers, (5) pour point depressants, and (6) antifouling agents.
NASA Astrophysics Data System (ADS)
Wang, Kang-Kang; Zong, De-Cai; Wang, Ya-Jun; Li, Sheng-Hong
2016-05-01
In this paper, the transition between the stable state of a big density and the extinction state and stochastic resonance (SR) for a time-delayed metapopulation system disturbed by colored cross-correlated noises are investigated. By applying the fast descent method, the small time-delay approximation and McNamara and Wiesenfeld's SR theory, we investigate the impacts of time-delay, the multiplicative, additive noises and colored cross-correlated noise on the SNR and the shift between the two states of the system. Numerical results show that the multiplicative, additive noises and time-delay can all speed up the transition from the stable state to the extinction state, while the correlation noise and its correlation time can slow down the extinction process of the population system. With respect to SNR, the multiplicative noise always weakens the SR effect, while noise correlation time plays a dual role in motivating the SR phenomenon. Meanwhile, time-delay mainly plays a negative role in stimulating the SR phenomenon. Conversely, it could motivate the SR effect to increase the strength of the cross-correlation noise in the SNR-β plot, while the increase of additive noise intensity will firstly excite SR, and then suppress the SR effect.
Passive interferometric symmetries of multimode Gaussian pure states
NASA Astrophysics Data System (ADS)
Gabay, Natasha; Menicucci, Nicolas C.
2016-05-01
As large-scale multimode Gaussian states begin to become accessible in the laboratory, their representation and analysis become a useful topic of research in their own right. The graphical calculus for Gaussian pure states provides powerful tools for their representation, while this work presents a useful tool for their analysis: passive interferometric (i.e., number-conserving) symmetries. Here we show that these symmetries of multimode Gaussian states simplify calculations in measurement-based quantum computing and provide constructive tools for engineering large-scale harmonic systems with specific physical properties, and we provide a general mathematical framework for deriving them. Such symmetries are generated by linear combinations of operators expressed in the Schwinger representation of U (2 ) , called nullifiers because the Gaussian state in question is a zero eigenstate of them. This general framework is shown to have applications in the noise analysis of continuous-various cluster states and is expected to have additional applications in future work with large-scale multimode Gaussian states.
Long-distance continuous-variable quantum key distribution with a Gaussian modulation
Jouguet, Paul; Kunz-Jacques, Sebastien; Leverrier, Anthony
2011-12-15
We designed high-efficiency error correcting codes allowing us to extract an errorless secret key in a continuous-variable quantum key distribution (CVQKD) protocol using a Gaussian modulation of coherent states and a homodyne detection. These codes are available for a wide range of signal-to-noise ratios on an additive white Gaussian noise channel with a binary modulation and can be combined with a multidimensional reconciliation method proven secure against arbitrary collective attacks. This improved reconciliation procedure considerably extends the secure range of a CVQKD with a Gaussian modulation, giving a secret key rate of about 10{sup -3} bit per pulse at a distance of 120 km for reasonable physical parameters.
NASA Astrophysics Data System (ADS)
Seddik, Hassene
2014-12-01
Noise can occur during image capture, transmission, or processing phases. Image de-noising is a very important step in image processing, and many approaches are developed in order to achieve this goal such as the Gaussian filter which is efficient in noise removal. Its smoothing efficiency depends on the value of its standard deviation. The mask representing the filter presents generally static weights with invariant lobe. In this paper, an adaptive de-noising approach is proposed. The proposed approach uses a Gaussian kernel with variable width and direction called adaptive Gaussian kernel (AGK). In each processed window of the image, the smoothing strength changes according to the image content, noise kind, and intensity. In addition, the location of its lobe changes in eight different directions over the processed window. This directional variability avoids averaging details by the highest mask weights in order to preserve the edges and the borders. The recovered data is de-noised efficiently without introducing blur or losing details. A comparative study with the static Gaussian filter and other recent techniques is presented to prove the efficiency of the proposed approach.
Robustness of Ant Colony Optimization to Noise.
Friedrich, Tobias; Kötzing, Timo; Krejca, Martin S; Sutton, Andrew M
2016-01-01
Recently, ant colony optimization (ACO) algorithms have proven to be efficient in uncertain environments, such as noisy or dynamically changing fitness functions. Most of these analyses have focused on combinatorial problems such as path finding. We rigorously analyze an ACO algorithm optimizing linear pseudo-Boolean functions under additive posterior noise. We study noise distributions whose tails decay exponentially fast, including the classical case of additive Gaussian noise. Without noise, the classical [Formula: see text] EA outperforms any ACO algorithm, with smaller [Formula: see text] being better; however, in the case of large noise, the [Formula: see text] EA fails, even for high values of [Formula: see text] (which are known to help against small noise). In this article, we show that ACO is able to deal with arbitrarily large noise in a graceful manner; that is, as long as the evaporation factor [Formula: see text] is small enough, dependent on the variance [Formula: see text] of the noise and the dimension n of the search space, optimization will be successful. We also briefly consider the case of prior noise and prove that ACO can also efficiently optimize linear functions under this noise model. PMID:26928850
NASA Astrophysics Data System (ADS)
Monien, H.
2010-04-01
Gaussian quadrature is a well-known technique for numerical integration. Recently Gaussian quadrature with respect to discrete measures corresponding to finite sums has found some new interest. In this paper we apply these ideas to infinite sums in general and give an explicit construction for the weights and abscissae of Gaussian formulas. The abscissae of the Gaussian summation have a very interesting asymptotic distribution function with a kink singularity. We apply the Gaussian summation technique to two problems which have been discussed in the literature. We find that the Gaussian summation has a very rapid convergence rate for the Hardy-Littlewood sum for a large range of parameters.
NASA Astrophysics Data System (ADS)
Zhao, Fan; Zhao, Jian; Zhao, Wenda; Qu, Feng
2016-05-01
Infrared images are characterized by low signal-to-noise ratio and low contrast. Therefore, the edge details are easily immerged in the background and noise, making it much difficult to achieve infrared image edge detail enhancement and denoising. This article proposes a novel method of Gaussian mixture model-based gradient field reconstruction, which enhances image edge details while suppressing noise. First, by analyzing the gradient histogram of noisy infrared image, Gaussian mixture model is adopted to simulate the distribution of the gradient histogram, and divides the image information into three parts corresponding to faint details, noise and the edges of clear targets, respectively. Then, the piecewise function is constructed based on the characteristics of the image to increase gradients of faint details and suppress gradients of noise. Finally, anisotropic diffusion constraint is added while visualizing enhanced image from the transformed gradient field to further suppress noise. The experimental results show that the method possesses unique advantage of effectively enhancing infrared image edge details and suppressing noise as well, compared with the existing methods. In addition, it can be used to effectively enhance other types of images such as the visible and medical images.
NASA Astrophysics Data System (ADS)
Wan, Xiazi; Kobayashi, Hiroyuki; Aoki, Naokazu
2015-03-01
In a preceding study, we investigated the effects of image noise on the perception of image sharpness using white noise, and one- and two-dimensional single-frequency sinusoidal patterns as stimuli. This study extends our preceding study by evaluating natural color images, rather than black-and-white patterns. The results showed that the effect of noise in improving image sharpness perception is more evident in blurred images than in sharp images. This is consistent with the results of the preceding study. In another preceding study, we proposed "memory texture" to explain the preferred granularity of images, as a concept similar to "memory color" for preferred color reproduction. We observed individual differences in type of memory texture for each object, that is, white or 1/f noise. This study discusses the relationship between improvement of sharpness perception by adding noise, and the memory texture, following its individual differences. We found that memory texture is one of the elements that affect sharpness perception.
Performance of correlation receivers in the presence of impulse noise.
NASA Technical Reports Server (NTRS)
Moore, J. D.; Houts, R. C.
1972-01-01
An impulse noise model, which assumes that each noise burst contains a randomly weighted version of a basic waveform, is used to derive the performance equations for a correlation receiver. The expected number of bit errors per noise burst is expressed as a function of the average signal energy, signal-set correlation coefficient, bit time, noise-weighting-factor variance and probability density function, and a time range function which depends on the crosscorrelation of the signal-set basis functions and the noise waveform. Unlike the performance results for additive white Gaussian noise, it is shown that the error performance for impulse noise is affected by the choice of signal-set basis function, and that Orthogonal signaling is not equivalent to On-Off signaling with the same average energy. Furthermore, it is demonstrated that the correlation-receiver error performance can be improved by inserting a properly specified nonlinear device prior to the receiver input.
Statistics of a neuron model driven by asymmetric colored noise
NASA Astrophysics Data System (ADS)
Müller-Hansen, Finn; Droste, Felix; Lindner, Benjamin
2015-02-01
Irregular firing of neurons can be modeled as a stochastic process. Here we study the perfect integrate-and-fire neuron driven by dichotomous noise, a Markovian process that jumps between two states (i.e., possesses a non-Gaussian statistics) and exhibits nonvanishing temporal correlations (i.e., represents a colored noise). Specifically, we consider asymmetric dichotomous noise with two different transition rates. Using a first-passage-time formulation, we derive exact expressions for the probability density and the serial correlation coefficient of the interspike interval (time interval between two subsequent neural action potentials) and the power spectrum of the spike train. Furthermore, we extend the model by including additional Gaussian white noise, and we give approximations for the interspike interval (ISI) statistics in this case. Numerical simulations are used to validate the exact analytical results for pure dichotomous noise, and to test the approximations of the ISI statistics when Gaussian white noise is included. The results may help to understand how correlations and asymmetry of noise and signals in nerve cells shape neuronal firing statistics.
2010-01-01
Background Liquid chromatography-mass spectrometry (LC-MS) is one of the major techniques for the quantification of metabolites in complex biological samples. Peak modeling is one of the key components in LC-MS data pre-processing. Results To quantify asymmetric peaks with high noise level, we developed an estimation procedure using the bi-Gaussian function. In addition, to accurately quantify partially overlapping peaks, we developed a deconvolution method using the bi-Gaussian mixture model combined with statistical model selection. Conclusions Using extensive simulations and real data, we demonstrated the advantage of the bi-Gaussian mixture model over the Gaussian mixture model and the method of kernel smoothing combined with signal summation in peak quantification and deconvolution. The method is implemented in the R package apLCMS: http://www.sph.emory.edu/apLCMS/. PMID:21073736
REJUVENATING POWER SPECTRA. II. THE GAUSSIANIZED GALAXY DENSITY FIELD
Neyrinck, Mark C.; Szalay, Alexander S.; Szapudi, Istvan
2011-04-20
We find that, even in the presence of discreteness noise, a Gaussianizing transform (producing a more Gaussian one-point distribution) reduces nonlinearities in the power spectra of cosmological matter and galaxy density fields, in many cases drastically. Although Gaussianization does increase the effective shot noise, it also increases the power spectrum's fidelity to the linear power spectrum on scales where the shot noise is negligible. Gaussianizing also increases the Fisher information in the power spectrum in all cases and resolutions, although the gains are smaller in redshift space than in real space. We also find that the gain in cumulative Fisher information from Gaussianizing peaks at a particular grid resolution depends on the sampling level.
Shen, Luan
1995-10-06
This dissertation is focused on three problem areas in the performance of inductively coupled plasma (ICP) source. The noise characteristics of aerosols produced by ICP nebulizers are investigated. A laser beam is scattered by aerosol and detected by a photomultiplier tube and the noise amplitude spectrum of the scattered radiation is measured by a spectrum analyzer. Discrete frequency noise in the aerosol generated by a Meinhard nebulizer or a direct injection nebulizer is primarily caused by pulsation in the liquid flow from the pump. A Scott-type spray chamber suppresses white noise, while a conical, straight-pass spray chamber enhances white noise, relative to the noise seen from the primary aerosol. Simultaneous correction for both spectral interferences and matrix effects in ICP atomic emission spectrometry (AES) can be accomplished by using the generalized standard additions method (GSAM). Results obtained with the application of the GSAM to the Perkin-Elmer Optima 3000 ICP atomic emission spectrometer are presented. The echelle-based polychromator with segmented-array charge-coupled device detectors enables the direct, visual examination of the overlapping lines Cd (1) 228.802 nm and As (1) 228.812 nm. The slit translation capability allows a large number of data points to be sampled, therefore, the advantage of noise averaging is gained. An ICP is extracted into a small quartz vacuum chamber through a sampling orifice in a water-cooled copper plate. Optical emission from the Mach disk region is measured with a new type of echelle spectrometer equipped with two segmented-array charge-coupled-device detectors, with an effort to improve the detection limits for simultaneous multielement analysis by ICP-AES.
NASA Astrophysics Data System (ADS)
Baker, C. R.; Chao, I. F.
1990-10-01
The additive infinite-dimensional Gaussian channel subject to jamming is modeled as a two-person zero-sum game with mutual information as the payoff function. The jammer's noise is added to the ambient Gaussian noise. The coder's signal energy is subject to a constraint is necessary in order that the capacity without feedback be finite. It is shown that use of this same RKHS constraint on the jammer's process is too strong; the jammer would then not be able to reduce capacity, regardless of the amount of jamming energy available. The constraint on the jammer is thus on the total jamming energy, without regard to its distribution relative to that of the ambient noise energy. The existence of a saddle value for the problem does not follow from the von Neuman minimax theorem in the original problem formulation. However, a solution is shown to exist. A saddle point, saddle value, and the jammer's minimax strategy are determined. The solution is a function of the problem parameters: the constraint on the coder, the constraint on the jammer, and the covariance of the ambient Gaussian noise.
NASA Astrophysics Data System (ADS)
Dybiec, Bartłomiej; Gudowska-Nowak, Ewa
2009-05-01
A standard approach to analysis of noise-induced effects in stochastic dynamics assumes a Gaussian character of the noise term describing interaction of the analyzed system with its complex surroundings. An additional assumption about the existence of timescale separation between the dynamics of the measured observable and the typical timescale of the noise allows external fluctuations to be modeled as temporally uncorrelated and therefore white. However, in many natural phenomena the assumptions concerning the above mentioned properties of 'Gaussianity' and 'whiteness' of the noise can be violated. In this context, in contrast to the spatiotemporal coupling characterizing general forms of non-Markovian or semi-Markovian Lévy walks, so called Lévy flights correspond to the class of Markov processes which can still be interpreted as white, but distributed according to a more general, infinitely divisible, stable and non-Gaussian law. Lévy noise-driven non-equilibrium systems are known to manifest interesting physical properties and have been addressed in various scenarios of physical transport exhibiting a superdiffusive behavior. Here we present a brief overview of our recent investigations aimed at understanding features of stochastic dynamics under the influence of Lévy white noise perturbations. We find that the archetypal phenomena of noise-induced ordering are robust and can be detected also in systems driven by memoryless, non-Gaussian, heavy-tailed fluctuations with infinite variance.
Detection of Gaussian signals in Poisson-modulated interference.
Streit, R L
2000-10-01
Passive broadband detection of target signals by an array of hydrophones in the presence of multiple discrete interferers is analyzed under Gaussian statistics and low signal-to-noise ratio conditions. A nonhomogeneous Poisson-modulated interference process is used to model the ensemble of possible arrival directions of the discrete interferers. Closed-form expressions are derived for the recognition differential of the passive-sonar equation in the presence of Poisson-modulated interference. The interference-compensated recognition differential differs from the classical recognition differential by an additive positive term that depend on the interference-to-noise ratio, the directionality of the Poisson-modulated interference, and the array beam pattern. PMID:11051502
Application of Gaussian moment method to a gene autoregulation model of rational vector field
NASA Astrophysics Data System (ADS)
Kang, Yan-Mei; Chen, Xi
2016-07-01
We take a lambda expression autoregulation model driven by multiplicative and additive noises as example to extend the Gaussian moment method from nonlinear stochastic systems of polynomial vector field to noisy biochemical systems of rational polynomial vector field. As a direct application of the extended method, we also disclose the phenomenon of stochastic resonance. It is found that the transcription rate can inhibit the stochastic resonant effect, but the degradation rate may enhance the phenomenon. These observations should be helpful in understanding the functional role of noise in gene autoregulation.
Design criteria for noncoherent Gaussian channels with MFSK signaling and coding
NASA Technical Reports Server (NTRS)
Butman, S. A.; Levitt, B. K.; Bar-David, I.; Lyon, R. F.; Klass, M. J.
1976-01-01
This paper presents data and criteria to assess and guide the design of modems for coded noncoherent communication systems subject to practical system constraints of power, bandwidth, noise spectral density, coherence time, and number of orthogonal signals M. Three basic receiver types are analyzed for the noncoherent multifrequency-shift keying (MFSK) additive white Gaussian noise channel: hard decision, unquantized (optimum), and quantized (soft decision). Channel capacity and computational cutoff rate are computed for each type and presented as functions of the predetection signal-to-noise ratio and the number of orthogonal signals. This relates the channel constraints of power, bandwidth, coherence time, and noise power to the optimum choice of signal duration and signal number.
Kawasaki, Masahiro; Nakayama, Kazunori; Takahashi, Fuminobu E-mail: nakayama@icrr.u-tokyo.ac.jp
2009-01-15
We study non-Gaussianity induced by a pseudo Nambu-Goldstone boson with a cosine-type scalar potential. We focus on how the non-Gaussianity is affected when the pseudo Nambu-Goldstone boson rolls down from near the top of the scalar potential where the deviation from a quadratic potential is large. We find that the resultant non-Gaussianity is similar to that obtained in the quadratic potential, if the pseudo Nambu-Goldstone boson accounts for the curvature perturbation; the non-Gaussianity is enhanced, otherwise.
NASA Astrophysics Data System (ADS)
Khodja, Mohamed; Belouchrani, Adel; Abed-Meraim, Karim
2012-12-01
This article deals with the application of Spatial Time-Frequency Distribution (STFD) to the direction finding problem using the Multiple Signal Classification (MUSIC)algorithm. A comparative performance analysis is performed for the method under consideration with respect to that using data covariance matrix when the received array signals are subject to calibration errors in a non-stationary environment. An unified analytical expression of the Direction Of Arrival (DOA) error estimation is derived for both methods. Numerical results show the effect of the parameters intervening in the derived expression on the algorithm performance. It is particularly observed that for low Signal to Noise Ratio (SNR) and high Signal to sensor Perturbation Ratio (SPR) the STFD method gives better performance, while for high SNR and for the same SPR both methods give similar performance.
Noise-driven optical absorption coefficients of impurity doped quantum dots
NASA Astrophysics Data System (ADS)
Ganguly, Jayanta; Saha, Surajit; Pal, Suvajit; Ghosh, Manas
2016-01-01
We make an extensive investigation of linear, third-order nonlinear, and total optical absorption coefficients (ACs) of impurity doped quantum dots (QDs) in presence and absence of noise. The noise invoked in the present study is a Gaussian white noise. The quantum dot is doped with repulsive Gaussian impurity. Noise has been introduced to the system additively and multiplicatively. A perpendicular magnetic field acts as a source of confinement and a static external electric field has been applied. The AC profiles have been studied as a function of incident photon energy when several important parameters such as optical intensity, electric field strength, magnetic field strength, confinement energy, dopant location, relaxation time, Al concentration, dopant potential, and noise strength take on different values. In addition, the role of mode of application of noise (additive/multiplicative) on the AC profiles has also been analyzed meticulously. The AC profiles often consist of a number of interesting observations such as one photon resonance enhancement, shift of AC peak position, variation of AC peak intensity, and bleaching of AC peak. However, presence of noise alters the features of AC profiles and leads to some interesting manifestations. Multiplicative noise brings about more complexity in the AC profiles than its additive counterpart. The observations indeed illuminate several useful aspects in the study of linear and nonlinear optical properties of doped QD systems, specially in presence of noise. The findings are expected to be quite relevant from a technological perspective.
Gaussian benchmark for optical communication aiming towards ultimate capacity
NASA Astrophysics Data System (ADS)
Lee, Jaehak; Ji, Se-Wan; Park, Jiyong; Nha, Hyunchul
2016-05-01
We establish the fundamental limit of communication capacity within Gaussian schemes under phase-insensitive Gaussian channels, which employ multimode Gaussian states for encoding and collective Gaussian operations and measurements for decoding. We prove that this Gaussian capacity is additive, i.e., its upper bound occurs with separable encoding and separable receivers so that a single-mode communication suffices to achieve the largest capacity under Gaussian schemes. This rigorously characterizes the gap between the ultimate Holevo capacity and the capacity within Gaussian communication, showing that Gaussian regime is not sufficient to achieve the Holevo bound particularly in the low-photon regime. Furthermore, the Gaussian benchmark established here can be used to critically assess the performance of non-Gaussian protocols for optical communication. We move on to identify non-Gaussian schemes to beat the Gaussian capacity and show that a non-Gaussian receiver recently implemented by Becerra et al. [F. E. Becerra et al., Nat. Photon. 7, 147 (2013), 10.1038/nphoton.2012.316] can achieve this aim with an appropriately chosen encoding strategy.
A gaussian band pass filter for digital enhancement of nuclear medicine images
Madsen, M.T.; Park, C.H.; Hichwa, R.D.
1985-05-01
Information in nuclear medicine images is obscured due to the presence of Poisson noise and the finite resolution of the detection system. Many filters have been developed to recover resolution and suppress noise, most notably the Metz and Wiener filters. The generation of these filters requires knowledge of the system MTF. The authors have investigated the properties of a two dimensional circularly symmetric truncated Gaussian function as a filter to be applied in the spatial frequency domain. The filter is expressed as exp(-(..mu..-..mu../sub o/)/sup 2//2sigma/sup 2/) where ..mu../sub o/ is the displacement of the Gaussian from the origin and sigma is the degree of spread. These parameters are optimized from the image power spectrum according to the following empirical rules the magnitude at the origin is 0.3, and the spatial frequency at which the magnitude of the power spectrum exceeds twice that of the noise level is 2sigma from the mean of the Gaussian (..mu../sub o/). Condition 1 preferentially enhances the information in the middle frequencies while condition 2 assures that the filter goes to 0 at spatial frequencies where noise dominates. The filter can be generated automatically by computer program. It does not require the knowledge of MTF. In addition, the coordinate space representation is a Gaussian modulated by a cosine function which can be analytically determined allowing straightfoward application of this filter as a convolution in coordinate space. The filter has been successfully applied to all types of nuclear medicine images including PET brain section images.
GAUSSIAN BEAM LASER RESONATOR PROGRAM
NASA Technical Reports Server (NTRS)
Cross, P. L.
1994-01-01
In designing a laser cavity, the laser engineer is frequently concerned with more than the stability of the resonator. Other considerations include the size of the beam at various optical surfaces within the resonator or the performance of intracavity line-narrowing or other optical elements. Laser resonators obey the laws of Gaussian beam propagation, not geometric optics. The Gaussian Beam Laser Resonator Program models laser resonators using Gaussian ray trace techniques. It can be used to determine the propagation of radiation through laser resonators. The algorithm used in the Gaussian Beam Resonator program has three major components. First, the ray transfer matrix for the laser resonator must be calculated. Next calculations of the initial beam parameters, specifically, the beam stability, the beam waist size and location for the resonator input element, and the wavefront curvature and beam radius at the input surface to the first resonator element are performed. Finally the propagation of the beam through the optical elements is computed. The optical elements can be modeled as parallel plates, lenses, mirrors, dummy surfaces, or Gradient Index (GRIN) lenses. A Gradient Index lens is a good approximation of a laser rod operating under a thermal load. The optical system may contain up to 50 elements. In addition to the internal beam elements the optical system may contain elements external to the resonator. The Gaussian Beam Resonator program was written in Microsoft FORTRAN (Version 4.01). It was developed for the IBM PS/2 80-071 microcomputer and has been implemented on an IBM PC compatible under MS DOS 3.21. The program was developed in 1988 and requires approximately 95K bytes to operate.
Effect of luminance noise on the object frequencies mediating letter identification
Hall, Cierra; Wang, Shu; Bhagat, Reema; McAnany, J. Jason
2014-01-01
Purpose: To determine if the same object frequency information mediates letter contrast threshold in the presence and absence of additive luminance noise (i.e., “noise-invariant processing”) for letters of different size. Methods: Contrast thresholds for Sloan letters ranging in size from 0.9 to 1.8 log MAR were obtained from three visually normal observers under three paradigms: (1) high- and low-pass Gaussian filtered letters were presented against a uniform adapting field; (2) high- and low-pass Gaussian filtered letters were presented in additive white luminance noise; and (3) unfiltered letters were presented in high- and low-pass Gaussian filtered luminance noise. A range of high- and low-pass filter cutoffs were used to limit selectively the object frequency content of the letters (paradigms 1 and 2) or noise (paradigm 3). The object frequencies mediating letter identification under each paradigm were derived from plots of log contrast threshold vs. log filter cutoff frequency. Results: The object frequency band mediating letter identification systematically shifted to higher frequencies with increasing log MAR letter size under all three paradigms. However, the relationship between object frequency and letter size depended on the paradigm under which the measurements were obtained. The largest difference in object frequency among the paradigms was observed at 1.8 log MAR, where the addition of white noise nearly doubled the center frequency of the band of object frequencies mediating letter identification, compared to measurements made in the absence of noise. Conclusion: Noise can affect the object frequency band mediating letter contrast threshold, particularly for large letters, an effect that is likely due to strong masking of the low frequency letter components by low frequency noise checks. This finding indicates that noise-invariant processing cannot necessarily be assumed for large letters presented in white noise. PMID:25071637
Cloning of Gaussian states by linear optics
Olivares, Stefano; Paris, Matteo G. A.; Andersen, Ulrik L.
2006-06-15
We analyze in details a scheme for cloning of Gaussian states based on linear optical components and homodyne detection recently demonstrated by Andersen et al. [Phys. Rev. Lett. 94, 240503 (2005)]. The input-output fidelity is evaluated for a generic (pure or mixed) Gaussian state taking into account the effect of nonunit quantum efficiency and unbalanced mode mixing. In addition, since in most quantum information protocols the covariance matrix of the set of input states is not perfectly known, we evaluate the average cloning fidelity for classes of Gaussian states with the degree of squeezing and the number of thermal photons being only partially known.
Noise-induced dispersion and breakup of clusters in cell cycle dynamics
Gong, Xue; Moses, Gregory; Neiman, Alexander B.; Young, Todd
2014-01-01
We study the effects of random perturbations on collective dynamics of a large ensemble of interacting cells in a model of the cell division cycle. We consider a parameter region for which the unperturbed model possesses asymptotically stable two-cluster periodic solutions. Two biologically motivated forms of random perturbations are considered: bounded variations in growth rate and asymmetric division. We compare the effects of these two dispersive mechanisms with additive Gaussian white noise perturbations. We observe three distinct phases of the response to noise in the model. First, for weak noise there is a linear relationship between the applied noise strength and the dispersion of the clusters. Second, for moderate noise strengths the clusters begin to mix, i.e. individual cells move between clusters, yet the population distribution clearly continues to maintain a two-cluster structure. Third, for strong noise the clusters are destroyed and the population is characterized by a uniform distribution. The second and third phases are separated by an order - disorder phase transition that has the characteristics of a Hopf bifurcation. Furthermore, we show that for the cell cycle model studied, the effects of bounded random perturbations are virtually indistinguishable from those induced by additive Gaussian noise, after appropriate scaling of the variance of noise strength. We then use the model to predict the strength of coupling among the cells from experimental data. In particular, we show that coupling must be rather strong to account for the observed clustering of cells given experimentally estimated noise variance. PMID:24694583
The method of narrow-band audio classification based on universal noise background model
NASA Astrophysics Data System (ADS)
Rui, Rui; Bao, Chang-chun
2013-03-01
Audio classification is the basis of content-based audio analysis and retrieval. The conventional classification methods mainly depend on feature extraction of audio clip, which certainly increase the time requirement for classification. An approach for classifying the narrow-band audio stream based on feature extraction of audio frame-level is presented in this paper. The audio signals are divided into speech, instrumental music, song with accompaniment and noise using the Gaussian mixture model (GMM). In order to satisfy the demand of actual environment changing, a universal noise background model (UNBM) for white noise, street noise, factory noise and car interior noise is built. In addition, three feature schemes are considered to optimize feature selection. The experimental results show that the proposed algorithm achieves a high accuracy for audio classification, especially under each noise background we used and keep the classification time less than one second.
Study of the intensity noise and intensity modulation in a of hybrid soliton pulsed source
Dogru, Nuran; Oziazisi, M Sadetin
2005-10-31
The relative intensity noise (RIN) and small-signal intensity modulation (IM) of a hybrid soliton pulsed source (HSPS) with a linearly chirped Gaussian apodised fibre Bragg grating (FBG) are considered in the electric-field approximation. The HSPS is described by solving the dynamic coupled-mode equations. It is shown that consideration of the carrier density noise in the HSPS in addition to the spontaneous noise is necessary to analyse accurately noise in the mode-locked HSPS. It is also shown that the resonance peak spectral splitting (RPSS) of the IM near the frequency inverse to the round-trip time of light in the external cavity can be eliminated by selecting an appropriate linear chirp rate in the Gaussian apodised FBG. (laser applications and other topics in quantum electronics)
Gaussian operations and privacy
Navascues, Miguel; Acin, Antonio
2005-07-15
We consider the possibilities offered by Gaussian states and operations for two honest parties, Alice and Bob, to obtain privacy against a third eavesdropping party, Eve. We first extend the security analysis of the protocol proposed in [Navascues et al. Phys. Rev. Lett. 94, 010502 (2005)]. Then, we prove that a generalized version of this protocol does not allow one to distill a secret key out of bound entangled Gaussian states.
Rényi entropy and complexity measure for skew-gaussian distributions and related families
NASA Astrophysics Data System (ADS)
Contreras-Reyes, Javier E.
2015-09-01
In this paper, we provide the Rényi entropy and complexity measure for a novel, flexible class of skew-gaussian distributions and their related families, as a characteristic form of the skew-gaussian Shannon entropy. We give closed expressions considering a more general class of closed skew-gaussian distributions and the weighted moments estimation method. In addition, closed expressions of Rényi entropy are presented for extended skew-gaussian and truncated skew-gaussian distributions. Finally, additional inequalities for skew-gaussian and extended skew-gaussian Rényi and Shannon entropies are reported.
Mixed noise removal by weighted encoding with sparse nonlocal regularization.
Jiang, Jielin; Zhang, Lei; Yang, Jian
2014-06-01
Mixed noise removal from natural images is a challenging task since the noise distribution usually does not have a parametric model and has a heavy tail. One typical kind of mixed noise is additive white Gaussian noise (AWGN) coupled with impulse noise (IN). Many mixed noise removal methods are detection based methods. They first detect the locations of IN pixels and then remove the mixed noise. However, such methods tend to generate many artifacts when the mixed noise is strong. In this paper, we propose a simple yet effective method, namely weighted encoding with sparse nonlocal regularization (WESNR), for mixed noise removal. In WESNR, there is not an explicit step of impulse pixel detection; instead, soft impulse pixel detection via weighted encoding is used to deal with IN and AWGN simultaneously. Meanwhile, the image sparsity prior and nonlocal self-similarity prior are integrated into a regularization term and introduced into the variational encoding framework. Experimental results show that the proposed WESNR method achieves leading mixed noise removal performance in terms of both quantitative measures and visual quality. PMID:24760906
Measurement of Mechanical Excess Noise from the Stressed Silicate Bonding
NASA Astrophysics Data System (ADS)
Pashentseva, Maria; Bilenko, Igor
2015-01-01
The main goal of this work is an experimental search for excess mechanical noise which might be generated in a contact area of parts glued to each other by silicate bonding technique under external stress. This technique is an important method developed for the second generation of the ground based gravitational wave detectors. Although this technique is already used in AdvLIGO for the attachment of "ears" with suspension fibers to the test masses, the absence of additional non-gaussian noise caused by the bond area subjected by heavy load wasn't proved yet.
A neural-network based estimator to search for primordial non-Gaussianity in Planck CMB maps
NASA Astrophysics Data System (ADS)
Novaes, C. P.; Bernui, A.; Ferreira, I. S.; Wuensche, C. A.
2015-09-01
We present an upgraded combined estimator, based on Minkowski Functionals and Neural Networks, with excellent performance in detecting primordial non-Gaussianity in simulated maps that also contain a weighted mixture of Galactic contaminations, besides real pixel's noise from Planck cosmic microwave background radiation data. We rigorously test the efficiency of our estimator considering several plausible scenarios for residual non-Gaussianities in the foreground-cleaned Planck maps, with the intuition to optimize the training procedure of the Neural Network to discriminate between contaminations with primordial and secondary non-Gaussian signatures. We look for constraints of primordial local non-Gaussianity at large angular scales in the foreground-cleaned Planck maps. For the SMICA map we found fNL = 33 ± 23, at 1σ confidence level, in excellent agreement with the WMAP-9yr and Planck results. In addition, for the other three Planck maps we obtain similar constraints with values in the interval fNL in [33, 41], concomitant with the fact that these maps manifest distinct features in reported analyses, like having different pixel's noise intensities.
NASA Astrophysics Data System (ADS)
Černotík, Ondřej; Fiurášek, Jaromír
2014-04-01
Multipartite quantum correlations, in spite of years of intensive research, still leave many questions unanswered. While bipartite entanglement is relatively well understood for Gaussian states, the complexity of mere qualitative characterization grows rapidly with increasing number of parties. Here, we present two schemes for transformations of multipartite permutation invariant Gaussian states by Gaussian local operations and classical communication. To this end, we use a scheme for possible experimental realization, making use of the fact that in this picture the whole N-partite state can be described by specifying the states of two separable modes. Numerically, we study entanglement transformations of tripartite states. Finally, we look at the effect our protocols have on fidelity of assisted quantum teleportation and find that, while adding correlated noise does not affect the fidelity at all, there is strong evidence that partial nondemolition measurement leads to a drop in teleportation fidelity.
Contrast vs noise effects on image quality
NASA Astrophysics Data System (ADS)
Hadar, Ofer; Corse, N.; Rotman, Stanley R.; Kopeika, Norman S.
1996-11-01
Low noise images are contract-limited, and image restoration techniques can improve resolution significantly. However, as noise level increases, resolution improvements via image processing become more limited because image restoration increases noise. This research attempts to construct a reliable quantitative means of characterizing the perceptual difference between target and background. A method is suggested for evaluating the extent to which it is possible to discriminate an object which has merged with its surroundings, in noise-limited and contrast limited images, i.e., how hard it would be for an observer to recognize the object against various backgrounds as a function of noise level. The suggested model will be a first order model to begin with, using a regular bar-chart with additive uncorrelated Gaussian noise degraded by standard atmospheric blurring filters. The second phase will comprise a model dealing with higher-order images. This computational model relates the detectability or distinctness of the object to measurable parameters. It also must characterize human perceptual response, i.e. the model must develop metrics which are highly correlated to the ease or difficulty which the human observer experiences in discerning the target from its background. This requirement can be fulfilled only by conducting psychophysical experiments quantitatively comparing the perceptual evaluations of the observers with the results of the mathematical model.
Quantum steering of Gaussian states via non-Gaussian measurements
Ji, Se-Wan; Lee, Jaehak; Park, Jiyong; Nha, Hyunchul
2016-01-01
Quantum steering—a strong correlation to be verified even when one party or its measuring device is fully untrusted—not only provides a profound insight into quantum physics but also offers a crucial basis for practical applications. For continuous-variable (CV) systems, Gaussian states among others have been extensively studied, however, mostly confined to Gaussian measurements. While the fulfilment of Gaussian criterion is sufficient to detect CV steering, whether it is also necessary for Gaussian states is a question of fundamental importance in many contexts. This critically questions the validity of characterizations established only under Gaussian measurements like the quantification of steering and the monogamy relations. Here, we introduce a formalism based on local uncertainty relations of non-Gaussian measurements, which is shown to manifest quantum steering of some Gaussian states that Gaussian criterion fails to detect. To this aim, we look into Gaussian states of practical relevance, i.e. two-mode squeezed states under a lossy and an amplifying Gaussian channel. Our finding significantly modifies the characteristics of Gaussian-state steering so far established such as monogamy relations and one-way steering under Gaussian measurements, thus opening a new direction for critical studies beyond Gaussian regime. PMID:27411853
Quantum steering of Gaussian states via non-Gaussian measurements
NASA Astrophysics Data System (ADS)
Ji, Se-Wan; Lee, Jaehak; Park, Jiyong; Nha, Hyunchul
2016-07-01
Quantum steering—a strong correlation to be verified even when one party or its measuring device is fully untrusted—not only provides a profound insight into quantum physics but also offers a crucial basis for practical applications. For continuous-variable (CV) systems, Gaussian states among others have been extensively studied, however, mostly confined to Gaussian measurements. While the fulfilment of Gaussian criterion is sufficient to detect CV steering, whether it is also necessary for Gaussian states is a question of fundamental importance in many contexts. This critically questions the validity of characterizations established only under Gaussian measurements like the quantification of steering and the monogamy relations. Here, we introduce a formalism based on local uncertainty relations of non-Gaussian measurements, which is shown to manifest quantum steering of some Gaussian states that Gaussian criterion fails to detect. To this aim, we look into Gaussian states of practical relevance, i.e. two-mode squeezed states under a lossy and an amplifying Gaussian channel. Our finding significantly modifies the characteristics of Gaussian-state steering so far established such as monogamy relations and one-way steering under Gaussian measurements, thus opening a new direction for critical studies beyond Gaussian regime.
A weighted dictionary learning model for denoising images corrupted by mixed noise.
Liu, Jun; Tai, Xue-Cheng; Huang, Haiyang; Huan, Zhongdan
2013-03-01
This paper proposes a general weighted l(2)-l(0) norms energy minimization model to remove mixed noise such as Gaussian-Gaussian mixture, impulse noise, and Gaussian-impulse noise from the images. The approach is built upon maximum likelihood estimation framework and sparse representations over a trained dictionary. Rather than optimizing the likelihood functional derived from a mixture distribution, we present a new weighting data fidelity function, which has the same minimizer as the original likelihood functional but is much easier to optimize. The weighting function in the model can be determined by the algorithm itself, and it plays a role of noise detection in terms of the different estimated noise parameters. By incorporating the sparse regularization of small image patches, the proposed method can efficiently remove a variety of mixed or single noise while preserving the image textures well. In addition, a modified K-SVD algorithm is designed to address the weighted rank-one approximation. The experimental results demonstrate its better performance compared with some existing methods. PMID:23193456
Additive attacks on speaker recognition
NASA Astrophysics Data System (ADS)
Farrokh Baroughi, Alireza; Craver, Scott
2014-02-01
Speaker recognition is used to identify a speaker's voice from among a group of known speakers. A common method of speaker recognition is a classification based on cepstral coefficients of the speaker's voice, using a Gaussian mixture model (GMM) to model each speaker. In this paper we try to fool a speaker recognition system using additive noise such that an intruder is recognized as a target user. Our attack uses a mixture selected from a target user's GMM model, inverting the cepstral transformation to produce noise samples. In our 5 speaker data base, we achieve an attack success rate of 50% with a noise signal at 10dB SNR, and 95% by increasing noise power to 0dB SNR. The importance of this attack is its simplicity and flexibility: it can be employed in real time with no processing of an attacker's voice, and little computation is needed at the moment of detection, allowing the attack to be performed by a small portable device. For any target user, knowing that user's model or voice sample is sufficient to compute the attack signal, and it is enough that the intruder plays it while he/she is uttering to be classiffed as the victim.
Noise-induced pattern formation in a semiconductor nanostructure.
Stegemann, G; Balanov, A G; Schöll, E
2005-01-01
We investigate the influence of noise upon the dynamics of the current density distribution in a model of a semiconductor nanostructure, namely, a double barrier resonant tunneling diode. We fix the parameters of the device below the Hopf bifurcation, where the only stable state of the system is a spatially inhomogeneous "filamentary" steady state. We show that the addition of weak Gaussian white noise to the system gives rise to spatially inhomogeneous oscillations that can be quite coherent. As the noise intensity grows, the oscillations tend to become more and more spatially homogeneous, while simultaneously the temporal correlation of the oscillations decreases. Thus, while on one hand noise destroys temporal coherence, on the other hand it enhances the spatial coherence of the current density pattern. PMID:15697712
Noise to lubricate qubit transfer in a spin network
NASA Astrophysics Data System (ADS)
Rafiee, Morteza; Lupo, Cosmo; Mancini, Stefano
2013-09-01
We consider quantum state transfer in a fully connected spin network, in which the results indicate that it is impossible to achieve high fidelity by free dynamics. However, the addition of certain kinds of noise can be helpful for this purpose. In fact, we introduce a model of Gaussian white noise affecting the spin-spin couplings (edges), except those linked to the input and output node, and prove that it enhances the fidelity of state transfer. The observed noise benefit is scale free as it applies to a quantum network of any size. The amount of the fidelity enhancement, depending on the noise strength as well as on the number of edges to which it is applied, can be so high as to take the fidelity close to one.
Filter function formalism beyond pure dephasing and non-Markovian noise in singlet-triplet qubits
NASA Astrophysics Data System (ADS)
Barnes, Edwin; Rudner, Mark S.; Martins, Frederico; Malinowski, Filip K.; Marcus, Charles M.; Kuemmeth, Ferdinand
2016-03-01
The filter function formalism quantitatively describes the dephasing of a qubit by a bath that causes Gaussian fluctuations in the qubit energies with an arbitrary noise power spectrum. Here, we extend this formalism to account for more general types of noise that couple to the qubit through terms that do not commute with the qubit's bare Hamiltonian. Our approach applies to any power spectrum that generates slow noise fluctuations in the qubit's evolution. We demonstrate our formalism in the case of singlet-triplet qubits subject to both quasistatic nuclear noise and 1 /ωα charge noise and find good agreement with recent experimental findings. This comparison shows the efficacy of our approach in describing real systems and additionally highlights the challenges with distinguishing different types of noise in free induction decay experiments.
Adaptive noise Wiener filter for scanning electron microscope imaging system.
Sim, K S; Teh, V; Nia, M E
2016-01-01
Noise on scanning electron microscope (SEM) images is studied. Gaussian noise is the most common type of noise in SEM image. We developed a new noise reduction filter based on the Wiener filter. We compared the performance of this new filter namely adaptive noise Wiener (ANW) filter, with four common existing filters as well as average filter, median filter, Gaussian smoothing filter and the Wiener filter. Based on the experiments results the proposed new filter has better performance on different noise variance comparing to the other existing noise removal filters in the experiments. PMID:26235517
Gaussian discriminating strength
NASA Astrophysics Data System (ADS)
Rigovacca, L.; Farace, A.; De Pasquale, A.; Giovannetti, V.
2015-10-01
We present a quantifier of nonclassical correlations for bipartite, multimode Gaussian states. It is derived from the Discriminating Strength measure, introduced for finite dimensional systems in Farace et al., [New J. Phys. 16, 073010 (2014), 10.1088/1367-2630/16/7/073010]. As the latter the new measure exploits the quantum Chernoff bound to gauge the susceptibility of the composite system with respect to local perturbations induced by unitary gates extracted from a suitable set of allowed transformations (the latter being identified by posing some general requirements). Closed expressions are provided for the case of two-mode Gaussian states obtained by squeezing or by linearly mixing via a beam splitter a factorized two-mode thermal state. For these density matrices, we study how nonclassical correlations are related with the entanglement present in the system and with its total photon number.
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.
Flauger, Raphael; Pajer, Enrico E-mail: ep295@cornell.edu
2011-01-01
We provide a derivation from first principles of the primordial bispectrum of scalar perturbations produced during inflation driven by a canonically normalized scalar field whose potential exhibits small sinusoidal modulations. A potential of this type has been derived in a class of string theory models of inflation based on axion monodromy. We use this model as a concrete example, but we present our derivations and results for a general slow-roll potential with superimposed modulations. We show analytically that a resonance between the oscillations of the background and the oscillations of the fluctuations is responsible for the production of an observably large non-Gaussian signal. We provide an explicit expression for the shape of this resonant non-Gaussianity. We show that there is essentially no overlap between this shape and the local, equilateral, and orthogonal shapes, and we stress that resonant non-Gaussianity is not captured by the simplest version of the effective field theory of inflation. We hope our analytic expression will be useful to further observationally constrain this class of models.
Gaussian quadrature formulae for arbitrary positive measures.
Fernandes, Andrew D; Atchley, William R
2006-01-01
We present computational methods and subroutines to compute Gaussian quadrature integration formulas for arbitrary positive measures. For expensive integrands that can be factored into well-known forms, Gaussian quadrature schemes allow for efficient evaluation of high-accuracy and -precision numerical integrals, especially compared to general ad hoc schemes. In addition, for certain well-known density measures (the normal, gamma, log-normal, Student's t, inverse-gamma, beta, and Fisher's F) we present exact formulae for computing the respective quadrature scheme. PMID:19455218
Distributions of Conductance and Shot Noise and Associated Phase Transitions
Vivo, Pierpaolo; Majumdar, Satya N.; Bohigas, Oriol
2008-11-21
For a chaotic cavity with two identical leads each supporting N channels, we compute analytically, for large N, the full distribution of the conductance and the shot noise power and show that in both cases there is a central Gaussian region flanked on both sides by non-Gaussian tails. The distribution is weakly singular at the junction of Gaussian and non-Gaussian regimes, a direct consequence of two phase transitions in an associated Coulomb gas problem.
Graphical calculus for Gaussian pure states
Menicucci, Nicolas C.; Flammia, Steven T.; Loock, Peter van
2011-04-15
We provide a unified graphical calculus for all Gaussian pure states, including graph transformation rules for all local and semilocal Gaussian unitary operations, as well as local quadrature measurements. We then use this graphical calculus to analyze continuous-variable (CV) cluster states, the essential resource for one-way quantum computing with CV systems. Current graphical approaches to CV cluster states are only valid in the unphysical limit of infinite squeezing, and the associated graph transformation rules only apply when the initial and final states are of this form. Our formalism applies to all Gaussian pure states and subsumes these rules in a natural way. In addition, the term 'CV graph state' currently has several inequivalent definitions in use. Using this formalism we provide a single unifying definition that encompasses all of them. We provide many examples of how the formalism may be used in the context of CV cluster states: defining the 'closest' CV cluster state to a given Gaussian pure state and quantifying the error in the approximation due to finite squeezing; analyzing the optimality of certain methods of generating CV cluster states; drawing connections between this graphical formalism and bosonic Hamiltonians with Gaussian ground states, including those useful for CV one-way quantum computing; and deriving a graphical measure of bipartite entanglement for certain classes of CV cluster states. We mention other possible applications of this formalism and conclude with a brief note on fault tolerance in CV one-way quantum computing.
Gaussian entanglement in the turbulent atmosphere
NASA Astrophysics Data System (ADS)
Bohmann, M.; Semenov, A. A.; Sperling, J.; Vogel, W.
2016-07-01
We provide a rigorous treatment of the entanglement properties of two-mode Gaussian states in atmospheric channels by deriving and analyzing the input-output relations for the corresponding entanglement test. A key feature of such turbulent channels is a nontrivial dependence of the transmitted continuous-variable entanglement on coherent displacements of the quantum state of the input field. Remarkably, this allows one to optimize the entanglement certification by modifying local coherent amplitudes using a finite, but optimal amount of squeezing. In addition, we propose a protocol which, in principle, renders it possible to transfer the Gaussian entanglement through any turbulent channel over arbitrary distances. Therefore, our approach provides the theoretical foundation for advanced applications of Gaussian entanglement in free-space quantum communication.
Enhanced corticomuscular coherence by external stochastic noise
Trenado, Carlos; Mendez-Balbuena, Ignacio; Manjarrez, Elias; Huethe, Frank; Schulte-Mönting, Jürgen; Feige, Bernd; Hepp-Reymond, Marie-Claude; Kristeva, Rumyana
2014-01-01
Noise can have beneficial effects as shown by the stochastic resonance (SR) phenomenon which is characterized by performance improvement when an optimal noise is added. Modern attempts to improve human performance utilize this phenomenon. The purpose of the present study was to investigate whether performance improvement by addition of optimum noise (ON) is related to increased cortical motor spectral power (SP) and increased corticomuscular coherence. Eight subjects performed a visuomotor task requiring to compensate with the right index finger a static force (SF) generated by a manipulandum on which Gaussian noise was applied. The finger position was displayed on-line on a monitor as a small white dot which the subjects had to maintain in the center of a green bigger circle. Electroencephalogram from the contralateral motor area, electromyogram from active muscles and finger position were recorded. The performance was measured by the mean absolute deviation (MAD) of the white dot from the zero position. ON compared to the zero noise condition induced an improvement in motor accuracy together with an enhancement of cortical motor SP and corticomuscular coherence in beta-range. These data suggest that the improved sensorimotor performance via SR is consistent with an increase in the cortical motor SP and in the corticomuscular coherence. PMID:24904365
Judgments of aircraft noise in a traffic noise background
NASA Technical Reports Server (NTRS)
Powell, C. A.; Rice, C. G.
1975-01-01
An investigation was conducted to determine subjective response to aircraft noise in different road traffic backgrounds. In addition, two laboratory techniques for presenting the aircraft noise with the background noise were evaluated. For one technique, the background noise was continuous over an entire test session; for the other, the background noise level was changed with each aircraft noise during a session. Subjective response to aircraft noise was found to decrease with increasing background noise level, for a range of typical indoor noise levels. Subjective response was found to be highly correlated with the Noise Pollution Level (NPL) measurement scale.
M-Ary Alpha-Stable Noise Modulation in Spread-Spectrum Communication
NASA Astrophysics Data System (ADS)
Cek, Mehmet Emre
2015-04-01
In this paper, a spread-spectrum communication system based on a random carrier is proposed which transmits M-ary information. The random signal is considered as a single realization of a random process taken from prescribed symmetric α-stable (SαS) distribution that carries digital M-ary information to be transmitted. Considering the noise model in the channel as additive white Gaussian noise (AWGN), the transmitter sends the information carrying random signal from non-Gaussian density. Alpha-stable distribution is used to encode the M-ary message. Inspired by the chaos shift keying techniques, the proposed method is called M-ary symmetric alpha-stable differential shift keying (M-ary SαS-DSK). The main purpose of preferring non-Gaussian noise instead of conventional pseudo-noise (PN) sequence is to overcome the drawback of self-repeating noise-like sequences which are detectable due to the periodic behavior of the autocorrelation function of PN sequences. Having infinite second order moment in α-stable random carrier offers secrecy of the information due to the non-constant autocorrelation behavior. The bit error rate (BER) performance of the proposed method is illustrated by Monte Carlo simulations with respect to various characteristic exponent values and different data length.
... Info » Hearing, Ear Infections, and Deafness Noise-Induced Hearing Loss On this page: What is noise-induced hearing ... additional information about NIHL? What is noise-induced hearing loss? Every day, we experience sound in our environment, ...
Gaussian-optimized preparation of non-Gaussian pure states
NASA Astrophysics Data System (ADS)
Menzies, David; Filip, Radim
2009-01-01
Non-Gaussian states are highly sought-after resources in continuous-variable quantum optical information processing protocols. We outline a method for the optimized preparation of any pure non-Gaussian state to a given desired accuracy. Our proposal arises from two connected concepts. First, we define the operational cost of a desired state as the largest Fock state required for its approximate preparation. Second, we suggest that this non-Gaussian operational cost can be reduced by judicial application of optimized Gaussian operations. In particular, we identify a minimal core non-Gaussian state for any target pure state, which is related to the core state by Gaussian operations alone. We demonstrate this method for Schrödinger cat states.
Effects of transmission on Gaussian optical states.
McKinstrie, C J; Marshall, K; Weedbrook, C
2015-04-20
The noise properties of phase-insensitive and phase-sensitive optical transmission links are described in detail, for Gaussian input signals. Formulas are derived for the quadrature covariance matrices of the output signals, which allow one to quantify the noise figures of the links and the fidelities of transmission. Another formula is derived, which relates the density operator of an output signal, in the number-state representation, to its covariance matrix. This density matrix allows one to quantify the decrease in coherence and changes in photon-number probabilities associated with transmission. Based on the aforementioned performance metrics, links with distributed phase-sensitive amplification perform significantly better than other links. PMID:25969122
Yu, Hancheng; Gao, Jianlin; Li, Aiting
2016-03-01
In this Letter, a probability-based non-local means filter is proposed for speckle reduction in optical coherence tomography (OCT). Originally developed for additive white Gaussian noise, the non-local means filter is not suitable for multiplicative speckle noise suppression. This Letter presents a two-stage non-local means algorithm using the uncorrupted probability of each pixel to effectively reduce speckle noise in OCT. Experiments on real OCT images demonstrate that the proposed filter is competitive with other state-of-the-art speckle removal techniques and able to accurately preserve edges and structural details with small computational cost. PMID:26974099
Image signal-to-noise ratio estimation using adaptive slope nearest-neighbourhood model.
Sim, K S; Teh, V
2015-12-01
A new technique based on nearest neighbourhood method is proposed. In this paper, considering the noise as Gaussian additive white noise, new technique single-image-based estimator is proposed. The performance of this new technique such as adaptive slope nearest neighbourhood is compared with three of the existing method which are original nearest neighbourhood (simple method), first-order interpolation method and shape-preserving piecewise cubic hermite autoregressive moving average. In a few cases involving images with different brightness and edges, this adaptive slope nearest neighbourhood is found to deliver an optimum solution for signal-to-noise ratio estimation problems. For different values of noise variance, the adaptive slope nearest neighbourhood has highest accuracy and less percentage estimation error. Being more robust with white noise, the new proposed technique estimator has efficiency that is significantly greater than those of the three methods. PMID:26292081
Mapping possible non-Gaussianity in the Planck maps
NASA Astrophysics Data System (ADS)
Bernui, A.; Rebouças, M. J.
2015-01-01
Context. The study of the non-Gaussianity of the temperature fluctuations of cosmic background radiation (CMB) can be used to break the degeneracy between the inflationary models and to test alternative scenarios of the early universe. However, there are several sources of non-Gaussian contaminants in the CMB data, which make a convincing extraction of primordial non-Gaussianity into an ambitious observational and statistical enterprise. It is conceivable that no single statistical estimator can be sensitive to all forms and levels of non-Gaussianity that may be present in observed CMB data. In recent works a statistical procedure based upon the calculation of the skewness and kurtosis of the patches of CMB sky sphere has been proposed and used to find out significant large-angle deviation from Gaussianity in the foreground-reduced WMAP maps. Aims: Here we address the question of how previous recent analyses of Gaussianity of WMAP maps are modified if the nearly full-sky foreground-cleaned Planck maps are used, therefore extending and complementing such an examination in several regards. Methods: Once the foregrounds are cleaned through different component separation procedures, each of the resulting Planck maps is then tested for Gaussianity. We determine quantitatively the effects for Gaussianity when masking the foreground-cleaned Planck maps with the inpmask, valmask, and U73 Planck masks. Results: We show that although the foreground-cleaned Planck maps present significant deviation from Gaussianity of different degrees when the less severe inpmask and valmask are used, they become consistent with Gaussianity as detected by our indicator S when masked with the union U73 mask. A slightly smaller consistency with Gaussianity is found when the K indicator is employed, which seems to be associated with the large-angle anomalies reported by the Planck team. Finally, we examine the robustness of the Gaussianity analyses with respect to the real pixel's noise as
Calabrese, Erminia; Smidt, Joseph; Amblard, Alexandre; Cooray, Asantha; Serra, Paolo; Melchiorri, Alessandro; Heavens, Alan; Munshi, Dipak
2010-02-15
We measure the skewness power spectrum of the CMB anisotropies optimized for a detection of the secondary bispectrum generated by the correlation of the CMB lensing potential with integrated Sachs-Wolfe effect and the Sunyaev-Zel'dovich effect. The covariance of our measurements is generated by Monte Carlo simulations of Gaussian CMB fields with noise properties consistent with WMAP 5-year data. When interpreting multifrequency measurements we also take into account the confusion resulting from unresolved radio point sources. We analyze Q, V and W-band WMAP 5-year raw and foreground-cleaned maps using the KQ75 mask out to l{sub max}=600. We find no significant evidence for a nonzero non-Gaussian signal from the lensing-secondary correlation in all three bands and we constrain the overall amplitude of the cross-power spectrum between CMB lensing potential and the sum of SZ and ISW fluctuations to be 0.42{+-}0.86 and 1.19{+-}0.86 in combined V and W-band raw and foreground-cleaned maps provided by the WMAP team, respectively. The point-source amplitude at the bispectrum level measured with this skewness power spectrum is higher than previous measurements of point-source non-Gaussianity. We also consider an analysis where we also account for the primordial non-Gaussianity in addition to lensing-secondary bispectrum and point sources. The focus of this paper is on secondary anisotropies. Consequently the estimator is not optimized for primordial non-Gaussianity and the limit we find on local non-Gaussianity from the foreground-cleaned V+W maps is f{sub NL}=-13{+-}62, when marginalized over point sources and lensing-ISW/SZ contributions to the total bispectrum.
Noise filtering algorithm for the MFTF-B computer based control system
Minor, E.G.
1983-11-30
An algorithm to reduce the message traffic in the MFTF-B computer based control system is described. The algorithm filters analog inputs to the control system. Its purpose is to distinguish between changes in the inputs due to noise and changes due to significant variations in the quantity being monitored. Noise is rejected while significant changes are reported to the control system data base, thus keeping the data base updated with a minimum number of messages. The algorithm is memory efficient, requiring only four bytes of storage per analog channel, and computationally simple, requiring only subtraction and comparison. Quantitative analysis of the algorithm is presented for the case of additive Gaussian noise. It is shown that the algorithm is stable and tends toward the mean value of the monitored variable over a wide variety of additive noise distributions.
Distillation and purification of symmetric entangled Gaussian states
Fiurasek, Jaromir
2010-10-15
We propose an entanglement distillation and purification scheme for symmetric two-mode entangled Gaussian states that allows to asymptotically extract a pure entangled Gaussian state from any input entangled symmetric Gaussian state. The proposed scheme is a modified and extended version of the entanglement distillation protocol originally developed by Browne et al. [Phys. Rev. A 67, 062320 (2003)]. A key feature of the present protocol is that it utilizes a two-copy degaussification procedure that involves a Mach-Zehnder interferometer with single-mode non-Gaussian filters inserted in its two arms. The required non-Gaussian filtering operations can be implemented by coherently combining two sequences of single-photon addition and subtraction operations.
Pérez Suárez, Santiago T.; Travieso González, Carlos M.; Alonso Hernández, Jesús B.
2013-01-01
This article presents a design methodology for designing an artificial neural network as an equalizer for a binary signal. Firstly, the system is modelled in floating point format using Matlab. Afterward, the design is described for a Field Programmable Gate Array (FPGA) using fixed point format. The FPGA design is based on the System Generator from Xilinx, which is a design tool over Simulink of Matlab. System Generator allows one to design in a fast and flexible way. It uses low level details of the circuits and the functionality of the system can be fully tested. System Generator can be used to check the architecture and to analyse the effect of the number of bits on the system performance. Finally the System Generator design is compiled for the Xilinx Integrated System Environment (ISE) and the system is described using a hardware description language. In ISE the circuits are managed with high level details and physical performances are obtained. In the Conclusions section, some modifications are proposed to improve the methodology and to ensure portability across FPGA manufacturers.
Investigating binocular summation in human vision using complementary fused external noise
NASA Astrophysics Data System (ADS)
Howell, Christopher L.; Olson, Jeffrey T.
2016-05-01
The impact noise has on the processing of visual information at various stages within the human visual system (HVS) is still an open research area. To gain additional insight, twelve experiments were administered to human observers using sine wave targets to determine their contrast thresholds. A single frame of additive white Gaussian noise (AWGN) and its complement were used to investigate the effect of noise on the summation of visual information within the HVS. A standard contrast threshold experiment served as the baseline for comparisons. In the standard experiment, a range of sine wave targets are shown to the observers and their ability to detect the targets at varying contrast levels were recorded. The remaining experiments added some form of noise (noise image or its complement) and/or an additional sine wave target separated between one to three octaves to the test target. All of these experiments were tested using either a single monitor for viewing the targets or with a dual monitor presentation method for comparison. In the dual monitor experiments, a ninety degree mirror was used to direct each target to a different eye, allowing for the information to be fused binocularly. The experiments in this study present different approaches for delivering external noise to the HVS, and should allow for an improved understanding regarding how noise enters the HVS and what impact noise has on the processing of visual information.
Geometry of Gaussian quantum states
NASA Astrophysics Data System (ADS)
Link, Valentin; Strunz, Walter T.
2015-07-01
We study the Hilbert-Schmidt measure on the manifold of mixed Gaussian states in multi-mode continuous variable quantum systems. An analytical expression for the Hilbert-Schmidt volume element is derived. Its corresponding probability measure can be used to study typical properties of Gaussian states. It turns out that although the manifold of Gaussian states is unbounded, an ensemble of Gaussian states distributed according to this measure still has a normalizable distribution of symplectic eigenvalues, from which unitarily invariant properties can be obtained. By contrast, we find that for an ensemble of one-mode Gaussian states based on the Bures measure the corresponding distribution cannot be normalized. As important applications, we determine the distribution and the mean value of von Neumann entropy and purity for the Hilbert-Schmidt measure.
Shanghai alleviates noise pollution
Ding Runling
1983-07-14
''Environmental noise is now under control in Shanghai, the level of environmental noise is basically holding steady, and in some areas industrial and traffic noise has decreased.'' These were the conclusions of research by Hong Zonghui (3163 1350 6540) and Wang Shixian (3769 6164 6343) of Tongji University's Acoustics Laboratory, as put forward at a recent public academic lecture at Tongji University. In order to eliminate noise from the environment, Tongji University in the early 1970's began conducting investigations and research on noise pollution and its control together with concerned units in this city. After tests in a network of 2,117 points throughout the city, they determined that the most common form of noise pollution is traffic, which accounts for 50 percent of all noise. Since 1979, this city has adopted successive measures in the area of traffic control in order to eliminate the source of noise. Traffic noise has now dropped about 3 decibels in the city. This research report also pointed out that according to the results of regional environmental noise tests, this city does not meet the noise pollution standards set by the state. Tugboats on the Suzhou He blow their whistles late at night, and the noise at riverside homes can reach 82 decibels; the Fangua Lane residential district is close to a railroad where engine noise can reach 89 decibels and affect the residents' health. In addition, rather serious noise pollution is produced by more than 300 handicraft, light industry, textile, and electrical machinery plants.
Errors associated with fitting Gaussian profiles to noisy emission-line spectra
NASA Technical Reports Server (NTRS)
Lenz, Dawn D.; Ayres, Thomas R.
1992-01-01
Landman et al. (1982) developed prescriptions to predict profile fitting errors for Gaussian emission lines perturbed by white noise. We show that their scaling laws can be generalized to more complicated signal-dependent 'noise models' of common astronomical detector systems.
Normal form decomposition for Gaussian-to-Gaussian superoperators
De Palma, Giacomo; Mari, Andrea; Giovannetti, Vittorio; Holevo, Alexander S.
2015-05-15
In this paper, we explore the set of linear maps sending the set of quantum Gaussian states into itself. These maps are in general not positive, a feature which can be exploited as a test to check whether a given quantum state belongs to the convex hull of Gaussian states (if one of the considered maps sends it into a non-positive operator, the above state is certified not to belong to the set). Generalizing a result known to be valid under the assumption of complete positivity, we provide a characterization of these Gaussian-to-Gaussian (not necessarily positive) superoperators in terms of their action on the characteristic function of the inputs. For the special case of one-mode mappings, we also show that any Gaussian-to-Gaussian superoperator can be expressed as a concatenation of a phase-space dilatation, followed by the action of a completely positive Gaussian channel, possibly composed with a transposition. While a similar decomposition is shown to fail in the multi-mode scenario, we prove that it still holds at least under the further hypothesis of homogeneous action on the covariance matrix.
Growth of Gaussian instabilities in Gaussian laser beams
Abbi, S.C.; Kothari, N.C.
1980-03-01
We present a theory for the growth of a Gaussian perturbation superimposed on a Gaussian profile laser beam. This theory gives an exponential growth of the perturbation for small distances z traveled inside the nonlinear medium. For larger values of z, the growth is not exponential. The growth parameter ..cap alpha.. is defined and an analytical expression for this parameter is obtained. Our theory gives a smooth matching between the exponential growth of perturbations in a linearized instability theory and the sharp self-focusing thresholds expected for smooth Gaussian profile laser beams propagating in nonlinear media.
Efficient entanglement criteria beyond Gaussian limits using Gaussian measurements.
Nha, Hyunchul; Lee, Su-Yong; Ji, Se-Wan; Kim, M S
2012-01-20
We present a formalism to derive entanglement criteria beyond the Gaussian regime that can be readily tested by only homodyne detection. The measured observable is the Einstein-Podolsky-Rosen (EPR) correlation. Its arbitrary functional form enables us to detect non-Gaussian entanglement even when an entanglement test based on second-order moments fails. We illustrate the power of our experimentally friendly criteria for a broad class of non-Gaussian states under realistic conditions. We also show rigorously that quantum teleportation for continuous variables employs a specific functional form of EPR correlation. PMID:22400723
Recurrence plots of discrete-time Gaussian stochastic processes
NASA Astrophysics Data System (ADS)
Ramdani, Sofiane; Bouchara, Frédéric; Lagarde, Julien; Lesne, Annick
2016-09-01
We investigate the statistical properties of recurrence plots (RPs) of data generated by discrete-time stationary Gaussian random processes. We analytically derive the theoretical values of the probabilities of occurrence of recurrence points and consecutive recurrence points forming diagonals in the RP, with an embedding dimension equal to 1. These results allow us to obtain theoretical values of three measures: (i) the recurrence rate (REC) (ii) the percent determinism (DET) and (iii) RP-based estimation of the ε-entropy κ(ε) in the sense of correlation entropy. We apply these results to two Gaussian processes, namely first order autoregressive processes and fractional Gaussian noise. For these processes, we simulate a number of realizations and compare the RP-based estimations of the three selected measures to their theoretical values. These comparisons provide useful information on the quality of the estimations, such as the minimum required data length and threshold radius used to construct the RP.
Modelling of sub-wavelength THz sources as Gaussian apertures.
Lin, Hungyen; Fumeaux, Christophe; Fischer, Bernd Michael; Abbott, Derek
2010-08-16
The THz emission point on a nonlinear electro-optical crystal for generating broadband THz radiation is modeled as a radiating Gaussian aperture. With the wavelengths of the infrared pump beam being much smaller than the wavelength components of the generated THz pulse, a THz sub-wavelength radiating aperture with Gaussian profile is effectively created. This paper comprehensively investigates Gaussian apertures in focused THz radiation generation in electro-optical crystals and illustrates the breakdown of the paraxial approximation at low THz frequencies. The findings show that the shape of the radiation pattern causes a reduction in detectable THz radiation and hence contributes significantly to low signal-to-noise ratio in THz radiation generation. Whilst we have demonstrated the findings on optical rectification in this paper, the model may apply without a loss of generality to other types of apertures sources in THz radiation generation. PMID:20721154
Detection methods for non-Gaussian gravitational wave stochastic backgrounds
NASA Astrophysics Data System (ADS)
Drasco, Steve; Flanagan, Éanna É.
2003-04-01
A gravitational wave stochastic background can be produced by a collection of independent gravitational wave events. There are two classes of such backgrounds, one for which the ratio of the average time between events to the average duration of an event is small (i.e., many events are on at once), and one for which the ratio is large. In the first case the signal is continuous, sounds something like a constant hiss, and has a Gaussian probability distribution. In the second case, the discontinuous or intermittent signal sounds something like popcorn popping, and is described by a non-Gaussian probability distribution. In this paper we address the issue of finding an optimal detection method for such a non-Gaussian background. As a first step, we examine the idealized situation in which the event durations are short compared to the detector sampling time, so that the time structure of the events cannot be resolved, and we assume white, Gaussian noise in two collocated, aligned detectors. For this situation we derive an appropriate version of the maximum likelihood detection statistic. We compare the performance of this statistic to that of the standard cross-correlation statistic both analytically and with Monte Carlo simulations. In general the maximum likelihood statistic performs better than the cross-correlation statistic when the stochastic background is sufficiently non-Gaussian, resulting in a gain factor in the minimum gravitational-wave energy density necessary for detection. This gain factor ranges roughly between 1 and 3, depending on the duty cycle of the background, for realistic observing times and signal strengths for both ground and space based detectors. The computational cost of the statistic, although significantly greater than that of the cross-correlation statistic, is not unreasonable. Before the statistic can be used in practice with real detector data, further work is required to generalize our analysis to accommodate separated, misaligned
The design and research of anti-color-noise chaos M-ary communication system
NASA Astrophysics Data System (ADS)
Fu, Yongqing; Li, Xingyuan; Li, Yanan; Zhang, Lin
2016-03-01
Previously a novel chaos M-ary digital communication method based on spatiotemporal chaos Hamilton oscillator has been proposed. Without chaos synchronization circumstance, it has performance improvement in bandwidth efficiency, transmission efficiency and anti-white-noise performance compared with traditional communication method. In this paper, the channel noise influence on chaotic modulation signals and the construction problem of anti-color-noise chaotic M-ary communication system are studied. The formula of zone partition demodulator's boundary in additive white Gaussian noise is derived, besides, the problem about how to determine the boundary of zone partition demodulator in additive color noise is deeply studied; Then an approach on constructing anti-color-noise chaos M-ary communication system is proposed, in which a pre-distortion filter is added after the chaos baseband modulator in the transmitter and whitening filter is added before zone partition demodulator in the receiver. Finally, the chaos M-ary communication system based on Hamilton oscillator is constructed and simulated in different channel noise. The result shows that the proposed method in this paper can improve the anti-color-noise performance of the whole communication system compared with the former system, and it has better anti-fading and resisting disturbance performance than Quadrature Phase Shift Keying system.
Research on Bayes matting algorithm based on Gaussian mixture model
NASA Astrophysics Data System (ADS)
Quan, Wei; Jiang, Shan; Han, Cheng; Zhang, Chao; Jiang, Zhengang
2015-12-01
The digital matting problem is a classical problem of imaging. It aims at separating non-rectangular foreground objects from a background image, and compositing with a new background image. Accurate matting determines the quality of the compositing image. A Bayesian matting Algorithm Based on Gaussian Mixture Model is proposed to solve this matting problem. Firstly, the traditional Bayesian framework is improved by introducing Gaussian mixture model. Then, a weighting factor is added in order to suppress the noises of the compositing images. Finally, the effect is further improved by regulating the user's input. This algorithm is applied to matting jobs of classical images. The results are compared to the traditional Bayesian method. It is shown that our algorithm has better performance in detail such as hair. Our algorithm eliminates the noise well. And it is very effectively in dealing with the kind of work, such as interested objects with intricate boundaries.
Noise generator for tinnitus treatment based on look-up tables
NASA Astrophysics Data System (ADS)
Uriz, Alejandro J.; Agüero, Pablo; Tulli, Juan C.; Castiñeira Moreira, Jorge; González, Esteban; Hidalgo, Roberto; Casadei, Manuel
2016-04-01
Treatment of tinnitus by means of masking sounds allows to obtain a significant improve of the quality of life of the individual that suffer that condition. In view of that, it is possible to develop noise synthesizers based on random number generators in digital signal processors (DSP), which are used in almost any digital hearing aid devices. DSP architecture have limitations to implement a pseudo random number generator, due to it, the noise statistics can be not as good as expectations. In this paper, a technique to generate additive white gaussian noise (AWGN) or other types of filtered noise using coefficients stored in program memory of the DSP is proposed. Also, an implementation of the technique is carried out on a dsPIC from Microchip®. Objective experiments and experimental measurements are performed to analyze the proposed technique.
Noise-induced standing waves in oscillatory systems with time-delayed feedback
NASA Astrophysics Data System (ADS)
Stich, Michael; Chattopadhyay, Amit K.
2016-05-01
In oscillatory reaction-diffusion systems, time-delay feedback can lead to the instability of uniform oscillations with respect to formation of standing waves. Here, we investigate how the presence of additive, Gaussian white noise can induce the appearance of standing waves. Combining analytical solutions of the model with spatiotemporal simulations, we find that noise can promote standing waves in regimes where the deterministic uniform oscillatory modes are stabilized. As the deterministic phase boundary is approached, the spatiotemporal correlations become stronger, such that even small noise can induce standing waves in this parameter regime. With larger noise strengths, standing waves could be induced at finite distances from the (deterministic) phase boundary. The overall dynamics is defined through the interplay of noisy forcing with the inherent reaction-diffusion dynamics.
NASA Technical Reports Server (NTRS)
Huston, R. J. (Compiler)
1982-01-01
The establishment of a realistic plan for NASA and the U.S. helicopter industry to develop a design-for-noise methodology, including plans for the identification and development of promising noise reduction technology was discussed. Topics included: noise reduction techniques, scaling laws, empirical noise prediction, psychoacoustics, and methods of developing and validing noise prediction methods.
NASA Technical Reports Server (NTRS)
Hultgren, Lennart S.
2010-01-01
This presentation is a technical progress report and near-term outlook for NASA-internal and NASA-sponsored external work on core (combustor and turbine) noise funded by the Fundamental Aeronautics Program Subsonic Fixed Wing (SFW) Project. Sections of the presentation cover: the SFW system level noise metrics for the 2015, 2020, and 2025 timeframes; the emerging importance of core noise and its relevance to the SFW Reduced-Noise-Aircraft Technical Challenge; the current research activities in the core-noise area, with some additional details given about the development of a high-fidelity combustion-noise prediction capability; the need for a core-noise diagnostic capability to generate benchmark data for validation of both high-fidelity work and improved models, as well as testing of future noise-reduction technologies; relevant existing core-noise tests using real engines and auxiliary power units; and examples of possible scenarios for a future diagnostic facility. The NASA Fundamental Aeronautics Program has the principal objective of overcoming today's national challenges in air transportation. The SFW Reduced-Noise-Aircraft Technical Challenge aims to enable concepts and technologies to dramatically reduce the perceived aircraft noise outside of airport boundaries. This reduction of aircraft noise is critical for enabling the anticipated large increase in future air traffic. Noise generated in the jet engine core, by sources such as the compressor, combustor, and turbine, can be a significant contribution to the overall noise signature at low-power conditions, typical of approach flight. At high engine power during takeoff, jet and fan noise have traditionally dominated over core noise. However, current design trends and expected technological advances in engine-cycle design as well as noise-reduction methods are likely to reduce non-core noise even at engine-power points higher than approach. In addition, future low-emission combustor designs could increase
A unifying review of linear gaussian models.
Roweis, S; Ghahramani, Z
1999-02-15
Factor analysis, principal component analysis, mixtures of gaussian clusters, vector quantization, Kalman filter models, and hidden Markov models can all be unified as variations of unsupervised learning under a single basic generative model. This is achieved by collecting together disparate observations and derivations made by many previous authors and introducing a new way of linking discrete and continuous state models using a simple nonlinearity. Through the use of other nonlinearities, we show how independent component analysis is also a variation of the same basic generative model. We show that factor analysis and mixtures of gaussians can be implemented in autoencoder neural networks and learned using squared error plus the same regularization term. We introduce a new model for static data, known as sensible principal component analysis, as well as a novel concept of spatially adaptive observation noise. We also review some of the literature involving global and local mixtures of the basic models and provide pseudocode for inference and learning for all the basic models. PMID:9950734
Brain MRI segmentation and lesion detection using generalized Gaussian and Rician modeling
NASA Astrophysics Data System (ADS)
Wu, Xuqiang; Bricq, Stéphanie; Collet, Christophe
2011-03-01
In this paper we propose a mixed noise modeling so as to segment the brain and to detect lesion. Indeed, accurate segmentation of multimodal (T1, T2 and Flair) brain MR images is of great interest for many brain disorders but requires to efficiently manage multivariate correlated noise between available modalities. We addressed this problem in1 by proposing an entirely unsupervised segmentation scheme, taking into account multivariate Gaussian noise, imaging artifacts,intrinsic tissue variation and partial volume effects in a Bayesian framework. Nevertheless, tissue classification remains a challenging task especially when one addresses the lesion detection during segmentation process2 as we did. In order to improve brain segmentation into White and Gray Matter (resp. WM and GM) and cerebro-spinal fluid (CSF), we propose to fit a Rician (RC) density distribution for CSF whereas Generalized Gaussian (GG) models are used to fit the likelihood between model and data corresponding to WM and GM. In this way, we present in this paper promising results showing that in a multimodal segmentation-detection scheme, this model fits better with the data and increases lesion detection rate. One of the main challenges consists in being able to take into account various pdf (Gaussian and non- Gaussian) for correlated noise between modalities and to show that lesion-detection is then clearly improved, probably because non-Gaussian noise better fits to the physic of MRI image acquisition.
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Pseudospectral Gaussian quantum dynamics: Efficient sampling of potential energy surfaces
NASA Astrophysics Data System (ADS)
Heaps, Charles W.; Mazziotti, David A.
2016-04-01
Trajectory-based Gaussian basis sets have been tremendously successful in describing high-dimensional quantum molecular dynamics. In this paper, we introduce a pseudospectral Gaussian-based method that achieves accurate quantum dynamics using efficient, real-space sampling of the time-dependent basis set. As in other Gaussian basis methods, we begin with a basis set expansion using time-dependent Gaussian basis functions guided by classical mechanics. Unlike other Gaussian methods but characteristic of the pseudospectral and collocation methods, the basis set is tested with N Dirac delta functions, where N is the number of basis functions, rather than using the basis function as test functions. As a result, the integration for matrix elements is reduced to function evaluation. Pseudospectral Gaussian dynamics only requires O ( N ) potential energy calculations, in contrast to O ( N 2 ) evaluations in a variational calculation. The classical trajectories allow small basis sets to sample high-dimensional potentials. Applications are made to diatomic oscillations in a Morse potential and a generalized version of the Henon-Heiles potential in two, four, and six dimensions. Comparisons are drawn to full analytical evaluation of potential energy integrals (variational) and the bra-ket averaged Taylor (BAT) expansion, an O ( N ) approximation used in Gaussian-based dynamics. In all cases, the pseudospectral Gaussian method is competitive with full variational calculations that require a global, analytical, and integrable potential energy surface. Additionally, the BAT breaks down when quantum mechanical coherence is particularly strong (i.e., barrier reflection in the Morse oscillator). The ability to obtain variational accuracy using only the potential energy at discrete points makes the pseudospectral Gaussian method a promising avenue for on-the-fly dynamics, where electronic structure calculations become computationally significant.
Pseudospectral Gaussian quantum dynamics: Efficient sampling of potential energy surfaces.
Heaps, Charles W; Mazziotti, David A
2016-04-28
Trajectory-based Gaussian basis sets have been tremendously successful in describing high-dimensional quantum molecular dynamics. In this paper, we introduce a pseudospectral Gaussian-based method that achieves accurate quantum dynamics using efficient, real-space sampling of the time-dependent basis set. As in other Gaussian basis methods, we begin with a basis set expansion using time-dependent Gaussian basis functions guided by classical mechanics. Unlike other Gaussian methods but characteristic of the pseudospectral and collocation methods, the basis set is tested with N Dirac delta functions, where N is the number of basis functions, rather than using the basis function as test functions. As a result, the integration for matrix elements is reduced to function evaluation. Pseudospectral Gaussian dynamics only requires O(N) potential energy calculations, in contrast to O(N(2)) evaluations in a variational calculation. The classical trajectories allow small basis sets to sample high-dimensional potentials. Applications are made to diatomic oscillations in a Morse potential and a generalized version of the Henon-Heiles potential in two, four, and six dimensions. Comparisons are drawn to full analytical evaluation of potential energy integrals (variational) and the bra-ket averaged Taylor (BAT) expansion, an O(N) approximation used in Gaussian-based dynamics. In all cases, the pseudospectral Gaussian method is competitive with full variational calculations that require a global, analytical, and integrable potential energy surface. Additionally, the BAT breaks down when quantum mechanical coherence is particularly strong (i.e., barrier reflection in the Morse oscillator). The ability to obtain variational accuracy using only the potential energy at discrete points makes the pseudospectral Gaussian method a promising avenue for on-the-fly dynamics, where electronic structure calculations become computationally significant. PMID:27131532
Core Noise - Increasing Importance
NASA Technical Reports Server (NTRS)
Hultgren, Lennart S.
2011-01-01
This presentation is a technical summary of and outlook for NASA-internal and NASA-sponsored external research on core (combustor and turbine) noise funded by the Fundamental Aeronautics Program Subsonic Fixed Wing (SFW) Project. Sections of the presentation cover: the SFW system-level noise metrics for the 2015, 2020, and 2025 timeframes; turbofan design trends and their aeroacoustic implications; the emerging importance of core noise and its relevance to the SFW Reduced-Perceived-Noise Technical Challenge; and the current research activities in the core-noise area, with additional details given about the development of a high-fidelity combustor-noise prediction capability as well as activities supporting the development of improved reduced-order, physics-based models for combustor-noise prediction. The need for benchmark data for validation of high-fidelity and modeling work and the value of a potential future diagnostic facility for testing of core-noise-reduction concepts are indicated. The NASA Fundamental Aeronautics Program has the principal objective of overcoming today's national challenges in air transportation. The SFW Reduced-Perceived-Noise Technical Challenge aims to develop concepts and technologies to dramatically reduce the perceived aircraft noise outside of airport boundaries. This reduction of aircraft noise is critical to enabling the anticipated large increase in future air traffic. Noise generated in the jet engine core, by sources such as the compressor, combustor, and turbine, can be a significant contribution to the overall noise signature at low-power conditions, typical of approach flight. At high engine power during takeoff, jet and fan noise have traditionally dominated over core noise. However, current design trends and expected technological advances in engine-cycle design as well as noise-reduction methods are likely to reduce non-core noise even at engine-power points higher than approach. In addition, future low-emission combustor
NASA Astrophysics Data System (ADS)
Artmann, Uwe; Wueller, Dietmar
2009-01-01
We present a method to improve the validity of noise and resolution measurements on digital cameras. If non-linear adaptive noise reduction is part of the signal processing in the camera, the measurement results for image noise and spatial resolution can be good, while the image quality is low due to the loss of fine details and a watercolor like appearance of the image. To improve the correlation between objective measurement and subjective image quality we propose to supplement the standard test methods with an additional measurement of the texture preserving capabilities of the camera. The proposed method uses a test target showing white Gaussian noise. The camera under test reproduces this target and the image is analyzed. We propose to use the kurtosis of the derivative of the image as a metric for the texture preservation of the camera. Kurtosis is a statistical measure for the closeness of a distribution compared to the Gaussian distribution. It can be shown, that the distribution of digital values in the derivative of the image showing the chart becomes the more leptokurtic (increased kurtosis) the stronger the noise reduction has an impact on the image.
Resonant non-Gaussianity with equilateral properties
Gwyn, Rhiannon; Rummel, Markus; Westphal, Alexander E-mail: markus.rummel@desy.de
2013-04-01
We discuss the effect of superimposing multiple sources of resonant non-Gaussianity, which arise for instance in models of axion inflation. The resulting sum of oscillating shape contributions can be used to ''Fourier synthesize'' different non-oscillating shapes in the bispectrum. As an example we reproduce an approximately equilateral shape from the superposition of O(10) oscillatory contributions with resonant shape. This implies a possible degeneracy between the equilateral-type non-Gaussianity typical of models with non-canonical kinetic terms, such as DBI inflation, and an equilateral-type shape arising from a superposition of resonant-type contributions in theories with canonical kinetic terms. The absence of oscillations in the 2-point function together with the structure of resonant N-point functions give a constraint of f{sub NL}∼
Quantum correlations in Gaussian states via Gaussian channels: steering, entanglement, and discord
NASA Astrophysics Data System (ADS)
Wang, Zhong-Xiao; Wang, Shuhao; Li, Qiting; Wang, Tie-Jun; Wang, Chuan
2016-06-01
Here we study the quantum steering, quantum entanglement, and quantum discord for Gaussian Einstein-Podolsky-Rosen states via Gaussian channels. And the sudden death phenomena for Gaussian steering and Gaussian entanglement are theoretically observed. We find that some Gaussian states have only one-way steering, which confirms the asymmetry of quantum steering. Also we investigate that the entangled Gaussian states without Gaussian steering and correlated Gaussian states own no Gaussian entanglement. Meanwhile, our results support the assumption that quantum entanglement is intermediate between quantum discord and quantum steering. Furthermore, we give experimental recipes for preparing quantum states with desired types of quantum correlations.
Statistical properties of two sine waves in Gaussian noise.
NASA Technical Reports Server (NTRS)
Esposito, R.; Wilson, L. R.
1973-01-01
A detailed study is presented of some statistical properties of a stochastic process that consists of the sum of two sine waves of unknown relative phase and a normal process. Since none of the statistics investigated seem to yield a closed-form expression, all the derivations are cast in a form that is particularly suitable for machine computation. Specifically, results are presented for the probability density function (pdf) of the envelope and the instantaneous value, the moments of these distributions, and the relative cumulative density function (cdf).
A Network of Kalman Filters for MAI and ISI Compensation in a Non-Gaussian Environment
NASA Astrophysics Data System (ADS)
Sayadi, Bessem; Marcos, Sylvie
2005-12-01
This paper develops a new multiuser detector based on a network of kalman filters (NKF) dealing with multiple access-interference (MAI), intersymbol Interference (ISI), and an impulsive observation noise. The two proposed schemes are based on the modeling of the DS-CDMA system by a discrete-time linear system that has non-Gaussian state and measurement noises. By approximating the non-Gaussian densities of the noises by a weighted sum of Gaussian terms and under the common MMSE estimation criterion, we first derive an NKF detector. This version is further optimized by introducing a feedback exploiting the ISI interference structure. The resulting scheme is an NKF detector based on a likelihood ratio test (LRT). Monte-Carlo simulations have shown that the NKF and the NKF based on LRT detectors significantly improve the efficiency and the performance of the classical Kalman algorithm.
Variational superposed Gaussian approximation for time-dependent solutions of Langevin equations
NASA Astrophysics Data System (ADS)
Hasegawa, Yoshihiko
2015-04-01
We propose a variational superposed Gaussian approximation (VSGA) for dynamical solutions of Langevin equations subject to applied signals, determining time-dependent parameters of superposed Gaussian distributions by the variational principle. We apply the proposed VSGA to systems driven by a chaotic signal, where the conventional Fourier method cannot be adopted, and calculate the time evolution of probability density functions (PDFs) and moments. Both white and colored Gaussian noises terms are included to describe fluctuations. Our calculations show that time-dependent PDFs obtained by VSGA agree excellently with those obtained by Monte Carlo simulations. The correlation between the chaotic input signal and the mean response are also calculated as a function of the noise intensity, which confirms the occurrence of aperiodic stochastic resonance with both white and colored noises.
Channel purification via continuous-variable quantum teleportation with Gaussian postselection
NASA Astrophysics Data System (ADS)
Blandino, Rémi; Walk, Nathan; Lund, Austin P.; Ralph, Timothy C.
2016-01-01
We present a protocol based on continuous-variable quantum teleportation and Gaussian postselection that can be used to correct errors introduced by a lossy channel. We first show that the global transformation enacted by the protocol is equivalent to an effective system composed of a noiseless amplification (or attenuation), and an effective quantum channel, which can in theory have no loss and an amount of thermal noise arbitrarily small, hence tending to an identity channel. An application of our protocol is the probabilistic purification of quantum non-Gaussian states using only Gaussian operations.
Information geometry of Gaussian channels
Monras, Alex; Illuminati, Fabrizio
2010-06-15
We define a local Riemannian metric tensor in the manifold of Gaussian channels and the distance that it induces. We adopt an information-geometric approach and define a metric derived from the Bures-Fisher metric for quantum states. The resulting metric inherits several desirable properties from the Bures-Fisher metric and is operationally motivated by distinguishability considerations: It serves as an upper bound to the attainable quantum Fisher information for the channel parameters using Gaussian states, under generic constraints on the physically available resources. Our approach naturally includes the use of entangled Gaussian probe states. We prove that the metric enjoys some desirable properties like stability and covariance. As a by-product, we also obtain some general results in Gaussian channel estimation that are the continuous-variable analogs of previously known results in finite dimensions. We prove that optimal probe states are always pure and bounded in the number of ancillary modes, even in the presence of constraints on the reduced state input in the channel. This has experimental and computational implications. It limits the complexity of optimal experimental setups for channel estimation and reduces the computational requirements for the evaluation of the metric: Indeed, we construct a converging algorithm for its computation. We provide explicit formulas for computing the multiparametric quantum Fisher information for dissipative channels probed with arbitrary Gaussian states and provide the optimal observables for the estimation of the channel parameters (e.g., bath couplings, squeezing, and temperature).
A ring-source model for jet noise
NASA Technical Reports Server (NTRS)
Maestrello, L.
1978-01-01
A model consisting of two ring sources was developed to study the direct radiation of jet noise in terms of correlation, coherence, and phase and also to aid in solving the inverse radiation problem of determining the noise source in terms of far-field measurements. The rings consist of discrete sources which are either monopoles or quadrupoles with Gaussian profiles. Only adjacent sources, both within the rings and between rings, are correlated. Results show that from the far-field information can be used to determine when the sources are compact or noncompact with respect to the acoustic wavelength and to distinguish between the types of sources. In addition, from the inverse radiation approach, the center of mass, the location and separation distance of the ring, and the diameters can be recovered.
NASA Astrophysics Data System (ADS)
Methods for noise abatement are discussed. Noise nuisance, types of noise (continuous, fluctuating, intermittent, pulsed), and types of noise abatement (absorption, vibration damping, isolation) are defined. Rockwool panels, industrial ceiling panels, baffles, acoustic foam panels, vibration dampers, acoustic mats, sandwich panels, isolating cabins and walls, ear protectors, and curtains are presented.
Capacity and optimal collusion attack channels for Gaussian fingerprinting games
NASA Astrophysics Data System (ADS)
Wang, Ying; Moulin, Pierre
2007-02-01
constraints. Under those constraints on the fingerprint embedder and the colluders, fingerprinting capacity is obtained as the solution of a mutual-information game involving probability density functions (pdf's) designed by the embedder and the colluders. We show that the optimal fingerprinting strategy is a Gaussian test channel where the fingerprinted signal is the sum of an attenuated version of the cover signal plus a Gaussian information-bearing noise, and the optimal collusion strategy is to average fingerprinted signals possessed by all the colluders and pass the averaged copy through a Gaussian test channel. The capacity result and the optimal strategies are the same for both the private and public games. In the former scenario, the original covertext is available to the decoder, while in the latter setup, the original covertext is available to the encoder but not to the decoder.
Chromatic dispersion and nonlinear phase noise compensation based on KLMS method
NASA Astrophysics Data System (ADS)
Nouri, Mahdi; Shayesteh, Mahrokh G.; Farhangian, Nooshin
2015-09-01
In this study, kernel least mean square (KLMS) algorithm with fractionally spaced equalizing structure is proposed for electrical compensation of chromatic dispersion (CD) and nonlinear phase noise (NLPN) in a dual polarization optical communications system with coherent detection. We consider single mode fiber channel. At the receiver, the additive optical noise is represented as additive white Gaussian noise. Phase modification is utilized at high signal powers to maintain the validity of Gaussian model of noise. We consider QAM and PSK modulations and evaluate the performance of the proposed method in terms of error rate, phase error, and error vector magnitude (EVM). The results are obtained in both linear and nonlinear regimes. In the linear region, the KLMS algorithm can compensate CD and NLPN effectively and outperforms the existing compensation methods such as LMS, minimum mean square error (MMSE), and time domain FIR filter. In nonlinear regime, where the input power is higher, NLPN is stronger which results in compensation performance degradation. However, KLMS still achieves better results than the above algorithms.
Comparative Analysis of Median and Average Filters in Impulse Noise Suppression
NASA Astrophysics Data System (ADS)
Shi, Luyao; Chen, Yang; Yuan, Wenlong; Zhang, Libo; Yang, Benqiang; Shu, Huazhong; Luo, Limin; Coatrieux, Jean-Louis
2015-10-01
Median type filters coupled with the Laplacian distribution assumption have shown a high efficiency in suppressing impulse noise. We however demonstrate in this paper that the Gaussian distribution assumption is more preferable than Laplacian distribution assumption in suppressing impulse noise, especially for high noise densities. This conclusion is supported by numerical experiments with different noise densities and filter models.
Gaussian entanglement distribution via satellite
NASA Astrophysics Data System (ADS)
Hosseinidehaj, Nedasadat; Malaney, Robert
2015-02-01
In this work we analyze three quantum communication schemes for the generation of Gaussian entanglement between two ground stations. Communication occurs via a satellite over two independent atmospheric fading channels dominated by turbulence-induced beam wander. In our first scheme, the engineering complexity remains largely on the ground transceivers, with the satellite acting simply as a reflector. Although the channel state information of the two atmospheric channels remains unknown in this scheme, the Gaussian entanglement generation between the ground stations can still be determined. On the ground, distillation and Gaussification procedures can be applied, leading to a refined Gaussian entanglement generation rate between the ground stations. We compare the rates produced by this first scheme with two competing schemes in which quantum complexity is added to the satellite, thereby illustrating the tradeoff between space-based engineering complexity and the rate of ground-station entanglement generation.
Optimum threshold selection method of centroid computation for Gaussian spot
NASA Astrophysics Data System (ADS)
Li, Xuxu; Li, Xinyang; Wang, Caixia
2015-10-01
Centroid computation of Gaussian spot is often conducted to get the exact position of a target or to measure wave-front slopes in the fields of target tracking and wave-front sensing. Center of Gravity (CoG) is the most traditional method of centroid computation, known as its low algorithmic complexity. However both electronic noise from the detector and photonic noise from the environment reduces its accuracy. In order to improve the accuracy, thresholding is unavoidable before centroid computation, and optimum threshold need to be selected. In this paper, the model of Gaussian spot is established to analyze the performance of optimum threshold under different Signal-to-Noise Ratio (SNR) conditions. Besides, two optimum threshold selection methods are introduced: TmCoG (using m % of the maximum intensity of spot as threshold), and TkCoG ( usingμn +κσ n as the threshold), μn and σn are the mean value and deviation of back noise. Firstly, their impact on the detection error under various SNR conditions is simulated respectively to find the way to decide the value of k or m. Then, a comparison between them is made. According to the simulation result, TmCoG is superior over TkCoG for the accuracy of selected threshold, and detection error is also lower.
NASA Technical Reports Server (NTRS)
Strahle, W. C.
1977-01-01
A review of the subject of combustion generated noise is presented. Combustion noise is an important noise source in industrial furnaces and process heaters, turbopropulsion and gas turbine systems, flaring operations, Diesel engines, and rocket engines. The state-of-the-art in combustion noise importance, understanding, prediction and scaling is presented for these systems. The fundamentals and available theories of combustion noise are given. Controversies in the field are discussed and recommendations for future research are made.
NASA Technical Reports Server (NTRS)
Pendley, R. E.
1982-01-01
The problem of airport noise at several airports and air bases is detailed. Community reactions to the noise, steps taken to reduce jet engine noise, and the effect of airport use restrictions and curfews on air transportation are discussed. The adverse effect of changes in allowable operational noise on airport safety and altenative means for reducing noise pollution are considered. Community-airport relations and public relations are discussed.
Capacity of Pulse-Position Modulation (PPM) on Gaussian and Webb Channels
NASA Technical Reports Server (NTRS)
Dolinar, S.; Divsalar, D.; Hamkins, J.; Pollara, F.
2000-01-01
This article computes the capacity of various idealized soft-decision channels modeling an optical channel using an avalanche photodiode detector (APD) and pulse-position modulation (PPM). The capacity of this optical channel depends in a complicated way on the physical parameters of the APD and the constraints imposed by the PPM orthogonal signaling set. This article attempts to identify and separate the effects of several fundamental parameters on the capacity of the APD-detected optical PPM channel. First, an overall signal-to-noise ratio (SNR) parameter is de ned such that the capacity as a function of a bit-normalized version of this SNR drops precipitously toward zero at quasi-brick-wall limits on bit SNR that are numerically the same as the well-understood brick-wall limits for the standard additive white Gaussian noise (AWGN) channel. A second parameter is used to quantify the effects on capacity of one unique facet of the optical PPM channel (as compared with the standard AWGN channel) that causes the noise variance to be higher in signal slots than in nonsignal slots. This nonuniform noise variance yields interesting capacity effects even when the channel model is AWGN. A third parameter is used to measure the effects on capacity of the difference between an AWGN model and a non-Gaussian model proposed by Webb (see reference in [2]) for approximating the statistics of the APD-detected optical channel. Finally, a fourth parameter is used to quantify the blending of a Webb model with a pure AWGN model to account for thermal noise. Numerical results show that the capacity of M-ary orthogonal signaling on the Webb channel exhibits the same brick-wall Shannon limit, (M ln 2)=(M 1), as on the AWGN channel ( 1:59 dB for large M). Results also compare the capacity obtained by hard- and soft-output channels and indicate that soft-output channels o er a 3-dB advantage.
On generalized averaged Gaussian formulas
NASA Astrophysics Data System (ADS)
Spalevic, Miodrag M.
2007-09-01
We present a simple numerical method for constructing the optimal (generalized) averaged Gaussian quadrature formulas which are the optimal stratified extensions of Gauss quadrature formulas. These extensions exist in many cases in which real positive Kronrod formulas do not exist. For the Jacobi weight functions w(x)equiv w^{(alpha,beta)}(x)D(1-x)^alpha(1+x)^beta ( alpha,beta>-1 ) we give a necessary and sufficient condition on the parameters alpha and beta such that the optimal averaged Gaussian quadrature formulas are internal.
Tachyon mediated non-Gaussianity
Dutta, Bhaskar; Leblond, Louis; Kumar, Jason
2008-10-15
We describe a general scenario where primordial non-Gaussian curvature perturbations are generated in models with extra scalar fields. The extra scalars communicate to the inflaton sector mainly through the tachyonic (waterfall) field condensing at the end of hybrid inflation. These models can yield significant non-Gaussianity of the local shape, and both signs of the bispectrum can be obtained. These models have cosmic strings and a nearly flat power spectrum, which together have been recently shown to be a good fit to WMAP data. We illustrate with a model of inflation inspired from intersecting brane models.
Non-gaussianity versus nonlinearity of cosmological perturbations.
Verde, L
2001-06-01
Following the discovery of the cosmic microwave background, the hot big-bang model has become the standard cosmological model. In this theory, small primordial fluctuations are subsequently amplified by gravity to form the large-scale structure seen today. Different theories for unified models of particle physics, lead to different predictions for the statistical properties of the primordial fluctuations, that can be divided in two classes: gaussian and non-gaussian. Convincing evidence against or for gaussian initial conditions would rule out many scenarios and point us toward a physical theory for the origin of structures. The statistical distribution of cosmological perturbations, as we observe them, can deviate from the gaussian distribution in several different ways. Even if perturbations start off gaussian, nonlinear gravitational evolution can introduce non-gaussian features. Additionally, our knowledge of the Universe comes principally from the study of luminous material such as galaxies, but galaxies might not be faithful tracers of the underlying mass distribution. The relationship between fluctuations in the mass and in the galaxies distribution (bias), is often assumed to be local, but could well be nonlinear. Moreover, galaxy catalogues use the redshift as third spatial coordinate: the resulting redshift-space map of the galaxy distribution is nonlinearly distorted by peculiar velocities. Nonlinear gravitational evolution, biasing, and redshift-space distortion introduce non-gaussianity, even in an initially gaussian fluctuation field. I investigate the statistical tools that allow us, in principle, to disentangle the above different effects, and the observational datasets we require to do so in practice. PMID:11411156
Liu, Yushun; Zhou, Wenjun; Li, Pengfei; Yang, Shuai; Tian, Yan
2016-01-01
Due to electromagnetic interference in power substations, the partial discharge (PD) signals detected by ultrahigh frequency (UHF) antenna sensors often contain various background noises, which may hamper high voltage apparatus fault diagnosis and localization. This paper proposes a novel de-noising method based on the generalized S-transform and module time-frequency matrix to suppress noise in UHF PD signals. The sub-matrix maximum module value method is employed to calculate the frequencies and amplitudes of periodic narrowband noise, and suppress noise through the reverse phase cancellation technique. In addition, a singular value decomposition de-noising method is employed to suppress Gaussian white noise in UHF PD signals. Effective singular values are selected by employing the fuzzy c-means clustering method to recover the PD signals. De-noising results of simulated and field detected UHF PD signals prove the feasibility of the proposed method. Compared with four conventional de-noising methods, the results show that the proposed method can suppress background noise in the UHF PD signal effectively, with higher signal-to-noise ratio and less waveform distortion. PMID:27338409
Liu, Yushun; Zhou, Wenjun; Li, Pengfei; Yang, Shuai; Tian, Yan
2016-01-01
Due to electromagnetic interference in power substations, the partial discharge (PD) signals detected by ultrahigh frequency (UHF) antenna sensors often contain various background noises, which may hamper high voltage apparatus fault diagnosis and localization. This paper proposes a novel de-noising method based on the generalized S-transform and module time-frequency matrix to suppress noise in UHF PD signals. The sub-matrix maximum module value method is employed to calculate the frequencies and amplitudes of periodic narrowband noise, and suppress noise through the reverse phase cancellation technique. In addition, a singular value decomposition de-noising method is employed to suppress Gaussian white noise in UHF PD signals. Effective singular values are selected by employing the fuzzy c-means clustering method to recover the PD signals. De-noising results of simulated and field detected UHF PD signals prove the feasibility of the proposed method. Compared with four conventional de-noising methods, the results show that the proposed method can suppress background noise in the UHF PD signal effectively, with higher signal-to-noise ratio and less waveform distortion. PMID:27338409
Constraining primordial non-Gaussianity with cosmological weak lensing: shear and flexion
Fedeli, C.; Bartelmann, M.; Moscardini, L. E-mail: bartelmann@uni-heidelberg.de
2012-10-01
We examine the cosmological constraining power of future large-scale weak lensing surveys on the model of the ESA planned mission Euclid, with particular reference to primordial non-Gaussianity. Our analysis considers several different estimators of the projected matter power spectrum, based on both shear and flexion. We review the covariance and Fisher matrix for cosmic shear and evaluate those for cosmic flexion and for the cross-correlation between the two. The bounds provided by cosmic shear alone are looser than previously estimated, mainly due to the reduced sky coverage and background number density of sources for the latest Euclid specifications. New constraints for the local bispectrum shape, marginalized over σ{sub 8}, are at the level of Δf{sub NL} ∼ 100, with the precise value depending on the exact multipole range that is considered in the analysis. We consider three additional bispectrum shapes, for which the cosmic shear constraints range from Δf{sub NL} ∼ 340 (equilateral shape) up to Δf{sub NL} ∼ 500 (orthogonal shape). Also, constraints on the level of non-Gaussianity and on the amplitude of the matter power spectrum σ{sub 8} are almost perfectly anti-correlated, except for the orthogonal bispectrum shape for which they are correlated. The competitiveness of cosmic flexion constraints against cosmic shear ones depends by and large on the galaxy intrinsic flexion noise, that is still virtually unconstrained. Adopting the very high value that has been occasionally used in the literature results in the flexion contribution being basically negligible with respect to the shear one, and for realistic configurations the former does not improve significantly the constraining power of the latter. Since the shear shot noise is white, while the flexion one decreases with decreasing scale, by considering high enough multipoles the two contributions have to become comparable. Extending the analysis up to l{sub max} = 20,000 cosmic flexion, while
Thermodynamically valid noise models for nonlinear devices
NASA Astrophysics Data System (ADS)
Coram, Geoffrey J.
2000-11-01
Noise has been a concern from the very beginning of signal processing and electrical engineering in general, although it was perhaps of less interest until vacuum- tube amplifiers made it audible just after 1900. Rigorous noise models for linear resistors were developed in 1927 by Nyquist and Johnson [1, 2]. However, the intervening years have not brought similarly well-established models for noise in nonlinear devices. This thesis proposes using thermodynamic principles to determine whether a given nonlinear device noise model is physically valid. These tests are applied to several models. One conclusion is that the standard Gaussian noise models for nonlinear devices predict thermodynamically impossible circuit behavior: these models should be abandoned. But the nonlinear shot-noise model predicts thermodynamically acceptable behavior under a constraint derived here. This thesis shows how the thermodynamic requirements can be reduced to concise mathematical tests, involving no approximations, for the Gaussian and shot-noise models. When the above-mentioned constraint is satisfied, the nonlinear shot-noise model specifies the current noise amplitude at each operating point from knowledge of the device v - i curve alone. This relation between the dissipative behavior and the noise fluctuations is called, naturally enough, a fluctuation- dissipation relation. This thesis further investigates such FDRs, including one for linear resistors in nonlinear circuits that was previously unexplored. The aim of this thesis is to provide thermodynamically solid foundations for noise models. It is hoped that hypothesized noise models developed to match experiment will be validated against the concise mathematical tests of this thesis. Finding a correct noise model will help circuit designers and physicists understand the actual processes causing the noise, and perhaps help them minimize the noise or its effect in the circuit. (Copies available exclusively from MIT Libraries, Rm
Stochastic bifurcation for a tumor-immune system with symmetric Lévy noise
NASA Astrophysics Data System (ADS)
Xu, Yong; Feng, Jing; Li, JuanJuan; Zhang, Huiqing
2013-10-01
In this paper, we investigate stochastic bifurcation for a tumor-immune system in the presence of a symmetric non-Gaussian Lévy noise. Stationary probability density functions will be numerically obtained to define stochastic bifurcation via the criteria of its qualitative change, and bifurcation diagram at parameter plane is presented to illustrate the bifurcation analysis versus noise intensity and stability index. The effects of both noise intensity and stability index on the average tumor population are also analyzed by simulation calculation. We find that stochastic dynamics induced by Gaussian and non-Gaussian Lévy noises are quite different.
General immunity and superadditivity of two-way Gaussian quantum cryptography
Ottaviani, Carlo; Pirandola, Stefano
2016-01-01
We consider two-way continuous-variable quantum key distribution, studying its security against general eavesdropping strategies. Assuming the asymptotic limit of many signals exchanged, we prove that two-way Gaussian protocols are immune to coherent attacks. More precisely we show the general superadditivity of the two-way security thresholds, which are proven to be higher than the corresponding one-way counterparts in all cases. We perform the security analysis first reducing the general eavesdropping to a two-mode coherent Gaussian attack, and then showing that the superadditivity is achieved by exploiting the random on/off switching of the two-way quantum communication. This allows the parties to choose the appropriate communication instances to prepare the key, accordingly to the tomography of the quantum channel. The random opening and closing of the circuit represents, in fact, an additional degree of freedom allowing the parties to convert, a posteriori, the two-mode correlations of the eavesdropping into noise. The eavesdropper is assumed to have no access to the on/off switching and, indeed, cannot adapt her attack. We explicitly prove that this mechanism enhances the security performance, no matter if the eavesdropper performs collective or coherent attacks. PMID:26928053
A two-step super-Gaussian independent component analysis approach for fMRI data.
Ge, Ruiyang; Yao, Li; Zhang, Hang; Long, Zhiying
2015-09-01
Independent component analysis (ICA) has been widely applied to functional magnetic resonance imaging (fMRI) data analysis. Although ICA assumes that the sources underlying data are statistically independent, it usually ignores sources' additional properties, such as sparsity. In this study, we propose a two-step super-GaussianICA (2SGICA) method that incorporates the sparse prior of the sources into the ICA model. 2SGICA uses the super-Gaussian ICA (SGICA) algorithm that is based on a simplified Lewicki-Sejnowski's model to obtain the initial source estimate in the first step. Using a kernel estimator technique, the source density is acquired and fitted to the Laplacian function based on the initial source estimates. The fitted Laplacian prior is used for each source at the second SGICA step. Moreover, the automatic target generation process for initial value generation is used in 2SGICA to guarantee the stability of the algorithm. An adaptive step size selection criterion is also implemented in the proposed algorithm. We performed experimental tests on both simulated data and real fMRI data to investigate the feasibility and robustness of 2SGICA and made a performance comparison between InfomaxICA, FastICA, mean field ICA (MFICA) with Laplacian prior, sparse online dictionary learning (ODL), SGICA and 2SGICA. Both simulated and real fMRI experiments showed that the 2SGICA was most robust to noises, and had the best spatial detection power and the time course estimation among the six methods. PMID:26057592
General immunity and superadditivity of two-way Gaussian quantum cryptography
NASA Astrophysics Data System (ADS)
Ottaviani, Carlo; Pirandola, Stefano
2016-03-01
We consider two-way continuous-variable quantum key distribution, studying its security against general eavesdropping strategies. Assuming the asymptotic limit of many signals exchanged, we prove that two-way Gaussian protocols are immune to coherent attacks. More precisely we show the general superadditivity of the two-way security thresholds, which are proven to be higher than the corresponding one-way counterparts in all cases. We perform the security analysis first reducing the general eavesdropping to a two-mode coherent Gaussian attack, and then showing that the superadditivity is achieved by exploiting the random on/off switching of the two-way quantum communication. This allows the parties to choose the appropriate communication instances to prepare the key, accordingly to the tomography of the quantum channel. The random opening and closing of the circuit represents, in fact, an additional degree of freedom allowing the parties to convert, a posteriori, the two-mode correlations of the eavesdropping into noise. The eavesdropper is assumed to have no access to the on/off switching and, indeed, cannot adapt her attack. We explicitly prove that this mechanism enhances the security performance, no matter if the eavesdropper performs collective or coherent attacks.
General immunity and superadditivity of two-way Gaussian quantum cryptography.
Ottaviani, Carlo; Pirandola, Stefano
2016-01-01
We consider two-way continuous-variable quantum key distribution, studying its security against general eavesdropping strategies. Assuming the asymptotic limit of many signals exchanged, we prove that two-way Gaussian protocols are immune to coherent attacks. More precisely we show the general superadditivity of the two-way security thresholds, which are proven to be higher than the corresponding one-way counterparts in all cases. We perform the security analysis first reducing the general eavesdropping to a two-mode coherent Gaussian attack, and then showing that the superadditivity is achieved by exploiting the random on/off switching of the two-way quantum communication. This allows the parties to choose the appropriate communication instances to prepare the key, accordingly to the tomography of the quantum channel. The random opening and closing of the circuit represents, in fact, an additional degree of freedom allowing the parties to convert, a posteriori, the two-mode correlations of the eavesdropping into noise. The eavesdropper is assumed to have no access to the on/off switching and, indeed, cannot adapt her attack. We explicitly prove that this mechanism enhances the security performance, no matter if the eavesdropper performs collective or coherent attacks. PMID:26928053
NON-GAUSSIANITIES IN THE LOCAL CURVATURE OF THE FIVE-YEAR WMAP DATA
Rudjord, Oeystein; Groeneboom, Nicolaas E.; Hansen, Frode K.; Cabella, Paolo
2010-07-20
Using the five-year WMAP data, we re-investigate claims of non-Gaussianities and asymmetries detected in local curvature statistics of the one-year WMAP data. In Hansen et al., it was found that the northern ecliptic hemisphere was non-Gaussian at the {approx}1% level testing the densities of hill, lake, and saddle points based on the second derivatives of the cosmic microwave background temperature map. The five-year WMAP data have a much lower noise level and better control of systematics. Using these, we find that the anomalies are still present at a consistent level. Also the direction of maximum non-Gaussianity remains. Due to limited availability of computer resources, Hansen et al. were unable to calculate the full covariance matrix for the {chi}{sup 2}-test used. Here, we apply the full covariance matrix instead of the diagonal approximation and find that the non-Gaussianities disappear and there is no preferred non-Gaussian direction. We compare with simulations of weak lensing to see if this may cause the observed non-Gaussianity when using a diagonal covariance matrix. We conclude that weak lensing does not produce non-Gaussianity in the local curvature statistics at the scales investigated in this paper. The cause of the non-Gaussian detection in the case of a diagonal matrix remains unclear.
NASA Technical Reports Server (NTRS)
Vazirani, P.
1995-01-01
The process of combining telemetry signals received at multiple antennas, commonly referred to as arraying, can be used to improve communication link performance in the Deep Space Network (DSN). By coherently adding telemetry from multiple receiving sites, arraying produces an enhancement in signal-to-noise ratio (SNR) over that achievable with any single antenna in the array. A number of different techniques for arraying have been proposed and their performances analyzed in past literature. These analyses have compared different arraying schemes under the assumption that the signals contain additive white Gaussian noise (AWGN) and that the noise observed at distinct antennas is independent. In situations where an unwanted background body is visible to multiple antennas in the array, however, the assumption of independent noises is no longer applicable. A planet with significant radiation emissions in the frequency band of interest can be one such source of correlated noise. For example, during much of Galileo's tour of Jupiter, the planet will contribute significantly to the total system noise at various ground stations. This article analyzes the effects of correlated noise on two arraying schemes currently being considered for DSN applications: full-spectrum combining (FSC) and complex-symbol combining (CSC). A framework is presented for characterizing the correlated noise based on physical parameters, and the impact of the noise correlation on the array performance is assessed for each scheme.
NASA Technical Reports Server (NTRS)
Hultgren, Lennart S.
2012-01-01
This presentation is a technical summary of and outlook for NASA-internal and NASA-sponsored external research on core noise funded by the Fundamental Aeronautics Program Subsonic Fixed Wing (SFW) Project. Sections of the presentation cover: the SFW system-level noise metrics for the 2015 (N+1), 2020 (N+2), and 2025 (N+3) timeframes; SFW strategic thrusts and technical challenges; SFW advanced subsystems that are broadly applicable to N+3 vehicle concepts, with an indication where further noise research is needed; the components of core noise (compressor, combustor and turbine noise) and a rationale for NASA's current emphasis on the combustor-noise component; the increase in the relative importance of core noise due to turbofan design trends; the need to understand and mitigate core-noise sources for high-efficiency small gas generators; and the current research activities in the core-noise area, with additional details given about forthcoming updates to NASA's Aircraft Noise Prediction Program (ANOPP) core-noise prediction capabilities, two NRA efforts (Honeywell International, Phoenix, AZ and University of Illinois at Urbana-Champaign, respectively) to improve the understanding of core-noise sources and noise propagation through the engine core, and an effort to develop oxide/oxide ceramic-matrix-composite (CMC) liners for broadband noise attenuation suitable for turbofan-core application. Core noise must be addressed to ensure that the N+3 noise goals are met. Focused, but long-term, core-noise research is carried out to enable the advanced high-efficiency small gas-generator subsystem, common to several N+3 conceptual designs, needed to meet NASA's technical challenges. Intermediate updates to prediction tools are implemented as the understanding of the source structure and engine-internal propagation effects is improved. The NASA Fundamental Aeronautics Program has the principal objective of overcoming today's national challenges in air transportation. The
NASA Astrophysics Data System (ADS)
Bera, Aindrila; Saha, Surajit; Ganguly, Jayanta; Ghosh, Manas
2016-08-01
We explore Diamagnetic susceptibility (DMS) of impurity doped quantum dot (QD) in presence of Gaussian white noise introduced to the system additively and multiplicatively. In view of this profiles of DMS have been pursued with variations of geometrical anisotropy and dopant location. We have invoked position-dependent effective mass (PDEM) and position-dependent dielectric screening function (PDDSF) of the system. Presence of noise sometimes suppresses and sometimes amplifies DMS from that of noise-free condition and the extent of suppression/amplification depends on mode of application of noise. It is important to mention that the said suppression/amplification exhibits subtle dependence on use of PDEM, PDDSF and geometrical anisotropy. The study reveals that DMS, or more fundamentally, the effective confinement of LDSS, can be tuned by appropriate mingling of geometrical anisotropy/effective mass/dielectric constant of the system with noise and also on the pathway of application of latter.
Gaussian quantum steering and its asymmetry in curved spacetime
NASA Astrophysics Data System (ADS)
Wang, Jieci; Cao, Haixin; Jing, Jiliang; Fan, Heng
2016-06-01
We study Gaussian quantum steering and its asymmetry in the background of a Schwarzschild black hole. We present a Gaussian channel description of quantum state evolution under the influence of Hawking radiation. We find that thermal noise introduced by the Hawking effect will destroy the steerability between an inertial observer Alice and an accelerated observer Bob who hovers outside the event horizon, while it generates steerability between Bob and a hypothetical observer anti-Bob inside the event horizon. Unlike entanglement behaviors in curved spacetime, here the steering from Alice to Bob suffers from a "sudden death" and the steering from anti-Bob to Bob experiences a "sudden birth" with increasing Hawking temperature. We also find that the Gaussian steering is always asymmetric and the maximum steering asymmetry cannot exceed ln 2 , which means the state never evolves to an extremal asymmetry state. Furthermore, we obtain the parameter settings that maximize steering asymmetry and find that (i) s =arccosh cosh/2r 1 -sinh2r is the critical point of steering asymmetry and (ii) the attainment of maximal steering asymmetry indicates the transition between one-way steerability and both-way steerability for the two-mode Gaussian state under the influence of Hawking radiation.
Non-Gaussian microwave background fluctuations from nonlinear gravitational effects
NASA Technical Reports Server (NTRS)
Salopek, D. S.; Kunstatter, G. (Editor)
1991-01-01
Whether the statistics of primordial fluctuations for structure formation are Gaussian or otherwise may be determined if the Cosmic Background Explorer (COBE) Satellite makes a detection of the cosmic microwave-background temperature anisotropy delta T(sub CMB)/T(sub CMB). Non-Gaussian fluctuations may be generated in the chaotic inflationary model if two scalar fields interact nonlinearly with gravity. Theoretical contour maps are calculated for the resulting Sachs-Wolfe temperature fluctuations at large angular scales (greater than 3 degrees). In the long-wavelength approximation, one can confidently determine the nonlinear evolution of quantum noise with gravity during the inflationary epoch because: (1) different spatial points are no longer in causal contact; and (2) quantum gravity corrections are typically small-- it is sufficient to model the system using classical random fields. If the potential for two scalar fields V(phi sub 1, phi sub 2) possesses a sharp feature, then non-Gaussian fluctuations may arise. An explicit model is given where cold spots in delta T(sub CMB)/T(sub CMB) maps are suppressed as compared to the Gaussian case. The fluctuations are essentially scale-invariant.
Non-gaussian shape recognition
Byun, Joyce; Bean, Rachel E-mail: rbean@astro.cornell.edu
2013-09-01
A detection of primordial non-Gaussianity could transform our understanding of the fundamental theory of inflation. The precision promised by upcoming cosmic microwave background (CMB) and large-scale structure (LSS) surveys raises a natural question: if a detection given a particular template is made, what does this truly tell us about the underlying theory? Even in the case of non-detections and upper bounds on deviations from Gaussianity, what can we then infer about the viable theories that remain? In this paper we present a systematic way to constrain a wide range of non-Gaussian shapes, including general single and multi-field models and models with excited initial states. We present a separable, divergent basis able to recreate many shapes in the literature to high accuracy with between three and seven basis functions. The basis allows shapes to be grouped into broad ''template classes'', satisfying theoretically-relevant priors on their divergence properties in the squeezed limit. We forecast how well a Planck-like CMB survey could not only detect a general non-Gaussian signal but discern more about its shape, using existing templates and new ones we propose. This approach offers an opportunity to tie together minimal theoretical priors with observational constraints on the shape in general, and in the squeezed limit, to gain a deeper insight into what drove inflation.
Gaussian processes for machine learning.
Seeger, Matthias
2004-04-01
Gaussian processes (GPs) are natural generalisations of multivariate Gaussian random variables to infinite (countably or continuous) index sets. GPs have been applied in a large number of fields to a diverse range of ends, and very many deep theoretical analyses of various properties are available. This paper gives an introduction to Gaussian processes on a fairly elementary level with special emphasis on characteristics relevant in machine learning. It draws explicit connections to branches such as spline smoothing models and support vector machines in which similar ideas have been investigated. Gaussian process models are routinely used to solve hard machine learning problems. They are attractive because of their flexible non-parametric nature and computational simplicity. Treated within a Bayesian framework, very powerful statistical methods can be implemented which offer valid estimates of uncertainties in our predictions and generic model selection procedures cast as nonlinear optimization problems. Their main drawback of heavy computational scaling has recently been alleviated by the introduction of generic sparse approximations.13,78,31 The mathematical literature on GPs is large and often uses deep concepts which are not required to fully understand most machine learning applications. In this tutorial paper, we aim to present characteristics of GPs relevant to machine learning and to show up precise connections to other "kernel machines" popular in the community. Our focus is on a simple presentation, but references to more detailed sources are provided. PMID:15112367
How Colored Environmental Noise Affects Population Extinction
NASA Astrophysics Data System (ADS)
Kamenev, Alex; Meerson, Baruch; Shklovskii, Boris
2008-12-01
Environmental noise can cause an exponential reduction in the mean time to extinction (MTE) of an isolated population. We study this effect on an example of a stochastic birth-death process with rates modulated by a colored (that is, correlated) Gaussian noise. A path integral formulation yields a transparent way of evaluating the MTE and finding the optimal realization of the environmental noise that determines the most probable path to extinction. The population-size dependence of the MTE changes from exponential in the absence of the environmental noise to a power law for a short-correlated noise and to no dependence for long-correlated noise. We also establish the validity domains of the white-noise limit and adiabatic limit.
Gaussian Velocity Distributions in Avalanches
NASA Astrophysics Data System (ADS)
Shattuck, Mark
2004-03-01
Imagine a world where gravity is so strong that if an ice cube is tilted the shear forces melt the surface and water avalanches down. Further imagine that the ambient temperature is so low that the water re-freezes almost immediately. This is the world of granular flows. As a granular solid is tilted the surface undergoes a sublimation phase transition and a granular gas avalanches down the surface, but the inelastic collisions rapidly remove energy from the flow lowering the granular temperature (kinetic energy per particle) until the gas solidifies again. It is under these extreme conditions that we attempt to uncover continuum granular flow properties. Typical continuum theories like Navier-Stokes equation for fluids follow the space-time evolution of the first few moments of the velocity distribution. We study continuously avalanching flow in a rotating two-dimensional granular drum using high-speed video imaging and extract the position and velocities of the particles. We find a universal near Gaussian velocity distribution throughout the flowing regions, which are characterized by a liquid-like radial distribution function. In the remaining regions, in which the radial distribution function develops sharp crystalline peaks, the velocity distribution has a Gaussian peak but is much broader in the tails. In a companion experiment on a vibrated two-dimensional granular fluid under constant pressure, we find a clear gas-solid phase transition in which both the temperature and density change discontinuously. This suggests that a low temperature crystal and a high temperature gas can coexist in steady state. This coexistence could result in a narrower, cooler, Gaussian peak and a broader, warmer, Gaussian tail like the non-Gaussian behavior seen in the crystalline portions of the rotating drum.
Describing 3D Geometric Primitives Using the Gaussian Sphere and the Gaussian Accumulator
NASA Astrophysics Data System (ADS)
Toony, Zahra; Laurendeau, Denis; Gagné, Christian
2015-12-01
Most complex object models are composed of basic parts or primitives. Being able to decompose a complex 3D model into such basic primitives is an important step in reverse engineering. Even when an algorithm can segment a complex model into its primitives, a description technique is still needed in order to identify the type of each primitive. Most feature extraction methods fail to describe these basic primitives or need a trained classifier on a database of prepared data to perform this identification. In this paper, we propose a method that can describe basic primitives such as planes, cones, cylinders, spheres, and tori as well as partial models of the latter four primitives. To achieve this task, we combine the concept of Gaussian sphere to a new concept introduced in this paper: the Gaussian accumulator. Comparison of the results of our method with other feature extractors reveals that our approach can distinguish all of these primitives from each other including partial models. Our method was also tested on real scanned data with noise and missing areas. The results show that our method is able to distinguish all of these models as well.
Hierarchical similarity transformations between Gaussian mixtures.
Rigas, George; Nikou, Christophoros; Goletsis, Yorgos; Fotiadis, Dimitrios I
2013-11-01
In this paper, we propose a method to estimate the density of a data space represented by a geometric transformation of an initial Gaussian mixture model. The geometric transformation is hierarchical, and it is decomposed into two steps. At first, the initial model is assumed to undergo a global similarity transformation modeled by translation, rotation, and scaling of the model components. Then, to increase the degrees of freedom of the model and allow it to capture fine data structures, each individual mixture component may be transformed by another, local similarity transformation, whose parameters are distinct for each component of the mixture. In addition, to constrain the order of magnitude of the local transformation (LT) with respect to the global transformation (GT), zero-mean Gaussian priors are imposed onto the local parameters. The estimation of both GT and LT parameters is obtained through the expectation maximization framework. Experiments on artificial data are conducted to evaluate the proposed model, with varying data dimensionality, number of model components, and transformation parameters. In addition, the method is evaluated using real data from a speech recognition task. The obtained results show a high model accuracy and demonstrate the potential application of the proposed method to similar classification problems. PMID:24808615
Fault diagnosis using noise modeling and a new artificial immune system based algorithm
NASA Astrophysics Data System (ADS)
Abbasi, Farshid; Mojtahedi, Alireza; Ettefagh, Mir Mohammad
2015-12-01
A new fault classification/diagnosis method based on artificial immune system (AIS) algorithms for the structural systems is proposed. In order to improve the accuracy of the proposed method, i.e., higher success rate, Gaussian and non-Gaussian noise generating models are applied to simulate environmental noise. The identification of noise model, known as training process, is based on the estimation of the noise model parameters by genetic algorithms (GA) utilizing real experimental features. The proposed fault classification/diagnosis algorithm is applied to the noise contaminated features. Then, the results are compared to that obtained without noise modeling. The performance of the proposed method is examined using three laboratory case studies in two healthy and damaged conditions. Finally three different types of noise models are studied and it is shown experimentally that the proposed algorithm with non-Gaussian noise modeling leads to more accurate clustering of memory cells as the major part of the fault classification procedure.
Inseparability of photon-added Gaussian states
Li Hongrong; Li Fuli; Zhu Shiyao
2007-06-15
The inseparability of photon-added Gaussian states which are generated from two-mode Gaussian states by adding photons is investigated. According to the established inseparability conditions [New J. Phys. 7, 211 (2005); Phys. Rev. Lett. 96, 050503 (2006)], we find that even if a two-mode Gaussian state is separable, the photon-added Gaussian state becomes entangled when the purity of the Gaussian state is larger than a certain value. The lower bound of entanglement of symmetric photon-added Gaussian states is derived. The result shows that entanglement of the photon-added Gaussian states is involved with high-order moment correlations. We find that fidelity of teleporting coherent states cannot be raised by employing the photon-added Gaussian states as a quantum channel of teleportation.
Galaxy-CMB and galaxy-galaxy lensing on large scales: Sensitivity to primordial non-Gaussianity
NASA Astrophysics Data System (ADS)
Jeong, Donghui; Komatsu, Eiichiro; Jain, Bhuvnesh
2009-12-01
A convincing detection of primordial non-Gaussianity in the local form of the bispectrum, whose amplitude is given by the fNL parameter, offers a powerful test of inflation. In this paper, we calculate the modification of two-point cross-correlation statistics of weak lensing—galaxy-galaxy lensing and galaxy-cosmic microwave background (CMB) crosscorrelation—due to fNL. We derive and calculate the covariance matrix of galaxy-galaxy lensing, including cosmic variance terms. We focus on large scales (l<100) for which the shape noise of the shear measurement becomes irrelevant and cosmic variance dominates the error budget. For a modest degree of non-Gaussianity, fNL=±50 modifications of the galaxy-galaxy-lensing signal at the 10% level are seen on scales R˜300Mpc, and grow rapidly toward larger scales as ∝R2. We also see a clear signature of the baryonic acoustic oscillation feature in the matter power spectrum at ˜150Mpc, which can be measured by next-generation lensing experiments. In addition, we can probe the local-form primordial non-Gaussianity in the galaxy-CMB lensing signal by correlating the lensing potential reconstructed from CMB with high-z galaxies. For example, for fNL=±50, we find that the galaxy-CMB lensing cross-power spectrum is modified by ˜10% at l˜40, and by a factor of 2 at l˜10, for a population of galaxies at z=2 with a bias of 2. The effect is greater for more highly biased populations at larger z; thus, high-z galaxy surveys cross correlated with CMB offer a yet another probe of primordial non-Gaussianity.
Brett, Tobias Galla, Tobias
2014-03-28
We present a heuristic derivation of Gaussian approximations for stochastic chemical reaction systems with distributed delay. In particular, we derive the corresponding chemical Langevin equation. Due to the non-Markovian character of the underlying dynamics, these equations are integro-differential equations, and the noise in the Gaussian approximation is coloured. Following on from the chemical Langevin equation, a further reduction leads to the linear-noise approximation. We apply the formalism to a delay variant of the celebrated Brusselator model, and show how it can be used to characterise noise-driven quasi-cycles, as well as noise-triggered spiking. We find surprisingly intricate dependence of the typical frequency of quasi-cycles on the delay period.
Sparsity based noise removal from low dose scanning electron microscopy images
NASA Astrophysics Data System (ADS)
Lazar, A.; Fodor, P. S.
2015-03-01
Scanning electron microscopes are some of the most versatile tools for imaging materials with nanometer resolution. However, images collected at high scan rates to increase throughput and avoid sample damage, suffer from low signalto- noise ratio (SNR) as a result of the Poisson distributed shot noise associated with the electron production and interaction with the surface imaged. The signal is further degraded by additive white Gaussian noise (AWGN) from the detection electronics. In this work, denoising frameworks are applied to this type of images, taking advantage of their sparsity character, along with a methodology for determining the AWGN. A variance stabilization technique is applied to the raw data followed by a patch-based denoising algorithm. Results are presented both for images with known levels of mixed Poisson-Gaussian noise, and for raw images. The quality of the image reconstruction is assessed based both on the PSNR as well as on measures specific to the application of the data collected. These include accurate identification of objects of interest and structural similarity. High-quality results are recovered from noisy observations collected at short dwell times that avoid sample damage.
NASA Technical Reports Server (NTRS)
Bragdon, C. R.
1982-01-01
Airport and community land use planning as they relate to airport noise reduction are discussed. Legislation, community relations, and the physiological effect of airport noise are considered. Noise at the Logan, Los Angeles, and Minneapolis/St. Paul airports is discussed.
Radiometric calibration of digital cameras using Gaussian processes
NASA Astrophysics Data System (ADS)
Schall, Martin; Grunwald, Michael; Umlauf, Georg; Franz, Matthias O.
2015-05-01
Digital cameras are subject to physical, electronic and optic effects that result in errors and noise in the image. These effects include for example a temperature dependent dark current, read noise, optical vignetting or different sensitivities of individual pixels. The task of a radiometric calibration is to reduce these errors in the image and thus improve the quality of the overall application. In this work we present an algorithm for radiometric calibration based on Gaussian processes. Gaussian processes are a regression method widely used in machine learning that is particularly useful in our context. Then Gaussian process regression is used to learn a temperature and exposure time dependent mapping from observed gray-scale values to true light intensities for each pixel. Regression models based on the characteristics of single pixels suffer from excessively high runtime and thus are unsuitable for many practical applications. In contrast, a single regression model for an entire image with high spatial resolution leads to a low quality radiometric calibration, which also limits its practical use. The proposed algorithm is predicated on a partitioning of the pixels such that each pixel partition can be represented by one single regression model without quality loss. Partitioning is done by extracting features from the characteristic of each pixel and using them for lexicographic sorting. Splitting the sorted data into partitions with equal size yields the final partitions, each of which is represented by the partition centers. An individual Gaussian process regression and model selection is done for each partition. Calibration is performed by interpolating the gray-scale value of each pixel with the regression model of the respective partition. The experimental comparison of the proposed approach to classical flat field calibration shows a consistently higher reconstruction quality for the same overall number of calibration frames.
Non-Gaussian Photon Probability Distribution
NASA Astrophysics Data System (ADS)
Solomon, Benjamin T.
2010-01-01
This paper investigates the axiom that the photon's probability distribution is a Gaussian distribution. The Airy disc empirical evidence shows that the best fit, if not exact, distribution is a modified Gamma mΓ distribution (whose parameters are α = r, βr/√u ) in the plane orthogonal to the motion of the photon. This modified Gamma distribution is then used to reconstruct the probability distributions along the hypotenuse from the pinhole, arc from the pinhole, and a line parallel to photon motion. This reconstruction shows that the photon's probability distribution is not a Gaussian function. However, under certain conditions, the distribution can appear to be Normal, thereby accounting for the success of quantum mechanics. This modified Gamma distribution changes with the shape of objects around it and thus explains how the observer alters the observation. This property therefore places additional constraints to quantum entanglement experiments. This paper shows that photon interaction is a multi-phenomena effect consisting of the probability to interact Pi, the probabilistic function and the ability to interact Ai, the electromagnetic function. Splitting the probability function Pi from the electromagnetic function Ai enables the investigation of the photon behavior from a purely probabilistic Pi perspective. The Probabilistic Interaction Hypothesis is proposed as a consistent method for handling the two different phenomena, the probability function Pi and the ability to interact Ai, thus redefining radiation shielding, stealth or cloaking, and invisibility as different effects of a single phenomenon Pi of the photon probability distribution. Sub wavelength photon behavior is successfully modeled as a multi-phenomena behavior. The Probabilistic Interaction Hypothesis provides a good fit to Otoshi's (1972) microwave shielding, Schurig et al. (2006) microwave cloaking, and Oulton et al. (2008) sub wavelength confinement; thereby providing a strong case that
Gaussian statistics for palaeomagnetic vectors
Love, J.J.; Constable, C.G.
2003-01-01
With the aim of treating the statistics of palaeomagnetic directions and intensities jointly and consistently, we represent the mean and the variance of palaeomagnetic vectors, at a particular site and of a particular polarity, by a probability density function in a Cartesian three-space of orthogonal magnetic-field components consisting of a single (unimoda) non-zero mean, spherically-symmetrical (isotropic) Gaussian function. For palaeomagnetic data of mixed polarities, we consider a bimodal distribution consisting of a pair of such symmetrical Gaussian functions, with equal, but opposite, means and equal variances. For both the Gaussian and bi-Gaussian distributions, and in the spherical three-space of intensity, inclination, and declination, we obtain analytical expressions for the marginal density functions, the cumulative distributions, and the expected values and variances for each spherical coordinate (including the angle with respect to the axis of symmetry of the distributions). The mathematical expressions for the intensity and off-axis angle are closed-form and especially manageable, with the intensity distribution being Rayleigh-Rician. In the limit of small relative vectorial dispersion, the Gaussian (bi-Gaussian) directional distribution approaches a Fisher (Bingham) distribution and the intensity distribution approaches a normal distribution. In the opposite limit of large relative vectorial dispersion, the directional distributions approach a spherically-uniform distribution and the intensity distribution approaches a Maxwell distribution. We quantify biases in estimating the properties of the vector field resulting from the use of simple arithmetic averages, such as estimates of the intensity or the inclination of the mean vector, or the variances of these quantities. With the statistical framework developed here and using the maximum-likelihood method, which gives unbiased estimates in the limit of large data numbers, we demonstrate how to
Near-Capacity Coding for Discrete Multitone Systems with Impulse Noise
NASA Astrophysics Data System (ADS)
Ardakani, Masoud; Kschischang, Frank R.; Yu, Wei
2006-12-01
We consider the design of near-capacity-achieving error-correcting codes for a discrete multitone (DMT) system in the presence of both additive white Gaussian noise and impulse noise. Impulse noise is one of the main channel impairments for digital subscriber lines (DSL). One way to combat impulse noise is to detect the presence of the impulses and to declare an erasure when an impulse occurs. In this paper, we propose a coding system based on low-density parity-check (LDPC) codes and bit-interleaved coded modulation that is capable of taking advantage of the knowledge of erasures. We show that by carefully choosing the degree distribution of an irregular LDPC code, both the additive noise and the erasures can be handled by a single code, thus eliminating the need for an outer code. Such a system can perform close to the capacity of the channel and for the same redundancy is significantly more immune to the impulse noise than existing methods based on an outer Reed-Solomon (RS) code. The proposed method has a lower implementation complexity than the concatenated coding approach.
A note on generalized averaged Gaussian formulas
NASA Astrophysics Data System (ADS)
Spalevic, Miodrag
2007-11-01
We have recently proposed a very simple numerical method for constructing the averaged Gaussian quadrature formulas. These formulas exist in many more cases than the real positive Gauss?Kronrod formulas. In this note we try to answer whether the averaged Gaussian formulas are an adequate alternative to the corresponding Gauss?Kronrod quadrature formulas, to estimate the remainder term of a Gaussian rule.
Simpson, Michael L; Allen, Michael S.; Cox, Chris D.; Dar, Roy D.; Karig, David K; McCollum, James M.; Cooke, John F
2009-01-01
Noise biology focuses on the sources, processing, and biological consequences of the inherent stochastic fluctuations in molecular transitions or interactions that control cellular behavior. These fluctuations are especially pronounced in small systems where the magnitudes of the fluctuations approach or exceed the mean value of the molecular population. Noise biology is an essential component of nanomedicine where the communication of information is across a boundary that separates small synthetic and biological systems that are bound by their size to reside in environments of large fluctuations. Here we review the fundamentals of the computational, analytical, and experimental approaches to noise biology. We review results that show that the competition between the benefits of low noise and those of low population has resulted in the evolution of genetic system architectures that produce an uneven distribution of stochasticity across the molecular components of cells and, in some cases, use noise to drive biological function. We review the exact and approximate approaches to gene circuit noise analysis and simulation, and reviewmany of the key experimental results obtained using flow cytometry and time-lapse fluorescent microscopy. In addition, we consider the probative value of noise with a discussion of using measured noise properties to elucidate the structure and function of the underlying gene circuit. We conclude with a discussion of the frontiers of and significant future challenges for noise biology.
Linear-Quadratic-Gaussian Regulator Developed for a Magnetic Bearing
NASA Technical Reports Server (NTRS)
Choi, Benjamin B.
2002-01-01
Linear-Quadratic-Gaussian (LQG) control is a modern state-space technique for designing optimal dynamic regulators. It enables us to trade off regulation performance and control effort, and to take into account process and measurement noise. The Structural Mechanics and Dynamics Branch at the NASA Glenn Research Center has developed an LQG control for a fault-tolerant magnetic bearing suspension rig to optimize system performance and to reduce the sensor and processing noise. The LQG regulator consists of an optimal state-feedback gain and a Kalman state estimator. The first design step is to seek a state-feedback law that minimizes the cost function of regulation performance, which is measured by a quadratic performance criterion with user-specified weighting matrices, and to define the tradeoff between regulation performance and control effort. The next design step is to derive a state estimator using a Kalman filter because the optimal state feedback cannot be implemented without full state measurement. Since the Kalman filter is an optimal estimator when dealing with Gaussian white noise, it minimizes the asymptotic covariance of the estimation error.
The Noisy Expectation-Maximization Algorithm for Multiplicative Noise Injection
NASA Astrophysics Data System (ADS)
Osoba, Osonde; Kosko, Bart
2016-03-01
We generalize the noisy expectation-maximization (NEM) algorithm to allow arbitrary modes of noise injection besides just adding noise to the data. The noise must still satisfy a NEM positivity condition. This generalization includes the important special case of multiplicative noise injection. A generalized NEM theorem shows that all measurable modes of injecting noise will speed the average convergence of the EM algorithm if the noise satisfies a generalized NEM positivity condition. This noise-benefit condition has a simple quadratic form for Gaussian and Cauchy mixture models in the case of multiplicative noise injection. Simulations show a multiplicative-noise EM speed-up of more than 27% in a simple Gaussian mixture model. Injecting blind noise only slowed convergence. A related theorem gives a sufficient condition for an average EM noise benefit for arbitrary modes of noise injection if the data model comes from the general exponential family of probability density functions. A final theorem shows that injected noise slows EM convergence on average if the NEM inequalities reverse and the noise satisfies a negativity condition.
The Switch in a Genetic Toggle System with Lévy Noise
Xu, Yong; Li, Yongge; Zhang, Hao; Li, Xiaofan; Kurths, Jürgen
2016-01-01
A bistable toggle switch is a paradigmatic model in the field of biology. The dynamics of the system induced by Gaussian noise has been intensively investigated, but Gaussian noise cannot incorporate large bursts typically occurring in real experiments. This paper aims to examine effects of variations from one protein imposed by a non-Gaussian Lévy noise, which is able to describe even large jumps, on the coherent switch and the on/off switch via the steady-state probability density, the joint steady-state probability density, and the mean first passage time. We find that a large burst of one protein due to the Lévy noises can induce coherent switches even with small noise intensities in contrast to the Gaussian case which requires large intensities for this. The influences of the stability index, skewness parameter and noise intensity on the on/off switch are analyzed, leading to an adjustment of the concentrations of both proteins and a decision which stable point to stay most. The mean first passage times show complex effects under Lévy noise, especially the stability index and skewness parameter. Our results also imply that the presence of non-Gaussian Lévy noises has fundamentally changed the escape mechanism in such a system compared with Gaussian noise. PMID:27539010
Focusing of truncated Gaussian beams
NASA Astrophysics Data System (ADS)
Horváth, Zoltán L.; Bor, Zsolt
2003-07-01
It is shown that the focusing of truncated Gaussian beams can be treated by the same manner as uniform spherical waves, i.e., the diffraction integral can be expressed by the Lommel functions, which offers a very efficient way for the calculation of the three-dimensional light distribution near focus. All the expressions for the uniform spherical waves hold good for Gaussian beams if the first variable in the Lommel functions is extended to the complex domain. The intensity distribution depending on the Fresnel number and the truncation coefficient is calculated. The location of the first few minima and maxima of the intensity in focal plane is given for different values of the truncation coefficient. The phase behavior depending on the truncation coefficient is studied.
NASA Technical Reports Server (NTRS)
Schmitz, F. H.
1991-01-01
The physical characteristics and sources of rotorcraft noise as they exist today are presented. Emphasis is on helicopter-like vehicles, that is, on rotorcraft in nonaxial flight. The mechanisms of rotor noise are reviewed in a simple physical manner for the most dominant sources of rotorcraft noise. With simple models, the characteristic time- and frequency-domain features of these noise sources are presented for idealized cases. Full-scale data on several rotorcraft are then reviewed to allow for the easy identification of the type and extent of the radiating noise. Methods and limitations of using scaled models to test for several noise sources are subsequently presented. Theoretical prediction methods are then discussed and compared with experimental data taken under very controlled conditions. Finally, some promising noise reduction technology is reviewed.
Industrial jet noise: Coanda nozzles
NASA Astrophysics Data System (ADS)
Li, P.; Halliwell, N. A.
1985-04-01
Within the U.K. manufacturing industries noise from industrial jets ranks third as a major contributor to industrial deafness. Noise control is hindered because use is made of the air once it has exuded from the nozzle exit. Important tasks include swarf removal, paint spreading, cooling, etc. Nozzles which employ the Coanda effect appear to offer the possibility of significant noise reduction whilst maintaining high thrust efficiency when compared with the commonly used simple open pipe or ordinary convergent nozzle. In this paper the performance of Coanda-type nozzles is examined in detail and an index rating for nozzle performance is introduced. Results show that far field stagnation pressure distributions are Gaussian and similar in all cases with a dispersion coefficient σ = 0·64. Noise reduction and thrust efficiency are shown to be closely related to the design geometry of the central body of the nozzle. Performance is based on four fundamental characteristics, these being the noise level at 1 m from the exit and at a 90° station to the nozzle axis, and the thrust on a chosen profile, the noise reduction and the thrust efficiency. Physically, performance is attributed to flow near field effects where, although all nozzles are choked, shock cell associated noise is absent.
Nurmi, Sami; Byrnes, Christian T.; Tasinato, Gianmassimo E-mail: ctb22@sussex.ac.uk
2013-06-01
Primordial perturbations with wavelengths greater than the observable universe shift the effective background fields in our observable patch from their global averages over the inflating space. This leads to a landscape picture where the properties of our observable patch depend on its location and may significantly differ from the expectation values predicted by the underlying fundamental inflationary model. We show that if multiple fields are present during inflation, this may happen even if our horizon exit would be preceded by only a few e-foldings of inflation. Non-Gaussian statistics are especially affected: for example models of local non-Gaussianity predicting |f{sub NL}{sup 0}| >> 10 over the entire inflating volume can have a probability up to a few tens of percent to generate a non-detectable bispectrum in our observable patch |f{sub NL}{sup obs.}|∼<10. In this work we establish systematic connections between the observable local properties of primordial perturbations and the global properties of the inflating space which reflect the underlying high energy physics. We study in detail the implications of both a detection and non-detection of primordial non-Gaussianity by Planck, and discover novel ways of characterising the naturalness of different observational configurations.
Hyperbranched polymer stars with Gaussian chain statistics revisited.
Polińska, P; Gillig, C; Wittmer, J P; Baschnagel, J
2014-02-01
Conformational properties of regular dendrimers and more general hyperbranched polymer stars with Gaussian statistics for the spacer chains between branching points are revisited numerically. We investigate the scaling for asymptotically long chains especially for fractal dimensions df = 3 (marginally compact) and df = 2.5 (diffusion limited aggregation). Power-law stars obtained by imposing the number of additional arms per generation are compared to truly self-similar stars. We discuss effects of weak excluded-volume interactions and sketch the regime where the Gaussian approximation should hold in dense solutions and melts for sufficiently large spacer chains. PMID:24574057
CMB hemispherical asymmetry: long mode modulation and non-Gaussianity
Namjoo, Mohammad Hossein; Baghram, Shant; Firouzjahi, Hassan; Abolhasani, Ali Akbar E-mail: abolhasani@ipm.ir E-mail: firouz@ipm.ir
2014-08-01
The observed hemispherical asymmetry in CMB map can be explained by modulation from a long wavelength super horizon mode which non-linearly couples to the CMB modes. We address the criticism in [1] about the role of non-Gaussianities in squeezed and equilateral configurations in generating hemispherical asymmetry from the long mode modulation. We stress that the modulation is sensitive to the non-Gaussianity in the squeezed limit. In addition, we demonstrate the validity of our approach in providing a consistency condition relating the amplitude of dipole asymmetry to f{sub NL} in the squeezed limit.
The topology of large-scale structure. II - Nonlinear evolution of Gaussian models
NASA Technical Reports Server (NTRS)
Melott, Adrian L.; Weinberg, David H.; Gott, J. Richard, III
1988-01-01
The evolution of non-Gaussian behavior in the large-scale universe from Gaussian initial conditions is studied. Topology measures developed in previous papers are applied to the smoothed initial, final, and biased matter distributions of cold dark matter, white noise, and massive neutrino simulations. When the smoothing length is approximately twice the mass correlation length or larger, the evolved models look like the initial conditions, suggesting that random phase hypotheses in cosmology can be tested with adequate data sets. When a smaller smoothing length is used, nonlinear effects are recovered, so nonlinear effects on topology can be detected in redshift surveys after smoothing at the mean intergalaxy separation. Hot dark matter models develop manifestly non-Gaussian behavior attributable to phase correlations, with a topology reminiscent of bubble or sheet distributions. Cold dark matter models remain Gaussian, and biasing does not disguise this.
Duan, Fabing; Chapeau-Blondeau, François; Abbott, Derek
2014-08-01
This paper studies the signal-to-noise ratio (SNR) gain of a parallel array of nonlinear elements that transmits a common input composed of a periodic signal and external noise. Aiming to further enhance the SNR gain, each element is injected with internal noise components or high-frequency sinusoidal vibrations. We report that the SNR gain exhibits two maxima at different values of the internal noise level or of the sinusoidal vibration amplitude. For the addition of internal noise to an array of threshold-based elements, the condition for occurrence of stochastic resonance is analytically investigated in the limit of weak signals. Interestingly, when the internal noise components are replaced by high-frequency sinusoidal vibrations, the SNR gain displays the vibrational multiresonance phenomenon. In both considered cases, there are certain regions of the internal noise intensity or the sinusoidal vibration amplitude wherein the achieved maximal SNR gain can be considerably beyond unity for a weak signal buried in non-Gaussian external noise. Due to the easy implementation of sinusoidal vibration modulation, this approach is potentially useful for improving the output SNR in an array of nonlinear devices. PMID:25215715
Non-Gaussian bias: insights from discrete density peaks
Desjacques, Vincent; Riotto, Antonio; Gong, Jinn-Ouk E-mail: jinn-ouk.gong@apctp.org
2013-09-01
Corrections induced by primordial non-Gaussianity to the linear halo bias can be computed from a peak-background split or the widespread local bias model. However, numerical simulations clearly support the prediction of the former, in which the non-Gaussian amplitude is proportional to the linear halo bias. To understand better the reasons behind the failure of standard Lagrangian local bias, in which the halo overdensity is a function of the local mass overdensity only, we explore the effect of a primordial bispectrum on the 2-point correlation of discrete density peaks. We show that the effective local bias expansion to peak clustering vastly simplifies the calculation. We generalize this approach to excursion set peaks and demonstrate that the resulting non-Gaussian amplitude, which is a weighted sum of quadratic bias factors, precisely agrees with the peak-background split expectation, which is a logarithmic derivative of the halo mass function with respect to the normalisation amplitude. We point out that statistics of thresholded regions can be computed using the same formalism. Our results suggest that halo clustering statistics can be modelled consistently (in the sense that the Gaussian and non-Gaussian bias factors agree with peak-background split expectations) from a Lagrangian bias relation only if the latter is specified as a set of constraints imposed on the linear density field. This is clearly not the case of standard Lagrangian local bias. Therefore, one is led to consider additional variables beyond the local mass overdensity.
Gaussian weighted projection for visualization of cardiac calcification
NASA Astrophysics Data System (ADS)
Chen, Xiang; Li, Ke; Gilkeson, Robert; Fei, Baowei
2008-03-01
At our institution, we are using dual-energy digital radiography (DEDR) as a cost-effective screening tool for the detection of cardiac calcification. We are evaluating DEDR using CT as the gold standard. We are developing image projection methods for the generation of digitally reconstructed radiography (DRR) from CT image volumes. Traditional visualization methods include maximum intensity projection (MIP) and average-based projection (AVG) that have difficulty to show cardiac calcification. Furthermore, MIP can over estimate the calcified lesion as it displays the maximum intensity along the projection rays regardless of tissue types. For AVG projection, the calcified tissue is usually overlapped with bone, lung and mediastinum. In order to improve the visualization of calcification on DRR images, we developed a Gaussian-weighted projection method for this particular application. We assume that the CT intensity values of calcified tissues have a Gaussian distribution. We then use multiple Gaussian functions to fit the intensity histogram. Based on the mean and standard deviation parameters, we incorporate a Gaussian weighted function into the perspective projection and display the calcification exclusively. Our digital and physical phantom studies show that the new projection method can display tissues selectively. In addition, clinical images show that the Gaussian-weighted projection method better visualizes cardiac calcification than either the AVG or MIP method and can be used to evaluate DEDR as a screening tool for the detection of coronary artery diseases.
NASA Astrophysics Data System (ADS)
Fraile, Rubén; Sáenz-Lechón, Nicolás; Godino-Llorente, Juan Ignacio; Osma-Ruiz, Víctor; Fredouille, Corinne
Advances in speech signal analysis during the last decade have allowed the development of automatic algorithms for a non-invasive detection of laryngeal pathologies. Performance assessment of such techniques reveals that classification success rates over 90 % are achievable. Bearing in mind the extension of these automatic methods to remote diagnosis scenarios, this paper analyses the performance of a pathology detector based on Mel Frequency Cepstral Coefficients when the speech signal has undergone the distortion of an analogue communications channel, namely the phone channel. Such channel is modeled as a concatenation of linear effects. It is shown that while the overall performance of the system is degraded, success rates in the range of 80% can still be achieved. This study also shows that the performance degradation is mainly due to band limitation and noise addition.
A statistical analysis of NMR spectrometer noise.
Grage, Halfdan; Akke, Mikael
2003-05-01
Estimation of NMR spectral parameters, using e.g. maximum likelihood methods, is commonly based on the assumption of white complex Gaussian noise in the signal obtained by quadrature detection. Here we present a statistical analysis with the purpose of discussing and testing the validity of this fundamental assumption. Theoretical expressions are derived for the correlation structure of the noise under various conditions, showing that in general the noise in the sampled signal is not strictly white, even if the thermal noise in the receiver steps prior to digitisation can be characterised as white Gaussian noise. It is shown that the noise correlation properties depend on the ratio between the sampling frequency and the filter cut-off frequency, as well as the filter characteristics. The theoretical analysis identifies conditions that are expected to yield non-white noise in the sampled signal. Extensive statistical characterisation of experimental noise confirms the theoretical predictions. The statistical methods outlined here are also useful for residual analysis in connection with validation of the model and the parameter estimates. PMID:12762994
Probabilistic stellar rotation periods with Gaussian processes
NASA Astrophysics Data System (ADS)
Angus, Ruth; Aigrain, Suzanne; Foreman-Mackey, Daniel
2015-08-01
Stellar rotation has many applications in the field of exoplanets. High-precision photometry from space-based missions like Kepler and K2 allows us to measure stellar rotation periods directly from light curves. Stellar variability produced by rotation is usually not sinusoidal or perfectly periodic, therefore sine-fitting periodograms are not well suited to rotation period measurement. Autocorrelation functions are often used to extract periodic information from light curves, however uncertainties on rotation periods measured by autocorrelation are difficult to define. A ‘by eye’ check, or a set of heuristic criteria are used to validate measurements and rotation periods are only reported for stars that pass this vetting process. A probabilistic rotation period measurement method, with a suitable generative model bypasses the need for a validation stage and can produce realistic uncertainties. The physics driving the production of variability in stellar light curves is still poorly understood and difficult to model. We therefore use an effective model for stellar variability: a Gaussian process with a quasi-periodic covariance function. By injecting fake signals into Kepler light curves we show that the GP model is well suited to quasi-periodic, non-sinusoidal signals, is capable of modelling noise and physical signals simultaneously and provides probabilistic rotation period measurements with realistic uncertainties.
Laser line shape and spectral density of frequency noise
Stephan, G.M.; Blin, S.; Besnard, P.; Tam, T.T.; Tetu, M.
2005-04-01
Published experimental results show that single-mode laser light is characterized in the microwave range by a frequency noise which essentially includes a white part and a 1/f (flicker) part. We theoretically show that the spectral density (the line shape) which is compatible with these results is a Voigt profile whose Lorentzian part or homogeneous component is linked to the white noise and the Gaussian part to the 1/f noise. We measure semiconductor laser line profiles and verify that they can be fit with Voigt functions. It is also verified that the width of the Lorentzian part varies like 1/P where P is the laser power while the width of the Gaussian part is more of a constant. Finally, we theoretically show from first principles that laser line shapes are also described by Voigt functions where the Lorentzian part is the laser Airy function and the Gaussian part originates from population noise.
Highway traffic segmentation using super-resolution and Gaussian mixture model
NASA Astrophysics Data System (ADS)
Yousef, Amr Hussein; Flora, Jeff; Iftekharuddin, Khan
2013-09-01
One benefit of employing computer vision techniques to extract individual vehicles from a highway traffic scene is the abundance of networked, traffic surveillance cameras that may be leveraged as the input video. However, the acquisition sensors that are monitoring the highway traffic will have very limited quality. Additionally, video streams are heavily compressed, causing noise and, in some cases, visible artifacts to be introduced into the video. Further challenges are presented by external environmental and weather conditions, such as rain, fog, and snow, that cause video blurring or noise. The resulting output of a segmentation algorithm yields poorer results, with many vehicles undetected or partially detected. Our goal is to extract individual vehicles from a highway traffic scenes using super-resolution and the utilization of Gaussian mixture model algorithm (GMM). We used a speeded-up enhanced stochastic Wiener filter for SR reconstruction and restoration. It can be used to remove artifacts and enhance the visual quality of the reconstructed images and can be implemented efficiently in the frequency domain. The filter derivation depends on the continuous-discrete-continuous (CDC) model that represents most of the degradations encountered during the image-gathering and image-display processes. Then, we use GMM followed by the clustering of individual vehicles. Individual vehicles are detected from the segmented scene through the use of a series of morphological operations, followed by two-dimensional connected component labeling. We evaluate our hybrid approach quantitatively in the segmentation of the extracted vehicles.
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.
Audience noise in concert halls during musical performances.
Jeong, Cheol-Ho; Marie, Pierre; Brunskog, Jonas; Møller Petersen, Claus
2012-04-01
Noise generated by the audience during musical performances is audible and sometimes disturbing. In this study, an attempt to estimate such audience noise was carried out. From the recordings of performances in five performance spaces (four concert halls and one opera house), probability density functions of the sound pressure levels were obtained in octave bands, which were fitted with three Gaussian distribution curves. The Gaussian distribution curve with the lowest mean value corresponds to a mixture of the technical background noise and audience generated noise, which is named the mixed background noise. Finally, the audience noise distribution is extracted by energy subtraction of the technical background noise levels measured in an empty condition from the mixed background noise levels. As a single index, L(90) of the audience noise distribution is named the audience noise level. Empirical prediction models were made using the four orchestra concert halls, revealing that the audience noise level is significantly correlated with the technical background noise level. It is therefore concluded that a relaxation of the current background noise recommendations for concert halls is not recommended. PMID:22501054
NASA Technical Reports Server (NTRS)
Mixson, John S.; Wilby, John F.
1991-01-01
The generation and control of flight vehicle interior noise is discussed. Emphasis is placed on the mechanisms of transmission through airborne and structure-borne paths and the control of cabin noise by path modification. Techniques for identifying the relative contributions of the various source-path combinations are also discussed along with methods for the prediction of aircraft interior noise such as those based on the general modal theory and statistical energy analysis.
NASA Technical Reports Server (NTRS)
1980-01-01
Environmental Health Systems puts forth an increasing effort in the U.S. to develop ways of controlling noise, particularly in industrial environments due to Federal and State laws, labor union insistence and new findings relative to noise pollution impact on human health. NASA's Apollo guidance control system aided in the development of a noise protection product, SMART. The basis of all SMART products is SMART compound a liquid plastic mixture with exceptional energy/sound absorbing qualities. The basic compound was later refined for noise protection use.
Area scintillations of Bessel Gaussian and modified Bessel Gaussian beams of zeroth order
NASA Astrophysics Data System (ADS)
Eyyuboğlu, H. T.
2010-01-01
As an extension of our previous study, the area scintillation aspects of Bessel Gaussian and modified Bessel Gaussian beams of zeroth order are investigated. The analysis is carried out on the basis of equal source sizes and equal source powers. It is found that, when compared on equal source size basis, modified Bessel Gaussian beams always have less area scintillations than a Gaussian beam, while Bessel Gaussian beams exhibit more area scintillations. Comparison on equal source power basis, however, removes the advantage of modified Bessel Gaussian beams, that is, their area scintillations become nearly the same as those of the Gaussian beam. On the other hand, for the case of equal source powers, Bessel Gaussian beams with larger width parameters continue to have higher area scintillations than the Gaussian beam. We provide graphical illustrations for profiles of equal source size beams, equal source power beams and the curves to aid the selection of equal source power beams.
Noise-Induced Phase Transitions: Effects of the Noises' Statistics and Spectrum
NASA Astrophysics Data System (ADS)
Deza, Roberto R.; Wio, Horacio S.; Fuentes, Miguel A.
2007-05-01
The local, uncorrelated multiplicative noises driving a second-order, purely noise-induced, ordering phase transition (NIPT) were assumed to be Gaussian and white in the model of [Phys. Rev. Lett. 73, 3395 (1994)]. The potential scientific and technological interest of this phenomenon calls for a study of the effects of the noises' statistics and spectrum. This task is facilitated if these noises are dynamically generated by means of stochastic differential equations (SDE) driven by white noises. One such case is that of Ornstein-Uhlenbeck noises which are stationary, with Gaussian pdf and a variance reduced by the self-correlation time τ, and whose effect on the NIPT phase diagram has been studied some time ago. Another such case is when the stationary pdf is a (colored) Tsallis' q-Gaussian which, being a fat-tail distribution for q > 1 and a compact-support one for q < 1, allows for a controlled exploration of the effects of the departure from Gaussian statistics. As done before with stochastic resonance and other phenomena, we now exploit this tool to study—within a simple mean-field approximation and with an emphasis on the order parameter and the "susceptibility"—the combined effect on NIPT of the noises' statistics and spectrum. Even for relatively small τ, it is shown that whereas fat-tail noise distributions (q > 1) counteract the effect of self-correlation, compact-support ones (q < 1) enhance it. Also, an interesting effect on the susceptibility is seen in the last case.
FPGA design and implementation of Gaussian filter
NASA Astrophysics Data System (ADS)
Yang, Zhihui; Zhou, Gang
2015-12-01
In this paper , we choose four different variances of 1,3,6 and 12 to conduct FPGA design with three kinds of Gaussian filtering algorithm ,they are implementing Gaussian filter with a Gaussian filter template, Gaussian filter approximation with mean filtering and Gaussian filter approximation with IIR filtering. By waveform simulation and synthesis, we get the processing results on the experimental image and the consumption of FPGA resources of the three methods. We set the result of Gaussian filter used in matlab as standard to get the result error. By comparing the FPGA resources and the error of FPGA implementation methods, we get the best FPGA design to achieve a Gaussian filter. Conclusions can be drawn based on the results we have already got. When the variance is small, the FPGA resources is enough for the algorithm to implement Gaussian filter with a Gaussian filter template which is the best choice. But when the variance is so large that there is no more FPGA resources, we can chose the mean to approximate Gaussian filter with IIR filtering.
An adaptive unsupervised hyperspectral classification method based on Gaussian distribution
NASA Astrophysics Data System (ADS)
Yue, Jiang; Wu, Jing-wei; Zhang, Yi; Bai, Lian-fa
2014-11-01
In order to achieve adaptive unsupervised clustering in the high precision, a method using Gaussian distribution to fit the similarity of the inter-class and the noise distribution is proposed in this paper, and then the automatic segmentation threshold is determined by the fitting result. First, according with the similarity measure of the spectral curve, this method assumes that the target and the background both in Gaussian distribution, the distribution characteristics is obtained through fitting the similarity measure of minimum related windows and center pixels with Gaussian function, and then the adaptive threshold is achieved. Second, make use of the pixel minimum related windows to merge adjacent similar pixels into a picture-block, then the dimensionality reduction is completed and the non-supervised classification is realized. AVIRIS data and a set of hyperspectral data we caught are used to evaluate the performance of the proposed method. Experimental results show that the proposed algorithm not only realizes the adaptive but also outperforms K-MEANS and ISODATA on the classification accuracy, edge recognition and robustness.
NASA Astrophysics Data System (ADS)
Michel, Ulf; Dobrzynski, Werner; Splettstoesser, Wolf; Delfs, Jan; Isermann, Ullrich; Obermeier, Frank
Aircraft industry is exposed to increasing public pressure aiming at a continuing reduction of aircraft noise levels. This is necessary to both compensate for the detrimental effect on noise of the expected increase in air traffic and improve the quality of living in residential areas around airports.
NASA Astrophysics Data System (ADS)
Rumberg, Martin
Environmental noise may be defined as unwanted sound that is caused by emissions from traffic (roads, air traffic corridors, and railways), industrial sites and recreational infrastructures, which may cause both annoyance and damage to health. Noise in the environment or community seriously affects people, interfering with daily activities at school, work and home and during leisure time.
Incremental mixed lognormal-Gaussian 4D VAR
NASA Astrophysics Data System (ADS)
Forsythe, J.; Fletcher, S. J.; Kliewer, A.; Jones, A. S.
2013-12-01
One of the advances that allowed 4DVAR to be operational for synoptic numerical weather prediction was the introduction of incremental 4DVAR. This method assumes that the errors are additive and Gaussian in nature. However, as work recently has shown, there are errors which are multiplicative. A full field version of the 4DVAR equations have been derived and tested in a toy problem for the situation where there is a mix of Gaussian and lognormal background and observational errors. It is not straight-forward, however, to extend the incremental theory to multiplicative errors. One approach which has been suggested recently involves using a transform for the increment. It is shown here that the increment that is found is not the 'incremental mode', i.e. the most likely state for the increment, but rather a median state for the increment. To overcome the multiplicative nature of the errors we present a geometric tangent linear approximation which enables us to linearize the observation operator with respect to a consistent lognormal multiplicative increment. In this paper we present an equivalent incremental version of the mixed lognormal-Gaussian which is based upon finding the most-likely state for additive increments for the Gaussian variables and lognormal for the multiplicative lognormal variables. We test this new approach with the Lorenz 1963 model under different size observational errors and observation window lengths.
Sivakumar, Vidyashankar; Banerjee, Arindam; Ravikumar, Pradeep
2016-01-01
We consider the problem of high-dimensional structured estimation with norm-regularized estimators, such as Lasso, when the design matrix and noise are drawn from sub-exponential distributions. Existing results only consider sub-Gaussian designs and noise, and both the sample complexity and non-asymptotic estimation error have been shown to depend on the Gaussian width of suitable sets. In contrast, for the sub-exponential setting, we show that the sample complexity and the estimation error will depend on the exponential width of the corresponding sets, and the analysis holds for any norm. Further, using generic chaining, we show that the exponential width for any set will be at most logp times the Gaussian width of the set, yielding Gaussian width based results even for the sub-exponential case. Further, for certain popular estimators, viz Lasso and Group Lasso, using a VC-dimension based analysis, we show that the sample complexity will in fact be the same order as Gaussian designs. Our general analysis and results are the first in the sub-exponential setting, and are readily applicable to special sub-exponential families such as log-concave and extreme-value distributions. PMID:27563230
Nonuniformity correction algorithm based on Gaussian mixture model
NASA Astrophysics Data System (ADS)
Mou, Xin-gang; Zhang, Gui-lin; Hu, Ruo-lan; Zhou, Xiao
2011-08-01
As an important tool to acquire information of target scene, infrared detector is widely used in imaging guidance field. Because of the limit of material and technique, the performance of infrared imaging system is known to be strongly affected by the spatial nonuniformity in the photoresponse of the detectors in the array. Temporal highpass filter(THPF) is a popular adaptive NUC algorithm because of its simpleness and effectiveness. However, there still exists the problem of ghosting artifact in the algorithms caused by blind update of parameters, and the performance is noticeably degraded when the methods are applied over scenes with lack of motion. In order to tackle with this problem, a novel adaptive NUC algorithm based on Gaussian mixed model (GMM) is put forward according to traditional THPF. The drift of the detectors is assumed to obey a single Gaussian distribution, and the update of the parameters is selectively performed based on the scene. GMM is applied in the new algorithm for background modeling, in which the background is updated selectively so as to avoid the influence of the foreground target on the update of the background, thus eliminating the ghosting artifact. The performance of the proposed algorithm is evaluated with infrared image sequences with simulated and real fixed-pattern noise. The results show a more reliable fixed-pattern noise reduction, tracking the parameter drift, and presenting a good adaptability to scene changes.
Monogamy inequality for distributed gaussian entanglement.
Hiroshima, Tohya; Adesso, Gerardo; Illuminati, Fabrizio
2007-02-01
We show that for all n-mode Gaussian states of continuous variable systems, the entanglement shared among n parties exhibits the fundamental monogamy property. The monogamy inequality is proven by introducing the Gaussian tangle, an entanglement monotone under Gaussian local operations and classical communication, which is defined in terms of the squared negativity in complete analogy with the case of n-qubit systems. Our results elucidate the structure of quantum correlations in many-body harmonic lattice systems. PMID:17358836
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.
Elegant Gaussian beams for enhanced optical manipulation
Alpmann, Christina Schöler, Christoph; Denz, Cornelia
2015-06-15
Generation of micro- and nanostructured complex light beams attains increasing impact in photonics and laser applications. In this contribution, we demonstrate the implementation and experimental realization of the relatively unknown, but highly versatile class of complex-valued Elegant Hermite- and Laguerre-Gaussian beams. These beams create higher trapping forces compared to standard Gaussian light fields due to their propagation changing properties. We demonstrate optical trapping and alignment of complex functional particles as nanocontainers with standard and Elegant Gaussian light beams. Elegant Gaussian beams will inspire manifold applications in optical manipulation, direct laser writing, or microscopy, where the design of the point-spread function is relevant.
Classical nature of nuclear spin noise near clock transitions of Bi donors in silicon
NASA Astrophysics Data System (ADS)
Ma, Wen-Long; Wolfowicz, Gary; Li, Shu-Shen; Morton, John J. L.; Liu, Ren-Bao
2015-10-01
Whether a quantum bath can be approximated as classical Gaussian noise is a fundamental issue in central spin decoherence and also of practical importance in designing noise-resilient quantum control. Spin qubits based on bismuth donors in silicon have tunable interactions with nuclear spin baths and are first-order insensitive to magnetic noise at so-called clock transitions (CTs). This system is therefore ideal for studying the quantum/classical Gaussian nature of nuclear spin baths since the qubit-bath interaction strength determines the back-action on the baths and hence the adequacy of a Gaussian noise model. We develop a Gaussian noise model with noise correlations determined by quantum calculations and compare the classical noise approximation to the full quantum bath theory. We experimentally test our model through a dynamical decoupling sequence of up to 128 pulses, finding good agreement with simulations and measuring electron spin coherence times approaching 1 s—notably using natural silicon. Our theoretical and experimental study demonstrates that the noise from a nuclear spin bath is analogous to classical Gaussian noise if the back-action of the qubit on the bath is small compared to the internal bath dynamics, as is the case close to CTs. However, far from the CTs, the back-action of the central spin on the bath is such that the quantum model is required to accurately model spin decoherence.
Non-Gaussian Photon Probability Distribution
Solomon, Benjamin T.
2010-01-28
This paper investigates the axiom that the photon's probability distribution is a Gaussian distribution. The Airy disc empirical evidence shows that the best fit, if not exact, distribution is a modified Gamma mGAMMA distribution (whose parameters are alpha = r, betar/sq root(u)) in the plane orthogonal to the motion of the photon. This modified Gamma distribution is then used to reconstruct the probability distributions along the hypotenuse from the pinhole, arc from the pinhole, and a line parallel to photon motion. This reconstruction shows that the photon's probability distribution is not a Gaussian function. However, under certain conditions, the distribution can appear to be Normal, thereby accounting for the success of quantum mechanics. This modified Gamma distribution changes with the shape of objects around it and thus explains how the observer alters the observation. This property therefore places additional constraints to quantum entanglement experiments. This paper shows that photon interaction is a multi-phenomena effect consisting of the probability to interact P{sub i}, the probabilistic function and the ability to interact A{sub i}, the electromagnetic function. Splitting the probability function P{sub i} from the electromagnetic function A{sub i} enables the investigation of the photon behavior from a purely probabilistic P{sub i} perspective. The Probabilistic Interaction Hypothesis is proposed as a consistent method for handling the two different phenomena, the probability function P{sub i} and the ability to interact A{sub i}, thus redefining radiation shielding, stealth or cloaking, and invisibility as different effects of a single phenomenon P{sub i} of the photon probability distribution. Sub wavelength photon behavior is successfully modeled as a multi-phenomena behavior. The Probabilistic Interaction Hypothesis provides a good fit to Otoshi's (1972) microwave shielding, Schurig et al.(2006) microwave cloaking, and Oulton et al.(2008) sub
NASA Astrophysics Data System (ADS)
Beristain, Sergio
2001-05-01
Mexico City is known to be the largest city in the world, inhabited by some 20 percent of the national population, so noise pollution is not strange to it, particularly in view of the fact that industry is not concentrated, but rather spread throughout the city. The international airport also lies within the city limits, in the midst of residential areas. The heavy traffic during rush hours in the morning and in the evening and the activities of the populace, together with special events, produce a noise problem that is difficult to assess and to solve. Nevertheless, with educational programs begun several years ago and noise campaigns planned for the near future, in addition to existing regulations, the problem is not completely out of control. This paper presents a discussion of the general noise problem and describes how authorities and institutions are dealing with it.
Airframe noise prediction evaluation
NASA Technical Reports Server (NTRS)
Yamamoto, Kingo J.; Donelson, Michael J.; Huang, Shumei C.; Joshi, Mahendra C.
1995-01-01
The objective of this study is to evaluate the accuracy and adequacy of current airframe noise prediction methods using available airframe noise measurements from tests of a narrow body transport (DC-9) and a wide body transport (DC-10) in addition to scale model test data. General features of the airframe noise from these aircraft and models are outlined. The results of the assessment of two airframe prediction methods, Fink's and Munson's methods, against flight test data of these aircraft and scale model wind tunnel test data are presented. These methods were extensively evaluated against measured data from several configurations including clean, slat deployed, landing gear-deployed, flap deployed, and landing configurations of both DC-9 and DC-10. They were also assessed against a limited number of configurations of scale models. The evaluation was conducted in terms of overall sound pressure level (OASPL), tone corrected perceived noise level (PNLT), and one-third-octave band sound pressure level (SPL).
Constrained Gaussian mixture model framework for automatic segmentation of MR brain images.
Greenspan, Hayit; Ruf, Amit; Goldberger, Jacob
2006-09-01
An automated algorithm for tissue segmentation of noisy, low-contrast magnetic resonance (MR) images of the brain is presented. A mixture model composed of a large number of Gaussians is used to represent the brain image. Each tissue is represented by a large number of Gaussian components to capture the complex tissue spatial layout. The intensity of a tissue is considered a global feature and is incorporated into the model through tying of all the related Gaussian parameters. The expectation-maximization (EM) algorithm is utilized to learn the parameter-tied, constrained Gaussian mixture model. An elaborate initialization scheme is suggested to link the set of Gaussians per tissue type, such that each Gaussian in the set has similar intensity characteristics with minimal overlapping spatial supports. Segmentation of the brain image is achieved by the affiliation of each voxel to the component of the model that maximized the a posteriori probability. The presented algorithm is used to segment three-dimensional, T1-weighted, simulated and real MR images of the brain into three different tissues, under varying noise conditions. Results are compared with state-of-the-art algorithms in the literature. The algorithm does not use an atlas for initialization or parameter learning. Registration processes are therefore not required and the applicability of the framework can be extended to diseased brains and neonatal brains. PMID:16967808
Primordial non-Gaussianity in the bispectrum of the halo density field
Baldauf, Tobias; Seljak, Uroš; Senatore, Leonardo E-mail: seljak@physik.uzh.ch
2011-04-01
The bispectrum vanishes for linear Gaussian fields and is thus a sensitive probe of non-linearities and non-Gaussianities in the cosmic density field. Hence, a detection of the bispectrum in the halo density field would enable tight constraints on non-Gaussian processes in the early Universe and allow inference of the dynamics driving inflation. We present a tree level derivation of the halo bispectrum arising from non-linear clustering, non-linear biasing and primordial non-Gaussianity. A diagrammatic description is developed to provide an intuitive understanding of the contributing terms and their dependence on scale, shape and the non-Gaussianity parameter f{sub NL}. We compute the terms based on a multivariate bias expansion and the peak-background split method and show that non-Gaussian modifications to the bias parameters lead to amplifications of the tree level bispectrum that were ignored in previous studies. Our results are in a good agreement with published simulation measurements of the halo bispectrum. Finally, we estimate the expected signal to noise on f{sub NL} and show that the constraint obtainable from the bispectrum analysis significantly exceeds the one obtainable from the power spectrum analysis.
Gras, S.; Blair, D. G.; Ju, L.
2010-02-15
To reduce the thermal noise in the future generation of gravitational wave detectors, flat-top beams have been proposed to replace conventional Gaussian beams, so as to obtain better averaging over the Brownian motion of the test masses. Here, we present a detailed investigation of the unwanted opto-acoustic interactions in such interferometers, which can lead to the phenomenon of parametric instability. Our results show that the increased overlap of the Mesa beams with the test masses leads to approximately 3 times as many unstable modes in comparison to a similar interferometer with Gaussian beams.
Search for non-Gaussianity in pixel, harmonic, and wavelet space: Compared and combined
NASA Astrophysics Data System (ADS)
Cabella, Paolo; Hansen, Frode; Marinucci, Domenico; Pagano, Daniele; Vittorio, Nicola
2004-03-01
We present a comparison between three approaches to test the non-Gaussianity of cosmic microwave background data. The Minkowski functionals, the empirical process method, and the skewness of wavelet coefficients are applied to maps generated from nonstandard inflationary models and to Gaussian maps with point sources included. We discuss the different power of the pixel, harmonic, and wavelet space methods on these simulated almost full-sky data (with Planck-like noise). We also suggest a new procedure consisting of a combination of statistics in pixel, harmonic, and wavelet space.
Continuous-variable quantum cryptography is secure against non-Gaussian attacks.
Grosshans, Frédéric; Cerf, Nicolas J
2004-01-30
A general study of arbitrary finite-size coherent attacks against continuous-variable quantum cryptographic schemes is presented. It is shown that, if the size of the blocks that can be coherently attacked by an eavesdropper is fixed and much smaller than the key size, then the optimal attack for a given signal-to-noise ratio in the transmission line is an individual Gaussian attack. Consequently, non-Gaussian coherent attacks do not need to be considered in the security analysis of such quantum cryptosystems. PMID:14995411
Near grazing scattering from non-Gaussian ocean surfaces
NASA Technical Reports Server (NTRS)
Kim, Yunjin; Rodriguez, Ernesto
1993-01-01
We investigate the behavior of the scattered electromagnetic waves from non-Gaussian ocean surfaces at near grazing incidence. Even though the scattering mechanisms at moderate incidence angles are relatively well understood, the same is not true for near grazing rough surface scattering. However, from the experimental ocean scattering data, it has been observed that the backscattering cross section of a horizontally polarized wave can be as large as the vertical counterpart at near grazing incidence. In addition, these returns are highly intermittent in time. There have been some suggestions that these unexpected effects may come from shadowing or feature scattering. Using numerical scattering simulations, it can be shown that the horizontal backscattering cannot be larger than the vertical one for the Gaussian surfaces. Our main objective of this study is to gain a clear understanding of scattering mechanisms underlying the near grazing ocean scattering. In order to evaluate the backscattering cross section from ocean surfaces at near grazing incidence, both the hydrodynamic modeling of ocean surfaces and an accurate near grazing scattering theory are required. For the surface modeling, we generate Gaussian surfaces from the ocean surface power spectrum which is derived using several experimental data. Then, weakly nonlinear large scale ocean surfaces are generated following Longuet-Higgins. In addition, the modulation of small waves by large waves is included using the conservation of wave action. For surface scattering, we use MOM (Method of Moments) to calculate the backscattering from scattering patches with the two scale shadowing approximation. The differences between Gaussian and non-Gaussian surface scattering at near grazing incidence are presented.
Okokon, Enembe Oku; Turunen, Anu W.; Ung-Lanki, Sari; Vartiainen, Anna-Kaisa; Tiittanen, Pekka; Lanki, Timo
2015-01-01
Exposure to road-traffic noise commonly engenders annoyance, the extent of which is determined by factors not fully understood. Our aim was to estimate the prevalence and determinants of road-traffic noise annoyance and noise sensitivity in the Finnish adult population, while comparing the perceptions of road-traffic noise to exhausts as environmental health problems. Using a questionnaire that yielded responses from 1112 randomly selected adult Finnish respondents, we estimated road-traffic noise- and exhausts-related perceived exposures, health-risk perceptions, and self-reported annoyance on five-point scales, while noise sensitivity estimates were based on four questions. Determinants of noise annoyance and sensitivity were investigated using multivariate binary logistic regression and linear regression models, respectively. High or extreme noise annoyance was reported by 17% of respondents. Noise sensitivity scores approximated a Gaussian distribution. Road-traffic noise and exhausts were, respectively, considered high or extreme population-health risks by 22% and 27% of respondents. Knowledge of health risks from traffic noise, OR: 2.04 (1.09–3.82) and noise sensitivity, OR: 1.07 (1.00–1.14) were positively associated with annoyance. Knowledge of health risks (p < 0.045) and positive environmental attitudes (p < 000) were associated with higher noise sensitivity. Age and sex were associated with annoyance and sensitivity only in bivariate models. A considerable proportion of Finnish adults are highly annoyed by road-traffic noise, and perceive it to be a significant health risk, almost comparable to traffic exhausts. There is no distinct noise-sensitive population subgroup. Knowledge of health risks of road-traffic noise, and attitudinal variables are associated with noise annoyance and sensitivity. PMID:26016432
Okokon, Enembe Oku; Turunen, Anu W; Ung-Lanki, Sari; Vartiainen, Anna-Kaisa; Tiittanen, Pekka; Lanki, Timo
2015-06-01
Exposure to road-traffic noise commonly engenders annoyance, the extent of which is determined by factors not fully understood. Our aim was to estimate the prevalence and determinants of road-traffic noise annoyance and noise sensitivity in the Finnish adult population, while comparing the perceptions of road-traffic noise to exhausts as environmental health problems. Using a questionnaire that yielded responses from 1112 randomly selected adult Finnish respondents, we estimated road-traffic noise- and exhausts-related perceived exposures, health-risk perceptions, and self-reported annoyance on five-point scales, while noise sensitivity estimates were based on four questions. Determinants of noise annoyance and sensitivity were investigated using multivariate binary logistic regression and linear regression models, respectively. High or extreme noise annoyance was reported by 17% of respondents. Noise sensitivity scores approximated a Gaussian distribution. Road-traffic noise and exhausts were, respectively, considered high or extreme population-health risks by 22% and 27% of respondents. Knowledge of health risks from traffic noise, OR: 2.04 (1.09-3.82) and noise sensitivity, OR: 1.07 (1.00-1.14) were positively associated with annoyance. Knowledge of health risks (p<0.045) and positive environmental attitudes (p<000) were associated with higher noise sensitivity. Age and sex were associated with annoyance and sensitivity only in bivariate models. A considerable proportion of Finnish adults are highly annoyed by road-traffic noise, and perceive it to be a significant health risk, almost comparable to traffic exhausts. There is no distinct noise-sensitive population subgroup. Knowledge of health risks of road-traffic noise, and attitudinal variables are associated with noise annoyance and sensitivity. PMID:26016432
Image deconvolution under Poisson noise using SURE-LET approach
NASA Astrophysics Data System (ADS)
Xue, Feng; Liu, Jiaqi; Meng, Gang; Yan, Jing; Zhao, Min
2015-10-01
We propose an image deconvolution algorithm when the data is contaminated by Poisson noise. By minimizing Stein's unbiased risk estimate (SURE), the SURE-LET method was firstly proposed to deal with Gaussian noise corruption. Our key contribution is to demonstrate that the SURE-LET algorithm is also applicable for Poisson noisy image and proposed an efficient algorithm. The formulation of SURE requires knowledge of Gaussian noise variance. We experimentally found a simple and direct link between the noise variance estimated by median absolute difference (MAD) method and the optimal one that leads to the best deconvolution performance in terms of mean squared error (MSE). Extensive experiments show that this optimal noise variance works satisfactorily for a wide range of natural images.
Reionization and CMB non-Gaussianity
NASA Astrophysics Data System (ADS)
Munshi, D.; Corasaniti, P. S.; Coles, P.; Heavens, A.; Pandolfi, S.
2014-08-01
We show how cross-correlating a high-redshift external tracer field, such as the 21-cm neutral hydrogen distribution and product maps involving cosmic microwave background (CMB) temperature and polarization fields, that probe mixed bispectrum involving these fields, can help to determine the reionization history of the Universe, beyond what can be achieved from cross-spectrum analysis. Taking clues from recent studies for the detection of primordial non-Gaussianity, we develop a set of estimators that can study reionization using a power spectrum associated with the bispectrum (or skew-spectrum). We use the matched filtering inherent in this method to investigate different reionization histories. We check to what extent they can be used to rule out various models of reionization and study cross-contamination from different sources such as the lensing of the CMB. The estimators can be fine-tuned to optimize study of a specific reionization history. We consider three different types of tracers in our study, namely: proto-galaxies; 21-cm maps of neutral hydrogen; and quasars. We also consider four alternative models of reionization. We find that the cumulative signal-to-noise ratio (S/N) for detection at ℓmax = 2000 can reach O(70) for cosmic variance limited all-sky experiments. Combining 100 GHz, 143 GHz and 217 GHz channels of the Planck experiment, we find that the S/N lies in the range O(5)-O(35). The S/N depends on the specific choice of a tracer field, and multiple tracers can be effectively used to map out the entire reionization history with reasonable S/N. Contamination from weak lensing is investigated and found to be negligible, and the effects of Thomson scattering from patchy reionization are also considered.
Entanglement generation via non-Gaussian transfer over atmospheric fading channels
NASA Astrophysics Data System (ADS)
Hosseinidehaj, Nedasadat; Malaney, Robert
2015-12-01
In this work we probe the usefulness of non-Gaussian entangled states as a resource for quantum communication through atmospheric channels. We outline the initial conditions in which non-Gaussian state transfer leads to enhanced entanglement transfer relative to that obtainable via Gaussian state transfer. However, we conclude that in (anticipated) operational scenarios—where most of the non-Gaussian states to be transferred over the air are created just in time via photonic subtraction, addition, or replacement from incoming Gaussian states—the entanglement-generation rate between stations via non-Gaussian state transfer will be substantially less than that created by direct Gaussian state transfer. The role of postselection, distillation, and quantum memory in altering this conclusion is discussed, and comparison with entanglement rates produced via single-photon technologies is provided. Our results suggest that in the near term entangled Gaussian states, squeezed beyond some modest level, offer the most attractive proposition for the distribution of entanglement through high-loss atmospheric channels. The implications of our results for entanglement-based quantum key distribution to low-Earth orbit are presented.
Halo/galaxy bispectrum with primordial non-Gaussianity from integrated perturbation theory
NASA Astrophysics Data System (ADS)
Yokoyama, Shuichiro; Matsubara, Takahiko; Taruya, Atsushi
2014-02-01
We derive a formula for the halo/galaxy bispectrum on the basis of the integrated perturbation theory (iPT). In addition to the gravity-induced non-Gaussianity, we consider the non-Gaussianity of the primordial curvature perturbations and investigate in detail the effect of such primordial non-Gaussianity on the large-scale halo/galaxy bispectrum. In iPT, the effects of primordial non-Gaussianity are wholly encapsulated in the linear (primordial) polyspectra, and we systematically calculate the contributions to the large-scale behaviors arising from the three types of primordial bispectrum (local, equilateral, and orthogonal types), and primordial trispectrum of the local-type non-Gaussianity. We find that the equilateral- and orthogonal-type non-Gaussianities show distinct scale-dependent behaviors which can dominate the gravity-induced non-Gaussianity at very large scales. For the local-type non-Gaussianity, higher-order loop corrections are found to give a significantly large contribution to the halo/galaxy bispectrum of the squeezed shape and eventually dominate over the other contributions on large scales. A diagrammatic approach based on the iPT helps us to systematically investigate an impact of such higher-order contributions to the large-scale halo/galaxy bispectrum.
Detection, classification, and extraction of helicopter-radiated noise
NASA Astrophysics Data System (ADS)
Dwyer, R. F.
1984-07-01
Surface ships operating in conjunction with supporting helicopters may experience sonar performance degradation due to the accompanying interference from helicopter-radiated noise. The interference manifests itself in the time domain as impulses due to blade vortex interactions and in the frequency domain as harmonic components from both the main and tail rotors. But these components are not pure sinusoids. In addition, they have non-Gaussian probability distributions. They appear to be caused by frequency modulation due to the rotating blades. The paper discusses detection and classification of helicopter-radiated noise from cumulative distribution function estimates, autocorrelation estimate, spectrum estimates, and from higher-order moment estimates. After the detection and classification problem is discussed a method to extract the interference by implementing a non-linearity in the frequency domain is presented. It is shown with real helicopter-radiated noise data that autocorrelation estimates can be improved by extracting the interfering components. The extracted components are also available as an enhanced time domain representation.
Noise and mental performance: personality attributes and noise sensitivity.
Belojevic, G; Jakovljevic, B; Slepcevic, V
2003-01-01
The contradictory and confusing results in noise research on humans may partly be due to individual differences between the subjects participating in different studies. This review is based on a twelve year research on the role of neuroticism, extroversion and subjective noise sensitivity during mental work in noisy environment. Neurotic persons might show enhanced "arousability" i.e. their arousal level increases more in stress. Additional unfavorable factors for neurotics are worrying and anxiety, which might prevent them coping successfully with noise, or some other stressors during mental performance. In numerous experiments introverts have showed higher sensitivity to noise during mental performance compared to extroverts, while extroverts often cope with a boring task even by requesting short periods of noise during performance. Correlation analyses have regularly revealed a highly significant negative relation between extroversion and noise annoyance during mental processing. Numerous studies have shown that people with high noise sensitivity may be prevented from achieving the same work results as other people in noisy environment, thus leading to psychosomatic, neurotic or other difficulties. Positive relation between noise annoyance and subjective noise sensitivity might be very strong. Our results have shown, after matching with the results of other relevant studies, that more stable personality, with extroversive tendencies and with a relatively lower subjective noise sensitivity measured with standard questionnaires, may be expected to better adapt to noise during mental performance, compared to people with opposite personality traits. PMID:14965455
Noise-enhanced convolutional neural networks.
Audhkhasi, Kartik; Osoba, Osonde; Kosko, Bart
2016-06-01
Injecting carefully chosen noise can speed convergence in the backpropagation training of a convolutional neural network (CNN). The Noisy CNN algorithm speeds training on average because the backpropagation algorithm is a special case of the generalized expectation-maximization (EM) algorithm and because such carefully chosen noise always speeds up the EM algorithm on average. The CNN framework gives a practical way to learn and recognize images because backpropagation scales with training data. It has only linear time complexity in the number of training samples. The Noisy CNN algorithm finds a special separating hyperplane in the network's noise space. The hyperplane arises from the likelihood-based positivity condition that noise-boosts the EM algorithm. The hyperplane cuts through a uniform-noise hypercube or Gaussian ball in the noise space depending on the type of noise used. Noise chosen from above the hyperplane speeds training on average. Noise chosen from below slows it on average. The algorithm can inject noise anywhere in the multilayered network. Adding noise to the output neurons reduced the average per-iteration training-set cross entropy by 39% on a standard MNIST image test set of handwritten digits. It also reduced the average per-iteration training-set classification error by 47%. Adding noise to the hidden layers can also reduce these performance measures. The noise benefit is most pronounced for smaller data sets because the largest EM hill-climbing gains tend to occur in the first few iterations. This noise effect can assist random sampling from large data sets because it allows a smaller random sample to give the same or better performance than a noiseless sample gives. PMID:26700535
Gaussianity and localization of N -qubit states
NASA Astrophysics Data System (ADS)
Gaeta, M.; Muñoz, C.; Klimov, A. B.
2016-06-01
We analyze collective properties of N -qubit states. In particular, we exhaustively discuss the localization aspect of distributions in the measurement space and introduce the concept of Gaussian states in the macroscopic limit. The effect of local shifts on the localization and Gaussianity is analyzed.
NASA Astrophysics Data System (ADS)
Way, M. J.; Foster, L. V.; Gazis, P. R.; Srivastava, A. N.
2009-11-01
Expanding upon the work of Way & Srivastava we demonstrate how the use of training sets of comparable size continue to make Gaussian process regression (GPR) a competitive approach to that of neural networks and other least-squares fitting methods. This is possible via new large-size matrix inversion techniques developed for Gaussian processes (GPs) that do not require that the kernel matrix be sparse. This development, combined with a neural-network kernel function appears to give superior results for this problem. Our best-fit results for the Sloan Digital Sky Survey (SDSS) Main Galaxy Sample using u, g, r, i, z filters gives an rms error of 0.0201 while our results for the same filters in the luminous red galaxy sample yield 0.0220. We also demonstrate that there appears to be a minimum number of training-set galaxies needed to obtain the optimal fit when using our GPR rank-reduction methods. We find that morphological information included with many photometric surveys appears, for the most part, to make the photometric redshift evaluation slightly worse rather than better. This would indicate that most morphological information simply adds noise from the GP point of view in the data used herein. In addition, we show that cross-match catalog results involving combinations of the Two Micron All Sky Survey, SDSS, and Galaxy Evolution Explorer have to be evaluated in the context of the resulting cross-match magnitude and redshift distribution. Otherwise one may be misled into overly optimistic conclusions.
The Airframe Noise Reduction Challenge
NASA Technical Reports Server (NTRS)
Lockhard, David P.; Lilley, Geoffrey M.
2004-01-01
The NASA goal of reducing external aircraft noise by 10 dB in the near-term presents the acoustics community with an enormous challenge. This report identifies technologies with the greatest potential to reduce airframe noise. Acoustic and aerodynamic effects will be discussed, along with the likelihood of industry accepting and implementing the different technologies. We investigate the lower bound, defined as noise generated by an aircraft modified with a virtual retrofit capable of eliminating all noise associated with the high lift system and landing gear. However, the airframe noise of an aircraft in this 'clean' configuration would only be about 8 dB quieter on approach than current civil transports. To achieve the NASA goal of 10 dB noise reduction will require that additional noise sources be addressed. Research shows that energy in the turbulent boundary layer of a wing is scattered as it crosses trailing edge. Noise generated by scattering is the dominant noise mechanism on an aircraft flying in the clean configuration. Eliminating scattering would require changes to much of the aircraft, and practical reduction devices have yet to receive serious attention. Evidence suggests that to meet NASA goals in civil aviation noise reduction, we need to employ emerging technologies and improve landing procedures; modified landing patterns and zoning restrictions could help alleviate aircraft noise in communities close to airports.
Non-gaussianity in the strong regime of warm inflation
Moss, Ian G.; Yeomans, Timothy E-mail: timothy.yeomans@ncl.ac.uk
2011-08-01
The bispectrum of scalar mode density perturbations is analysed for the strong regime of warm inflationary models. This analysis generalises previous results by allowing damping terms in the inflaton equation of motion that are dependent on temperature. A significant amount of non-gaussianity emerges with constant (or local) non-linearity parameter f{sub NL} ∼ 20, in addition to the terms with non-constant f{sub NL} which are characteristic of warm inflation.
Probabilistic density function method for nonlinear dynamical systems driven by colored noise.
Barajas-Solano, David A; Tartakovsky, Alexandre M
2016-05-01
We present a probability density function (PDF) method for a system of nonlinear stochastic ordinary differential equations driven by colored noise. The method provides an integrodifferential equation for the temporal evolution of the joint PDF of the system's state, which we close by means of a modified large-eddy-diffusivity (LED) closure. In contrast to the classical LED closure, the proposed closure accounts for advective transport of the PDF in the approximate temporal deconvolution of the integrodifferential equation. In addition, we introduce the generalized local linearization approximation for deriving a computable PDF equation in the form of a second-order partial differential equation. We demonstrate that the proposed closure and localization accurately describe the dynamics of the PDF in phase space for systems driven by noise with arbitrary autocorrelation time. We apply the proposed PDF method to analyze a set of Kramers equations driven by exponentially autocorrelated Gaussian colored noise to study nonlinear oscillators and the dynamics and stability of a power grid. Numerical experiments show the PDF method is accurate when the noise autocorrelation time is either much shorter or longer than the system's relaxation time, while the accuracy decreases as the ratio of the two timescales approaches unity. Similarly, the PDF method accuracy decreases with increasing standard deviation of the noise. PMID:27300844
Mill, Robert W; Brown, Guy J
2016-02-01
Visual displays in passive sonar based on the Fourier spectrogram are underpinned by detection models that rely on signal and noise power statistics. Time-frequency representations specialised for sparse signals achieve a sharper signal representation, either by reassigning signal energy based on temporal structure or by conveying temporal structure directly. However, temporal representations involve nonlinear transformations that make it difficult to reason about how they respond to additive noise. This article analyses the effect of noise on temporal fine structure measurements such as zero crossings and instantaneous frequency. Detectors that rely on zero crossing intervals, intervals and peak amplitudes, and instantaneous frequency measurements are developed, and evaluated for the detection of a sinusoid in Gaussian noise, using the power detector as a baseline. Detectors that rely on fine structure outperform the power detector under certain circumstances; and detectors that rely on both fine structure and power measurements are superior. Reassigned spectrograms assume that the statistics used to reassign energy are reliable, but the derivation of the fine structure detectors indicates the opposite. The article closes by proposing and demonstrating the concept of a doubly reassigned spectrogram, wherein temporal measurements are reassigned according to a statistical model of the noise background. PMID:26936571
Probabilistic density function method for nonlinear dynamical systems driven by colored noise
NASA Astrophysics Data System (ADS)
Barajas-Solano, David A.; Tartakovsky, Alexandre M.
2016-05-01
We present a probability density function (PDF) method for a system of nonlinear stochastic ordinary differential equations driven by colored noise. The method provides an integrodifferential equation for the temporal evolution of the joint PDF of the system's state, which we close by means of a modified large-eddy-diffusivity (LED) closure. In contrast to the classical LED closure, the proposed closure accounts for advective transport of the PDF in the approximate temporal deconvolution of the integrodifferential equation. In addition, we introduce the generalized local linearization approximation for deriving a computable PDF equation in the form of a second-order partial differential equation. We demonstrate that the proposed closure and localization accurately describe the dynamics of the PDF in phase space for systems driven by noise with arbitrary autocorrelation time. We apply the proposed PDF method to analyze a set of Kramers equations driven by exponentially autocorrelated Gaussian colored noise to study nonlinear oscillators and the dynamics and stability of a power grid. Numerical experiments show the PDF method is accurate when the noise autocorrelation time is either much shorter or longer than the system's relaxation time, while the accuracy decreases as the ratio of the two timescales approaches unity. Similarly, the PDF method accuracy decreases with increasing standard deviation of the noise.
Effects of the Noises' Statistics and Spectrum on Noise-Induced Phase Transitions
NASA Astrophysics Data System (ADS)
Deza, Roberto R.; Fuentes, Miguel A.; Wio, Horacio S.
2007-07-01
The study of the effect of the noises' statistics and spectrum on second-order, purely noise-induced phase transition (NIPT) is of wide interest: It is simplified if the noises are dynamically generated by means of stochastic differential equations driven by white noises, a well known case being that of Ornstein-Uhlenbeck noises with a self-correlation time τ whose effect on the NIPT phase diagram has been studied some time ago. Another case is when the stationary pdf is a (colored) q-Gaussian which, being a fat-tail distribution for q > 1 and a compact-support one for q < 1, allows for a controlled study of the effects of the departure from Gaussian statistics. As done with stochastic resonance and other phenomena, we exploit this tool to study—within a simple mean-field approximation—the combined effect on NIPT of the noises' statistics and spectrum. Even for relatively small τ, it is shown that whereas for fat-tail noise distributions counteract the effect of self-correlation, compact-support ones enhance it.
NASA Astrophysics Data System (ADS)
Li, Zhengyu; Zhang, Yichen; Wang, Xiangyu; Xu, Bingjie; Peng, Xiang; Guo, Hong
2016-01-01
Photon subtraction can enhance the performance of continuous-variable quantum key distribution (CV QKD). However, the enhancement effect will be reduced by the imperfections of practical devices, especially the limited efficiency of a single-photon detector. In this paper, we propose a non-Gaussian postselection method to emulate the photon substraction used in coherent-state CV QKD protocols. The virtual photon subtraction not only can avoid the complexity and imperfections of a practical photon-subtraction operation, which extends the secure transmission distance as the ideal case does, but also can be adjusted flexibly according to the channel parameters to optimize the performance. Furthermore, our preliminary tests on the information reconciliation suggest that in the low signal-to-noise ratio regime, the performance of reconciliating the postselected non-Gaussian data is better than that of the Gaussian data, which implies the feasibility of implementing this method practically.
Gaussian translation operator in a multilevel scheme
NASA Astrophysics Data System (ADS)
Hansen, Thorkild B.; Borries, Oscar
2015-08-01
A multilevel computation scheme for time-harmonic fields in three dimensions will be formulated with a new Gaussian translation operator that decays exponentially outside a circular cone centered on the line connecting the source and observation groups. This Gaussian translation operator is directional and diagonal with its sharpness determined by a beam parameter. When the beam parameter is set to zero, the Gaussian translation operator reduces to the standard fast multipole method translation operator. The directionality of the Gaussian translation operator makes it possible to reduce the number of plane waves required to achieve a given accuracy. The sampling rate can be determined straightforwardly to achieve any desired accuracy. The use of the computation scheme will be illustrated through a near-field scanning problem where the far-field pattern of a source is determined from near-field measurements with a known probe. Here the Gaussian translation operator improves the condition number of the matrix equation that determines the far-field pattern. The Gaussian translation operator can also be used when the probe pattern is known only in one hemisphere, as is common in practice. Also, the Gaussian translation operator will be used to solve the scattering problem of the perfectly conducting sphere.
Asymmetric Laguerre-Gaussian beams
NASA Astrophysics Data System (ADS)
Kovalev, A. A.; Kotlyar, V. V.; Porfirev, A. P.
2016-06-01
We introduce a family of asymmetric Laguerre-Gaussian (aLG) laser beams. The beams have been derived via a complex-valued shift of conventional LG beams in the Cartesian plane. While propagating in a uniform medium, the first bright ring of the aLG beam becomes less asymmetric and the energy is redistributed toward peripheral diffraction rings. The projection of the orbital angular momentum (OAM) onto the optical axis is calculated. The OAM is shown to grow quadratically with increasing asymmetry parameter of the aLG beam, which equals the ratio of the shift to the waist radius. Conditions for the OAM becoming equal to the topological charge have been derived. For aLG beams with zero radial index, we have deduced an expression to define the intensity maximum coordinates and shown the crescent-shaped intensity pattern to rotate during propagation. Results of the experimental generation and rotation of aLG beams agree well with theoretical predictions.
Random Copolymer: Gaussian Variational Approach
NASA Astrophysics Data System (ADS)
Moskalenko, A.; Kuznetsov, Yu. A.; Dawson, K. A.
1997-03-01
We study the phase transitions of a random copolymer chain with quenched disorder. We calculate the average over the quenched disorder in replica space and apply a Gaussian variational approach based on a generic quadratic trial Hamiltonian in terms of the correlation functions of monomer Fourier coordinates. This has the advantage that it allows us to incorporate fluctuations of the density, determined self-consistently, and to study collapse, phase separation transitions and the onset of the freezing transition within the same mean field theory. The effective free energy of the system is derived analytically and analyzed numerically in the one-step Parisi scheme. Such quantities as the radius of gyration, end-to-end distance or the average value of the overlap between different replicas are treated as observables and evaluated by introducing appropriate external fields to the Hamiltonian. As a result we obtain the phase diagram in terms of model parameters, scaling for the freezing transition and the dependence of correlation functions on the chain index.
Speckle noise in laser bar-code-scanner systems
NASA Astrophysics Data System (ADS)
Yu, Daoqi; Stern, Miklos; Katz, Joseph
1996-07-01
We present a theoretical model and its experimental verification for speckle-induced noise in laser-based bar-code-scanner systems. We measured the dependence of the signal-to-speckle-noise ratio on distance, spot size, and detector size. Analyses of the power spectra of both the speckle noise and of the measured surface profiles of different substrates suggest that the paper surface granularity can be approximated by a white Gaussian noise process, thus confirming the assumption of the theoretical model.
NASA Astrophysics Data System (ADS)
Song, Kechen; Yan, Yunhui
2013-11-01
Automatic recognition method for hot-rolled steel strip surface defects is important to the steel surface inspection system. In order to improve the recognition rate, a new, simple, yet robust feature descriptor against noise named the adjacent evaluation completed local binary patterns (AECLBPs) is proposed for defect recognition. In the proposed approach, an adjacent evaluation window which is around the neighbor is constructed to modify the threshold scheme of the completed local binary pattern (CLBP). Experimental results demonstrate that the proposed approach presents the performance of defect recognition under the influence of the feature variations of the intra-class changes, the illumination and grayscale changes. Even in the toughest situation with additive Gaussian noise, the AECLBP can still achieve the moderate recognition accuracy. In addition, the strategy of using adjacent evaluation window can also be used in other methods of local binary pattern (LBP) variants.
NASA Technical Reports Server (NTRS)
Misoda, J.; Magliozzi, B.
1973-01-01
The development is described of improved, low noise level fan and pump concepts for the space shuttle. In addition, a set of noise design criteria for small fans and pumps was derived. The concepts and criteria were created by obtaining Apollo hardware test data to correlate and modify existing noise estimating procedures. A set of space shuttle selection criteria was used to determine preliminary fan and pump concepts. These concepts were tested and modified to obtain noise sources and characteristics which yield the design criteria and quiet, efficient space shuttle fan and pump concepts.
Equilateral non-Gaussianity from heavy fields
Gong, Jinn-Ouk; Pi, Shi; Sasaki, Misao E-mail: spi@apctp.org
2013-11-01
The effect of self-interactions of heavy scalar fields during inflation on the primordial non-Gaussianity is studied. We take a specific constant-turn quasi-single field inflation as an example. We derive an effective theory with emphasis on non-linear self-interactions of heavy fields and calculate the corresponding non-Gaussianity, which is of equilateral type and can be as relevant as those computed previously in the literature. We also derive the non-Gaussianity by directly using the in-in formalism, and verify the equivalence of these two approaches.
Gaussian Mixture Model of Heart Rate Variability
Costa, Tommaso; Boccignone, Giuseppe; Ferraro, Mario
2012-01-01
Heart rate variability (HRV) is an important measure of sympathetic and parasympathetic functions of the autonomic nervous system and a key indicator of cardiovascular condition. This paper proposes a novel method to investigate HRV, namely by modelling it as a linear combination of Gaussians. Results show that three Gaussians are enough to describe the stationary statistics of heart variability and to provide a straightforward interpretation of the HRV power spectrum. Comparisons have been made also with synthetic data generated from different physiologically based models showing the plausibility of the Gaussian mixture parameters. PMID:22666386
Quark and Lepton Masses from Gaussian Landscapes
Hall, Lawrence J.; Salem, Michael P.; Watari, Taizan
2008-04-11
The flavor structure of the standard model (SM) might arise from random selection on a landscape. We propose a class of simple models, 'Gaussian landscapes', where Yukawa couplings derive from overlap integrals of Gaussian wave functions on extra-dimensions. Statistics of vacua are generated by scanning the peak positions of these zero-modes, giving probability distributions for all flavor observables. Gaussian landscapes can account for all observed flavor patterns with few free parameters. Although they give broad probability distributions, the predictions are correlated and accounting for measured parameters sharpens the distributions of future neutrino measurements.
Non-Gaussianity from isocurvature perturbations
Kawasaki, Masahiro; Nakayama, Kazunori; Sekiguchi, Toyokazu; Suyama, Teruaki; Takahashi, Fuminobu E-mail: nakayama@icrr.u-tokyo.ac.jp E-mail: suyama@icrr.u-tokyo.ac.jp
2008-11-15
We develop a formalism for studying non-Gaussianity in both curvature and isocurvature perturbations. It is shown that non-Gaussianity in the isocurvature perturbation between dark matter and photons leaves distinct signatures in the cosmic microwave background temperature fluctuations, which may be confirmed in future experiments, or possibly even in the currently available observational data. As an explicit example, we consider the quantum chromodynamics axion and show that it can actually induce sizable non-Gaussianity for the inflationary scale, H{sub inf} = O(10{sup 9}-10{sup 11}) GeV.
Quantum bit commitment under Gaussian constraints
NASA Astrophysics Data System (ADS)
Mandilara, Aikaterini; Cerf, Nicolas J.
2012-06-01
Quantum bit commitment has long been known to be impossible. Nevertheless, just as in the classical case, imposing certain constraints on the power of the parties may enable the construction of asymptotically secure protocols. Here, we introduce a quantum bit commitment protocol and prove that it is asymptotically secure if cheating is restricted to Gaussian operations. This protocol exploits continuous-variable quantum optical carriers, for which such a Gaussian constraint is experimentally relevant as the high optical nonlinearity needed to effect deterministic non-Gaussian cheating is inaccessible.
Gaussian measures of entanglement versus negativities: Ordering of two-mode Gaussian states
Adesso, Gerardo; Illuminati, Fabrizio
2005-09-15
We study the entanglement of general (pure or mixed) two-mode Gaussian states of continuous-variable systems by comparing the two available classes of computable measures of entanglement: entropy-inspired Gaussian convex-roof measures and positive partial transposition-inspired measures (negativity and logarithmic negativity). We first review the formalism of Gaussian measures of entanglement, adopting the framework introduced in M. M. Wolf et al., Phys. Rev. A 69, 052320 (2004), where the Gaussian entanglement of formation was defined. We compute explicitly Gaussian measures of entanglement for two important families of nonsymmetric two-mode Gaussian state: namely, the states of extremal (maximal and minimal) negativities at fixed global and local purities, introduced in G. Adesso et al., Phys. Rev. Lett. 92, 087901 (2004). This analysis allows us to compare the different orderings induced on the set of entangled two-mode Gaussian states by the negativities and by the Gaussian measures of entanglement. We find that in a certain range of values of the global and local purities (characterizing the covariance matrix of the corresponding extremal states), states of minimum negativity can have more Gaussian entanglement of formation than states of maximum negativity. Consequently, Gaussian measures and negativities are definitely inequivalent measures of entanglement on nonsymmetric two-mode Gaussian states, even when restricted to a class of extremal states. On the other hand, the two families of entanglement measures are completely equivalent on symmetric states, for which the Gaussian entanglement of formation coincides with the true entanglement of formation. Finally, we show that the inequivalence between the two families of continuous-variable entanglement measures is somehow limited. Namely, we rigorously prove that, at fixed negativities, the Gaussian measures of entanglement are bounded from below. Moreover, we provide some strong evidence suggesting that they
Low-noise macroscopic twin beams
NASA Astrophysics Data System (ADS)
Iskhakov, Timur Sh.; Usenko, Vladyslav C.; Filip, Radim; Chekhova, Maria V.; Leuchs, Gerd
2016-04-01
Applying a multiphoton-subtraction technique to the two-color macroscopic squeezed vacuum state of light generated via high-gain parametric down-conversion we conditionally prepare a different state of light: bright multimode low-noise twin beams. A lower noise in the sum of the photon numbers opens a possibility to encode information into this variable while keeping the nonclassical character of the state. The obtained results demonstrate up to eightfold suppression of noise in each beam while preserving and even moderately improving the nonclassical photon-number correlations between the beams. The prepared low-noise macroscopic state, containing up to 2000 photons per mode, is not among the Gaussian states achievable through nonlinear optical processes. Apart from that, we suggest a method for measuring quantum efficiency, which is based on the Fano factor measurement. The proposed technique substantially improves the usefulness of twin beams for quantum communication and metrology.
Xiao, Zhu; Havyarimana, Vincent; Li, Tong; Wang, Dong
2016-01-01
In this paper, a novel nonlinear framework of smoothing method, non-Gaussian delayed particle smoother (nGDPS), is proposed, which enables vehicle state estimation (VSE) with high accuracy taking into account the non-Gaussianity of the measurement and process noises. Within the proposed method, the multivariate Student’s t-distribution is adopted in order to compute the probability distribution function (PDF) related to the process and measurement noises, which are assumed to be non-Gaussian distributed. A computation approach based on Ensemble Kalman Filter (EnKF) is designed to cope with the mean and the covariance matrix of the proposal non-Gaussian distribution. A delayed Gibbs sampling algorithm, which incorporates smoothing of the sampled trajectories over a fixed-delay, is proposed to deal with the sample degeneracy of particles. The performance is investigated based on the real-world data, which is collected by low-cost on-board vehicle sensors. The comparison study based on the real-world experiments and the statistical analysis demonstrates that the proposed nGDPS has significant improvement on the vehicle state accuracy and outperforms the existing filtering and smoothing methods. PMID:27187405
Deviation of 1/ f voltage fluctuations from scale-similar Gaussian behavior
NASA Astrophysics Data System (ADS)
Nelkin, Mark; Tremblay, A.-M. S.
1981-06-01
Recent measurements on thin metal films suggest a pulse model of resistance fluctuations in which scale similarity and power law spectra are only approximate. We show that such a pulse model is consistent with stationary Gaussian resistance fluctuations. This is to be contrasted with the phenomenological behavior, of fluctuations near phase transitions and in turbulent fluids where the fluctuations are non-Gaussian, but exhibit scale similarity of deep physical origin. We then critically examine other tests of the Gaussian behavior of the fluctuating voltage V(t) across a resistor. These include the relaxation of the conditional mean < V(t)¦V(0)= V 0>, and the spectrum of V 2( t). We consider also the question of time reversal invariance. We further ask under what conditions 1/f noise can be measured through fluctuations of the Johnson noise power with no applied voltage. We emphasize that this possibility, suggested and observed by Voss and Clarke, requires that V(t) contain a non-Gaussian component.
Xiao, Zhu; Havyarimana, Vincent; Li, Tong; Wang, Dong
2016-01-01
In this paper, a novel nonlinear framework of smoothing method, non-Gaussian delayed particle smoother (nGDPS), is proposed, which enables vehicle state estimation (VSE) with high accuracy taking into account the non-Gaussianity of the measurement and process noises. Within the proposed method, the multivariate Student's t-distribution is adopted in order to compute the probability distribution function (PDF) related to the process and measurement noises, which are assumed to be non-Gaussian distributed. A computation approach based on Ensemble Kalman Filter (EnKF) is designed to cope with the mean and the covariance matrix of the proposal non-Gaussian distribution. A delayed Gibbs sampling algorithm, which incorporates smoothing of the sampled trajectories over a fixed-delay, is proposed to deal with the sample degeneracy of particles. The performance is investigated based on the real-world data, which is collected by low-cost on-board vehicle sensors. The comparison study based on the real-world experiments and the statistical analysis demonstrates that the proposed nGDPS has significant improvement on the vehicle state accuracy and outperforms the existing filtering and smoothing methods. PMID:27187405
NASA Astrophysics Data System (ADS)
Zhou, Xiang; Baird, John P.; Arnold, John F.
1999-02-01
We analyze the effect of image noise on the estimation of fringe orientation in principle and interpret the application of a texture-analysis technique to the problem of estimating fringe orientation in interferograms. The gradient of a Gaussian filter and neighboring-direction averaging are shown to meet the requirements of fringe-orientation estimation by reduction of the effects of low-frequency background and contrast variances as well as high-frequency random image noise. The technique also improves inaccurate orientation estimation at low-modulation points, such as fringe centers and broken fringes. Experiments demonstrate that the scales of the Gaussian gradient filter and the direction averaging should be chosen according to the fringe spacings of the interferograms.
Advanced Study for Active Noise Control in Aircraft (ASANCA)
NASA Technical Reports Server (NTRS)
Borchers, Ingo U.; Emborg, Urban; Sollo, Antonio; Waterman, Elly H.; Paillard, Jacques; Larsen, Peter N.; Venet, Gerard; Goeransson, Peter; Martin, Vincent
1992-01-01
Aircraft interior noise and vibration measurements are included in this paper from ground and flight tests. In addition, related initial noise calculations with and without active noise control are conducted. The results obtained to date indicate that active noise control may be an effective means for reducing the critical low frequency aircraft noise.
Single-electron thermal noise.
Nishiguchi, Katsuhiko; Ono, Yukinori; Fujiwara, Akira
2014-07-11
We report the observation of thermal noise in the motion of single electrons in an ultimately small dynamic random access memory (DRAM). The nanometer-scale transistors that compose the DRAM resolve the thermal noise in single-electron motion. A complete set of fundamental tests conducted on this single-electron thermal noise shows that the noise perfectly follows all the aspects predicted by statistical mechanics, which include the occupation probability, the law of equipartition, a detailed balance, and the law of kT/C. In addition, the counting statistics on the directional motion (i.e., the current) of the single-electron thermal noise indicate that the individual electron motion follows the Poisson process, as it does in shot noise. PMID:25093235
Aerodynamic Noise Generated by Shinkansen Cars
NASA Astrophysics Data System (ADS)
KITAGAWA, T.; NAGAKURA, K.
2000-03-01
The noise value (A -weighted sound pressure level, SLOW) generated by Shinkansen trains, now running at 220-300 km/h, should be less than 75 dB(A) at the trackside. Shinkansen noise, such as rolling noise, concrete support structure noise, and aerodynamic noise are generated by various parts of Shinkansen trains. Among these aerodynamic noise is important because it is the major contribution to the noise generated by the coaches running at high speed. In order to reduce the aerodynamic noise, a number of improvements to coaches have been made. As a result, the aerodynamic noise has been reduced, but it still remains significant. In addition, some aerodynamic noise generated from the lower parts of cars remains. In order to investigate the contributions of these noises, a method of analyzing Shinkansen noise has been developed and applied to the measured data of Shinkansen noise at speeds between 120 and 315 km/h. As a result, the following conclusions have been drawn: (1) Aerodynamic noise generated from the upper parts of cars was reduced considerably by smoothing car surfaces. (2) Aerodynamic noise generated from the lower parts of cars has a major influence upon the wayside noise.
Near-unit-fidelity entanglement distribution scheme using Gaussian communication
Praxmeyer, Ludmila; Loock, Peter van
2010-06-15
We show how to distribute with percentage success probabilities almost perfectly entangled qubit memory pairs over repeater channel segments of the order of the optical attenuation distance. In addition to some weak, dispersive light-matter interactions, only Gaussian state transmissions and measurements are needed for this scheme. Our protocol outperforms the existing coherent-state-based schemes for entanglement distribution, even those using error-free non-Gaussian measurements. This is achieved through two innovations: First, optical squeezed states are utilized instead of coherent states. Second, the amplitudes of the bright signal pulses are reamplified at each repeater station. This latter variation is a strategy reminiscent of classical repeaters and would be impossible in single-photon-based schemes.
Performance of some block codes on a Gaussian channel
NASA Technical Reports Server (NTRS)
Baumert, L. D.; Mceliece, R. J.
1975-01-01
A technique proposed by Chase (1972) is used to evaluate the performance of several fairly long binary block codes on a wideband additive Gaussian channel. Considerations leading to the use of Chase's technique are discussed. Chase's concepts are first applied to the most powerful practical class of binary codes, the BCH codes with Berlekamp's (1972) decoding algorithm. Chase's algorithm is then described along with proposed selection of candidate codes. Results are presented of applying Chase's algorithm to four binary codes: (23, 12) Golay code, (32, 16) second-order Reed-Muller code, (63, 36) 5-error correcting BCH code, and (95, 39) 9-error correcting shortened BCH code. It is concluded that there are many block codes of length not exceeding 100 with extremely attractive maximum likelihood decoding performance on a Gaussian channel. BCH codes decoded via Berlekamp's binary decoding algorithm and Chase's idea are close to being practical competitors to short-constraint length convolutional codes with Viterbi decoding.
Uncertainty, entropy, and non-Gaussianity for mixed states
NASA Astrophysics Data System (ADS)
Mandilara, Aikaterini; Karpov, Evgueni; Cerf, Nicolas J.
2010-06-01
In the space of mixed states the Schrödinger-Robertson uncertainty relation holds though it can never be saturated. Two tight extensions of this relation in the space of mixed states exist; one proposed by Dodonov and Man'ko, where the lower limit on the uncertainty depends on the purity of the state, and another where the uncertainty is bounded by the von Neumann entropy of the state proposed by Bastiaans. Driven by the needs that have emerged in the field of quantum information, in a recent work we have extended the puritybounded uncertainty relation by adding an additional parameter characterizing the state, namely its degree of non-Gaussianity. In this work we alternatively present a extension of the entropy-bounded uncertainty relation. The common points and differences between the two extensions of the uncertainty relation help us to draw more general conclusions concerning the bounds on the non-Gaussianity of mixed states.
Stability criterion for Gaussian pulse propagation through negative index materials
Joseph, Ancemma; Porsezian, K.
2010-02-15
We analyze the dynamics of propagation of a Gaussian light pulse through a medium having a negative index of refraction employing the recently reported projection operator technique. The governing modified nonlinear Schroedinger equation, obtained by taking into account the Drude dispersive model, is expressed in terms of the parameters of Gaussian pulse, called collective variables, such as width, amplitude, chirp, and phase. This approach yields a system of ordinary differential equations for the evolution of all the pulse parameters. We demonstrate the dependence of stability of the fixed-point solutions of these ordinary differential equations on the linear and nonlinear dispersion parameters. In addition, we validate the analytical approach numerically utilizing the method of split-step Fourier transform.
Li, Derong; Lv, Xiaohua; Bowlan, Pamela; Du, Rui; Zeng, Shaoqun; Luo, Qingming
2009-09-14
The evolution of the frequency chirp of a laser pulse inside a classical pulse compressor is very different for plane waves and Gaussian beams, although after propagating through the last (4th) dispersive element, the two models give the same results. In this paper, we have analyzed the evolution of the frequency chirp of Gaussian pulses and beams using a method which directly obtains the spectral phase acquired by the compressor. We found the spatiotemporal couplings in the phase to be the fundamental reason for the difference in the frequency chirp acquired by a Gaussian beam and a plane wave. When the Gaussian beam propagates, an additional frequency chirp will be introduced if any spatiotemporal couplings (i.e. angular dispersion, spatial chirp or pulse front tilt) are present. However, if there are no couplings present, the chirp of the Gaussian beam is the same as that of a plane wave. When the Gaussian beam is well collimated, the introduced frequency chirp predicted by the plane wave and Gaussian beam models are in closer agreement. This work improves our understanding of pulse compressors and should be helpful for optimizing dispersion compensation schemes in many applications of femtosecond laser pulses. PMID:19770925
Extracting features of Gaussian self-similar stochastic processes via the Bandt-Pompe approach.
Rosso, O A; Zunino, L; Pérez, D G; Figliola, A; Larrondo, H A; Garavaglia, M; Martín, M T; Plastino, A
2007-12-01
By recourse to appropriate information theory quantifiers (normalized Shannon entropy and Martín-Plastino-Rosso intensive statistical complexity measure), we revisit the characterization of Gaussian self-similar stochastic processes from a Bandt-Pompe viewpoint. We show that the ensuing approach exhibits considerable advantages with respect to other treatments. In particular, clear quantifiers gaps are found in the transition between the continuous processes and their associated noises. PMID:18233821
Stochastic bifurcation in a model of love with colored noise
NASA Astrophysics Data System (ADS)
Yue, Xiaokui; Dai, Honghua; Yuan, Jianping
2015-07-01
In this paper, we wish to examine the stochastic bifurcation induced by multiplicative Gaussian colored noise in a dynamical model of love where the random factor is used to describe the complexity and unpredictability of psychological systems. First, the dynamics in deterministic love-triangle model are considered briefly including equilibrium points and their stability, chaotic behaviors and chaotic attractors. Then, the influences of Gaussian colored noise with different parameters are explored such as the phase plots, top Lyapunov exponents, stationary probability density function (PDF) and stochastic bifurcation. The stochastic P-bifurcation through a qualitative change of the stationary PDF will be observed and bifurcation diagram on parameter plane of correlation time and noise intensity is presented to find the bifurcation behaviors in detail. Finally, the top Lyapunov exponent is computed to determine the D-bifurcation when the noise intensity achieves to a critical value. By comparison, we find there is no connection between two kinds of stochastic bifurcation.
NASA Technical Reports Server (NTRS)
Mashiku, Alinda; Garrison, James L.; Carpenter, J. Russell
2012-01-01
The tracking of space objects requires frequent and accurate monitoring for collision avoidance. As even collision events with very low probability are important, accurate prediction of collisions require the representation of the full probability density function (PDF) of the random orbit state. Through representing the full PDF of the orbit state for orbit maintenance and collision avoidance, we can take advantage of the statistical information present in the heavy tailed distributions, more accurately representing the orbit states with low probability. The classical methods of orbit determination (i.e. Kalman Filter and its derivatives) provide state estimates based on only the second moments of the state and measurement errors that are captured by assuming a Gaussian distribution. Although the measurement errors can be accurately assumed to have a Gaussian distribution, errors with a non-Gaussian distribution could arise during propagation between observations. Moreover, unmodeled dynamics in the orbit model could introduce non-Gaussian errors into the process noise. A Particle Filter (PF) is proposed as a nonlinear filtering technique that is capable of propagating and estimating a more complete representation of the state distribution as an accurate approximation of a full PDF. The PF uses Monte Carlo runs to generate particles that approximate the full PDF representation. The PF is applied in the estimation and propagation of a highly eccentric orbit and the results are compared to the Extended Kalman Filter and Splitting Gaussian Mixture algorithms to demonstrate its proficiency.
Galaxy bias and primordial non-Gaussianity
NASA Astrophysics Data System (ADS)
Assassi, Valentin; Baumann, Daniel; Schmidt, Fabian
2015-12-01
We present a systematic study of galaxy biasing in the presence of primordial non-Gaussianity. For a large class of non-Gaussian initial conditions, we define a general bias expansion and prove that it is closed under renormalization, thereby showing that the basis of operators in the expansion is complete. We then study the effects of primordial non-Gaussianity on the statistics of galaxies. We show that the equivalence principle enforces a relation between the scale-dependent bias in the galaxy power spectrum and that in the dipolar part of the bispectrum. This provides a powerful consistency check to confirm the primordial origin of any observed scale-dependent bias. Finally, we also discuss the imprints of anisotropic non-Gaussianity as motivated by recent studies of higher-spin fields during inflation.
Why Should We Pivot in Gaussian Elimination?
ERIC Educational Resources Information Center
Rozema, Edward
1988-01-01
The article discusses the use of computers to teacher college level mathematics. In particular, the Gaussian elimination procedure for solving a system of n linear equations in n unknowns, using a computer, is examined. (PK)
Improved Gaussian beam-scattering algorithm.
Lock, J A
1995-01-20
The localized model of the beam-shape coefficients for Gaussian beam-scattering theory by a spherical particle provides a great simplification in the numerical implementation of the theory. We derive an alternative form for the localized coefficients that is more convenient for computer computations and that provides physical insight into the details of the scattering process. We construct a FORTRAN program for Gaussian beam scattering with the localized model and compare its computer run time on a personal computer with that of a traditional Mie scattering program and with three other published methods for computing Gaussian beam scattering. We show that the analytical form of the beam-shape coefficients makes evident the fact that the excitation rate of morphology-dependent resonances is greatly enhanced for far off-axis incidence of the Gaussian beam. PMID:20963151
Improved Gaussian Beam-Scattering Algorithm
NASA Technical Reports Server (NTRS)
Lock, James A.
1995-01-01
The localized model of the beam-shape coefficients for Gaussian beam-scattering theory by a spherical particle provides a great simplification in the numerical implementation of the theory. We derive an alternative form for the localized coefficients that is more convenient for computer computations and that provides physical insight into the details of the scattering process. We construct a FORTRAN program for Gaussian beam scattering with the localized model and compare its computer run time on a personal computer with that of a traditional Mie scattering program and with three other published methods for computing Gaussian beam scattering. We show that the analytical form of the beam-shape coefficients makes evident the fact that the excitation rate of morphology-dependent resonances is greatly enhanced for far off-axis incidence of the Gaussian beam.
Optimal cloning of mixed Gaussian states
Guta, Madalin; Matsumoto, Keiji
2006-09-15
We construct the optimal one to two cloning transformation for the family of displaced thermal equilibrium states of a harmonic oscillator, with a fixed and known temperature. The transformation is Gaussian and it is optimal with respect to the figure of merit based on the joint output state and norm distance. The proof of the result is based on the equivalence between the optimal cloning problem and that of optimal amplification of Gaussian states which is then reduced to an optimization problem for diagonal states of a quantum oscillator. A key concept in finding the optimum is that of stochastic ordering which plays a similar role in the purely classical problem of Gaussian cloning. The result is then extended to the case of n to m cloning of mixed Gaussian states.
Gaussian Multiplicative Chaos for Symmetric Isotropic Matrices
NASA Astrophysics Data System (ADS)
Chevillard, Laurent; Rhodes, Rémi; Vargas, Vincent
2013-02-01
Motivated by isotropic fully developed turbulence, we define a theory of symmetric matrix valued isotropic Gaussian multiplicative chaos. Our construction extends the scalar theory developed by J.P. Kahane in 1985.
Multi-resolution low-power Gaussian filtering by reconfigurable focal-plane binning
NASA Astrophysics Data System (ADS)
Fernández-Berni, J.; Carmona-Galán, R.; Pozas-Flores, F.; Zarándy, Á.; Rodríguez-Vázquez, Á.
2011-05-01
Gaussian filtering is a basic tool for image processing. Noise reduction, scale-space generation or edge detection are examples of tasks where different Gaussian filters can be successfully utilized. However, their implementation in a conventional digital processor by applying a convolution kernel throughout the image is quite inefficient. Not only the value of every single pixel is taken into consideration sucessively, but also contributions from their neighbors need to be taken into account. Processing of the frame is serialized and memory access is intensive and recurrent. The result is a low operation speed or, alternatively, a high power consumption. This inefficiency is specially remarkable for filters with large variance, as the kernel size increases significantly. In this paper, a different approach to achieve Gaussian filtering is proposed. It is oriented to applications with very low power budgets. The key point is a reconfigurable focal-plane binning. Pixels are grouped according to the targeted resolution by means of a division grid. Then, two consecutive shifts of this grid in opposite directions carry out the spread of information to the neighborhood of each pixel in parallel. The outcome is equivalent to the application of a 3×3 binomial filter kernel, which in turns is a good approximation of a Gaussian filter, on the original image. The variance of the closest Gaussian filter is around 0.5. By repeating the operation, Gaussian filters with larger variances can be achieved. A rough estimation of the necessary energy for each repetition until reaching the desired filter is below 20nJ for a QCIF-size array. Finally, experimental results of a QCIF proofof- concept focal-plane array manufactured in 0.35μm CMOS technology are presented. A maximum RMSE of only 1.2% is obtained by the on-chip Gaussian filtering with respect to the corresponding equivalent ideal filter implemented off-chip.
Quantum key distribution using gaussian-modulated coherent states
NASA Astrophysics Data System (ADS)
Grosshans, Frédéric; Van Assche, Gilles; Wenger, Jérôme; Brouri, Rosa; Cerf, Nicolas J.; Grangier, Philippe
2003-01-01
Quantum continuous variables are being explored as an alternative means to implement quantum key distribution, which is usually based on single photon counting. The former approach is potentially advantageous because it should enable higher key distribution rates. Here we propose and experimentally demonstrate a quantum key distribution protocol based on the transmission of gaussian-modulated coherent states (consisting of laser pulses containing a few hundred photons) and shot-noise-limited homodyne detection; squeezed or entangled beams are not required. Complete secret key extraction is achieved using a reverse reconciliation technique followed by privacy amplification. The reverse reconciliation technique is in principle secure for any value of the line transmission, against gaussian individual attacks based on entanglement and quantum memories. Our table-top experiment yields a net key transmission rate of about 1.7 megabits per second for a loss-free line, and 75 kilobits per second for a line with losses of 3.1dB. We anticipate that the scheme should remain effective for lines with higher losses, particularly because the present limitations are essentially technical, so that significant margin for improvement is available on both the hardware and software.
Quantum key distribution using gaussian-modulated coherent states.
Grosshans, Frédéric; Van Assche, Gilles; Wenger, Jérôme; Brouri, Rosa; Cerf, Nicolas J; Grangier, Philippe
2003-01-16
Quantum continuous variables are being explored as an alternative means to implement quantum key distribution, which is usually based on single photon counting. The former approach is potentially advantageous because it should enable higher key distribution rates. Here we propose and experimentally demonstrate a quantum key distribution protocol based on the transmission of gaussian-modulated coherent states (consisting of laser pulses containing a few hundred photons) and shot-noise-limited homodyne detection; squeezed or entangled beams are not required. Complete secret key extraction is achieved using a reverse reconciliation technique followed by privacy amplification. The reverse reconciliation technique is in principle secure for any value of the line transmission, against gaussian individual attacks based on entanglement and quantum memories. Our table-top experiment yields a net key transmission rate of about 1.7 megabits per second for a loss-free line, and 75 kilobits per second for a line with losses of 3.1 dB. We anticipate that the scheme should remain effective for lines with higher losses, particularly because the present limitations are essentially technical, so that significant margin for improvement is available on both the hardware and software. PMID:12529636
Spike Triggered Covariance in Strongly Correlated Gaussian Stimuli
Aljadeff, Johnatan; Segev, Ronen; Berry, Michael J.; Sharpee, Tatyana O.
2013-01-01
Many biological systems perform computations on inputs that have very large dimensionality. Determining the relevant input combinations for a particular computation is often key to understanding its function. A common way to find the relevant input dimensions is to examine the difference in variance between the input distribution and the distribution of inputs associated with certain outputs. In systems neuroscience, the corresponding method is known as spike-triggered covariance (STC). This method has been highly successful in characterizing relevant input dimensions for neurons in a variety of sensory systems. So far, most studies used the STC method with weakly correlated Gaussian inputs. However, it is also important to use this method with inputs that have long range correlations typical of the natural sensory environment. In such cases, the stimulus covariance matrix has one (or more) outstanding eigenvalues that cannot be easily equalized because of sampling variability. Such outstanding modes interfere with analyses of statistical significance of candidate input dimensions that modulate neuronal outputs. In many cases, these modes obscure the significant dimensions. We show that the sensitivity of the STC method in the regime of strongly correlated inputs can be improved by an order of magnitude or more. This can be done by evaluating the significance of dimensions in the subspace orthogonal to the outstanding mode(s). Analyzing the responses of retinal ganglion cells probed with Gaussian noise, we find that taking into account outstanding modes is crucial for recovering relevant input dimensions for these neurons. PMID:24039563
From weak lensing to non-Gaussianity via Minkowski functionals
NASA Astrophysics Data System (ADS)
Munshi, Dipak; van Waerbeke, Ludovic; Smidt, Joseph; Coles, Peter
2012-01-01
We present a new harmonic-domain-based approach for extracting morphological information, in the form of Minkowski functionals (MFs), from weak-lensing convergence maps. Using a perturbative expansion of the MFs, which is expected to be valid for the range of angular scales probed by most current weak-lensing surveys, we show that the study of three generalized skewness parameters is equivalent to the study of the three MFs defined in 2D. We then extend these skewness parameters to three associated skew spectra which carry more information about the convergence bispectrum than their one-point counterparts. We discuss various issues such as noise and incomplete sky coverage in the context of estimation of these skew spectra from realistic data. Our technique provides an alternative to the pixel-space approaches typically used in the estimation of MFs, and it can be particularly useful in the presence of masks with non-trivial topology. Analytical modelling of weak-lensing statistics relies on an accurate modelling of the statistics of the underlying density distribution. We apply three different formalisms to model the underlying dark matter bispectrum: the hierarchical ansatz, halo model and a fitting function based on numerical simulations; MFs resulting from each of these formalisms are computed and compared. We investigate the extent to which late-time gravity-induced non-Gaussianity (to which weak lensing is primarily sensitive) can be separated from primordial non-Gaussianity and how this separation depends on source redshift and angular scale.
Power spectrum and non-Gaussianities in anisotropic inflation
Dey, Anindya; Kovetz, Ely D.; Paban, Sonia E-mail: elykovetz@gmail.com
2014-06-01
We study the planar regime of curvature perturbations for single field inflationary models in an axially symmetric Bianchi I background. In a theory with standard scalar field action, the power spectrum for such modes has a pole as the planarity parameter goes to zero. We show that constraints from back reaction lead to a strong lower bound on the planarity parameter for high-momentum planar modes and use this bound to calculate the signal-to-noise ratio of the anisotropic power spectrum in the CMB, which in turn places an upper bound on the Hubble scale during inflation allowed in our model. We find that non-Gaussianities for these planar modes are enhanced for the flattened triangle and the squeezed triangle configurations, but show that the estimated values of the f{sub NL} parameters remain well below the experimental bounds from the CMB for generic planar modes (other, more promising signatures are also discussed). For a standard action, f{sub NL} from the squeezed configuration turns out to be larger compared to that from the flattened triangle configuration in the planar regime. However, in a theory with higher derivative operators, non-Gaussianities from the flattened triangle can become larger than the squeezed configuration in a certain limit of the planarity parameter.
Generating functionals and Gaussian approximations for interruptible delay reactions
NASA Astrophysics Data System (ADS)
Brett, Tobias; Galla, Tobias
2015-10-01
We develop a generating functional description of the dynamics of non-Markovian individual-based systems in which delay reactions can be terminated before completion. This generalizes previous work in which a path-integral approach was applied to dynamics in which delay reactions complete with certainty. We construct a more widely applicable theory, and from it we derive Gaussian approximations of the dynamics, valid in the limit of large, but finite, population sizes. As an application of our theory we study predator-prey models with delay dynamics due to gestation or lag periods to reach the reproductive age. In particular, we focus on the effects of delay on noise-induced cycles.
NASA Astrophysics Data System (ADS)
Niesl, G.; Laudien, E.
1994-09-01
Compared to fixed wing aircraft, helicopter interior noise is higher, and subjectively more annoying. This is mainly due to discrete frequencies by the main transmission system, and also from other components like main and tail rotor, engines, or cooling fans. Up to now, mainly passive measures have been used for interior noise reduction. Despite intensive experimental and theoretical investigation to improve acoustic treatment, their weight penalties remain high especially in the low frequency range. Here, active noise control offers additional capacities without excessive weight efforts. Loud-speaker based systems are sufficiently well developed for implementing a prototype system in the helicopter. Two other principles are in development: active panel control which introduces mechanical actuators to excite the cabin walls, and active control of gearbox struts with actuators in the load path between gearbox and fuselage.
NASA Astrophysics Data System (ADS)
Yoo, Youngjin; Lee, SeongDeok; Choe, Wonhee; Kim, Chang-Yong
2007-02-01
Digital images captured from CMOS image sensors suffer Gaussian noise and impulsive noise. To efficiently reduce the noise in Image Signal Processor (ISP), we analyze noise feature for imaging pipeline of ISP where noise reduction algorithm is performed. The Gaussian noise reduction and impulsive noise reduction method are proposed for proper ISP implementation in Bayer domain. The proposed method takes advantage of the analyzed noise feature to calculate noise reduction filter coefficients. Thus, noise is adaptively reduced according to the scene environment. Since noise is amplified and characteristic of noise varies while the image sensor signal undergoes several image processing steps, it is better to remove noise in earlier stage on imaging pipeline of ISP. Thus, noise reduction is carried out in Bayer domain on imaging pipeline of ISP. The method is tested on imaging pipeline of ISP and images captured from Samsung 2M CMOS image sensor test module. The experimental results show that the proposed method removes noise while effectively preserves edges.
Gaussian maximally multipartite-entangled states
Facchi, Paolo; Florio, Giuseppe; Pascazio, Saverio; Lupo, Cosmo; Mancini, Stefano
2009-12-15
We study maximally multipartite-entangled states in the context of Gaussian continuous variable quantum systems. By considering multimode Gaussian states with constrained energy, we show that perfect maximally multipartite-entangled states, which exhibit the maximum amount of bipartite entanglement for all bipartitions, only exist for systems containing n=2 or 3 modes. We further numerically investigate the structure of these states and their frustration for n<=7.
Gaussian-Beam Laser-Resonator Program
NASA Technical Reports Server (NTRS)
Cross, Patricia L.; Bair, Clayton H.; Barnes, Norman
1989-01-01
Gaussian Beam Laser Resonator Program models laser resonators by use of Gaussian-beam-propagation techniques. Used to determine radii of beams as functions of position in laser resonators. Algorithm used in program has three major components. First, ray-transfer matrix for laser resonator must be calculated. Next, initial parameters of beam calculated. Finally, propagation of beam through optical elements computed. Written in Microsoft FORTRAN (Version 4.01).
Ultrasonic transducer with Gaussian radial pressure distribution
NASA Technical Reports Server (NTRS)
Claus, R. O.; Zerwekh, P. S. (Inventor)
1984-01-01
An ultrasonic transducer that produces an output that is a symmetrical function comprises a piezoelectric crystal with several concentric ring electrodes on one side of the crystal. A resistor network applies different amplitudes of an ac source to each of the several electrodes. A plot of the different amplitudes from the outermost electrode to the innermost electrode is the first half of a Gaussian function. Consequently, the output of the crystal from the side opposite the electrodes has a Gaussian profile.
Noise Prediction for Maneuvering Rotorcraft
NASA Technical Reports Server (NTRS)
Brentner, Kenneth S.; Jones, Henry E.
2000-01-01
This paper presents the initial work toward first-principles noise prediction for maneuvering rotors. Both the aeromechanical and acoustics aspects of the maneuver noise problem are discussed. The comprehensive analysis code, CAMRAD 2. was utilized to predict the time-dependent aircraft position and attitude, along - with the rotor blade airloads and motion. The major focus of this effort was the enhancement of the acoustic code WOPWOP necessary to compute the noise from a maneuvering rotorcraft. Full aircraft motion, including arbitrary transient motion, is modeled together with arbitrary rotor blade motions. Noise from a rotorcraft in turning and descending flight is compared to level flight. A substantial increase in the rotor noise is found both for turning flight and during a transient maneuver. Additional enhancements to take advantage of parallel computers and clusters of workstations, in addition to a new compact-chordwise loading formulation, are also described.
Uncertainty in perception and the Hierarchical Gaussian Filter.
Mathys, Christoph D; Lomakina, Ekaterina I; Daunizeau, Jean; Iglesias, Sandra; Brodersen, Kay H; Friston, Karl J; Stephan, Klaas E
2014-01-01
In its full sense, perception rests on an agent's model of how its sensory input comes about and the inferences it draws based on this model. These inferences are necessarily uncertain. Here, we illustrate how the Hierarchical Gaussian Filter (HGF) offers a principled and generic way to deal with the several forms that uncertainty in perception takes. The HGF is a recent derivation of one-step update equations from Bayesian principles that rests on a hierarchical generative model of the environment and its (in)stability. It is computationally highly efficient, allows for online estimates of hidden states, and has found numerous applications to experimental data from human subjects. In this paper, we generalize previous descriptions of the HGF and its account of perceptual uncertainty. First, we explicitly formulate the extension of the HGF's hierarchy to any number of levels; second, we discuss how various forms of uncertainty are accommodated by the minimization of variational free energy as encoded in the update equations; third, we combine the HGF with decision models and demonstrate the inversion of this combination; finally, we report a simulation study that compared four optimization methods for inverting the HGF/decision model combination at different noise levels. These four methods (Nelder-Mead simplex algorithm, Gaussian process-based global optimization, variational Bayes and Markov chain Monte Carlo sampling) all performed well even under considerable noise, with variational Bayes offering the best combination of efficiency and informativeness of inference. Our results demonstrate that the HGF provides a principled, flexible, and efficient-but at the same time intuitive-framework for the resolution of perceptual uncertainty in behaving agents. PMID:25477800
Uncertainty in perception and the Hierarchical Gaussian Filter
Mathys, Christoph D.; Lomakina, Ekaterina I.; Daunizeau, Jean; Iglesias, Sandra; Brodersen, Kay H.; Friston, Karl J.; Stephan, Klaas E.
2014-01-01
In its full sense, perception rests on an agent's model of how its sensory input comes about and the inferences it draws based on this model. These inferences are necessarily uncertain. Here, we illustrate how the Hierarchical Gaussian Filter (HGF) offers a principled and generic way to deal with the several forms that uncertainty in perception takes. The HGF is a recent derivation of one-step update equations from Bayesian principles that rests on a hierarchical generative model of the environment and its (in)stability. It is computationally highly efficient, allows for online estimates of hidden states, and has found numerous applications to experimental data from human subjects. In this paper, we generalize previous descriptions of the HGF and its account of perceptual uncertainty. First, we explicitly formulate the extension of the HGF's hierarchy to any number of levels; second, we discuss how various forms of uncertainty are accommodated by the minimization of variational free energy as encoded in the update equations; third, we combine the HGF with decision models and demonstrate the inversion of this combination; finally, we report a simulation study that compared four optimization methods for inverting the HGF/decision model combination at different noise levels. These four methods (Nelder–Mead simplex algorithm, Gaussian process-based global optimization, variational Bayes and Markov chain Monte Carlo sampling) all performed well even under considerable noise, with variational Bayes offering the best combination of efficiency and informativeness of inference. Our results demonstrate that the HGF provides a principled, flexible, and efficient—but at the same time intuitive—framework for the resolution of perceptual uncertainty in behaving agents. PMID:25477800
NASA Astrophysics Data System (ADS)
Xu, Shaoping; Hu, Lingyan; Yang, Xiaohui
2016-01-01
The performance of conventional denoising algorithms is usually controlled by one or several parameters whose optimal settings depend on the contents of the processed images and the characteristics of the noises. Among these parameters, noise level is a fundamental parameter that is always assumed to be known by most of the existing denoising algorithms (so-called nonblind denoising algorithms), which largely limits the applicability of these nonblind denoising algorithms in many applications. Moreover, these nonblind algorithms do not always achieve the best denoised images in visual quality even when fed with the actual noise level parameter. To address these shortcomings, in this paper we propose a new quality-aware features-based noise level estimator (NLE), which consists of quality-aware features extraction and optimal noise level parameter prediction. First, considering that image local contrast features convey important structural information that is closely related to image perceptual quality, we utilize the marginal statistics of two local contrast operators, i.e., the gradient magnitude and the Laplacian of Gaussian (LOG), to extract quality-aware features. The proposed quality-aware features have very low computational complexity, making them well suited for time-constrained applications. Then we propose a learning-based framework where the noise level parameter is estimated based on the quality-aware features. Based on the proposed NLE, we develop a blind block matching and three-dimensional filtering (BBM3D) denoising algorithm which is capable of effectively removing additive white Gaussian noise, even coupled with impulse noise. The noise level parameter of the BBM3D algorithm is automatically tuned according to the quality-aware features, guaranteeing the best performance. As such, the classical block matching and three-dimensional algorithm can be transformed into a blind one in an unsupervised manner. Experimental results demonstrate that the
Bayesian soft X-ray tomography using non-stationary Gaussian Processes
Li, Dong; Svensson, J.; Thomsen, H.; Werner, A.; Wolf, R.; Medina, F.
2013-08-15
In this study, a Bayesian based non-stationary Gaussian Process (GP) method for the inference of soft X-ray emissivity distribution along with its associated uncertainties has been developed. For the investigation of equilibrium condition and fast magnetohydrodynamic behaviors in nuclear fusion plasmas, it is of importance to infer, especially in the plasma center, spatially resolved soft X-ray profiles from a limited number of noisy line integral measurements. For this ill-posed inversion problem, Bayesian probability theory can provide a posterior probability distribution over all possible solutions under given model assumptions. Specifically, the use of a non-stationary GP to model the emission allows the model to adapt to the varying length scales of the underlying diffusion process. In contrast to other conventional methods, the prior regularization is realized in a probability form which enhances the capability of uncertainty analysis, in consequence, scientists who concern the reliability of their results will benefit from it. Under the assumption of normally distributed noise, the posterior distribution evaluated at a discrete number of points becomes a multivariate normal distribution whose mean and covariance are analytically available, making inversions and calculation of uncertainty fast. Additionally, the hyper-parameters embedded in the model assumption can be optimized through a Bayesian Occam's Razor formalism and thereby automatically adjust the model complexity. This method is shown to produce convincing reconstructions and good agreements with independently calculated results from the Maximum Entropy and Equilibrium-Based Iterative Tomography Algorithm methods.
Bayesian soft X-ray tomography using non-stationary Gaussian Processes
NASA Astrophysics Data System (ADS)
Li, Dong; Svensson, J.; Thomsen, H.; Medina, F.; Werner, A.; Wolf, R.
2013-08-01
In this study, a Bayesian based non-stationary Gaussian Process (GP) method for the inference of soft X-ray emissivity distribution along with its associated uncertainties has been developed. For the investigation of equilibrium condition and fast magnetohydrodynamic behaviors in nuclear fusion plasmas, it is of importance to infer, especially in the plasma center, spatially resolved soft X-ray profiles from a limited number of noisy line integral measurements. For this ill-posed inversion problem, Bayesian probability theory can provide a posterior probability distribution over all possible solutions under given model assumptions. Specifically, the use of a non-stationary GP to model the emission allows the model to adapt to the varying length scales of the underlying diffusion process. In contrast to other conventional methods, the prior regularization is realized in a probability form which enhances the capability of uncertainty analysis, in consequence, scientists who concern the reliability of their results will benefit from it. Under the assumption of normally distributed noise, the posterior distribution evaluated at a discrete number of points becomes a multivariate normal distribution whose mean and covariance are analytically available, making inversions and calculation of uncertainty fast. Additionally, the hyper-parameters embedded in the model assumption can be optimized through a Bayesian Occam's Razor formalism and thereby automatically adjust the model complexity. This method is shown to produce convincing reconstructions and good agreements with independently calculated results from the Maximum Entropy and Equilibrium-Based Iterative Tomography Algorithm methods.
NASA Astrophysics Data System (ADS)
Samanta, Sudeshna; Raychaudhuri, A. K.; Zhong, Xing; Gupta, A.
2015-11-01
We have carried out an extensive investigation on the resistance fluctuations (noise) in an epitaxial thin film of VO2 encompassing the metal-insulator transition (MIT) region to investigate the dynamic phase coexistence of metal and insulating phases. Both flicker noise as well as the Nyquist noise (thermal noise) were measured. The experiments showed that flicker noise, which has a 1 /f spectral power dependence, evolves with temperature in the transition region following the evolution of the phase fractions and is governed by activated kinetics. Importantly, closer to the insulating end of the transition, when the metallic phase fraction is low, the magnitude of the noise shows an anomaly and a strong non-Gaussian component of noise develops. In this region, the local electron temperature (as measured through the Nyquist noise thermometry) shows a deviation from the equilibrium bath temperature. It is proposed that this behavior arises due to current crowding where a substantial amount of the current is carried through well separated small metallic islands leading to a dynamic correlated current path redistribution and an enhanced effective local current density. This leads to a non-Gaussian component to the resistance fluctuation and an associated local deviation of the electron temperature from the bath. Our experiment establishes that phase coexistence leads to a strong inhomogeneity in the region of MIT that makes the current transport strongly inhomogeneous and correlated.
NASA Technical Reports Server (NTRS)
Biswas, Rahul; Blackburn, Lindy L.; Cao, Junwei; Essick, Reed; Hodge, Kari Alison; Katsavounidis, Erotokritos; Kim, Kyungmin; Young-Min, Kim; Le Bigot, Eric-Olivier; Lee, Chang-Hwan; Oh, John J.; Oh, Sang Hoon; Son, Edwin J.; Vaulin, Ruslan; Wang, Xiaoge; Ye, Tao
2014-01-01
The sensitivity of searches for astrophysical transients in data from the Laser Interferometer Gravitationalwave Observatory (LIGO) is generally limited by the presence of transient, non-Gaussian noise artifacts, which occur at a high-enough rate such that accidental coincidence across multiple detectors is non-negligible. Furthermore, non-Gaussian noise artifacts typically dominate over the background contributed from stationary noise. These "glitches" can easily be confused for transient gravitational-wave signals, and their robust identification and removal will help any search for astrophysical gravitational-waves. We apply Machine Learning Algorithms (MLAs) to the problem, using data from auxiliary channels within the LIGO detectors that monitor degrees of freedom unaffected by astrophysical signals. Terrestrial noise sources may manifest characteristic disturbances in these auxiliary channels, inducing non-trivial correlations with glitches in the gravitational-wave data. The number of auxiliary-channel parameters describing these disturbances may also be extremely large; high dimensionality is an area where MLAs are particularly well-suited. We demonstrate the feasibility and applicability of three very different MLAs: Artificial Neural Networks, Support Vector Machines, and Random Forests. These classifiers identify and remove a substantial fraction of the glitches present in two very different data sets: four weeks of LIGO's fourth science run and one week of LIGO's sixth science run. We observe that all three algorithms agree on which events are glitches to within 10% for the sixth science run data, and support this by showing that the different optimization criteria used by each classifier generate the same decision surface, based on a likelihood-ratio statistic. Furthermore, we find that all classifiers obtain similar limiting performance, suggesting that most of the useful information currently contained in the auxiliary channel parameters we extract
Noise-induced transitions in optomechanical synchronization
NASA Astrophysics Data System (ADS)
Weiss, Talitha; Kronwald, Andreas; Marquardt, Florian
2016-01-01
We study how quantum and thermal noise affects synchronization of two optomechanical limit-cycle oscillators. Classically, in the absence of noise, optomechanical systems tend to synchronize either in-phase or anti-phase. Taking into account the fundamental quantum noise, we find a regime where fluctuations drive transitions between these classical synchronization states. We investigate how this ‘mixed’ synchronization regime emerges from the noiseless system by studying the classical-to-quantum crossover and we show how the time scales of the transitions vary with the effective noise strength. In addition, we compare the effects of thermal noise to the effects of quantum noise.
All-optical polarization control and noise cleaning based on a nonlinear lossless polarizer
NASA Astrophysics Data System (ADS)
Barozzi, Matteo; Vannucci, Armando; Picchi, Giorgio
2015-01-01
We propose an all-optical fiber-based device able to accomplish both polarization control and OSNR enhancement of an amplitude modulated optical signal, affected by unpolarized additive white Gaussian noise, at the same time. The proposed noise cleaning device is made of a nonlinear lossless polarizer (NLP), that performs polarization control, followed by an ideal polarizing filter that removes the orthogonally polarized half of additive noise. The NLP transforms every input signal polarization into a unique, well defined output polarization (without any loss of signal energy) and its task is to impose a signal polarization aligned with the transparent eigenstate of the polarizing filter. In order to effectively control the polarization of the modulated signal, we show that two different NLP configurations (with counter- or co-propagating pump laser) are needed, as a function of the signal polarization coherence time. The NLP is designed so that polarization attraction is effective only on the "noiseless" (i.e., information-bearing) component of the signal and not on noise, that remains unpolarized at the NLP output. Hence, the proposed device is able to discriminate signal power (that is preserved) from in-band noise power (that is partly suppressed). Since signal repolarization is detrimental if applied to polarization-multiplexed formats, the noise cleaner application is limited here to "legacy" links, with 10 Gb/s OOK modulation, still representing the most common format in deployed networks. By employing the appropriate NLP configurations, we obtain an OSNR gain close to 3dB. Furthermore, we show how the achievable OSNR gain can be estimated theoretically.
Community noise sources and noise control issues
NASA Technical Reports Server (NTRS)
Nihart, Gene L.
1992-01-01
The topics covered include the following: community noise sources and noise control issues; noise components for turbine bypass turbojet engine (TBE) turbojet; engine cycle selection and noise; nozzle development schedule; NACA nozzle design; NACA nozzle test results; nearly fully mixed (NFM) nozzle design; noise versus aspiration rate; peak noise test results; nozzle test in the Low Speed Aeroacoustic Facility (LSAF); and Schlieren pictures of NACA nozzle.
Nonparaxial multi-Gaussian beam models and measurement models for phased array transducers.
Zhao, Xinyu; Gang, Tie
2009-01-01
A nonparaxial multi-Gaussian beam model is proposed in order to overcome the limitation that paraxial Gaussian beam models lose accuracy in simulating the beam steering behavior of phased array transducers. Using this nonparaxial multi-Gaussian beam model, the focusing and steering sound fields generated by an ultrasonic linear phased array transducer are calculated and compared with the corresponding results obtained by paraxial multi-Gaussian beam model and more exact Rayleigh-Sommerfeld integral model. In addition, with help of this novel nonparaxial method, an ultrasonic measurement model is provided to investigate the sensitivity of linear phased array transducers versus steering angles. Also the comparisons of model predictions with experimental results are presented to certify the accuracy of this provided measurement model. PMID:18774152
On a (β, q)-generalized Fisher information and inequalities involving q-Gaussian distributions
NASA Astrophysics Data System (ADS)
Bercher, J.-F.
2012-06-01
In the present paper, we would like to draw attention to a possible generalized Fisher information that fits well in the formalism of nonextensive thermostatistics. This generalized Fisher information is defined for densities on {R}n. Just as the maximum Rényi or Tsallis entropy subject to an elliptic moment constraint is a generalized q-Gaussian, we show that the minimization of the generalized Fisher information also leads a generalized q-Gaussian. This yields a generalized Cramér-Rao inequality. In addition, we show that the generalized Fisher information naturally pops up in a simple inequality that links the generalized entropies, the generalized Fisher information, and an elliptic moment. Finally, we give an extended Stam inequality. In this series of results, the extremal functions are the generalized q-Gaussians. Thus, these results complement the classical characterization of the generalized q-Gaussian and introduce a generalized Fisher information as a new information measure in nonextensive thermostatistics.
Dynamic generation of Ince-Gaussian modes with a digital micromirror device
Ren, Yu-Xuan; Fang, Zhao-Xiang; Chen, Yue; Lu, Rong-De; Gong, Lei; Huang, Kun
2015-04-07
Ince-Gaussian (IG) beam with elliptical profile, as a connection between Hermite-Gaussian (HG) and Laguerre-Gaussian (LG) beams, has showed unique advantages in some applications such as quantum entanglement and optical micromanipulation. However, its dynamic generation with high switching frequency is still challenging. Here, we experimentally reported the quick generation of Ince-Gaussian beam by using a digital micro-mirror device (DMD), which has the highest switching frequency of 5.2 kHz in principle. The configurable properties of DMD allow us to observe the quasi-smooth variation from LG (with ellipticity ε=0) to IG and HG (ε=∞) beam. This approach might pave a path to high-speed quantum communication in terms of IG beam. Additionally, the characterized axial plane intensity distribution exhibits a 3D mould potentially being employed for optical micromanipulation.
Born modeling for heterogeneous media using the Gaussian beam summation based Green's function
NASA Astrophysics Data System (ADS)
Huang, Xingguo; Sun, Hui; Sun, Jianguo
2016-08-01
Born approximation is a commonly used approximation in the simulation of seismic wave propagation. Calculation of the Green's function in Born approximation integral is essential for Born modeling. We derive a new Born formula based on the Gaussian beam representations of Green's functions. This procedure can be used to mitigate the problems like the caustic, shadow region, and multivalued traveltime caused by multipathing that traditional geometric ray theory cannot deal with. However, due to the characteristic of complex traveltime in the Gaussian beam, we present a new isochronous stack method for Gaussian beam based Born modeling. Additionally, two basic issues, background velocity and integral region selection, are discussed. Numerical results demonstrate the accuracy and efficiency of the Gaussian beam based Born theory and implementation.
Optimal application of Morrison's iterative noise removal for deconvolution. Appendices
NASA Technical Reports Server (NTRS)
Ioup, George E.; Ioup, Juliette W.
1987-01-01
Morrison's iterative method of noise removal, or Morrison's smoothing, is applied in a simulation to noise-added data sets of various noise levels to determine its optimum use. Morrison's smoothing is applied for noise removal alone, and for noise removal prior to deconvolution. For the latter, an accurate method is analyzed to provide confidence in the optimization. The method consists of convolving the data with an inverse filter calculated by taking the inverse discrete Fourier transform of the reciprocal of the transform of the response of the system. Various length filters are calculated for the narrow and wide Gaussian response functions used. Deconvolution of non-noisy data is performed, and the error in each deconvolution calculated. Plots are produced of error versus filter length; and from these plots the most accurate length filters determined. The statistical methodologies employed in the optimizations of Morrison's method are similar. A typical peak-type input is selected and convolved with the two response functions to produce the data sets to be analyzed. Both constant and ordinate-dependent Gaussian distributed noise is added to the data, where the noise levels of the data are characterized by their signal-to-noise ratios. The error measures employed in the optimizations are the L1 and L2 norms. Results of the optimizations for both Gaussians, both noise types, and both norms include figures of optimum iteration number and error improvement versus signal-to-noise ratio, and tables of results. The statistical variation of all quantities considered is also given.
Catlin, F I
1986-03-01
Hearing loss affects 30 million people in the United States; of these, 21 million are over the age of 65 years. This disorder may have several causes: heredity, noise, aging, and disease. Hearing loss from noise has been recognized for centuries but was generally ignored until some time after the Industrial Revolution. Hearing loss from occupational exposure to hazardous noise was identified as a compensable disability by the United States courts in 1948 to 1959. Development of noisy jet engines and supersonic aircraft created additional claims for personal and property damage in the 1950s and 1960s. These conditions led to legislation for noise control in the form of the Occupational Safety and Health Act of 1970 and the Noise Control Act of 1972. Protection of the noise-exposed employee was also an objective of the Hearing Conservation Act of 1971. Subsequent studies have confirmed the benefits of periodic hearing tests for workers exposed to hazardous noise and of otologic evaluation as part of the hearing conservation process. Research studies in laboratory animals, using scanning electron microscopical techniques, have demonstrated that damage to the inner ear and organ of hearing can occur even though subjective (conditioned) response to sound stimuli remains unaffected. Some investigators have employed an epidemiologic approach to identify risk factors and to develop profiles to susceptibility to noise-induced hearing loss. The need for joint involvement of workers and employers in the reduction and control of occupational noise hazards is evident. PMID:2938482
Catlin, F.I.
1986-03-01
Hearing loss affects 30 million people in the United States; of these, 21 million are over the age of 65 years. This disorder may have several causes: heredity, noise, aging, and disease. Hearing loss from noise has been recognized for centuries but was generally ignored until some time after the Industrial Revolution. Hearing loss from occupational exposure to hazardous noise was identified as a compensable disability by the United States courts in 1948 to 1959. Development of noisy jet engines and supersonic aircraft created additional claims for personal and property damage in the 1950s and 1960s. These conditions led to legislation for noise control in the form of the Occupational Safety and Health Act of 1970 and the Noise Control Act of 1972. Protection of the noise-exposed employee was also an objective of the Hearing Conservation Act of 1971. Subsequent studies have confirmed the benefits of periodic hearing tests for workers exposed to hazardous noise and of otologic evaluation as part of the hearing conservation process. Research studies in laboratory animals, using scanning electron microscopical techniques, have demonstrated that damage to the inner ear and organ of hearing can occur even though subjective (conditioned) response to sound stimuli remains unaffected. Some investigators have employed an epidemiologic approach to identify risk factors and to develop profiles to susceptibility to noise-induced hearing loss. The need for joint involvement of workers and employers in the reduction and control of occupational noise hazards is evident. 19 references.
Gaussian vs non-Gaussian turbulence: impact on wind turbine loads
NASA Astrophysics Data System (ADS)
Berg, J.; Mann, J.; Natarajan, A.; Patton, E. G.
2014-12-01
In wind energy applications the turbulent velocity field of the Atmospheric Boundary Layer (ABL) is often characterised by Gaussian probability density functions. When estimating the dynamical loads on wind turbines this has been the rule more than anything else. From numerous studies in the laboratory, in Direct Numerical Simulations, and from in-situ measurements of the ABL we know, however, that turbulence is not purely Gaussian: the smallest and fastest scales often exhibit extreme behaviour characterised by strong non-Gaussian statistics. In this contribution we want to investigate whether these non-Gaussian effects are important when determining wind turbine loads, and hence of utmost importance to the design criteria and lifetime of a wind turbine. We devise a method based on Principal Orthogonal Decomposition where non-Gaussian velocity fields generated by high-resolution pseudo-spectral Large-Eddy Simulation (LES) of the ABL are transformed so that they maintain the exact same second-order statistics including variations of the statistics with height, but are otherwise Gaussian. In that way we can investigate in isolation the question whether it is important for wind turbine loads to include non-Gaussian properties of atmospheric turbulence. As an illustration the Figure show both a non-Gaussian velocity field (left) from our LES, and its transformed Gaussian Counterpart (right). Whereas the horizontal velocity components (top) look close to identical, the vertical components (bottom) are not: the non-Gaussian case is much more fluid-like (like in a sketch by Michelangelo). The question is then: Does the wind turbine see this? Using the load simulation software HAWC2 with both the non-Gaussian and newly constructed Gaussian fields, respectively, we show that the Fatigue loads and most of the Extreme loads are unaltered when using non-Gaussian velocity fields. The turbine thus acts like a low-pass filter which average out the non-Gaussian behaviour on time
Inflation: Long Wavelength Modes and Non-Gaussianities
NASA Astrophysics Data System (ADS)
Deutsch, Anne-Sylvie; Shandera, Sarah; Bonga, Béatrice; Brahma, Suddhasattwa
2015-04-01
For our work, we assume that the whole inflation process can be separated into two main regimes; one described by a field Φ (the inflaton field) interacting weakly with Σ (in the hidden sector), and another one, at energies Λ2 --> 1 and lower, where the field Σ has been integrated out and we are in a single field Φ model with a small sound speed cs. During the two-field regime, coupling between short and long wavelength can generate non-equilateral non-Gaussianities. Upon imposing some conditions, such a generation of non-Gaussianities is not allowed in a single field regime. Our objective is to include the contribution of these long and short wavelength couplings in the single effective field model. For that, we derived an effective Lagrangian and studied the influence of each interaction term on the physics of inflation. We saw that both terms would lead to a similar sound speed and non-Gaussianities. Open questions remain concerning the effect of the splitting, which we are currently investigating. One could expect a different background evolution of the theory, or additional terms in the effective Lagrangian for the fluctuations Leff . Another possibility would be to also consider a modified initial state.
Relativistic corrections and non-Gaussianity in radio continuum surveys
Maartens, Roy; Zhao, Gong-Bo; Bacon, David; Koyama, Kazuya; Raccanelli, Alvise E-mail: Gong-bo.Zhao@port.ac.uk E-mail: Kazuya.Koyama@port.ac.uk
2013-02-01
Forthcoming radio continuum surveys will cover large volumes of the observable Universe and will reach to high redshifts, making them potentially powerful probes of dark energy, modified gravity and non-Gaussianity. We consider the continuum surveys with LOFAR, WSRT and ASKAP, and examples of continuum surveys with the SKA. We extend recent work on these surveys by including redshift space distortions and lensing convergence in the radio source auto-correlation. In addition we compute the general relativistic (GR) corrections to the angular power spectrum. These GR corrections to the standard Newtonian analysis of the power spectrum become significant on scales near and beyond the Hubble scale at each redshift. We find that the GR corrections are at most percent-level in LOFAR, WODAN and EMU surveys, but they can produce O(10%) changes for high enough sensitivity SKA continuum surveys. The signal is however dominated by cosmic variance, and multiple-tracer techniques will be needed to overcome this problem. The GR corrections are suppressed in continuum surveys because of the integration over redshift — we expect that GR corrections will be enhanced for future SKA HI surveys in which the source redshifts will be known. We also provide predictions for the angular power spectra in the case where the primordial perturbations have local non-Gaussianity. We find that non-Gaussianity dominates over GR corrections, and rises above cosmic variance when f{sub NL}∼>5 for SKA continuum surveys.
Semiconductor Laser Low Frequency Noise Characterization
NASA Technical Reports Server (NTRS)
Maleki, Lute; Logan, Ronald T.
1996-01-01
This work summarizes the efforts in identifying the fundamental noise limit in semiconductor optical sources (lasers) to determine the source of 1/F noise and it's associated behavior. In addition, the study also addresses the effects of this 1/F noise on RF phased arrays. The study showed that the 1/F noise in semiconductor lasers has an ultimate physical limit based upon similar factors to fundamental noise generated in other semiconductor and solid state devices. The study also showed that both additive and multiplicative noise can be a significant detriment to the performance of RF phased arrays especially in regard to very low sidelobe performance and ultimate beam steering accuracy. The final result is that a noise power related term must be included in a complete analysis of the noise spectrum of any semiconductor device including semiconductor lasers.
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…
Principal components of CMB non-Gaussianity
NASA Astrophysics Data System (ADS)
Regan, Donough; Munshi, Dipak
2015-04-01
The skew-spectrum statistic introduced by Munshi & Heavens has recently been used in studies of non-Gaussianity from diverse cosmological data sets including the detection of primary and secondary non-Gaussianity of cosmic microwave background (CMB) radiation. Extending previous work, focused on independent estimation, here we deal with the question of joint estimation of multiple skew-spectra from the same or correlated data sets. We consider the optimum skew-spectra for various models of primordial non-Gaussianity as well as secondary bispectra that originate from the cross-correlation of secondaries and lensing of CMB: coupling of lensing with the Integrated Sachs-Wolfe effect, coupling of lensing with thermal Sunyaev-Zeldovich, as well as from unresolved point sources. For joint estimation of various types of non-Gaussianity, we use the principal component analysis (PCA) to construct the linear combinations of amplitudes of various models of non-Gaussianity, e.g. f^loc_NL,f^eq_NL,f^ortho_NL that can be estimated from CMB maps. We describe how the bias induced in the estimation of primordial non-Gaussianity due to secondary non-Gaussianity may be evaluated for arbitrary primordial models using a PCA analysis. The PCA approach allows one to infer approximate (but generally accurate) constraints using CMB data sets on any reasonably smooth model by use of a look-up table and performing a simple computation. This principle is validated by computing constraints on the Dirac-Born-Infeld bispectrum using a PCA analysis of the standard templates.
From particle counting to Gaussian tomography
NASA Astrophysics Data System (ADS)
Parthasarathy, K. R.; Sengupta, Ritabrata
2015-12-01
The momentum and position observables in an n-mode boson Fock space Γ(ℂn) have the whole real line ℝ as their spectrum. But the total number operator N has a discrete spectrum ℤ+ = {0, 1, 2,…}. An n-mode Gaussian state in Γ(ℂn) is completely determined by the mean values of momentum and position observables and their covariance matrix which together constitute a family of n(2n + 3) real parameters. Starting with N and its unitary conjugates by the Weyl displacement operators and operators from a representation of the symplectic group Sp(2n) in Γ(ℂn), we construct n(2n + 3) observables with spectrum ℤ+ but whose expectation values in a Gaussian state determine all its mean and covariance parameters. Thus measurements of discrete-valued observables enable the tomography of the underlying Gaussian state and it can be done by using five one-mode and four two-mode Gaussian symplectic gates in single and pair mode wires of Γ(ℂn) = Γ(ℂ)⊗n. Thus the tomography protocol admits a simple description in a language similar to circuits in quantum computation theory. Such a Gaussian tomography applied to outputs of a Gaussian channel with coherent input states permit a tomography of the channel parameters. However, in our procedure the number of counting measurements exceeds the number of channel parameters slightly. Presently, it is not clear whether a more efficient method exists for reducing this tomographic complexity. As a byproduct of our approach an elementary derivation of the probability generating function of N in a Gaussian state is given. In many cases the distribution turns out to be infinitely divisible and its underlying Lévy measure can be obtained. However, we are unable to derive the exact distribution in all cases. Whether this property of infinite divisibility holds in general is left as an open problem.
NASA Astrophysics Data System (ADS)
Griesbach, J.; Wetterer, C.; Sydney, P.; Gerber, J.
Photometric processing of non-resolved Electro-Optical (EO) images has commonly required the use of dark and flat calibration frames that are obtained to correct for charge coupled device (CCD) dark (thermal) noise and CCD quantum efficiency/optical path vignetting effects respectively. It is necessary to account/calibrate for these effects so that the brightness of objects of interest (e.g. stars or resident space objects (RSOs)) may be measured in a consistent manner across the CCD field of view. Detected objects typically require further calibration using aperture photometry to compensate for sky background (shot noise). For this, annuluses are measured around each detected object whose contained pixels are used to estimate an average background level that is subtracted from the detected pixel measurements. In a new photometric calibration software tool developed for AFRL/RD, called Efficient Photometry In-Frame Calibration (EPIC), an automated background normalization technique is proposed that eliminates the requirement to capture dark and flat calibration images. The proposed technique simultaneously corrects for dark noise, shot noise, and CCD quantum efficiency/optical path vignetting effects. With this, a constant detection threshold may be applied for constant false alarm rate (CFAR) object detection without the need for aperture photometry corrections. The detected pixels may be simply summed (without further correction) for an accurate instrumental magnitude estimate. The noise distribution associated with each pixel is assumed to be sampled from a Poisson distribution. Since Poisson distributed data closely resembles Gaussian data for parameterized means greater than 10, the data may be corrected by applying bias subtraction and standard-deviation division. EPIC performs automated background normalization on rate-tracked satellite images using the following technique. A deck of approximately 50-100 images is combined by performing an independent median
Conformal invariance, dark energy, and CMB non-gaussianity
NASA Astrophysics Data System (ADS)
Antoniadis, Ignatios; Mazur, Pawel O.; Mottola, Emil
2012-09-01
In addition to simple scale invariance, a universe dominated by dark energy naturally gives rise to correlation functions possessing full conformal invariance. This is due to the mathematical isomorphism between the conformal group of certain three dimensional slices of de Sitter space and the de Sitter isometry group SO(4,1). In the standard homogeneous, isotropic cosmological model in which primordial density perturbations are generated during a long vacuum energy dominated de Sitter phase, the embedding of flat spatial Bbb R3 sections in de Sitter space induces a conformal invariant perturbation spectrum and definite prediction for the shape of the non-Gaussian CMB bispectrum. In the case in which the density fluctuations are generated instead on the de Sitter horizon, conformal invariance of the Bbb S2 horizon embedding implies a different but also quite definite prediction for the angular correlations of CMB non-Gaussianity on the sky. Each of these forms for the bispectrum is intrinsic to the symmetries of de Sitter space, and in that sense, independent of specific model assumptions. Each is different from the predictions of single field slow roll inflation models, which rely on the breaking of de Sitter invariance. We propose a quantum origin for the CMB fluctuations in the scalar gravitational sector from the conformal anomaly that could give rise to these non-Gaussianities without a slow roll inflaton field, and argue that conformal invariance also leads to the expectation for the relation nS-1 = nT between the spectral indices of the scalar and tensor power spectrum. Confirmation of this prediction or detection of non-Gaussian correlations in the CMB of one of the bispectral shape functions predicted by conformal invariance can be used both to establish the physical origins of primordial density fluctuations, and distinguish between different dynamical models of cosmological vacuum dark energy.
Conformal invariance, dark energy, and CMB non-gaussianity
Antoniadis, Ignatios; Mazur, Pawel O.; Mottola, Emil E-mail: mazur@physics.sc.edu
2012-09-01
In addition to simple scale invariance, a universe dominated by dark energy naturally gives rise to correlation functions possessing full conformal invariance. This is due to the mathematical isomorphism between the conformal group of certain three dimensional slices of de Sitter space and the de Sitter isometry group SO(4,1). In the standard homogeneous, isotropic cosmological model in which primordial density perturbations are generated during a long vacuum energy dominated de Sitter phase, the embedding of flat spatial R{sup 3} sections in de Sitter space induces a conformal invariant perturbation spectrum and definite prediction for the shape of the non-Gaussian CMB bispectrum. In the case in which the density fluctuations are generated instead on the de Sitter horizon, conformal invariance of the S{sup 2} horizon embedding implies a different but also quite definite prediction for the angular correlations of CMB non-Gaussianity on the sky. Each of these forms for the bispectrum is intrinsic to the symmetries of de Sitter space, and in that sense, independent of specific model assumptions. Each is different from the predictions of single field slow roll inflation models, which rely on the breaking of de Sitter invariance. We propose a quantum origin for the CMB fluctuations in the scalar gravitational sector from the conformal anomaly that could give rise to these non-Gaussianities without a slow roll inflaton field, and argue that conformal invariance also leads to the expectation for the relation n{sub S}−1 = n{sub T} between the spectral indices of the scalar and tensor power spectrum. Confirmation of this prediction or detection of non-Gaussian correlations in the CMB of one of the bispectral shape functions predicted by conformal invariance can be used both to establish the physical origins of primordial density fluctuations, and distinguish between different dynamical models of cosmological vacuum dark energy.
Control of Environmental Noise
ERIC Educational Resources Information Center
Jensen, Paul
1973-01-01
Discusses the physical properties, sources, physiological effects, and legislation pertaining to noise, especially noise characteristics in the community. Indicates that noise reduction steps can be taken more intelligently after determination of the true noise sources and paths. (CC)
Efficient gradient projection methods for edge-preserving removal of Poisson noise
NASA Astrophysics Data System (ADS)
Zanella, R.; Boccacci, P.; Zanni, L.; Bertero, M.
2009-04-01
Several methods based on different image models have been proposed and developed for image denoising. Some of them, such as total variation (TV) and wavelet thresholding, are based on the assumption of additive Gaussian noise. Recently the TV approach has been extended to the case of Poisson noise, a model describing the effect of photon counting in applications such as emission tomography, microscopy and astronomy. For the removal of this kind of noise we consider an approach based on a constrained optimization problem, with an objective function describing TV and other edge-preserving regularizations of the Kullback-Leibler divergence. We introduce a new discrepancy principle for the choice of the regularization parameter, which is justified by the statistical properties of the Poisson noise. For solving the optimization problem we propose a particular form of a general scaled gradient projection (SGP) method, recently introduced for image deblurring. We derive the form of the scaling from a decomposition of the gradient of the regularization functional into a positive and a negative part. The beneficial effect of the scaling is proved by means of numerical simulations, showing that the performance of the proposed form of SGP is superior to that of the most efficient gradient projection methods. An extended numerical analysis of the dependence of the solution on the regularization parameter is also performed to test the effectiveness of the proposed discrepancy principle.
Noise determination in silicon micro strips
Dubbs, T.; Kashigin, S.; Kratzer, M.
1996-06-01
The authors report the study of amplifier noise on silicon micro strip detectors. They have used a fast, low noise amplifier-comparator VLSI chip with 22ns shaping time developed for the LHC to determine the noise at the pre-amp as a function of strip length and strip geometry, i.e., interstrip capacitance and ohmic strip resistance. In addition, they have tested the noise in irradiated detectors. They have compared the results with simulations using SPICE.
Neural Field Models with Threshold Noise.
Thul, Rüdiger; Coombes, Stephen; Laing, Carlo R
2016-12-01
The original neural field model of Wilson and Cowan is often interpreted as the averaged behaviour of a network of switch like neural elements with a distribution of switch thresholds, giving rise to the classic sigmoidal population firing-rate function so prevalent in large scale neuronal modelling. In this paper we explore the effects of such threshold noise without recourse to averaging and show that spatial correlations can have a strong effect on the behaviour of waves and patterns in continuum models. Moreover, for a prescribed spatial covariance function we explore the differences in behaviour that can emerge when the underlying stationary distribution is changed from Gaussian to non-Gaussian. For travelling front solutions, in a system with exponentially decaying spatial interactions, we make use of an interface approach to calculate the instantaneous wave speed analytically as a series expansion in the noise strength. From this we find that, for weak noise, the spatially averaged speed depends only on the choice of covariance function and not on the shape of the stationary distribution. For a system with a Mexican-hat spatial connectivity we further find that noise can induce localised bump solutions, and using an interface stability argument show that there can be multiple stable solution branches. PMID:26936267
Hydraulic Conductivity Fields: Gaussian or Not?
Meerschaert, Mark M.; Dogan, Mine; Van Dam, Remke L.; Hyndman, David W.; Benson, David A.
2013-01-01
Hydraulic conductivity (K) fields are used to parameterize groundwater flow and transport models. Numerical simulations require a detailed representation of the K field, synthesized to interpolate between available data. Several recent studies introduced high resolution K data (HRK) at the Macro Dispersion Experiment (MADE) site, and used ground-penetrating radar (GPR) to delineate the main structural features of the aquifer. This paper describes a statistical analysis of these data, and the implications for K field modeling in alluvial aquifers. Two striking observations have emerged from this analysis. The first is that a simple fractional difference filter can have a profound effect on data histograms, organizing non-Gaussian ln K data into a coherent distribution. The second is that using GPR facies allows us to reproduce the significantly non-Gaussian shape seen in real HRK data profiles, using a simulated Gaussian ln K field in each facies. This illuminates a current controversy in the literature, between those who favor Gaussian ln K models, and those who observe non-Gaussian ln K fields. Both camps are correct, but at different scales. PMID:24415806
Comparison of Gaussian and super Gaussian laser beams for addressing atomic qubits
NASA Astrophysics Data System (ADS)
Gillen-Christandl, Katharina; Gillen, Glen D.; Piotrowicz, M. J.; Saffman, M.
2016-05-01
We study the fidelity of single-qubit quantum gates performed with two-frequency laser fields that have a Gaussian or super Gaussian spatial mode. Numerical simulations are used to account for imperfections arising from atomic motion in an optical trap, spatially varying Stark shifts of the trapping and control beams, and transverse and axial misalignment of the control beams. Numerical results that account for the three-dimensional distribution of control light show that a super Gaussian mode with intensity I˜ e^{-2(r/w_0)^n} provides reduced sensitivity to atomic motion and beam misalignment. Choosing a super Gaussian with n=6 the decay time of finite temperature Rabi oscillations can be increased by a factor of 60 compared to an n=2 Gaussian beam, while reducing crosstalk to neighboring qubit sites.
Analysis and removing noise from speech using wavelet transform
NASA Astrophysics Data System (ADS)
Tomala, Karel; Voznak, Miroslav; Partila, Pavol; Rezac, Filip; Safarik, Jakub
2013-05-01
The paper discusses the use of Discrete Wavelet Transform (DWT) and Stationary Wavelet Transform (SWT) wavelet in removing noise from voice samples and evaluation of its impact on speech quality. One significant part of Quality of Service (QoS) in communication technology is the speech quality assessment. However, this part is seriously overlooked as telecommunication providers often focus on increasing network capacity, expansion of services offered and their enforcement in the market. Among the fundamental factors affecting the transmission properties of the communication chain is noise, either at the transmitter or the receiver side. A wavelet transform (WT) is a modern tool for signal processing. One of the most significant areas in which wavelet transforms are used is applications designed to suppress noise in signals. To remove noise from the voice sample in our experiment, we used the reference segment of the voice which was distorted by Gaussian white noise. An evaluation of the impact on speech quality was carried out by an intrusive objective algorithm Perceptual Evaluation of Speech Quality (PESQ). DWT and SWT transformation was applied to voice samples that were devalued by Gaussian white noise. Afterwards, we determined the effectiveness of DWT and SWT by means of objective algorithm PESQ. The decisive criterion for determining the quality of a voice sample once the noise had been removed was Mean Opinion Score (MOS) which we obtained in PESQ. The contribution of this work lies in the evaluation of efficiency of wavelet transformation to suppress noise in voice samples.
NASA Astrophysics Data System (ADS)
1981-01-01
The problems related to aircraft noise were studied. Physical origin (sound), human reaction (noise), quantization of noise and sound sources of aircraft noise are discussed. Noise abatement at the source, technical, fleet-political and air traffic measures are explained. The measurements and future developments are also discussed. The position of Lufthansa as regards aircraft noise problems is depicted.
Noise pollution resources compendium
NASA Technical Reports Server (NTRS)
1973-01-01
Abstracts of reports concerning noise pollution are presented. The abstracts are grouped in the following areas of activity: (1) sources of noise, (2) noise detection and measurement, (3) noise abatement and control, (4) physical effects of noise and (5) social effects of noise.
NASA Technical Reports Server (NTRS)
1983-01-01
SMART, Sound Modification and Regulated Temperature compound, is a liquid plastic mixture with exceptional energy and sound absorbing qualities. It is derived from a very elastic plastic which was an effective noise abatement material in the Apollo Guidance System. Discovered by a NASA employee, it is marketed by Environmental Health Systems, Inc. (EHS). The product has been successfully employed by a diaper company with noisy dryers and a sugar company with noisy blowers. The company also manufactures an audiometric test booth and acoustical office partitions.
Ghosh, Pradipta; Shit, Anindita; Chattopadhyay, Sudip; Chaudhuri, Jyotipratim Ray
2011-03-01
This work explores the observation that, even in the absence of a net externally applied bias, a symmetric homogeneous system coupled linearly to two heat baths is capable of producing unidirectional motion simply by nonlinearly driving one of the heat baths by an external Gaussian white noise. This is quite contrary to the traditional observation that, in order to obtain a net drift current, a state-dependent dissipation, which is a consequence of nonlinear system-bath coupling, is ubiquitous. PMID:21456831
Ghosh, Pradipta; Shit, Anindita; Chattopadhyay, Sudip; Chaudhuri, Jyotipratim Ray
2011-03-15
This work explores the observation that, even in the absence of a net externally applied bias, a symmetric homogeneous system coupled linearly to two heat baths is capable of producing unidirectional motion simply by nonlinearly driving one of the heat baths by an external Gaussian white noise. This is quite contrary to the traditional observation that, in order to obtain a net drift current, a state-dependent dissipation, which is a consequence of nonlinear system-bath coupling, is ubiquitous.
Laplace Approximation for Divisive Gaussian Processes for Nonstationary Regression.
Muñoz-González, Luis; Lázaro-Gredilla, Miguel; Figueiras-Vidal, Aníbal R
2016-03-01
The standard Gaussian Process regression (GP) is usually formulated under stationary hypotheses: The noise power is considered constant throughout the input space and the covariance of the prior distribution is typically modeled as depending only on the difference between input samples. These assumptions can be too restrictive and unrealistic for many real-world problems. Although nonstationarity can be achieved using specific covariance functions, they require a prior knowledge of the kind of nonstationarity, not available for most applications. In this paper we propose to use the Laplace approximation to make inference in a divisive GP model to perform nonstationary regression, including heteroscedastic noise cases. The log-concavity of the likelihood ensures a unimodal posterior and makes that the Laplace approximation converges to a unique maximum. The characteristics of the likelihood also allow to obtain accurate posterior approximations when compared to the Expectation Propagation (EP) approximations and the asymptotically exact posterior provided by a Markov Chain Monte Carlo implementation with Elliptical Slice Sampling (ESS), but at a reduced computational load with respect to both, EP and ESS. PMID:26890623
Computed tomography perfusion imaging denoising using Gaussian process regression
NASA Astrophysics Data System (ADS)
Zhu, Fan; Carpenter, Trevor; Rodriguez Gonzalez, David; Atkinson, Malcolm; Wardlaw, Joanna
2012-06-01
Brain perfusion weighted images acquired using dynamic contrast studies have an important clinical role in acute stroke diagnosis and treatment decisions. However, computed tomography (CT) images suffer from low contrast-to-noise ratios (CNR) as a consequence of the limitation of the exposure to radiation of the patient. As a consequence, the developments of methods for improving the CNR are valuable. The majority of existing approaches for denoising CT images are optimized for 3D (spatial) information, including spatial decimation (spatially weighted mean filters) and techniques based on wavelet and curvelet transforms. However, perfusion imaging data is 4D as it also contains temporal information. Our approach using Gaussian process regression (GPR), which takes advantage of the temporal information, to reduce the noise level. Over the entire image, GPR gains a 99% CNR improvement over the raw images and also improves the quality of haemodynamic maps allowing a better identification of edges and detailed information. At the level of individual voxel, GPR provides a stable baseline, helps us to identify key parameters from tissue time-concentration curves and reduces the oscillations in the curve. GPR is superior to the comparable techniques used in this study.
Computed tomography perfusion imaging denoising using gaussian process regression.
Zhu, Fan; Carpenter, Trevor; Rodriguez Gonzalez, David; Atkinson, Malcolm; Wardlaw, Joanna
2012-06-21
Brain perfusion weighted images acquired using dynamic contrast studies have an important clinical role in acute stroke diagnosis and treatment decisions. However, computed tomography (CT) images suffer from low contrast-to-noise ratios (CNR) as a consequence of the limitation of the exposure to radiation of the patient. As a consequence, the developments of methods for improving the CNR are valuable. The majority of existing approaches for denoising CT images are optimized for 3D (spatial) information, including spatial decimation (spatially weighted mean filters) and techniques based on wavelet and curvelet transforms. However, perfusion imaging data is 4D as it also contains temporal information. Our approach using gaussian process regression (GPR), which takes advantage of the temporal information, to reduce the noise level. Over the entire image, GPR gains a 99% CNR improvement over the raw images and also improves the quality of haemodynamic maps allowing a better identification of edges and detailed information. At the level of individual voxel, GPR provides a stable baseline, helps us to identify key parameters from tissue time-concentration curves and reduces the oscillations in the curve. GPR is superior to the comparable techniques used in this study. PMID:22617159
Partial removal of correlated noise in thermal imagery
Borel, C.C.; Cooke, B.J.; Laubscher, B.E.
1996-04-01
Correlated noise occurs in many imaging systems such as scanners and push-broom imagers. The sources of correlated noise can be from the detectors, pre-amplifiers and sampling circuits. Correlated noise appears as streaking along the scan direction of a scanner or in the along track direction of a push-broom imager. We have developed algorithms to simulate correlated noise and pre-filter to reduce the amount of streaking while not destroying the scene content. The pre- filter in the Fourier domain consists of the product of two filters. One filter models the correlated noise spectrum, the other is a windowing function e.g. Gaussian or Hanning window with variable width to block high frequency noise away from the origin of the Fourier Transform of the image data. We have optimized the filter parameters for various scenes and find improvements of the RMS error of the original minus the pre-filtered noisy image.
Noise Intensity-Intensity Correlations and the Fourth Cumulant of Photo-assisted Shot Noise
Forgues, Jean-Charles; Sane, Fatou Bintou; Blanchard, Simon; Spietz, Lafe; Lupien, Christian; Reulet, Bertrand
2013-01-01
We report the measurement of the fourth cumulant of current fluctuations in a tunnel junction under both dc and ac (microwave) excitation. This probes the non-Gaussian character of photo-assisted shot noise. Our measurement reveals the existence of correlations between noise power measured at two different frequencies, which corresponds to two-mode intensity correlations in optics. We observe positive correlations, i.e. photon bunching, which exist only for certain relations between the excitation frequency and the two detection frequencies, depending on the dc bias of the sample. PMID:24100407
Noise intensity-intensity correlations and the fourth cumulant of photo-assisted shot noise.
Forgues, Jean-Charles; Sane, Fatou Bintou; Blanchard, Simon; Spietz, Lafe; Lupien, Christian; Reulet, Bertrand
2013-01-01
We report the measurement of the fourth cumulant of current fluctuations in a tunnel junction under both dc and ac (microwave) excitation. This probes the non-Gaussian character of photo-assisted shot noise. Our measurement reveals the existence of correlations between noise power measured at two different frequencies, which corresponds to two-mode intensity correlations in optics. We observe positive correlations, i.e. photon bunching, which exist only for certain relations between the excitation frequency and the two detection frequencies, depending on the dc bias of the sample. PMID:24100407
Interim prediction method for low frequency core engine noise
NASA Technical Reports Server (NTRS)
Huff, R. G.; Clark, B. J.; Dorsch, R. G.
1974-01-01
A literature survey on low-frequency core engine noise is presented. Possible sources of low frequency internally generated noise in core engines are discussed with emphasis on combustion and component scrubbing noise. An interim method is recommended for predicting low frequency core engine noise that is dominant when jet velocities are low. Suggestions are made for future research on low frequency core engine noise that will aid in improving the prediction method and help define possible additional internal noise sources.
Partially polarized Gaussian Schell-model beams
NASA Astrophysics Data System (ADS)
Gori, F.; Santarsiero, M.; Piquero, G.; Borghi, R.; Mondello, A.; Simon, R.
2001-01-01
We consider a class of beams that are both partially polarized and partially coherent from the spatial standpoint. They are characterized by a correlation matrix whose elements have the same form as the mutual intensity of a Gaussian Schell-model beam. We focus our attention on those beams that would appear identical to ordinary Gaussian Schell-model beams in a scalar treatment. After establishing some inequalities that limit the choice of the matrix parameters, we study the main effects of propagation. Starting from the source plane, in which the beam is assumed to be uniformly polarized, we find that in the course of propagation the degree of polarization generally becomes non-uniform across a typical section of the beam. Furthermore, we find that the intensity distribution at the output of an arbitrarily oriented linear polarizer is Gaussian shaped at the source plane whereas it can be quite different at other planes.
Renyi entropy measures of heart rate Gaussianity.
Lake, Douglas E
2006-01-01
Sample entropy and approximate entropy are measures that have been successfully utilized to study the deterministic dynamics of heart rate (HR). A complementary stochastic point of view and a heuristic argument using the Central Limit Theorem suggests that the Gaussianity of HR is a complementary measure of the physiological complexity of the underlying signal transduction processes. Renyi entropy (or q-entropy) is a widely used measure of Gaussianity in many applications. Particularly important members of this family are differential (or Shannon) entropy (q = 1) and quadratic entropy (q = 2). We introduce the concepts of differential and conditional Renyi entropy rate and, in conjunction with Burg's theorem, develop a measure of the Gaussianity of a linear random process. Robust algorithms for estimating these quantities are presented along with estimates of their standard errors. PMID:16402599
Index distribution of gaussian random matrices.
Majumdar, Satya N; Nadal, Céline; Scardicchio, Antonello; Vivo, Pierpaolo
2009-11-27
We compute analytically, for large N, the probability distribution of the number of positive eigenvalues (the index N+) of a random N x N matrix belonging to Gaussian orthogonal (beta=1), unitary (beta=2) or symplectic (beta=4) ensembles. The distribution of the fraction of positive eigenvalues c=N+/N scales, for large N, as P(c,N) approximately = exp[-betaN(2)Phi(c)] where the rate function Phi(c), symmetric around c=1/2 and universal (independent of beta), is calculated exactly. The distribution has non-Gaussian tails, but even near its peak at c=1/2 it is not strictly Gaussian due to an unusual logarithmic singularity in the rate function. PMID:20366083
Majorization preservation of Gaussian bosonic channels
NASA Astrophysics Data System (ADS)
Jabbour, Michael G.; García-Patrón, Raúl; Cerf, Nicolas J.
2016-07-01
It is shown that phase-insensitive Gaussian bosonic channels are majorization-preserving over the set of passive states of the harmonic oscillator. This means that comparable passive states under majorization are transformed into equally comparable passive states by any phase-insensitive Gaussian bosonic channel. Our proof relies on a new preorder relation called Fock-majorization, which coincides with regular majorization for passive states but also induces another order relation in terms of mean boson number, thereby connecting the concepts of energy and disorder of a quantum state. The consequences of majorization preservation are discussed in the context of the broadcast communication capacity of Gaussian bosonic channels. Because most of our results are independent of the specific nature of the system under investigation, they could be generalized to other quantum systems and Hamiltonians, providing a new tool that may prove useful in quantum information theory and especially quantum thermodynamics.
Gaussian state for the bouncing quantum cosmology
NASA Astrophysics Data System (ADS)
Mielczarek, Jakub; Piechocki, Włodzimierz
2012-10-01
We present results concerning propagation of the Gaussian state across the cosmological quantum bounce. The reduced phase space quantization of loop quantum cosmology is applied to the Friedman-Robertson-Walker universe with a free massless scalar field. Evolution of quantum moments of the canonical variables is investigated. The covariance turns out to be a monotonic function so it may be used as an evolution parameter having quantum origin. We show that for the Gaussian state the Universe is least quantum at the bounce. We propose explanation of this counter-intuitive feature using the entropy of squeezing. The obtained time dependence of entropy is in agreement with qualitative predictions based on von Neumann entropy for mixed states. We show that, for the considered Gaussian state, semiclassicality is preserved across the bounce, so there is no cosmic forgetfulness.
Gaussian beam photothermal single particle microscopy.
Selmke, Markus; Braun, Marco; Cichos, Frank
2012-10-01
We explore the intuitive lensing picture of laser-heated nanoparticles occurring in single particle photothermal (PT) microscopy. The effective focal length of the thermal lens (TL) is derived from a ray-optics treatment and used to transform the probing focused Gaussian beam with ABCD Gaussian matrix optics. The relative PT signal is obtained from the relative beam-waist change far from the TL. The analytical expression is semiquantitative, capable of describing the entire phenomenology of single particle PT microscopy, and shows that the signal is the product of the point-spread functions of the involved lasers times a linear function of the axial coordinate. The presented particularly simple and intuitive Gaussian beam lensing picture compares favorably to the experimental results for 60 nm gold nanoparticles and provides the prescription for optimum setup calibration. PMID:23201674
Tilted Gaussian beam propagation in inhomogeneous media.
Hadad, Yakir; Melamed, Timor
2010-08-01
The present work is concerned with applying a ray-centered non-orthogonal coordinate system which is a priori matched to linearly-phased localized aperture field distributions. The resulting beam-waveobjects serve as the building blocks for beam-type spectral expansions of aperture fields in 2D inhomogeneous media that are characterized by a generic wave-velocity profile. By applying a rigorous paraxial-asymptotic analysis, a novel parabolic wave equation is obtained and termed "Non-orthogonal domain parabolic equation"--NoDope. Tilted Gaussian beams, which are exact solutions to this equation, match Gaussian aperture distributions over a plane that is tilted with respect to the beam-axes initial directions. A numerical example, which demonstrates the enhanced accuracy of the tilted Gaussian beams over the conventional ones, is presented as well. PMID:20686589
Ab initio molar volumes and Gaussian radii.
Parsons, Drew F; Ninham, Barry W
2009-02-12
Ab initio molar volumes are calculated and used to derive radii for ions and neutral molecules using a spatially diffuse model of the electron distribution with Gaussian spread. The Gaussian radii obtained can be used for computation of nonelectrostatic ion-ion dispersion forces that underlie Hofmeister specific ion effects. Equivalent hard-sphere radii are also derived, and these are in reasonable agreement with crystalline ionic radii. The Born electrostatic self-energy is derived for a Gaussian model of the electronic charge distribution. It is shown that the ionic volumes used in electrostatic calculations of strongly hydrated cosmotropic ions ought best to include the first hydration shell. Ionic volumes for weakly hydrated chaotropic metal cations should exclude electron overlap (in electrostatic calculations). Spherical radii are calculated as well as nonisotropic ellipsoidal radii for nonspherical ions, via their nonisotropic static polarizability tensors. PMID:19140766
Informationally complete sets of Gaussian measurements
NASA Astrophysics Data System (ADS)
Kiukas, Jukka; Schultz, Jussi
2013-12-01
We prove the necessary and sufficient conditions for the informational completeness of an arbitrary set of Gaussian observables on continuous variable systems with a finite number of degrees of freedom. In particular, we show that an informationally complete set either contains a single informationally complete observable, or includes infinitely many observables. We show that for a single informationally complete observable, the minimal outcome space is the phase space, and the corresponding probability distribution can always be obtained from the quantum optical Q-function by linear postprocessing and Gaussian convolution, in a suitable symplectic coordinatization of the phase space. In the case of projection valued Gaussian observables, e.g., generalized field quadratures, we show that an informationally complete set of observables is necessarily infinite. Finally, we generalize the treatment to the case where the measurement coupling is given by a general linear bosonic channel, and characterize informational completeness for an arbitrary set of the associated observables.
CMB non-gaussianity from vector fields
Peloso, Marco
2014-01-01
The Planck satellite has recently measured the CMB temperature anisotropies with unprecedented accuracy, and it has provided strong bounds on primordial non-gaussianity. Such bounds constrain models of inflation, and mechanisms that produce the primordial perturbations. We discuss the non-gaussian signatures from the interactions of the inflation φ with spin-1 fields. We study the two different cases in which the inflaton is (i) a pseudo-scalar field with a (φ)/(fa) F·F interaction with a vector field, and (ii) a scalar field with a f (φ)F² interaction. In the first case we obtain the strong limit f{sub a} ≥ 10¹⁶GeV on the decay constant. In the second case, specific choices of the function f (φ) can lead to a non-gaussianity with a characteristic shape not encountered in standard models of scalar field inflation, and which has also been constrained by Planck.
Index Distribution of Gaussian Random Matrices
Majumdar, Satya N.; Nadal, Celine; Scardicchio, Antonello; Vivo, Pierpaolo
2009-11-27
We compute analytically, for large N, the probability distribution of the number of positive eigenvalues (the index N{sub +}) of a random NxN matrix belonging to Gaussian orthogonal (beta=1), unitary (beta=2) or symplectic (beta=4) ensembles. The distribution of the fraction of positive eigenvalues c=N{sub +}/N scales, for large N, as P(c,N){approx_equal}exp[-betaN{sup 2}PHI(c)] where the rate function PHI(c), symmetric around c=1/2 and universal (independent of beta), is calculated exactly. The distribution has non-Gaussian tails, but even near its peak at c=1/2 it is not strictly Gaussian due to an unusual logarithmic singularity in the rate function.
NASA Astrophysics Data System (ADS)
Mazer, Susan
2005-09-01
The argument is made that design does not stop when the fixed architectural and acoustical components are in place. Spaces live and breathe with the people who reside in them. Research and examples are presented that show that noise, auditory clutter, thrives on itself in hospitals. Application of the Lombard reflex studies fit into the hospital setting, but do not offer solutions as to how one might reduce the impact. In addition, the basis for looking at the noise component as a physical as well cultural dynamic will be addressed. Whether the result of the wrong conversation in the wrong place or the right conversation in an unfortunate place, talk mixed with sounds of technology is shown to cause its own symptoms. From heightened anxiety and stress to medical errors, staff burnout, or HIPAA violations, the case is made that noise is pandemic in hospitals and demands financial and operational investment. An explanation of how to reduce noise by design of the dynamic environment - equipment, technology, staff protocols is also provided.
Semisupervised Gaussian Process for Automated Enzyme Search.
Mellor, Joseph; Grigoras, Ioana; Carbonell, Pablo; Faulon, Jean-Loup
2016-06-17
Synthetic biology is today harnessing the design of novel and greener biosynthesis routes for the production of added-value chemicals and natural products. The design of novel pathways often requires a detailed selection of enzyme sequences to import into the chassis at each of the reaction steps. To address such design requirements in an automated way, we present here a tool for exploring the space of enzymatic reactions. Given a reaction and an enzyme the tool provides a probability estimate that the enzyme catalyzes the reaction. Our tool first considers the similarity of a reaction to known biochemical reactions with respect to signatures around their reaction centers. Signatures are defined based on chemical transformation rules by using extended connectivity fingerprint descriptors. A semisupervised Gaussian process model associated with the similar known reactions then provides the probability estimate. The Gaussian process model uses information about both the reaction and the enzyme in providing the estimate. These estimates were validated experimentally by the application of the Gaussian process model to a newly identified metabolite in Escherichia coli in order to search for the enzymes catalyzing its associated reactions. Furthermore, we show with several pathway design examples how such ability to assign probability estimates to enzymatic reactions provides the potential to assist in bioengineering applications, providing experimental validation to our proposed approach. To the best of our knowledge, the proposed approach is the first application of Gaussian processes dealing with biological sequences and chemicals, the use of a semisupervised Gaussian process framework is also novel in the context of machine learning applied to bioinformatics. However, the ability of an enzyme to catalyze a reaction depends on the affinity between the substrates of the reaction and the enzyme. This affinity is generally quantified by the Michaelis constant KM
Electrical noise in Circular Gate Tunnel FET in presence of interface traps
NASA Astrophysics Data System (ADS)
Goswami, Rupam; Bhowmick, Brinda; Baishya, Srimanta
2015-10-01
This paper presents a novel architecture of Tunnel Field Effect Transistor (TFET) with a circular gate and reports the effect of electrical noise on the device by comparing the results with a hetero-junction TFET. TCAD simulations involving uniform and Gaussian trap distribution conclude that the proposed Circular Gate TFET shows lesser values of noise spectral density than hetero-junction TFET. At lower frequencies, both generation-recombination noise and flicker noise dominate; at mid frequencies, only flicker noise contributes and at higher frequencies, diffusion noise dominates. Drain current in Circular Gate TFET is more prone to traps than Hetero-Junction TFET. The use of gate-drain underlap enhances the cut-off frequency of the CG-TFET in presence of Gaussian traps and makes it suitable for digital applications.
N-body simulations with generic non-Gaussian initial conditions II: halo bias
NASA Astrophysics Data System (ADS)
Wagner, Christian; Verde, Licia
2012-03-01
We present N-body simulations for generic non-Gaussian initial conditions with the aim of exploring and modelling the scale-dependent halo bias. This effect is evident on very large scales requiring large simulation boxes. In addition, the previously available prescription to implement generic non-Gaussian initial conditions has been improved to keep under control higher-order terms which were spoiling the power spectrum on large scales. We pay particular attention to the differences between physical, inflation-motivated primordial bispectra and their factorizable templates, and to the operational definition of the non-Gaussian halo bias (which has both a scale-dependent and an approximately scale-independent contributions). We find that analytic predictions for both the non-Gaussian halo mass function and halo bias work well once a fudge factor (which was introduced before but still lacks convincing physical explanation) is calibrated on simulations. The halo bias remains therefore an extremely promising tool to probe primordial non-Gaussianity and thus to give insights into the physical mechanism that generated the primordial perturbations. The simulation outputs and tables of the analytic predictions will be made publicly available via the non-Gaussian comparison project web site http://icc.ub.edu/~liciaverde/NGSCP.html.
Non-Gaussian Analysis of Turbulent Boundary Layer Fluctuating Pressure on Aircraft Skin Panels
NASA Technical Reports Server (NTRS)
Rizzi, Stephen A.; Steinwolf, Alexander
2005-01-01
The purpose of the study is to investigate the probability density function (PDF) of turbulent boundary layer fluctuating pressures measured on the outer sidewall of a supersonic transport aircraft and to approximate these PDFs by analytical models. Experimental flight results show that the fluctuating pressure PDFs differ from the Gaussian distribution even for standard smooth surface conditions. The PDF tails are wider and longer than those of the Gaussian model. For pressure fluctuations in front of forward-facing step discontinuities, deviations from the Gaussian model are more significant and the PDFs become asymmetrical. There is a certain spatial pattern of the skewness and kurtosis behavior depending on the distance upstream from the step. All characteristics related to non-Gaussian behavior are highly dependent upon the distance from the step and the step height, less dependent on aircraft speed, and not dependent on the fuselage location. A Hermite polynomial transform model and a piecewise-Gaussian model fit the flight data well both for the smooth and stepped conditions. The piecewise-Gaussian approximation can be additionally regarded for convenience in usage after the model is constructed.
Karakida, Ryo; Okada, Masato; Amari, Shun-Ichi
2016-07-01
The restricted Boltzmann machine (RBM) is an essential constituent of deep learning, but it is hard to train by using maximum likelihood (ML) learning, which minimizes the Kullback-Leibler (KL) divergence. Instead, contrastive divergence (CD) learning has been developed as an approximation of ML learning and widely used in practice. To clarify the performance of CD learning, in this paper, we analytically derive the fixed points where ML and CDn learning rules converge in two types of RBMs: one with Gaussian visible and Gaussian hidden units and the other with Gaussian visible and Bernoulli hidden units. In addition, we analyze the stability of the fixed points. As a result, we find that the stable points of CDn learning rule coincide with those of ML learning rule in a Gaussian-Gaussian RBM. We also reveal that larger principal components of the input data are extracted at the stable points. Moreover, in a Gaussian-Bernoulli RBM, we find that both ML and CDn learning can extract independent components at one of stable points. Our analysis demonstrates that the same feature components as those extracted by ML learning are extracted simply by performing CD1 learning. Expanding this study should elucidate the specific solutions obtained by CD learning in other types of RBMs or in deep networks. PMID:27131468
Experimental characterization of Gaussian quantum-communication channels
Di Guglielmo, James; Hage, Boris; Franzen, Alexander; Schnabel, Roman; Fiurasek, Jaromir
2007-07-15
We present a full experimental characterization of continuous-variable quantum-communication channels established by shared entanglement together with local operations and classical communication. The resulting teleportation channel was fully characterized by measuring all elements of the covariance matrix of the shared two-mode squeezed Gaussian state. From the experimental data we determined the lower bound to the quantum channel capacity, the teleportation fidelity of coherent states, and the logarithmic negativity and purity of the shared state. Additionally, a positive secret key rate was obtained for two of the established channels.
Fresnel filtering of Gaussian beams in microcavities.
Shinohara, Susumu; Harayama, Takahisa; Fukushima, Takehiro
2011-03-15
We study the output from the modes described by the superposition of Gaussian beams confined in the quasi-stadium microcavities. We experimentally observe the deviation from Snell's law in the output when the incident angle of the Gaussian beam at the cavity interface is near the critical angle for total internal reflection, providing direct experimental evidence on the Fresnel filtering. The theory of the Fresnel filtering for a planar interface qualitatively reproduces experimental data, and a discussion is given on small deviation between the measured data and the theory. PMID:21403763
Entropic characterization of separability in Gaussian states
Sudha; Devi, A. R. Usha; Rajagopal, A. K.
2010-02-15
We explore separability of bipartite divisions of mixed Gaussian states based on the positivity of the Abe-Rajagopal (AR) q-conditional entropy. The AR q-conditional entropic characterization provide more stringent restrictions on separability (in the limit q{yields}{infinity}) than that obtained from the corresponding von Neumann conditional entropy (q=1 case)--similar to the situation in finite dimensional states. Effectiveness of this approach, in relation to the results obtained by partial transpose criterion, is explicitly analyzed in three illustrative examples of two-mode Gaussian states of physical significance.
Invariant measures on multimode quantum Gaussian states
Lupo, C.; Mancini, S.; De Pasquale, A.; Facchi, P.; Florio, G.; Pascazio, S.
2012-12-15
We derive the invariant measure on the manifold of multimode quantum Gaussian states, induced by the Haar measure on the group of Gaussian unitary transformations. To this end, by introducing a bipartition of the system in two disjoint subsystems, we use a parameterization highlighting the role of nonlocal degrees of freedom-the symplectic eigenvalues-which characterize quantum entanglement across the given bipartition. A finite measure is then obtained by imposing a physically motivated energy constraint. By averaging over the local degrees of freedom we finally derive the invariant distribution of the symplectic eigenvalues in some cases of particular interest for applications in quantum optics and quantum information.
NASA Astrophysics Data System (ADS)
Ji, Se-Wan; Kim, M. S.; Nha, Hyunchul
2015-04-01
It is a topic of fundamental and practical importance how a quantum correlated state can be reliably distributed through a noisy channel for quantum information processing. The concept of quantum steering recently defined in a rigorous manner is relevant to study it under certain circumstances and here we address quantum steerability of Gaussian states to this aim. In particular, we attempt to reformulate the criterion for Gaussian steering in terms of local and global purities and show that it is sufficient and necessary for the case of steering a 1-mode system by an N-mode system. It subsequently enables us to reinforce a strong monogamy relation under which only one party can steer a local system of 1-mode. Moreover, we show that only a negative partial-transpose state can manifest quantum steerability by Gaussian measurements in relation to the Peres conjecture. We also discuss our formulation for the case of distributing a two-mode squeezed state via one-way quantum channels making dissipation and amplification effects, respectively. Finally, we extend our approach to include non-Gaussian measurements, more precisely, all orders of higher-order squeezing measurements, and find that this broad set of non-Gaussian measurements is not useful to demonstrate steering for Gaussian states beyond Gaussian measurements.
Construction Noise Decreases Reproductive Efficiency in Mice
Rasmussen, Skye; Glickman, Gary; Norinsky, Rada; Quimby, Fred W; Tolwani, Ravi J
2009-01-01
Excessive noise is well known to impair rodent health. To better understand the effect of construction noise and to establish effective noise limits during a planned expansion of our vivarium, we analyzed the effects of construction noise on mouse gestation and neonatal growth. Our hypothesis was that high levels of construction noise would reduce the number of live births and retard neonatal growth. Female Swiss Webster mice were individually implanted with 15 B6CBAF1/J embryos and then exposed to 70- and 90-dBA concrete saw cutting noise samples at defined time points during gestation. In addition, groups of mice with litters were exposed to noise at 70, 80, or 90 dBA for 1 h daily during the first week after parturition. Litter size, birth weight, incidence of stillborn pups, and rate of neonatal weight gain were analyzed. Noise decreased reproductive efficiency by decreasing live birth rates and increasing the number of stillborn pups. PMID:19653943
Construction noise decreases reproductive efficiency in mice.
Rasmussen, Skye; Glickman, Gary; Norinsky, Rada; Quimby, Fred W; Tolwani, Ravi J
2009-07-01
Excessive noise is well known to impair rodent health. To better understand the effect of construction noise and to establish effective noise limits during a planned expansion of our vivarium, we analyzed the effects of construction noise on mouse gestation and neonatal growth. Our hypothesis was that high levels of construction noise would reduce the number of live births and retard neonatal growth. Female Swiss Webster mice were individually implanted with 15 B6CBAF1/J embryos and then exposed to 70- and 90-dBA concrete saw cutting noise samples at defined time points during gestation. In addition, groups of mice with litters were exposed to noise at 70, 80, or 90 dBA for 1 h daily during the first week after parturition. Litter size, birth weight, incidence of stillborn pups, and rate of neonatal weight gain were analyzed. Noise decreased reproductive efficiency by decreasing live birth rates and increasing the number of stillborn pups. PMID:19653943
A real-time multi-scale 2D Gaussian filter based on FPGA
NASA Astrophysics Data System (ADS)
Luo, Haibo; Gai, Xingqin; Chang, Zheng; Hui, Bin
2014-11-01
Multi-scale 2-D Gaussian filter has been widely used in feature extraction (e.g. SIFT, edge etc.), image segmentation, image enhancement, image noise removing, multi-scale shape description etc. However, their computational complexity remains an issue for real-time image processing systems. Aimed at this problem, we propose a framework of multi-scale 2-D Gaussian filter based on FPGA in this paper. Firstly, a full-hardware architecture based on parallel pipeline was designed to achieve high throughput rate. Secondly, in order to save some multiplier, the 2-D convolution is separated into two 1-D convolutions. Thirdly, a dedicate first in first out memory named as CAFIFO (Column Addressing FIFO) was designed to avoid the error propagating induced by spark on clock. Finally, a shared memory framework was designed to reduce memory costs. As a demonstration, we realized a 3 scales 2-D Gaussian filter on a single ALTERA Cyclone III FPGA chip. Experimental results show that, the proposed framework can computing a Multi-scales 2-D Gaussian filtering within one pixel clock period, is further suitable for real-time image processing. Moreover, the main principle can be popularized to the other operators based on convolution, such as Gabor filter, Sobel operator and so on.
A Reflective Gaussian Coronagraph for Extreme Adaptive Optics: Laboratory Performance
NASA Astrophysics Data System (ADS)
Park, Ryeojin; Close, Laird M.; Siegler, Nick; Nielsen, Eric L.; Stalcup, Thomas
2006-11-01
We report laboratory results of a coronagraphic test bench to assess the intensity reduction differences between a ``Gaussian'' tapered focal plane coronagraphic mask and a classical hard-edged ``top hat'' function mask at extreme adaptive optics (ExAO) Strehl ratios of ~94%. However, unlike a traditional coronagraph design, we insert a reflective focal plane mask at 45° to the optical axis. We also use an intermediate secondary mask (mask 2) before a final image in order to block additional mask-edge-diffracted light. The test bench simulates the optical train of ground-based telescopes (in particular, the 8.1 m Gemini North Telescope). It includes one spider vane, different mask radii (r = 1.9λ/D, 3.7λ/D, and 7.4λ/D), and two types of reflective focal plane masks (hard-edged top-hat and Gaussian tapered profiles). In order to investigate the relative performance of these competing coronagraphic designs with regard to extrasolar planet detection sensitivity, we utilize the simulation of realistic extrasolar planet populations (Nielsen et al.). With an appropriate translation of our laboratory results to expected telescope performance, a Gaussian tapered mask radius of 3.7λ/D with an additional mask (mask 2) performs best (highest planet detection sensitivity). For a full survey with this optimal design, the simulation predicts that ~30% more planets would be detected than with a top-hat function mask of similar size with mask 2. Using the best design, the point contrast ratio between the stellar point-spread function (PSF) peak and the coronagraphic PSF at 10λ/D (0.4" in the H band if D = 8.1 m) is ~10 times higher than a classical Lyot top-hat coronagraph. Hence, we find that a Gaussian apodized mask with an additional blocking mask is superior (~10 times higher contrast) to the use of a classical Lyot coronagraph for ExAO-like Strehl ratios.
Noise-assisted estimation of attractor invariants
NASA Astrophysics Data System (ADS)
Restrepo, Juan F.; Schlotthauer, Gastón
2016-07-01
In this article, the noise-assisted correlation integral (NCI) is proposed. The purpose of the NCI is to estimate the invariants of a dynamical system, namely the correlation dimension (D ), the correlation entropy (K2), and the noise level (σ ). This correlation integral is induced by using random noise in a modified version of the correlation algorithm, i.e., the noise-assisted correlation algorithm. We demonstrate how the correlation integral by Grassberger et al. and the Gaussian kernel correlation integral (GCI) by Diks can be thought of as special cases of the NCI. A third particular case is the U -correlation integral proposed herein, from which we derived coarse-grained estimators of the correlation dimension (DmU), the correlation entropy (KmU), and the noise level (σmU). Using time series from the Henon map and the Mackey-Glass system, we analyze the behavior of these estimators under different noise conditions and data lengths. The results show that the estimators DmU and σmU behave in a similar manner to those based on the GCI. However, for the calculation of K2, the estimator KmU outperforms its GCI-based counterpart. On the basis of the behavior of these estimators, we have proposed an automatic algorithm to find D ,K2, and σ from a given time series. The results show that by using this approach, we are able to achieve statistically reliable estimations of those invariants.
Estimating noise and information for multispectral imagery
NASA Astrophysics Data System (ADS)
Aiazzi, Bruno; Alparone, Luciano; Barducci, Alessandro; Baronti, Stefano; Pippi, Ivan
2002-03-01
We focus on reliably estimating the information conveyed to a user by multispectral image data. The goal is establishing the extent to which an increase in spectral resolution can increase the amount of usable information. As a matter of fact, a trade- off exists between spatial and spectral resolution, due to physical constraints of sensors imaging with a prefixed SNR. After describing some methods developed for automatically estimating the variance of the noise introduced by multispectral imagers, lossless data compression is exploited to measure the useful information content of the multispectral data. In fact, the bit rate achieved by the reversible compression process takes into account both the contribution of the 'observation' noise, i.e., information regarded as statistical uncertainty, whose relevance is null to a user, and the intrinsic information of hypothetically noise free multispectral data. An entropic model of the image source is defined and, once the standard deviation of the noise, assumed to be white and Gaussian, has been preliminarily estimated, such a model is inverted to yield an estimate of the information content of the noise-free source from the code rate. Results of both noise and information assessment are reported and discussed on synthetic noisy images and on Landsat thematic mapper (TM) data.
Stochastic noise in atomic force microscopy.
Labuda, Aleksander; Lysy, Martin; Paul, William; Miyahara, Yoichi; Grütter, Peter; Bennewitz, Roland; Sutton, Mark
2012-09-01
Having reached the quantum and thermodynamic limits of detection, atomic force microscopy (AFM) experiments are routinely being performed at the fundamental limit of signal to noise. A critical understanding of the statistical properties of noise leads to more accurate interpretation of data, optimization of experimental protocols, advancements in instrumentation, and new measurement techniques. Furthermore, accurate simulation of cantilever dynamics requires knowledge of stochastic behavior of the system, as stochastic noise may exceed the deterministic signals of interest, and even dominate the outcome of an experiment. In this article, the power spectral density (PSD), used to quantify stationary stochastic processes, is introduced in the context of a thorough noise analysis of the light source used to detect cantilever deflections. The statistical properties of PSDs are then outlined for various stationary, nonstationary, and deterministic noise sources in the context of AFM experiments. Following these developments, a method for integrating PSDs to provide an accurate standard deviation of linear measurements is described. Lastly, a method for simulating stochastic Gaussian noise from any arbitrary power spectral density is presented. The result demonstrates that mechanical vibrations of the AFM can cause a logarithmic velocity dependence of friction and induce multiple slip events in the atomic stick-slip process, as well as predicts an artifactual temperature dependence of friction measured by AFM. PMID:23030863
Encoding information using Laguerre Gaussian modes
NASA Astrophysics Data System (ADS)
Trichili, Abderrahmen; Dudley, Angela; Ben Salem, Amine; Ndagano, Bienvenu; Zghal, Mourad; Forbes, Andrew
2015-08-01
We experimentally demonstrate an information encoding protocol using the two degrees of freedom of Laguerre Gaussian modes having different radial and azimuthal components. A novel method, based on digital holography, for information encoding and decoding using different data transmission scenarios is presented. The effects of the atmospheric turbulence introduced in free space communication is discussed as well.
The Gaussian entropy of fermionic systems
Prokopec, Tomislav; Schmidt, Michael G.; Weenink, Jan
2012-12-15
We consider the entropy and decoherence in fermionic quantum systems. By making a Gaussian Ansatz for the density operator of a collection of fermions we study statistical 2-point correlators and express the entropy of a system fermion in terms of these correlators. In a simple case when a set of N thermalised environmental fermionic oscillators interacts bi-linearly with the system fermion we can study its time dependent entropy, which also represents a quantitative measure for decoherence and classicalization. We then consider a relativistic fermionic quantum field theory and take a mass mixing term as a simple model for the Yukawa interaction. It turns out that even in this Gaussian approximation, the fermionic system decoheres quite effectively, such that in a large coupling and high temperature regime the system field approaches the temperature of the environmental fields. - Highlights: Black-Right-Pointing-Pointer We construct the Gaussian density operator for relativistic fermionic systems. Black-Right-Pointing-Pointer The Gaussian entropy of relativistic fermionic systems is described in terms of 2-point correlators. Black-Right-Pointing-Pointer We explicitly show the growth of entropy for fermionic fields mixing with a thermal fermionic environment.
Diffusion of Super-Gaussian Profiles
ERIC Educational Resources Information Center
Rosenberg, C.-J.; Anderson, D.; Desaix, M.; Johannisson, P.; Lisak, M.
2007-01-01
The present analysis describes an analytically simple and systematic approximation procedure for modelling the free diffusive spreading of initially super-Gaussian profiles. The approach is based on a self-similar ansatz for the evolution of the diffusion profile, and the parameter functions involved in the modelling are determined by suitable…
Characterization of impulse noise and analysis of its effect upon correlation receivers
NASA Technical Reports Server (NTRS)
Houts, R. C.; Moore, J. D.
1971-01-01
A noise model is formulated to describe the impulse noise in many digital systems. A simplified model, which assumes that each noise burst contains a randomly weighted version of the same basic waveform, is used to derive the performance equations for a correlation receiver. The expected number of bit errors per noise burst is expressed as a function of the average signal energy, signal-set correlation coefficient, bit time, noise-weighting-factor variance and probability density function, and a time range function which depends on the crosscorrelation of the signal-set basis functions and the noise waveform. A procedure is established for extending the results for the simplified noise model to the general model. Unlike the performance results for Gaussian noise, it is shown that for impulse noise the error performance is affected by the choice of signal-set basis functions and that Orthogonal signaling is not equivalent to On-Off signaling with the same average energy.
NASA Astrophysics Data System (ADS)
Vonglahn, U. H.
1982-07-01
Calculated engine core noise levels, based on NASA Lewis prediction procedures, for five representative helicopter engines are compared with measured total helicopter noise levels and ICAO helicopter noise certification requirements. Comparisons are made for level flyover and approach procedures. The measured noise levels are generally significantly greater than those predicted for the core noise levels, except for the Sikorsky S-61 and S-64 helicopters. However, the predicted engine core noise levels are generally at or within 3 dB of the ICAO noise rules. Consequently, helicopter engine core noise can be a significant contributor to the overall helicopter noise signature.
NASA Technical Reports Server (NTRS)
Vonglahn, U. H.
1982-01-01
Calculated engine core noise levels, based on NASA Lewis prediction procedures, for five representative helicopter engines are compared with measured total helicopter noise levels and ICAO helicopter noise certification requirements. Comparisons are made for level flyover and approach procedures. The measured noise levels are generally significantly greater than those predicted for the core noise levels, except for the Sikorsky S-61 and S-64 helicopters. However, the predicted engine core noise levels are generally at or within 3 dB of the ICAO noise rules. Consequently, helicopter engine core noise can be a significant contributor to the overall helicopter noise signature.
Airframe noise: A design and operating problem
NASA Technical Reports Server (NTRS)
Hardin, J. C.
1976-01-01
A critical assessment of the state of the art in airframe noise is presented. Full-scale data on the intensity, spectra, and directivity of this noise source are evaluated in light of the comprehensive theory developed by Ffowcs Williams and Hawkings. Vibration of panels on the aircraft is identified as a possible additional source of airframe noise. The present understanding and methods for prediction of other component sources - airfoils, struts, and cavities - are discussed. Operating problems associated with airframe noise as well as potential design methods for airframe noise reduction are identified.
NASA Astrophysics Data System (ADS)
Fidell, Sandy
The primary effects of community noise on residential populations are speech interference, sleep disturbance, and annoyance. This chapter focuses on transportation noise in general and on aircraft noise in particular because aircraft noise is one of the most prominent community noise sources, because airport/community controversies are often the most contentious and widespread, and because industrial and other specialized formsofcommunitynoise generally posemorelocalized problems.
Mukherjee, S; Yao, W
2015-06-15
Purpose: To study different noise-reduction algorithms and to improve the image quality of low dose cone beam CT for patient positioning in radiation therapy. Methods: In low-dose cone-beam CT, the reconstructed image is contaminated with excessive quantum noise. In this study, three well-developed noise reduction algorithms namely, a) penalized weighted least square (PWLS) method, b) split-Bregman total variation (TV) method, and c) compressed sensing (CS) method were studied and applied to the images of a computer–simulated “Shepp-Logan” phantom and a physical CATPHAN phantom. Up to 20% additive Gaussian noise was added to the Shepp-Logan phantom. The CATPHAN phantom was scanned by a Varian OBI system with 100 kVp, 4 ms and 20 mA. For comparing the performance of these algorithms, peak signal-to-noise ratio (PSNR) of the denoised images was computed. Results: The algorithms were shown to have the potential in reducing the noise level for low-dose CBCT images. For Shepp-Logan phantom, an improvement of PSNR of 2 dB, 3.1 dB and 4 dB was observed using PWLS, TV and CS respectively, while for CATPHAN, the improvement was 1.2 dB, 1.8 dB and 2.1 dB, respectively. Conclusion: Penalized weighted least square, total variation and compressed sensing methods were studied and compared for reducing the noise on a simulated phantom and a physical phantom scanned by low-dose CBCT. The techniques have shown promising results for noise reduction in terms of PSNR improvement. However, reducing the noise without compromising the smoothness and resolution of the image needs more extensive research.
NASA Technical Reports Server (NTRS)
Hubbard, Harvey H. (Editor)
1993-01-01
In the conference over 100 papers were presented in eight sessions: (1) Emission: Noise Sources; (2) Physical Phenomena; (3) Noise ControlElements; (4) Vibration and Shock: Generation, Transmission, Isolation, and Reduction; (5) Immission: Physical Aspects of Environmental Noise; (6) Immission: Effects of Noise; (7) Analysis; and (8) Requirements. In addition, the distinguished lecture series included presentations on the High Speed Civil Transport and on research from the United Kingdom on aircraft noise effects.
Shamis, Mira
2013-11-15
We use the supersymmetric formalism to derive an integral formula for the density of states of the Gaussian Orthogonal Ensemble, and then apply saddle-point analysis to give a new derivation of the 1/N-correction to Wigner's law. This extends the work of Disertori on the Gaussian Unitary Ensemble. We also apply our method to the interpolating ensembles of Mehta–Pandey.
Simple noise reduction for diffusion weighted images.
Konishi, Yuto; Kanazawa, Yuki; Usuda, Takatoshi; Matsumoto, Yuki; Hayashi, Hiroaki; Matsuda, Tsuyoshi; Ueno, Junji; Harada, Masafumi
2016-07-01
Our purpose in this study was to reduce the noise in order to improve the SNR of Dw images with high b-value by using two correction schemes. This study was performed with use of phantoms made from water and sucrose at different concentrations, which were 10, 30, and 50 weight percent (wt%). In noise reduction for Dw imaging of the phantoms, we compared two correction schemes that are based on the Rician distribution and the Gaussian distribution. The highest error values for each concentration with use of the Rician distribution scheme were 7.3 % for 10 wt%, 2.4 % for 30 wt%, and 0.1 % for 50 wt%. The highest error values for each concentration with use of the Gaussian distribution scheme were 20.3 % for 10 wt%, 11.6 % for 30 wt%, and 3.4 % for 50 wt%. In Dw imaging, the noise reduction makes it possible to apply the correction scheme of Rician distribution. PMID:26984734
NASA Technical Reports Server (NTRS)
Groeneweg, John F.; Sofrin, Thomas G.; Rice, Edward J.; Gliebe, Phillip R.
1991-01-01
Summarized here are key advances in experimental techniques and theoretical applications which point the way to a broad understanding and control of turbomachinery noise. On the experimental side, the development of effective inflow control techniques makes it possible to conduct, in ground based facilities, definitive experiments in internally controlled blade row interactions. Results can now be valid indicators of flight behavior and can provide a firm base for comparison with analytical results. Inflow control coupled with detailed diagnostic tools such as blade pressure measurements can be used to uncover the more subtle mechanisms such as rotor strut interaction, which can set tone levels for some engine configurations. Initial mappings of rotor wake-vortex flow fields have provided a data base for a first generation semiempirical flow disturbance model. Laser velocimetry offers a nonintrusive method for validating and improving the model. Digital data systems and signal processing algorithms are bringing mode measurement closer to a working tool that can be frequently applied to a real machine such as a turbofan engine. On the analytical side, models of most of the links in the chain from turbomachine blade source to far field observation point have been formulated. Three dimensional lifting surface theory for blade rows, including source noncompactness and cascade effects, blade row transmission models incorporating mode and frequency scattering, and modal radiation calculations, including hybrid numerical-analytical approaches, are tools which await further application.
Bingi, Jayachandra; Murukeshan, Vadakke Matham
2015-01-01
Laser speckle pattern is a granular structure formed due to random coherent wavelet interference and generally considered as noise in optical systems including photolithography. Contrary to this, in this paper, we use the speckle pattern to generate predictable and controlled Gaussian random structures and quasi-random structures photo-lithographically. The random structures made using this proposed speckle lithography technique are quantified based on speckle statistics, radial distribution function (RDF) and fast Fourier transform (FFT). The control over the speckle size, density and speckle clustering facilitates the successful fabrication of black silicon with different surface structures. The controllability and tunability of randomness makes this technique a robust method for fabricating predictable 2D Gaussian random structures and black silicon structures. These structures can enhance the light trapping significantly in solar cells and hence enable improved energy harvesting. Further, this technique can enable efficient fabrication of disordered photonic structures and random media based devices. PMID:26679513
Quantum metrology. Fisher information and entanglement of non-Gaussian spin states.
Strobel, Helmut; Muessel, Wolfgang; Linnemann, Daniel; Zibold, Tilman; Hume, David B; Pezzè, Luca; Smerzi, Augusto; Oberthaler, Markus K
2014-07-25
Entanglement is the key quantum resource for improving measurement sensitivity beyond classical limits. However, the production of entanglement in mesoscopic atomic systems has been limited to squeezed states, described by Gaussian statistics. Here, we report on the creation and characterization of non-Gaussian many-body entangled states. We develop a general method to extract the Fisher information, which reveals that the quantum dynamics of a classically unstable system creates quantum states that are not spin squeezed but nevertheless entangled. The extracted Fisher information quantifies metrologically useful entanglement, which we confirm by Bayesian phase estimation with sub-shot-noise sensitivity. These methods are scalable to large particle numbers and applicable directly to other quantum systems. PMID:25061206
Bingi, Jayachandra; Murukeshan, Vadakke Matham
2015-01-01
Laser speckle pattern is a granular structure formed due to random coherent wavelet interference and generally considered as noise in optical systems including photolithography. Contrary to this, in this paper, we use the speckle pattern to generate predictable and controlled Gaussian random structures and quasi-random structures photo-lithographically. The random structures made using this proposed speckle lithography technique are quantified based on speckle statistics, radial distribution function (RDF) and fast Fourier transform (FFT). The control over the speckle size, density and speckle clustering facilitates the successful fabrication of black silicon with different surface structures. The controllability and tunability of randomness makes this technique a robust method for fabricating predictable 2D Gaussian random structures and black silicon structures. These structures can enhance the light trapping significantly in solar cells and hence enable improved energy harvesting. Further, this technique can enable efficient fabrication of disordered photonic structures and random media based devices. PMID:26679513
NASA Astrophysics Data System (ADS)
Lafollette, Philip A.
1991-06-01
In this study of short-term noise variation in Air Force platforms, we followed two avenues of investigation. First, we applied quantitative measures of variation to individual noise recordings, and compared the results across various aircraft. Some measures used were simple descriptive statistics, but we also measured attenuation obtained by spectral restoration (spectral subtraction), applied to the noise signal alone. The noise attenuation obtained for real aircraft environments was in most cases about the same as predicted theoretically for white Gaussian noise, but in some instances was considerably higher, especially in the presence of propeller noise. Second, we applied the nonparametric Mann-Whitney statistic to test the stationarity of power spectrum estimates on time scales of 200 to 800 ms. There was little or no evidence of nonstationarity in large jet or turboprop aircraft. In fighter aircraft and helicopters, there was some evidence of nonstationarity confined to more or less narrow frequency ranges. The nonstationarity found did not appear to limit the performance of special restoration algorithms. The noise recordings used were taken from the RADC/EEV database of field recordings made in the E-3A, E-4B, EC-135, E-130, P-3C, F-15, F-16, F-4, A-10, HH-53 and Tornado aircraft.
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.
NASA Astrophysics Data System (ADS)
Xiang, Shao-Hua; Wen, Wei; Zhao, Yu-Jing; Song, Ke-Hui
2016-06-01
We characterize the non-Gaussianity of continuous-variable quantum states in terms of the cumulant theory and derive the exact formula of the cumulant of any order for such states. Exploiting the fourth-order cumulant method, we evaluate the quantum non-Gaussianity of two-mode single-photon squeezed Bell states and investigate their dynamics under the influence of two different types of decoherence models. It is shown that in a two-reservoir model, all the fourth-order cumulants of these states are very fragile, while in single-reservoir model, the fourth-order cumulants of one such state are insensitive to thermal noise, showing the time-invariant non-Gaussianity.
NASA Astrophysics Data System (ADS)
Valente, P.; Auyuanet, A.; Barreiro, S.; Failache, H.; Lezama, A.
2015-05-01
We show that the description of light in terms of Stokes operators in combination with the assumption of Gaussian statistics results in a dramatic simplification of the experimental study of fluctuations in the light transmitted through an atomic vapor: no local oscillator is required, the detected quadrature is easily selected by a wave-plate angle, and the complete noise ellipsis reconstruction is obtained via matrix diagonalization. We provide empirical support for the assumption of Gaussian statistics in quasiresonant light transmitted through an 87Rb vapor cell and we illustrate the suggested approach by studying the evolution of the fluctuation ellipsis as a function of laser detuning. Applying the method to two light beams obtained by parting squeezed light in a beam splitter, we have measured the entanglement and quantum Gaussian discord.
A reflective Gaussian coronagraph for ExAO: laboratory performance
NASA Astrophysics Data System (ADS)
Park, Ryeojin; Close, Laird M.; Siegler, Nick; Nielsen, Eric L.; Stalcup, Thomas
2006-06-01
We report laboratory results of a coronagraphic testbed to assess the intensity reduction differences between a "Gaussian" tapered focal plane coronagraphic mask and a classical hard-edged "Top Hat" function mask at Extreme Adaptive Optics (ExAO) Strehl ratios of ~94%. However, unlike a traditional coronagraph design, we insert a reflective focal plane mask at 45 ° to the optical axis and used a "spot of Arago blocker" (axicon stop) before a final image in order to block additional mask edge-diffracted light. The testbed simulates the optical train of ground-based telescopes (in particular the 8.1m Gemini North telescope) and includes one spider vane and different mask radii (r= 1.9λ/D, 3.7λ/D, 7.4λ/D) and two types of reflective focal plane masks (hard-edged "Top Hat" and "Gaussian" tapered profiles). In order to investigate the performance of these competing coronagraphic designs with regard to extra-solar planet detection sensitivity, we utilize the simulation of realistic extra-solar planet populations (Nielsen et al. 2006). With an appropriate translation of our laboratory results to expected telescope performance, a "Gaussian" tapered mask radius of 3.7λ/D with an axicon stop performs best (highest planet detection sensitivity). For a full survey with this optimal design, the simulation predicts ~30% more planets detected compared to a similar sized "Top Hat" function mask with an axicon stop. Using the best design, the "point contrast ratio" between the stellar PSF peak and the coronagraphic PSF at 10λ/D (0.4" in H band if D = 8.1m) is 1.4 x 10 6. This is ~10 times higher than a classical Lyot "Top Hat" coronagraph.
NASA Technical Reports Server (NTRS)
Dittmar, James H.; Elliott, David M.; Jeracki, Robert J.; Moore, Royce D.; Parrott, Tony L.
2000-01-01
A 106 bladed fan with a design takeoff tip speed of 1100 ft/sec was hypothesized as reducing perceived noise because of the shift of the blade passing harmonics to frequencies beyond the perceived noise rating range. A 22 in. model of this Alternative Low Noise Fan, ALNF, was tested in the NASA Glenn 9x 15 Wind Tunnel. 'Me fan was tested with a 7 vane long chord stator assembly and a 70 vane conventional stator assembly in both hard and acoustically treated configurations. In addition a partially treated 7 vane configuration was tested wherein the acoustic material between the 7 long chord stators was made inactive. The noise data from the 106 bladed fan with 7 long chord stators in a hard configuration was shown to be around 4 EPNdB quieter than a low tip speed Allison fan at takeoff and around 5 EPNdB quieter at approach. Although the tone noise behaved as hypothesized, the majority of this noise reduction was from reduced broadband noise related to the large number of rotor blades. This 106 bladed ALNF is a research fan designed to push the technology limits and as such is probably not a practical device with present materials technology. However, a low tip speed fan with around 50 blades would be a practical device and calculations indicate that it could be 2 to 3 EPNdB quieter at takeoff and 3 to 4 EPNdB quieter at approach than the Allison fan. 7 vane data compared with 70 vane data indicated that the tone noise was controlled by rotor wake-stator interaction but that the broadband noise is probably controlled by the interaction of the rotor with incoming flows. A possible multiple pure tone noise reduction technique for a fan/acoustic treatment system was identified. The data from the fully treated configuration showed significant noise reductions over a large frequency range thereby providing a real tribute to this bulk absorber treatment design. The tone noise data with the partially treated 7 vane configuration indicated that acoustic material in the
Acoustic noise during functional magnetic resonance imaginga)
Ravicz, Michael E.; Melcher, Jennifer R.; Kiang, Nelson Y.-S.
2007-01-01
Functional magnetic resonance imaging (fMRI) enables sites of brain activation to be localized in human subjects. For studies of the auditory system, acoustic noise generated during fMRI can interfere with assessments of this activation by introducing uncontrolled extraneous sounds. As a first step toward reducing the noise during fMRI, this paper describes the temporal and spectral characteristics of the noise present under typical fMRI study conditions for two imagers with different static magnetic field strengths. Peak noise levels were 123 and 138 dB re 20 μPa in a 1.5-tesla (T) and a 3-T imager, respectively. The noise spectrum (calculated over a 10-ms window coinciding with the highest-amplitude noise) showed a prominent maximum at 1 kHz for the 1.5-T imager (115 dB SPL) and at 1.4 kHz for the 3-T imager (131 dB SPL). The frequency content and timing of the most intense noise components indicated that the noise was primarily attributable to the readout gradients in the imaging pulse sequence. The noise persisted above background levels for 300-500 ms after gradient activity ceased, indicating that resonating structures in the imager or noise reverberating in the imager room were also factors. The gradient noise waveform was highly repeatable. In addition, the coolant pump for the imager’s permanent magnet and the room air handling system were sources of ongoing noise lower in both level and frequency than gradient coil noise. Knowledge of the sources and characteristics of the noise enabled the examination of general approaches to noise control that could be applied to reduce the unwanted noise during fMRI sessions. PMID:11051496
Continuous-variable entanglement distillation of non-Gaussian mixed states
Dong Ruifang; Lassen, Mikael; Heersink, Joel; Marquardt, Christoph; Leuchs, Gerd; Andersen, Ulrik L.
2010-07-15
Many different quantum-information communication protocols such as teleportation, dense coding, and entanglement-based quantum key distribution are based on the faithful transmission of entanglement between distant location in an optical network. The distribution of entanglement in such a network is, however, hampered by loss and noise that is inherent in all practical quantum channels. Thus, to enable faithful transmission one must resort to the protocol of entanglement distillation. In this paper we present a detailed theoretical analysis and an experimental realization of continuous variable entanglement distillation in a channel that is inflicted by different kinds of non-Gaussian noise. The continuous variable entangled states are generated by exploiting the third order nonlinearity in optical fibers, and the states are sent through a free-space laboratory channel in which the losses are altered to simulate a free-space atmospheric channel with varying losses. We use linear optical components, homodyne measurements, and classical communication to distill the entanglement, and we find that by using this method the entanglement can be probabilistically increased for some specific non-Gaussian noise channels.
NASA Technical Reports Server (NTRS)
Kenny, Patrick
2004-01-01
at the AAPL to measure Nozzle Acoustic Test Rig (NATR) background noise levels. Six condenser microphones were placed in strategic locations around the dome and the inlet tunnel to measure different noise sources. From the control room the jet was monitored with the help of video cameras and other sensors. The data points were recorded, reduced, and plotted, and will be used to plan future modifications to the NATR. The primary goal to create data reduction test programs and provide verification was completed. As a result of the internship, I learned C/C++, UNIX/LINUX, Excel, and acoustic data processing methods. I also recorded data at the AAPL, then processed and plotted it. These data would be useful to compare against existing data. In addition, I adjusted software to work on the Mac OSX platform. And I used the available training resources.
Mitigation of structureborne noise nuisance
NASA Astrophysics Data System (ADS)
Ko, Wing P.
2005-09-01
This paper presents a noise complaint case which was solved by me a few years ago in Hong Kong. A newlywed couple in the residential unit complained to the Government that the noise emitted from the pump room directly beneath their unit was very annoying, especially in the night-time period. The owner of the building was then required by the Government to mitigate the noise to the night-time statutory noise requirement within 30 days, otherwise he would be prosecuted. Ideally, the structureborne noise from the pump room could be effectively mitigated by installation of floating slab and vibration isolators under the pumps. Also, the water tanks and water pipes were required to be isolated from the walls and floor. However, this work was impossible to be completed within 30 days to stop the prosecution. Water supply to the above residents would be seriously interrupted during the construction period. As the only noise parameter of the statutory requirement was 30 minute A-weighted Leq, the most effective and practical way in this exigent situation was to reduce the pump operation time within any 30 minute period to decrease the Leq values. In addition, the water pipes and pumps were also required to be isolated from the walls and floor with resilient materials to break the vibration channels. These noise mitigation measures were successfully applied to the pump room before the end of the 30 days. Finally, the noise levels inside the complainant's unit were found to meet the statutory requirement. The noise complaint case was then closed by the Government.
Patrol Officer Daily Noise Exposure.
Gilbertson, Lynn R; Vosburgh, Donna J H
2015-01-01
Previous research shows that police officers are at a higher risk for noise induced hearing loss (NIHL). Little data exists on the occupational tasks, outside of the firing range, that might lead to the increased risk of NIHL. The current study collected noise dosimetry from patrol officers in a smaller department and a larger department in southern Wisconsin, United States. The noise dosimeters simultaneously measured noise in three virtual dosimeters that had different thresholds, criterion levels, and exchange rates. The virtual dosimeters were set to: the Occupational Safety and Health Administration (OSHA) hearing conservation criteria (OSHA-HC), the OSHA permissible exposure level criteria (OSHA-PEL), and the American Conference of Governmental Industrial Hygienists (ACGIH). In addition to wearing a noise dosimeter during their respective work days, officers completed a log form documenting the type of task performed, the duration of that task, if the task involved the use of a siren, and officer characteristics that may have influenced their noise exposure, such as the type of dispatch radio unit worn. Analysis revealed that the normalized 8-hour time weighted averages (TWA) for all officers fell below the recommended OSHA and ACGIH exposure limits. The tasks involving the use of the siren had significantly higher levels than the tasks without (p = 0.005). The highest noise exposure levels were encountered when patrol officers were assisting other public safety agencies such as a fire department or emergency medical services (79 dBA). Canine officers had higher normalized 8-hr TWA noise exposure than regular patrol officers (p = 0.002). Officers with an evening work schedule had significantly higher noise exposure than the officers with a day or night work schedule (p = 0.023). There were no significant differences in exposure levels between the two departments (p = 0.22). Results suggest that this study population is unlikely to experience NIHL as
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Effect of harmonic noise on a Brownian particle in a ratchet periodic potential
NASA Astrophysics Data System (ADS)
Zhou, Z. R.; Bai, L.; Shu, C. Z.; Nie, L. R.
2012-08-01
A Brownian particle in a ratchet periodic potential driven by harmonic noise, which is produced through a RLC oscillation circuit with Gaussian white noise, is investigated. The mean velocity and stationary probability distribution function (SPDF) of the system are obtained by means of numerical simulations. We also used the power spectrum of the harmonic noise, the peak position and semi-height width of which can be changed by modulating the driving oscillation circuit's parameters, to analyse contributions of characteristics of the power spectrum to the mean velocity. The results indicate that: (i) appropriate peak position and semi-height width of the harmonic noise's power spectrum can maximise the particle's mean velocity; (ii) the SPDF undergoes a state transition from monostability → bistability → tristability → monostability as the Gaussian white noise intensity is increased, and the other parameters of the driving oscillation circuit can also modify the system's state.
NASA Astrophysics Data System (ADS)
Koyama, Kazuya; Pettinari, Guido Walter; Mizuno, Shuntaro; Fidler, Christian
2014-06-01
In this paper, we study cosmic microwave background (CMB) constraints on primordial non-Gaussianity in Dirac-Born-Infeld (DBI) galileon models in which an induced gravity term is added to the DBI action. In this model, the non-Gaussianity of orthogonal shape can be generated. We provide a relation between theoretical parameters and orthogonal/equilateral nonlinear parameters using the Fisher matrix approach for the CMB bispectrum. In doing so, we include the effect of the CMB transfer functions and experimental noise properties by employing the recently developed second order non-Gaussianity code. The relation is also shown in the language of effective theory so that it can be applied to general single-field models. Using the bispectrum Fisher matrix and the central values for equilateral and orthogonal non-Gaussianities found by the Planck temperature survey, we provide forecasts on the theoretical parameters of the DBI galileon model. We consider the upcoming Planck polarization data and the proposed post-Planck experiments Cosmic Origins Explore (COrE) and Polarized Radiation Imaging and Spectroscopy Mission (PRISM). We find that Planck polarization measurements may provide a hint for a non-canonical sound speed at the 68% confidence level. COrE and PRISM will not only confirm a non-canonical sound speed but also exclude the conventional DBI inflation model at more than the 95% and 99% confidence level respectively, assuming that the central values will not change. This indicates that improving constraints on non-Gaussianity further by future CMB experiments is invaluable to constrain the physics of the early universe.
Curvature sensors: noise and its propagation.
Kellerer, Aglae
2010-11-01
The signal measured with a curvature sensor is analyzed. At the outset, we derive the required minimum number of sensing elements at the pupil edges, depending on the total number of sensing elements. The distribution of the sensor signal is further characterized in terms of its mean, variance, kurtosis, and skewness. It is established that while the approximation in terms of a Gaussian distribution is correct down to fairly low photon numbers, much higher numbers are required to obtain meaningful sensor measurements for small wavefront distortions. Finally, we indicate a closed expression for the error propagation factor and for the photon-noise-induced Strehl loss. PMID:21045888
A Fast Incremental Gaussian Mixture Model
Pinto, Rafael Coimbra; Engel, Paulo Martins
2015-01-01
This work builds upon previous efforts in online incremental learning, namely the Incremental Gaussian Mixture Network (IGMN). The IGMN is capable of learning from data streams in a single-pass by improving its model after analyzing each data point and discarding it thereafter. Nevertheless, it suffers from the scalability point-of-view, due to its asymptotic time complexity of O(NKD3) for N data points, K Gaussian components and D dimensions, rendering it inadequate for high-dimensional data. In this work, we manage to reduce this complexity to O(NKD2) by deriving formulas for working directly with precision matrices instead of covariance matrices. The final result is a much faster and scalable algorithm which can be applied to high dimensional tasks. This is confirmed by applying the modified algorithm to high-dimensional classification datasets. PMID:26444880
NASA Astrophysics Data System (ADS)
Meerburg, P. Daniel; Meyers, Joel; van Engelen, Alexander; Ali-Haïmoud, Yacine
2016-06-01
We study the degree to which the cosmic microwave background (CMB) can be used to constrain primordial non-Gaussianity involving one tensor and two scalar fluctuations, focusing on the correlation of one polarization B mode with two temperature modes. In the simplest models of inflation, the tensor-scalar-scalar primordial bispectrum is nonvanishing and is of the same order in slow-roll parameters as the scalar-scalar-scalar bispectrum. We calculate the ⟨B T T ⟩ correlation arising from a primordial tensor-scalar-scalar bispectrum, and show that constraints from an experiment like CMB-Stage IV using this observable are more than an order of magnitude better than those on the same primordial coupling obtained from temperature measurements alone. We argue that B -mode non-Gaussianity opens up an as-yet-unexplored window into the early Universe, demonstrating that significant information on primordial physics remains to be harvested from CMB anisotropies.
Quantum Fidelity for Arbitrary Gaussian States
NASA Astrophysics Data System (ADS)
Banchi, Leonardo; Braunstein, Samuel L.; Pirandola, Stefano
2015-12-01
We derive a computable analytical formula for the quantum fidelity between two arbitrary multimode Gaussian states which is simply expressed in terms of their first- and second-order statistical moments. We also show how such a formula can be written in terms of symplectic invariants and used to derive closed forms for a variety of basic quantities and tools, such as the Bures metric, the quantum Fisher information, and various fidelity-based bounds. Our result can be used to extend the study of continuous-variable protocols, such as quantum teleportation and cloning, beyond the current one-mode or two-mode analyses, and paves the way to solve general problems in quantum metrology and quantum hypothesis testing with arbitrary multimode Gaussian resources.
Adaptive Gaussian pattern classification. Final report
Priebe, C.E.; Marchette, D.J.
1988-08-01
A massively parallel architecture for pattern classification is described. The architecture is based on the field of density estimation. It makes use of a variant of the adaptive-kernel estimator to approximate the distributions of the classes as a sum of Gaussian distributions. These Gaussians are learned using a moved-mean, moving-covariance learning scheme. A temporal ordering scheme is implemented using decay at the input level, allowing the network to learn to recognize sequences. The learning scheme requires a single pass through the data, giving the architecture the capability of real-time learning. The first part of the paper develops the adaptive-kernel estimator. The parallel architecture is then described, and issues relevant to implementation are discussed. Finally, applications to robotic sensor fusion, intended word recognition, and vision are described.