Maximum precision closed-form solution for localizing diffraction-limited spots in noisy images
Larkin, Joshua D.; Cook, Peter R.
2012-01-01
Super-resolution techniques like PALM and STORM require accurate localization of single fluorophores detected using a CCD. Popular localization algorithms inefficiently assume each photon registered by a pixel can only come from an area in the specimen corresponding to that pixel (not from neighboring areas), before iteratively (slowly) fitting a Gaussian to pixel intensity; they fail with noisy images. We present an alternative; a probability distribution extending over many pixels is assigned to each photon, and independent distributions are joined to describe emitter location. We compare algorithms, and recommend which serves best under different conditions. At low signal-to-noise ratios, ours is 2-fold more precise than others, and 2 orders of magnitude faster; at high ratios, it closely approximates the maximum likelihood estimate. PMID:23038398
NASA Astrophysics Data System (ADS)
Wilting, Jens; Lehnertz, Klaus
2015-08-01
We investigate a recently published analysis framework based on Bayesian inference for the time-resolved characterization of interaction properties of noisy, coupled dynamical systems. It promises wide applicability and a better time resolution than well-established methods. At the example of representative model systems, we show that the analysis framework has the same weaknesses as previous methods, particularly when investigating interacting, structurally different non-linear oscillators. We also inspect the tracking of time-varying interaction properties and propose a further modification of the algorithm, which improves the reliability of obtained results. We exemplarily investigate the suitability of this algorithm to infer strength and direction of interactions between various regions of the human brain during an epileptic seizure. Within the limitations of the applicability of this analysis tool, we show that the modified algorithm indeed allows a better time resolution through Bayesian inference when compared to previous methods based on least square fits.
NASA Astrophysics Data System (ADS)
Crutchfield, James Patrick, Jr.
Deterministic dynamics often leads to complex, unpredictable behavior. This randomness or chaos produces information and limits one's ability to predict future events. There are two components to this imposed ignorance. The first arises in a mathematical context from highly convoluted orbit structures in state space. These allow a system to rapidly visit many regions of state space. In a physical context, the second comes from the coupling of the system -under-study to other systems that provide information to it. Extrinsic information sources preclude the exact determination of the system's state. By the mechanism of their complex orbits, chaotic systems amplify this uncertainty into unpredictable macroscopic behavior. The physical study of chaotic dynamical systems is incomplete without an appreciation of how external fluctuations affect their predictability. Using information theory we describe how to measure the unpredictability of (i) deterministic chaotic systems (without extrinsic noise), and (ii) nondeterministic chaotic systems (coupled to extrinsic noise). Scaling concepts are invaluable tools in this. Scaling reveals that extrinsic noise acts as a disordering field for chaos. Furthermore, even for systems with extrinsic noise, scaling captures fundamental features of chaotic behavior. It provides a unified framework for the topological, metric, and Renyi dimensions and entropies. The physical relevance of these concepts lies in their ability to analyze noisy chaotic signals. The information theoretic approach to temporally complex behavior is applied to chaotic signals from two hydrodynamic experiments. In addition, the dynamic aspects of pattern evolution and the possible breakdown of (naive) dynamical systems theory is discussed for experiments with an image processing system. The first appendix contains descriptions of algorithms for dynamical systems studies. The second discusses a movie on the geometric structure of chaotic driven oscillators using
NASA Astrophysics Data System (ADS)
Yee, Eugene
2007-04-01
Although a great deal of research effort has been focused on the forward prediction of the dispersion of contaminants (e.g., chemical and biological warfare agents) released into the turbulent atmosphere, much less work has been directed toward the inverse prediction of agent source location and strength from the measured concentration, even though the importance of this problem for a number of practical applications is obvious. In general, the inverse problem of source reconstruction is ill-posed and unsolvable without additional information. It is demonstrated that a Bayesian probabilistic inferential framework provides a natural and logically consistent method for source reconstruction from a limited number of noisy concentration data. In particular, the Bayesian approach permits one to incorporate prior knowledge about the source as well as additional information regarding both model and data errors. The latter enables a rigorous determination of the uncertainty in the inference of the source parameters (e.g., spatial location, emission rate, release time, etc.), hence extending the potential of the methodology as a tool for quantitative source reconstruction. A model (or, source-receptor relationship) that relates the source distribution to the concentration data measured by a number of sensors is formulated, and Bayesian probability theory is used to derive the posterior probability density function of the source parameters. A computationally efficient methodology for determination of the likelihood function for the problem, based on an adjoint representation of the source-receptor relationship, is described. Furthermore, we describe the application of efficient stochastic algorithms based on Markov chain Monte Carlo (MCMC) for sampling from the posterior distribution of the source parameters, the latter of which is required to undertake the Bayesian computation. The Bayesian inferential methodology for source reconstruction is validated against real
Dr. Katja Lindenberg
2005-11-20
During the one-year period 2004-2005 our work continued to focus on nonlinear noisy systems, with special attention to spatially extended systems. There is a history of many decades of research in the sciences and engineering on the behavior of noninear noisy systems, but only in the past ten years or so has a theoretical understanding of spatially extended systems begun to emerge. This has been the outcome of a symbiosis of numerical simulations not possible until recently, laboratory experiments, and new analytic methods.
Reentrant transition in coupled noisy oscillators.
Kobayashi, Yasuaki; Kori, Hiroshi
2015-01-01
We report on a synchronization-breaking instability observed in a noisy oscillator unidirectionally coupled to a pacemaker. Using a phase oscillator model, we find that, as the coupling strength is increased, the noisy oscillator lags behind the pacemaker more frequently and the phase slip rate increases, which may not be observed in averaged phase models such as the Kuramoto model. Investigation of the corresponding Fokker-Planck equation enables us to obtain the reentrant transition line between the synchronized state and the phase slip state. We verify our theory using the Brusselator model, suggesting that this reentrant transition can be found in a wide range of limit cycle oscillators. PMID:25679676
Optimal entrainment of heterogeneous noisy neurons
Wilson, Dan; Holt, Abbey B.; Netoff, Theoden I.; Moehlis, Jeff
2015-01-01
We develop a methodology to design a stimulus optimized to entrain nonlinear, noisy limit cycle oscillators with uncertain properties. Conditions are derived which guarantee that the stimulus will entrain the oscillators despite these uncertainties. Using these conditions, we develop an energy optimal control strategy to design an efficient entraining stimulus and apply it to numerical models of noisy phase oscillators and to in vitro hippocampal neurons. In both instances, the optimal stimuli outperform other similar but suboptimal entraining stimuli. Because this control strategy explicitly accounts for both noise and inherent uncertainty of model parameters, it could have experimental relevance to neural circuits where robust spike timing plays an important role. PMID:26074762
NASA Astrophysics Data System (ADS)
Chen, Jing-Ling; Kwek, L. C.; Oh, C. H.
2002-05-01
In a recent paper [D. A. Meyer, Phys. Rev. Lett. 82, 1052 (1999)], it has been shown that a classical zero-sum strategic game can become a winning quantum game for the player with a quantum device. Nevertheless, it is well known that quantum systems easily decohere in noisy environments. In this paper, we show that if the handicapped player with classical means can delay his action for a sufficiently long time, the quantum version reverts to the classical zero-sum game under decoherence.
Loudness, noisiness, and vibration effects
NASA Technical Reports Server (NTRS)
1984-01-01
The physical measurement of noise that determines psychological and physical behavioral effects in real life is investigated. The roles of loudness and noisiness judgement in the development of these measurement procedures are also examined.
Noisy metrology beyond the standard quantum limit.
Chaves, R; Brask, J B; Markiewicz, M; Kołodyński, J; Acín, A
2013-09-20
Parameter estimation is of fundamental importance in areas from atomic spectroscopy and atomic clocks to gravitational wave detection. Entangled probes provide a significant precision gain over classical strategies in the absence of noise. However, recent results seem to indicate that any small amount of realistic noise restricts the advantage of quantum strategies to an improvement by at most a multiplicative constant. Here, we identify a relevant scenario in which one can overcome this restriction and attain superclassical precision scaling even in the presence of uncorrelated noise. We show that precision can be significantly enhanced when the noise is concentrated along some spatial direction, while the Hamiltonian governing the evolution which depends on the parameter to be estimated can be engineered to point along a different direction. In the case of perpendicular orientation, we find superclassical scaling and identify a state which achieves the optimum. PMID:24093232
Capacity of very noisy communication channels based on Fisher information.
Duan, Fabing; Chapeau-Blondeau, François; Abbott, Derek
2016-01-01
We generalize the asymptotic capacity expression for very noisy communication channels to now include coloured noise. For the practical scenario of a non-optimal receiver, we consider the common case of a correlation receiver. Due to the central limit theorem and the cumulative characteristic of a correlation receiver, we model this channel noise as additive Gaussian noise. Then, the channel capacity proves to be directly related to the Fisher information of the noise distribution and the weak signal energy. The conditions for occurrence of a noise-enhanced capacity effect are discussed, and the capacity difference between this noisy communication channel and other nonlinear channels is clarified. PMID:27306041
Capacity of very noisy communication channels based on Fisher information
Duan, Fabing; Chapeau-Blondeau, François; Abbott, Derek
2016-01-01
We generalize the asymptotic capacity expression for very noisy communication channels to now include coloured noise. For the practical scenario of a non-optimal receiver, we consider the common case of a correlation receiver. Due to the central limit theorem and the cumulative characteristic of a correlation receiver, we model this channel noise as additive Gaussian noise. Then, the channel capacity proves to be directly related to the Fisher information of the noise distribution and the weak signal energy. The conditions for occurrence of a noise-enhanced capacity effect are discussed, and the capacity difference between this noisy communication channel and other nonlinear channels is clarified. PMID:27306041
Capacity of very noisy communication channels based on Fisher information
NASA Astrophysics Data System (ADS)
Duan, Fabing; Chapeau-Blondeau, François; Abbott, Derek
2016-06-01
We generalize the asymptotic capacity expression for very noisy communication channels to now include coloured noise. For the practical scenario of a non-optimal receiver, we consider the common case of a correlation receiver. Due to the central limit theorem and the cumulative characteristic of a correlation receiver, we model this channel noise as additive Gaussian noise. Then, the channel capacity proves to be directly related to the Fisher information of the noise distribution and the weak signal energy. The conditions for occurrence of a noise-enhanced capacity effect are discussed, and the capacity difference between this noisy communication channel and other nonlinear channels is clarified.
Globally coupled noisy oscillators with inhomogeneous periodic forcing
NASA Astrophysics Data System (ADS)
Gabbay, Michael; Larsen, Michael L.; Tsimring, Lev S.
2004-12-01
We study the collective properties of an array of nonlinear noisy oscillators driven by nonidentical periodic signals. We consider the case of a globally coupled array of harmonically forced, weakly nonlinear oscillators where there is a constant difference between the phases of the forcing signals applied to adjacent oscillators. This system is a prototypical model of a nonlinear phased array receiver. We derive analytical results for the array output in the limit of a large number of oscillators for the noise-free and noisy cases. Numerical simulations show good agreement with the theoretical analysis.
Neuromorphic Learning From Noisy Data
NASA Technical Reports Server (NTRS)
Merrill, Walter C.; Troudet, Terry
1993-01-01
Two reports present numerical study of performance of feedforward neural network trained by back-propagation algorithm in learning continuous-valued mappings from data corrupted by noise. Two types of noise considered: plant noise which affects dynamics of controlled process and data-processing noise, which occurs during analog processing and digital sampling of signals. Study performed with view toward use of neural networks as neurocontrollers to substitute for, or enhance, performances of human experts in controlling mechanical devices in presence of sensor and actuator noise and to enhance performances of more-conventional digital feedback electronic process controllers in noisy environments.
Extracting insight from noisy cellular networks.
Landry, Christian R; Levy, Emmanuel D; Abd Rabbo, Diala; Tarassov, Kirill; Michnick, Stephen W
2013-11-21
Network biologists attempt to extract meaningful relationships among genes or their products from very noisy data. We argue that what we categorize as noisy data may sometimes reflect noisy biology and therefore may shield a hidden meaning about how networks evolve and how matter is organized in the cell. We present practical solutions, based on existing evolutionary and biophysical concepts, through which our understanding of cell biology can be enormously enriched. PMID:24267884
Collective fluctuations in networks of noisy components
NASA Astrophysics Data System (ADS)
Masuda, Naoki; Kawamura, Yoji; Kori, Hiroshi
2010-09-01
Collective dynamics result from interactions among noisy dynamical components. Examples include heartbeats, circadian rhythms and various pattern formations. Because of noise in each component, collective dynamics inevitably involve fluctuations, which may crucially affect the functioning of the system. However, the relation between the fluctuations in isolated individual components and those in collective dynamics is not clear. Here, we study a linear dynamical system of networked components subjected to independent Gaussian noise and analytically show that the connectivity of networks determines the intensity of fluctuations in the collective dynamics. Remarkably, in general directed networks including scale-free networks, the fluctuations decrease more slowly with system size than the standard law stated by the central limit theorem. They even remain finite for a large system size when global directionality of the network exists. Moreover, such non-trivial behavior appears even in undirected networks when nonlinear dynamical systems are considered. We demonstrate it with a coupled oscillator system.
The Quantum Steganography Protocol via Quantum Noisy Channels
NASA Astrophysics Data System (ADS)
Wei, Zhan-Hong; Chen, Xiu-Bo; Niu, Xin-Xin; Yang, Yi-Xian
2015-08-01
As a promising branch of quantum information hiding, Quantum steganography aims to transmit secret messages covertly in public quantum channels. But due to environment noise and decoherence, quantum states easily decay and change. Therefore, it is very meaningful to make a quantum information hiding protocol apply to quantum noisy channels. In this paper, we make the further research on a quantum steganography protocol for quantum noisy channels. The paper proved that the protocol can apply to transmit secret message covertly in quantum noisy channels, and explicity showed quantum steganography protocol. In the protocol, without publishing the cover data, legal receivers can extract the secret message with a certain probability, which make the protocol have a good secrecy. Moreover, our protocol owns the independent security, and can be used in general quantum communications. The communication, which happen in our protocol, do not need entangled states, so our protocol can be used without the limitation of entanglement resource. More importantly, the protocol apply to quantum noisy channels, and can be used widely in the future quantum communication.
Object Detection under Noisy Condition
NASA Astrophysics Data System (ADS)
Halkarnikar, P. P.; Khandagle, H. P.; Talbar, S. N.; Vasambekar, P. N.
2010-11-01
Identifying moving objects from a video sequence is a fundamental and critical task in many computer-vision applications. Such automatic object detection soft wares have many applications in surveillance, auto navigation and robotics. A common approach is to perform background subtraction, which identifies the moving object from portion of video sequences. These soft wares work good under normal condition but tend to give false alarms when tested in real life conditions. Such a condition arises due to fog, smoke, glares ect. These situations are termed as noisy conditions and objects are detected under such conditions. In this paper we created noise by addition of standard Gaussian noise in clean video and compare the response of the detection system to various noise level.
Numerical Differentiation of Noisy, Nonsmooth Data
Chartrand, Rick
2011-01-01
We consider the problem of differentiating a function specified by noisy data. Regularizing the differentiation process avoids the noise amplification of finite-difference methods. We use total-variation regularization, which allows for discontinuous solutions. The resulting simple algorithm accurately differentiates noisy functions, including those which have a discontinuous derivative.
A practical test for noisy chaotic dynamics
NASA Astrophysics Data System (ADS)
BenSaïda, Ahmed
2015-12-01
This code computes the largest Lyapunov exponent and tests for the presence of a chaotic dynamics, as opposed to stochastic dynamics, in a noisy scalar series. The program runs under MATLAB® programming language.
Collective Chemotaxis through Noisy Multicellular Gradient Sensing
NASA Astrophysics Data System (ADS)
Varennes, Julien; Han, Bumsoo; Mugler, Andrew
2016-08-01
Collective cell migration in response to a chemical cue occurs in many biological processes such as morphogenesis and cancer metastasis. Clusters of migratory cells in these systems are capable of responding to gradients of less than 1% difference in chemical concentration across a cell length. Multicellular systems are extremely sensitive to their environment and while the limits to multicellular sensing are becoming known, how this information leads to coherent migration remains poorly understood. We develop a computational model of multicellular sensing and migration in which groups of cells collectively measure noisy chemical gradients. The output of the sensing process is coupled to individual cells polarization to model migratory behavior. Through the use of numerical simulations, we find that larger clusters of cells detect the gradient direction with higher precision and thus achieve stronger polarization bias, but larger clusters also induce more drag on collective motion. The trade-off between these two effects leads to an optimal cluster size for most efficient migration. We discuss how our model could be validated using simple, phenomenological experiments.
Collective Chemotaxis through Noisy Multicellular Gradient Sensing.
Varennes, Julien; Han, Bumsoo; Mugler, Andrew
2016-08-01
Collective cell migration in response to a chemical cue occurs in many biological processes such as morphogenesis and cancer metastasis. Clusters of migratory cells in these systems are capable of responding to gradients of <1% difference in chemical concentration across a cell length. Multicellular systems are extremely sensitive to their environment, and although the limits to multicellular sensing are becoming known, how this information leads to coherent migration remains poorly understood. We develop a computational model of multicellular sensing and migration in which groups of cells collectively measure noisy chemical gradients. The output of the sensing process is coupled to the polarization of individual cells to model migratory behavior. Through the use of numerical simulations, we find that larger clusters of cells detect the gradient direction with higher precision and thus achieve stronger polarization bias, but larger clusters also induce more drag on collective motion. The trade-off between these two effects leads to an optimal cluster size for most efficient migration. We discuss how our model could be validated using simple, phenomenological experiments. PMID:27508447
Reconstructing Directed Networks From Noisy Dynamics
NASA Astrophysics Data System (ADS)
Tam, Hiu Ching; Ching, Emily Sc
Complex systems can be fruitfully studied as networks of many elementary units, known as nodes, interacting with one another with the interactions being the links between the nodes. The overall behavior of the systems depends crucially on the network structure depicting how the nodes are linked with each other. It is usually possible to measure the dynamics of the individual nodes but difficult, if not impossible, to directly measure the interactions or links between the nodes. For most systems of interest, the links are directional in that one node affects the dynamics of the other but not vice versa. Moreover, the strength of interaction can vary for different links. Reconstructing directed and weighted networks from dynamics is one of the biggest challenges in network research. We have studied directed and weighted networks modelled by noisy dynamical systems with nonlinear dynamics and developed a method that reconstructs the links and their directions using only the dynamics of the nodes as input. Our method is motivated by a mathematical result derived for dynamical systems that approach a fixed point in the noise-free limit. We show that our method gives good reconstruction results for several directed and weighted networks with different nonlinear dynamics. Supported by Hong Kong Research Grants Council under Grant No. CUHK 14300914.
Nanotubes for noisy signal processing
NASA Astrophysics Data System (ADS)
Lee, Ian Yenyin
Nanotubes can process noisy signals. We present two central results in support of this general thesis and make an informed extrapolation that uses nanotubes to improve body armor. The first result is that noise can help nanotubes detect weak signals. The finding confirmed a stochastic-resonance theoretical prediction that noise can enhance detection at the nano-level. Laboratory experiments with nanotubes showed that three types of noise improved three measures of detection. Small amounts of Gaussian, uniform, and Cauchy additive white noise increased mutual-information, cross-correlation, and bit-error-rate measures before degrading them with further increases in noise. Nanotubes can apply this noise-enhancement and nanotube electrical and mechanical properties to improve signal processing. Similar noise enhancement may benefit a proposed nanotube-array cochlear-model spectral processing. The second result is that nanotube antennas can directly detect narrowband electromagnetic (EM) signals. The finding showed that nanotube and thin-wire dipoles are similar: They are resonant and narrowband and can implement linear-array designs if the EM waves in the nanotubes propagate at or near the free-space velocity of light. The nanotube-antenna prediction is based on a Fresnel-zone or near-zone analysis of antenna impedance using a quantum-conductor model. The analysis also predicts a failure to resonate if the nanotube EM-wave propagation is much slower than free-space light propagation. We extrapolate based on applied and theoretical analysis of body armor. Field experiments used a baseball comparison and statistical and other techniques to model body-armor bruising effects. A baseball comparison showed that a large caliber handgun bullet can hit an armored chest as hard as a fast baseball can hit a bare chest. Adaptive fuzzy systems learned to predict a bruise profile directly from the experimental data and also from statistical analysis of the data. Nanotube signal
Magic state distillation protocols with noisy Clifford gates
NASA Astrophysics Data System (ADS)
Brooks, Peter
2013-03-01
A promising approach to universal fault-tolerant quantum computation is to implement the non-universal group of Clifford gates, and to achieve universality by adding the ability to prepare high-fidelity copies of certain ``magic states''. By applying state distillation protocols, many noisy copies of a magic state ancilla can be purified into a smaller number of clean copies which are arbitrarily close to the perfect state, using only Clifford operations. In practice, the Clifford gates themselves will be noisy, which can limit the efficiency of state distillation and put a floor on the achievable fidelity with the desired state. Recently, a number of new state distillation protocols have been proposed that have the potential to reduce the required resource overhead. I analyze these protocols and explore the tradeoffs between these different approaches to magic state distillation when noisy Clifford gates are taken into account. Supported in part by IARPA under contract D11PC20165, by NSF under Grant No. PHY-0803371, by DOE under Grant No. DE-FG03-92-ER40701, and by NSA/ARO under Grant No. W911NF-09-1-0442.
Theory of noisy learning in nonlinear perceptrons: The cavity approach
NASA Astrophysics Data System (ADS)
Luo, Peixun
2001-08-01
The cavity method is applied to study the supervised learning of noisy examples in nonlinear perceptrons. The advantage of this mean field method is demonstrated in this study on the unique characteristics of nonlinear perceptrons. Mean field equations of this complex system are obtained. The information conflict inherent in noisy examples gives rise to instability of the perturbative calculation if the weight decay to the student weight vector is weak. The occurrence of rough energy landscape with many metastable states and preferentially learning some examples in the cost of sacrificing others are investigated. It is found that the distribution of activation to examples shows band gaps when information conflict is serious, which is the case when both the training set and the noise temperature are large. The generalization ability of a nonlinear perceptron trained with noisy examples is studied and compared with linear case. It is found that the student is able to decipher the rule of teacher in the large training set limit if it has the knowledge of the weight length of the teacher. Phase transition from a good generalization state to a poor one when the weight decay strength or the size of training set varies is predicted in theory and confirmed by simulation results. The full phase diagram of the system is plotted. The origin of discrepancy between theory and simulation is mainly attributed to the effect of rough energy landscape beside the finite size effect.
Aviation noise: Costs of phasing out noisy aircraft
NASA Astrophysics Data System (ADS)
1991-07-01
In Sept. 1990 this group testified on the costs of phasing out older, relatively noisy aircraft and on how these costs would be affected by the independent adoption of noise restrictions by airports. In Nov. 1990 the Airport Noise and Capacity Act of 1990 was enacted. This act phased out the noisiest jets currently in use by the year 2000 and limits the discretion of airports to adopt their own noise restrictions. This report briefly describes the likely effects of this Act on the costs to the airline industry of aviation noise restrictions.
Broadband time-reversing array retrofocusing in noisy environments
NASA Astrophysics Data System (ADS)
Sabra, Karim G.; Khosla, Sunny R.; Dowling, David R.
2002-02-01
Acoustic time reversal is a promising technique for spatial and temporal focusing of sound in unknown environments. Acoustic time reversal can be implemented with an array of transducers that listens to a remote sound source and then transmits a time-reversed version of what was heard. In a noisy environment, the performance of such a time-reversing array (TRA) will be degraded because the array will receive and transmit noise, and the intended signal may be masked by ambient noise at the retrofocus location. This article presents formal results for the signal-to-noise ratio at the intended focus (SNRf) for TRAs that receive and send finite-duration broadband signals in noisy environments. When the noise is homogeneous and uncorrelated, and a broadcast power limitation sets the TRA's electronic amplification, the formal results can be simplified to an algebraic formula that includes the characteristics of the signal, the remote source, the TRA, and the noisy environment. Here, SNRf is found to be proportional to the product of the signal bandwidth and the duration of the signal pulse after propagation through the environment. Using parabolic-equation propagation simulations, the formal results for SNRf are illustrated for a shallow water environment at source-array ranges of 1 to 40 km and bandwidths from several tens of Hz to more than 500 Hz for a signal center frequency of 500 Hz. Shallow-water TRA noise rejection is predicted to be superior to that possible in free space because TRAs successfully exploit multipath-propagation.
On covariance structure in noisy, big data
NASA Astrophysics Data System (ADS)
Paffenroth, Randy C.; Nong, Ryan; Du Toit, Philip C.
2013-09-01
Herein we describe theory and algorithms for detecting covariance structures in large, noisy data sets. Our work uses ideas from matrix completion and robust principal component analysis to detect the presence of low-rank covariance matrices, even when the data is noisy, distorted by large corruptions, and only partially observed. In fact, the ability to handle partial observations combined with ideas from randomized algorithms for matrix decomposition enables us to produce asymptotically fast algorithms. Herein we will provide numerical demonstrations of the methods and their convergence properties. While such methods have applicability to many problems, including mathematical finance, crime analysis, and other large-scale sensor fusion problems, our inspiration arises from applying these methods in the context of cyber network intrusion detection.
Synchronization of noisy systems by stochastic signals
Neiman, A.; Schimansky-Geier, L.; Moss, F.; Schimansky-Geier, L.; Shulgin, B.; Collins, J.J.
1999-07-01
We study, in terms of synchronization, the {ital nonlinear response} of noisy bistable systems to a stochastic external signal, represented by Markovian dichotomic noise. We propose a general kinetic model which allows us to conduct a full analytical study of the nonlinear response, including the calculation of cross-correlation measures, the mean switching frequency, and synchronization regions. Theoretical results are compared with numerical simulations of a noisy overdamped bistable oscillator. We show that dichotomic noise can instantaneously synchronize the switching process of the system. We also show that synchronization is most pronounced at an optimal noise level{emdash}this effect connects this phenomenon with aperiodic stochastic resonance. Similar synchronization effects are observed for a stochastic neuron model stimulated by a stochastic spike train. {copyright} {ital 1999} {ital The American Physical Society}
Lizards speed up visual displays in noisy motion habitats
Ord, Terry J; Peters, Richard A; Clucas, Barbara; Stamps, Judy A
2007-01-01
Extensive research over the last few decades has revealed that many acoustically communicating animals compensate for the masking effect of background noise by changing the structure of their signals. Familiar examples include birds using acoustic properties that enhance the transmission of vocalizations in noisy habitats. Here, we show that the effects of background noise on communication signals are not limited to the acoustic modality, and that visual noise from windblown vegetation has an equally important influence on the production of dynamic visual displays. We found that two species of Puerto Rican lizard, Anolis cristatellus and A. gundlachi, increase the speed of body movements used in territorial signalling to apparently improve communication in visually ‘noisy’ environments of rapidly moving vegetation. This is the first evidence that animals change how they produce dynamic visual signals when communicating in noisy motion habitats. Taken together with previous work on acoustic communication, our results show that animals with very different sensory ecologies can face similar environmental constraints and adopt remarkably similar strategies to overcome these constraints. PMID:17264059
Multi Agent Reward Analysis for Learning in Noisy Domains
NASA Technical Reports Server (NTRS)
Tumer, Kagan; Agogino, Adrian K.
2005-01-01
In many multi agent learning problems, it is difficult to determine, a priori, the agent reward structure that will lead to good performance. This problem is particularly pronounced in continuous, noisy domains ill-suited to simple table backup schemes commonly used in TD(lambda)/Q-learning. In this paper, we present a new reward evaluation method that allows the tradeoff between coordination among the agents and the difficulty of the learning problem each agent faces to be visualized. This method is independent of the learning algorithm and is only a function of the problem domain and the agents reward structure. We then use this reward efficiency visualization method to determine an effective reward without performing extensive simulations. We test this method in both a static and a dynamic multi-rover learning domain where the agents have continuous state spaces and where their actions are noisy (e.g., the agents movement decisions are not always carried out properly). Our results show that in the more difficult dynamic domain, the reward efficiency visualization method provides a two order of magnitude speedup in selecting a good reward. Most importantly it allows one to quickly create and verify rewards tailored to the observational limitations of the domain.
Recovering magnetization distributions from their noisy diffraction data
Loh, Ne-Te Duane; Eisebitt, Stefan; Flewett, Samuel; Elser, Veit
2010-12-15
We study, using simulated experiments inspired by thin-film magnetic domain patterns, the feasibility of phase retrieval in x-ray diffractive imaging in the presence of intrinsic charge scattering given only photon-shot-noise limited diffraction data. We detail a reconstruction algorithm to recover the sample's magnetization distribution under such conditions and compare its performance with that of Fourier transform holography. Concerning the design of future experiments, we also chart out the reconstruction limits of diffractive imaging when photon-shot-noise and the intensity of charge scattering noise are independently varied. This work is directly relevant to the time-resolved imaging of magnetic dynamics using coherent and ultrafast radiation from x-ray free-electron lasers and also to broader classes of diffractive imaging experiments which suffer noisy data, missing data, or both.
Period variability of coupled noisy oscillators
NASA Astrophysics Data System (ADS)
Mori, Fumito; Kori, Hiroshi
2013-03-01
Period variability, quantified by the standard deviation (SD) of the cycle-to-cycle period, is investigated for noisy phase oscillators. We define the checkpoint phase as the beginning or end point of one oscillation cycle and derive an expression for the SD as a function of this phase. We find that the SD is dependent on the checkpoint phase only when oscillators are coupled. The applicability of our theory is verified using a realistic model. Our work clarifies the relationship between period variability and synchronization from which valuable information regarding coupling can be inferred.
A Noisy 10GB Provenance Database
Cheah, You-Wei; Plale, Beth; Kendall-Morwick, Joey; Leake, David; Ramakrishnan, Lavanya
2011-06-06
Provenance of scientific data is a key piece of the metadata record for the data's ongoing discovery and reuse. Provenance collection systems capture provenance on the fly, however, the protocol between application and provenance tool may not be reliable. Consequently, the provenance record can be partial, partitioned, and simply inaccurate. We use a workflow emulator that models faults to construct a large 10GB database of provenance that we know is noisy (that is, has errors). We discuss the process of generating the provenance database, and show early results on the kinds of provenance analysis enabled by the large provenance.
Steering Chiral Swimmers along Noisy Helical Paths
NASA Astrophysics Data System (ADS)
Friedrich, Benjamin M.; Jülicher, Frank
2009-08-01
Chemotaxis along helical paths towards a target releasing a chemoattractant is found in sperm cells and many microorganisms. We discuss the stochastic differential geometry of the noisy helical swimming path of a chiral swimmer. A chiral swimmer equipped with a simple feedback system can navigate in a concentration gradient of chemoattractant. We derive an effective equation for the alignment of helical paths with a concentration gradient which is related to the alignment of a dipole in an external field and discuss the chemotaxis index.
Quantum private comparison over noisy channels
NASA Astrophysics Data System (ADS)
Siddhu, Vikesh; Arvind
2015-08-01
Quantum private comparison (QPC) allows us to protect private information during its comparison. In the past, various three-party quantum protocols have been proposed that claim to work well under noisy conditions. Here, we tackle the problem of QPC under noise. We analyze the EPR-based protocol under depolarizing noise, bit flip and phase flip noise. We show how noise affects the robustness of the EPR-based protocol. We then present a straightforward protocol based on CSS codes to perform QPC which is robust against noise and secure under general attacks.
Cohen, S.A.; Hosea, J.C.; Timberlake, J.R.
1984-10-19
A limiter with a specially contoured front face is provided. The front face of the limiter (the plasma-side face) is flat with a central indentation. In addition, the limiter shape is cylindrically symmetric so that the limiter can be rotated for greater heat distribution. This limiter shape accommodates the various power scrape-off distances lambda p, which depend on the parallel velocity, V/sub parallel/, of the impacting particles.
Optimal information storage in noisy synapses under resource constraints.
Varshney, Lav R; Sjöström, Per Jesper; Chklovskii, Dmitri B
2006-11-01
Experimental investigations have revealed that synapses possess interesting and, in some cases, unexpected properties. We propose a theoretical framework that accounts for three of these properties: typical central synapses are noisy, the distribution of synaptic weights among central synapses is wide, and synaptic connectivity between neurons is sparse. We also comment on the possibility that synaptic weights may vary in discrete steps. Our approach is based on maximizing information storage capacity of neural tissue under resource constraints. Based on previous experimental and theoretical work, we use volume as a limited resource and utilize the empirical relationship between volume and synaptic weight. Solutions of our constrained optimization problems are not only consistent with existing experimental measurements but also make nontrivial predictions. PMID:17088208
Stabilized quasi-Newton optimization of noisy potential energy surfaces
NASA Astrophysics Data System (ADS)
Schaefer, Bastian; Ghasemi, S. Alireza; Roy, Shantanu; Goedecker, Stefan; Goedecker Group Team
Optimizations of atomic positions belong to the most frequently performed tasks in electronic structure calculations. Many simulations like global minimum searches or the identification of chemical reaction pathways can require the computation of hundreds or thousands of minimizations or saddle points. To automatize these tasks, optimization algorithms must not only be efficient but also very reliable. Unfortunately, computational noise in forces and energies is inherent to electronic structure codes. This computational noise poses a severe problem to the stability of efficient optimization methods like the limited-memory Broyden-Fletcher-Goldfarb-Shanno algorithm. In this talk a recently published technique that allows to obtain significant curvature information of noisy potential energy surfaces is presented. This technique was used to construct both, a stabilized quasi-Newton minimization method and a stabilized quasi-Newton saddle finding approach. With the help of benchmarks both the minimizer and the saddle finding approach were demonstrated to be superior to comparable existing methods.
Characterization of noisy symbolic time series.
Kulp, Christopher W; Smith, Suzanne
2011-02-01
The 0-1 test for chaos is a recently developed time series characterization algorithm that can determine whether a system is chaotic or nonchaotic. While the 0-1 test was designed for deterministic series, in real-world measurement situations, noise levels may not be known and the 0-1 test may have difficulty distinguishing between chaos and randomness. In this paper, we couple the 0-1 test for chaos with a test for determinism and apply these tests to noisy symbolic series generated from various model systems. We find that the pairing of the 0-1 test with a test for determinism improves the ability to correctly distinguish between chaos and randomness from a noisy series. Furthermore, we explore the modes of failure for the 0-1 test and the test for determinism so that we can better understand the effectiveness of the two tests to handle various levels of noise. We find that while the tests can handle low noise and high noise situations, moderate levels of noise can lead to inconclusive results from the two tests. PMID:21405890
Classification with Noisy Labels by Importance Reweighting.
Liu, Tongliang; Tao, Dacheng
2016-03-01
In this paper, we study a classification problem in which sample labels are randomly corrupted. In this scenario, there is an unobservable sample with noise-free labels. However, before being observed, the true labels are independently flipped with a probability ρ ∈ [0,0.5), and the random label noise can be class-conditional. Here, we address two fundamental problems raised by this scenario. The first is how to best use the abundant surrogate loss functions designed for the traditional classification problem when there is label noise. We prove that any surrogate loss function can be used for classification with noisy labels by using importance reweighting, with consistency assurance that the label noise does not ultimately hinder the search for the optimal classifier of the noise-free sample. The other is the open problem of how to obtain the noise rate ρ. We show that the rate is upper bounded by the conditional probability P(∧Y|X) of the noisy sample. Consequently, the rate can be estimated, because the upper bound can be easily reached in classification problems. Experimental results on synthetic and real datasets confirm the efficiency of our methods. PMID:27046490
Cohen, Samuel A.; Hosea, Joel C.; Timberlake, John R.
1986-01-01
A limiter with a specially contoured front face accommodates the various power scrape-off distances .lambda..sub.p, which depend on the parallel velocity, V.sub..parallel., of the impacting particles. The front face of the limiter (the plasma-side face) is flat with a central indentation. In addition, the limiter shape is cylindrically symmetric so that the limiter can be rotated for greater heat distribution.
NASA Astrophysics Data System (ADS)
Rahmani, Armin
2015-10-01
Based on the Heisenberg-picture analog of the master equation, we develop a method for computing the exact time dependence of noise-averaged observables for general noninteracting fermionic systems with noisy fluctuations. Upon noise averaging, these fluctuations generate effective interactions, limiting analytical approaches. While the short-time dynamics can be studied with Langevin-type numerical simulations, the long-time limit is not amenable to such simulations. Our results provide access to this long-time limit. As a simple example, we examine the fate of the fractional charge in cold-atom emulations of polyacetylene after stochastic driving. We find that in a quantum quench to a fluctuating hopping Hamiltonian, the fractional charge remains robust for hopping between different sublattices, while it becomes unstable in the presence of noisy hopping on the same sublattice.
Noisy one-way quantum computations: The role of correlations
Chaves, Rafael; Melo, Fernando de
2011-08-15
A scheme to evaluate computation fidelities within the one-way model is developed and explored to understand the role of correlations in the quality of noisy quantum computations. The formalism is promptly applied to many computation instances and unveils that a higher amount of entanglement in the noisy resource state does not necessarily imply a better computation.
Entanglement evolution of two qubits under noisy environments
Li Jungang; Zou Jian; Shao Bin
2010-10-15
The entanglement evolution of two qubits under local, single-, and two-sided noisy channels is investigated. It is found that for all pure initial states, the entanglement under a one-sided noisy channel is completely determined by the maximal trace distance which is the main element to construct the measure of non-Markovianity. For the two-sided noisy channel case, when the qubits are initially prepared in a general class of states, either pure or mixed, the entanglement can be expressed as the product of the initial entanglement and the channels' action on the maximally entangled state.
Quantum steganography with noisy quantum channels
Shaw, Bilal A.; Brun, Todd A.
2011-02-15
Steganography is the technique of hiding secret information by embedding it in a seemingly ''innocent'' message. We present protocols for hiding quantum information by disguising it as noise in a codeword of a quantum error-correcting code. The sender (Alice) swaps quantum information into the codeword and applies a random choice of unitary operation, drawing on a secret random key she shares with the receiver (Bob). Using the key, Bob can retrieve the information, but an eavesdropper (Eve) with the power to monitor the channel, but without the secret key, cannot distinguish the message from channel noise. We consider two types of protocols: one in which the hidden quantum information is stored locally in the codeword, and another in which it is embedded in the space of error syndromes. We analyze how difficult it is for Eve to detect the presence of secret messages, and estimate rates of steganographic communication and secret key consumption for specific protocols and examples of error channels. We consider both the case where there is no actual noise in the channel (so that all errors in the codeword result from the deliberate actions of Alice), and the case where the channel is noisy and not controlled by Alice and Bob.
Textured surface identification in noisy color images
NASA Astrophysics Data System (ADS)
Celenk, Mehmet
1996-06-01
Automatic identification of textured surfaces is essential in many imaging applications such as image data compression and scene recognition. In these applications, a vision system is required to detect and identify irregular textures in the noisy color images. This work proposes a method for texture field characterization based on the local textural features. We first divide a given color image into n multiplied by n local windows and extract textural features in each window independently. In this step, the size of a window should be small enough so that each window can include only two texture fields. Separation of texture areas in a local window is first carried out by the Otsu or Kullback threshold selection technique on three color components separately. The 3-D class separation is then performed using the Fisher discriminant. The result of local texture classification is combined by the K-means clustering algorithm. The texture fields detected in a window are characterized by their mean vectors and an element-to-set membership relation. We have experimented with the local feature extraction part of the method using a color image of irregular textures. Results show that the method is effective for capturing the local textural features.
The noisy voter model on complex networks
NASA Astrophysics Data System (ADS)
Carro, Adrián; Toral, Raúl; San Miguel, Maxi
2016-04-01
We propose a new analytical method to study stochastic, binary-state models on complex networks. Moving beyond the usual mean-field theories, this alternative approach is based on the introduction of an annealed approximation for uncorrelated networks, allowing to deal with the network structure as parametric heterogeneity. As an illustration, we study the noisy voter model, a modification of the original voter model including random changes of state. The proposed method is able to unfold the dependence of the model not only on the mean degree (the mean-field prediction) but also on more complex averages over the degree distribution. In particular, we find that the degree heterogeneity—variance of the underlying degree distribution—has a strong influence on the location of the critical point of a noise-induced, finite-size transition occurring in the model, on the local ordering of the system, and on the functional form of its temporal correlations. Finally, we show how this latter point opens the possibility of inferring the degree heterogeneity of the underlying network by observing only the aggregate behavior of the system as a whole, an issue of interest for systems where only macroscopic, population level variables can be measured.
The noisy voter model on complex networks
Carro, Adrián; Toral, Raúl; San Miguel, Maxi
2016-01-01
We propose a new analytical method to study stochastic, binary-state models on complex networks. Moving beyond the usual mean-field theories, this alternative approach is based on the introduction of an annealed approximation for uncorrelated networks, allowing to deal with the network structure as parametric heterogeneity. As an illustration, we study the noisy voter model, a modification of the original voter model including random changes of state. The proposed method is able to unfold the dependence of the model not only on the mean degree (the mean-field prediction) but also on more complex averages over the degree distribution. In particular, we find that the degree heterogeneity—variance of the underlying degree distribution—has a strong influence on the location of the critical point of a noise-induced, finite-size transition occurring in the model, on the local ordering of the system, and on the functional form of its temporal correlations. Finally, we show how this latter point opens the possibility of inferring the degree heterogeneity of the underlying network by observing only the aggregate behavior of the system as a whole, an issue of interest for systems where only macroscopic, population level variables can be measured. PMID:27094773
The noisy voter model on complex networks.
Carro, Adrián; Toral, Raúl; San Miguel, Maxi
2016-01-01
We propose a new analytical method to study stochastic, binary-state models on complex networks. Moving beyond the usual mean-field theories, this alternative approach is based on the introduction of an annealed approximation for uncorrelated networks, allowing to deal with the network structure as parametric heterogeneity. As an illustration, we study the noisy voter model, a modification of the original voter model including random changes of state. The proposed method is able to unfold the dependence of the model not only on the mean degree (the mean-field prediction) but also on more complex averages over the degree distribution. In particular, we find that the degree heterogeneity-variance of the underlying degree distribution-has a strong influence on the location of the critical point of a noise-induced, finite-size transition occurring in the model, on the local ordering of the system, and on the functional form of its temporal correlations. Finally, we show how this latter point opens the possibility of inferring the degree heterogeneity of the underlying network by observing only the aggregate behavior of the system as a whole, an issue of interest for systems where only macroscopic, population level variables can be measured. PMID:27094773
Hearing conservation practices in eight noisy industries
NASA Astrophysics Data System (ADS)
Daniell, William E.; Swan, Susan S.; Camp, Janice; Cohen, Martin; McDaniel, Mary M.; Stebbins, John; Leo, Robert
2005-04-01
This study evaluated noise exposures and hearing conservation practices at 76 companies in eight industries with high rates of workers' compensation claims for hearing loss. Nearly all companies had exposures that required a hearing conservation program, and more than half had exposures that required consideration of noise controls. The use of noise measurements and consideration of controls was low in all industries. The completeness of hearing conservation programs was strongly associated with the extent of exposure in an industry, although practices varied widely within industries. Most companies had substantial deficiencies. More than one-third did not conduct annual training, and training had shortcomings at many others. One-third had not conducted audiometry. Hearing protection was commonly underused. Reported use was highest at companies with relatively complete programs, and in industries where exposure was most prevalent and least intermittent. Many employees had difficulty estimating how often, and presumably when, their exposure was excessive. There is a need for new strategies to promote and maintain hearing conservation efforts in noisy industries. The industries with greatest margin for improvement are not the noisiest industries but those where exposure is moderate or intermittent. [Work supported by the National Institute for Occupational Safety and Health.
Geometric quantum discord under noisy environment
NASA Astrophysics Data System (ADS)
Huang, Zhiming; Qiu, Daowen
2016-05-01
In this work, we mainly analyze the dynamics of geometric quantum discord under a common dissipating environment. Our results indicate that geometric quantum discord is generated when the initial state is a product state. The geometric quantum discord increases from zero to a stable value with the increasing time, and the variations of stable values depend on the system size. For different initial product states, geometric quantum discord has some different behaviors in contrast with entanglement. For initial maximally entangled state, it is shown that geometric quantum discord decays with the increasing dissipated time. It is found that for EPR state, entanglement is more robust than geometric quantum discord, which is a sharp contrast to the existing result that quantum discord is more robust than entanglement in noisy environments. However, for GHZ state and W state, geometric quantum discord is more stable than entanglement. By the comparison of quantum discord and entanglement, we find that a common dissipating environment brings complicated effects on quantum correlation, which may deepen our understanding of physical impacts of decohering environment on quantum correlation. In the end, we analyze the effects of collective dephasing noise and rotating noise to a class of two-qubit X states, and we find that quantum correlation is not altered by the collective noises.
Noisy signaling through promoter logic gates
NASA Astrophysics Data System (ADS)
Gerstung, Moritz; Timmer, Jens; Fleck, Christian
2009-01-01
We study the influence of noisy transcription factor signals on cis-regulatory promoter elements. These elements process the probability of binary binding events analogous to computer logic gates. At equilibrium, this probability is given by the so-called input function. We show that transcription factor noise causes deviations from the equilibrium value due to the nonlinearity of the input function. For a single binding site, the correction is always negative resulting in an occupancy below the mean-field level. Yet for more complex promoters it depends on the correlation of the transcription factor signals and the geometry of the input function. We present explicit solutions for the basic types of AND and OR gates. The correction size varies among these different types of gates and signal types, mainly being larger in AND gates and for correlated fluctuations. In all cases we find excellent agreement between the analytical results and numerical simulations. We also study the E. coli Lac operon as an example of an AND NOR gate. We present a consistent mathematical method that allows one to separate different sources of noise and quantifies their effect on promoter occupation. A surprising result of our analysis is that Poissonian molecular fluctuations, in contrast to external fluctuations, do no contribute to the correction.
The Noisiness of Low Frequency Bands of Noise
NASA Technical Reports Server (NTRS)
Lawton, B. W.
1975-01-01
The relative noisiness of low frequency 1/3-octave bands of noise was examined. The frequency range investigated was bounded by the bands centered at 25 and 200 Hz, with intensities ranging from 50 to 95 db (SPL). Thirty-two subjects used a method of adjustment technique, producing comparison band intensities as noisy as 100 and 200 Hz standard bands at 60 and 72 db. The work resulted in contours of equal noisiness for 1/3-octave bands, ranging in intensity from approximately 58 to 86 db (SPL). These contours were compared with the standard equal noisiness contours; in the region of overlap, between 50 and 200 Hz, the agreement was good.
Exploring the Noisy Threshold Function in Designing Bayesian Networks
NASA Astrophysics Data System (ADS)
Jurgelenaite, Rasa; Lucas, Peter; Heskes, Tom
Causal independence modelling is a well-known method both for reducing the size of probability tables and for explaining the underlying mechanisms in Bayesian networks. Many Bayesian network models incorporate causal independence assumptions; however, only the noisy OR and noisy AND, two examples of causal independence models, are used in practice. Their underlying assumption that either at least one cause, or all causes together, give rise to an effect, however, seems unnecessarily restrictive. In the present paper a new, more flexible, causal independence model is proposed, based on the Boolean threshold function. A connection is established between conditional probability distributions based on the noisy threshold model and Poisson binomial distributions, and the basic properties of this probability distribution are studied in some depth. The successful application of the noisy threshold model in the refinement of a Bayesian network for the diagnosis and treatment of ventilator-associated pneumonia demo nstrates the practical value of the presented theory.
Unconditional security from noisy quantum storage
NASA Astrophysics Data System (ADS)
Wehner, Stephanie
2010-03-01
We consider the implementation of two-party cryptographic primitives based on the sole physical assumption that no large-scale reliable quantum storage is available to the cheating party. An important example of such a task is secure identification. Here, Alice wants to identify herself to Bob (possibly an ATM machine) without revealing her password. More generally, Alice and Bob wish to solve problems where Alice holds an input x (e.g. her password), and Bob holds an input y (e.g. the password an honest Alice should possess), and they want to obtain the value of some function f(x,y) (e.g. the equality function). Security means that the legitimate users should not learn anything beyond this specification. That is, Alice should not learn anything about y and Bob should not learn anything about x, other than what they may be able to infer from the value of f(x,y). We show that any such problem can be solved securely in the noisy-storage model by constructing protocols for bit commitment and oblivious transfer, where we prove security against the most general attack. Our protocols can be implemented with present-day hardware used for quantum key distribution. In particular, no quantum storage is required for the honest parties. Our work raises a large number of immediate theoretical as well as experimental questions related to many aspects of quantum information science, such as for example understanding the information carrying properties of quantum channels and memories, randomness extraction, min-entropy sampling, as well as constructing small handheld devices which are suitable for the task of secure identification. [4pt] Full version available at arXiv:0906.1030 (theoretical) and arXiv:0911.2302 (practically oriented).
Computational quantum-classical boundary of noisy commuting quantum circuits
Fujii, Keisuke; Tamate, Shuhei
2016-01-01
It is often said that the transition from quantum to classical worlds is caused by decoherence originated from an interaction between a system of interest and its surrounding environment. Here we establish a computational quantum-classical boundary from the viewpoint of classical simulatability of a quantum system under decoherence. Specifically, we consider commuting quantum circuits being subject to decoherence. Or equivalently, we can regard them as measurement-based quantum computation on decohered weighted graph states. To show intractability of classical simulation in the quantum side, we utilize the postselection argument and crucially strengthen it by taking noise effect into account. Classical simulatability in the classical side is also shown constructively by using both separable criteria in a projected-entangled-pair-state picture and the Gottesman-Knill theorem for mixed state Clifford circuits. We found that when each qubit is subject to a single-qubit complete-positive-trace-preserving noise, the computational quantum-classical boundary is sharply given by the noise rate required for the distillability of a magic state. The obtained quantum-classical boundary of noisy quantum dynamics reveals a complexity landscape of controlled quantum systems. This paves a way to an experimentally feasible verification of quantum mechanics in a high complexity limit beyond classically simulatable region. PMID:27189039
Computational quantum-classical boundary of noisy commuting quantum circuits
NASA Astrophysics Data System (ADS)
Fujii, Keisuke; Tamate, Shuhei
2016-05-01
It is often said that the transition from quantum to classical worlds is caused by decoherence originated from an interaction between a system of interest and its surrounding environment. Here we establish a computational quantum-classical boundary from the viewpoint of classical simulatability of a quantum system under decoherence. Specifically, we consider commuting quantum circuits being subject to decoherence. Or equivalently, we can regard them as measurement-based quantum computation on decohered weighted graph states. To show intractability of classical simulation in the quantum side, we utilize the postselection argument and crucially strengthen it by taking noise effect into account. Classical simulatability in the classical side is also shown constructively by using both separable criteria in a projected-entangled-pair-state picture and the Gottesman-Knill theorem for mixed state Clifford circuits. We found that when each qubit is subject to a single-qubit complete-positive-trace-preserving noise, the computational quantum-classical boundary is sharply given by the noise rate required for the distillability of a magic state. The obtained quantum-classical boundary of noisy quantum dynamics reveals a complexity landscape of controlled quantum systems. This paves a way to an experimentally feasible verification of quantum mechanics in a high complexity limit beyond classically simulatable region.
Computational quantum-classical boundary of noisy commuting quantum circuits.
Fujii, Keisuke; Tamate, Shuhei
2016-01-01
It is often said that the transition from quantum to classical worlds is caused by decoherence originated from an interaction between a system of interest and its surrounding environment. Here we establish a computational quantum-classical boundary from the viewpoint of classical simulatability of a quantum system under decoherence. Specifically, we consider commuting quantum circuits being subject to decoherence. Or equivalently, we can regard them as measurement-based quantum computation on decohered weighted graph states. To show intractability of classical simulation in the quantum side, we utilize the postselection argument and crucially strengthen it by taking noise effect into account. Classical simulatability in the classical side is also shown constructively by using both separable criteria in a projected-entangled-pair-state picture and the Gottesman-Knill theorem for mixed state Clifford circuits. We found that when each qubit is subject to a single-qubit complete-positive-trace-preserving noise, the computational quantum-classical boundary is sharply given by the noise rate required for the distillability of a magic state. The obtained quantum-classical boundary of noisy quantum dynamics reveals a complexity landscape of controlled quantum systems. This paves a way to an experimentally feasible verification of quantum mechanics in a high complexity limit beyond classically simulatable region. PMID:27189039
Equivalence between learning in noisy perceptrons and tree committee machines
NASA Astrophysics Data System (ADS)
Copelli, Mauro; Kinouchi, Osame; Caticha, Nestor
1996-06-01
We study learning from single presentation of examples (on-line learning) in single-layer perceptrons and tree committee machines (TCMs). Lower bounds for the perceptron generalization error as a function of the noise level ɛ in the teacher output are calculated. We find that local learning in a TCM with K hidden units is simply related to learning in a simple perceptron with a corresponding noise level ɛ(K). For a large number of examples and finite K the generalization error decays as α-1CM, where αCM is the number of examples per adjustable weight in the TCM. We also show that on-line learning is possible even in the K-->∞ limit, but with the generalization error decaying as α-1/2CM. The simple Hebb rule can also be applied to the TCM, but now the error decays as α-1/2CM for finite K and α-1/4CM for K-->∞. Exponential decay of the generalization error in both the noisy perceptron learning and in the TCM is obtained by using the learning by queries strategy.
Pandemics and immune memory in the noisy Penna model
NASA Astrophysics Data System (ADS)
Cebrat, Stanisław; Bonkowska, Katarzyna; Biecek, Przemysław
2007-06-01
In the noisy Penna model of ageing, instead of counting the number of defective loci which eventually kill an individual, the noise describing the health status of individuals is introduced. This white noise is composed of two components: the environmental one and the personal one. If the sum of both trespasses the limit set for the individuals homeodynamics the individual dies. The energy of personal fluctuations depends on the number of defective loci expressed in the individuals genome. Environmental fluctuations, the same for all individuals can include some signals, corresponding to the exposition to pathogens which could be dangerous for a fraction of the organisms. Personal noise and the component of random environmental fluctuations, when superimposed on the signal can be life threatening if they are stronger than the limit set for individuals homeodynamics. Nevertheless, some organisms survive the period of dangerous signal and they may remember the signal in the future, like antigens are remembered by our immune systems. Unfortunately, this memory weakens with time and, even worse, some additional defective genes are switched on during the ageing. If the same pathogens (signals) emerge during the lifespan of the population, a fraction of the population could remember it and could respond by increasing the resistance to it. Again, unfortunately for some individuals, their memory could be too weak and their own health status has worsened due to the accumulated mutations, they have to die. Though, a fraction of individuals can survive the pandemics due to the immune memory, but a fraction of population has no such a memory because they were born after the last pandemic or they didnt notice this pandemic. Our simple model, by implementing the noise instead of deterministic threshold of genetic defects, describes how the impact of pandemics on populations depends on the time which elapsed between the two incidents and how the different age groups of
Extortion under uncertainty: Zero-determinant strategies in noisy games
NASA Astrophysics Data System (ADS)
Hao, Dong; Rong, Zhihai; Zhou, Tao
2015-05-01
Repeated game theory has been one of the most prevailing tools for understanding long-running relationships, which are the foundation in building human society. Recent works have revealed a new set of "zero-determinant" (ZD) strategies, which is an important advance in repeated games. A ZD strategy player can exert unilateral control on two players' payoffs. In particular, he can deterministically set the opponent's payoff or enforce an unfair linear relationship between the players' payoffs, thereby always seizing an advantageous share of payoffs. One of the limitations of the original ZD strategy, however, is that it does not capture the notion of robustness when the game is subjected to stochastic errors. In this paper, we propose a general model of ZD strategies for noisy repeated games and find that ZD strategies have high robustness against errors. We further derive the pinning strategy under noise, by which the ZD strategy player coercively sets the opponent's expected payoff to his desired level, although his payoff control ability declines with the increase of noise strength. Due to the uncertainty caused by noise, the ZD strategy player cannot ensure his payoff to be permanently higher than the opponent's, which implies dominant extortions do not exist even under low noise. While we show that the ZD strategy player can still establish a novel kind of extortions, named contingent extortions, where any increase of his own payoff always exceeds that of the opponent's by a fixed percentage, and the conditions under which the contingent extortions can be realized are more stringent as the noise becomes stronger.
Methods for measuring the loudness and noisiness of complex sounds
NASA Technical Reports Server (NTRS)
Kryter, K.
1970-01-01
Physical and temporal aspects of sound which influence the rating of subjective noisiness are intensity, spectrum shape and bandwidth, spectral complexity, and duration. Objective rating methods include a graphic method, full octave and one-third octave methods, and methods that measure one value over all frequencies.
Data and Network Science for Noisy Heterogeneous Systems
ERIC Educational Resources Information Center
Rider, Andrew Kent
2013-01-01
Data in many growing fields has an underlying network structure that can be taken advantage of. In this dissertation we apply data and network science to problems in the domains of systems biology and healthcare. Data challenges in these fields include noisy, heterogeneous data, and a lack of ground truth. The primary thesis of this work is that…
The Effects of Noisy Data on Text Retrieval.
ERIC Educational Resources Information Center
Taghva, Kazem; And Others
1994-01-01
Discusses the use of optical character recognition (OCR) for inputting documents in an information retrieval system and describes a study that used an OCR-generated database and its corresponding corrected version to examine query evaluation in the presence of noisy data. Scanning technology, recognition technology, and retrieval technology are…
Synchronization of the Noisy Electrosensitive Cells in the Paddlefish
Neiman, A.; Pei, X.; Russell, D.; Wojtenek, W.; Wilkens, L.; Moss, F.; Braun, H.A.; Voigt, K.; Huber, M.T.
1999-01-01
Synchronization of electrosensitive cells of the paddlefish is studied by means of electrophysiological experiments. Different types of noisy phase locked regimes are observed. The experimental data are compared with computer simulations of a noise-mediated modified Hodgkin-Huxley neuron model and of a stochastic circle map. {copyright} {ital 1999} {ital The American Physical Society }
Neural basis of identity information extraction from noisy face images.
Hermann, Petra; Bankó, Éva M; Gál, Viktor; Vidnyánszky, Zoltán
2015-05-01
Previous research has made significant progress in identifying the neural basis of the remarkably efficient and seemingly effortless face perception in humans. However, the neural processes that enable the extraction of facial information under challenging conditions when face images are noisy and deteriorated remains poorly understood. Here we investigated the neural processes underlying the extraction of identity information from noisy face images using fMRI. For each participant, we measured (1) face-identity discrimination performance outside the scanner, (2) visual cortical fMRI responses for intact and phase-randomized face stimuli, and (3) intrinsic functional connectivity using resting-state fMRI. Our whole-brain analysis showed that the presence of noise led to reduced and increased fMRI responses in the mid-fusiform gyrus and the lateral occipital cortex, respectively. Furthermore, the noise-induced modulation of the fMRI responses in the right face-selective fusiform face area (FFA) was closely associated with individual differences in the identity discrimination performance of noisy faces: smaller decrease of the fMRI responses was accompanied by better identity discrimination. The results also revealed that the strength of the intrinsic functional connectivity within the visual cortical network composed of bilateral FFA and bilateral object-selective lateral occipital cortex (LOC) predicted the participants' ability to discriminate the identity of noisy face images. These results imply that perception of facial identity in the case of noisy face images is subserved by neural computations within the right FFA as well as a re-entrant processing loop involving bilateral FFA and LOC. PMID:25948266
Immunity in the Noisy Penna Model
NASA Astrophysics Data System (ADS)
Biecek, Przemysław; Cebrat, Stanisław
We have modified the Penna standard sexual model in such a way, that the state of each individual has been determined by the individual fluctuation and the fluctuation of the environment. If the sum of both fluctuations is higher than the assumed limit, the organism dies. Additionally, the individuals can learn the trends of the environment's fluctuations, diminishing their deleterious effects. This mechanism leads to the higher mortality of the youngest individuals and the lowest mortality of individuals just before reaching the minimum reproduction age. These phenomena are observed in any mortality curve describing the age structures of human populations.
Coordinating Multi-Rover Systems: Evaluation Functions for Dynamic and Noisy Environments
NASA Technical Reports Server (NTRS)
Turner, Kagan; Agogino, Adrian
2005-01-01
This paper addresses the evolution of control strategies for a collective: a set of entities that collectively strives to maximize a global evaluation function that rates the performance of the full system. Directly addressing such problems by having a population of collectives and applying the evolutionary algorithm to that population is appealing, but the search space is prohibitively large in most cases. Instead, we focus on evolving control policies for each member of the collective. The fundamental issue in this approach is how to create an evaluation function for each member of the collective that is both aligned with the global evaluation function and is sensitive to the fitness changes of the member, while relatively insensitive to the fitness changes of other members. We show how to construct evaluation functions in dynamic, noisy and communication-limited collective environments. On a rover coordination problem, a control policy evolved using aligned and member-sensitive evaluations outperfoms global evaluation methods by up to 400%. More notably, in the presence of a larger number of rovers or rovers with noisy and communication limited sensors, the proposed method outperforms global evaluation by a higher percentage than in noise-free conditions with a small number of rovers.
Desert ants achieve reliable recruitment across noisy interactions
Razin, Nitzan; Eckmann, Jean-Pierre; Feinerman, Ofer
2013-01-01
We study how desert ants, Cataglyphis niger, a species that lacks pheromone-based recruitment mechanisms, inform each other about the presence of food. Our results are based on automated tracking that allows us to collect a large database of ant trajectories and interactions. We find that interactions affect an ant's speed within the nest. Fast ants tend to slow down, whereas slow ones increase their speed when encountering a faster ant. Faster ants tend to exit the nest more frequently than slower ones. So, if an ant gains enough speed through encounters with others, then she tends to leave the nest and look for food. On the other hand, we find that the probability for her to leave the nest depends only on her speed, but not on whether she had recently interacted with a recruiter that has found the food. This suggests a recruitment system in which ants communicate their state by very simple interactions. Based on this assumption, we estimate the information-theoretical channel capacity of the ants’ pairwise interactions. We find that the response to the speed of an interacting nest-mate is very noisy. The question is then how random interactions with ants within the nest can be distinguished from those interactions with a recruiter who has found food. Our measurements and model suggest that this distinction does not depend on reliable communication but on behavioural differences between ants that have found the food and those that have not. Recruiters retain high speeds throughout the experiment, regardless of the ants they interact with; non-recruiters communicate with a limited number of nest-mates and adjust their speed following these interactions. These simple rules lead to the formation of a bistable switch on the level of the group that allows the distinction between recruitment and random noise in the nest. A consequence of the mechanism we propose is a negative effect of ant density on exit rates and recruitment success. This is, indeed, confirmed by
Continuous data assimilation with stochastically noisy data
NASA Astrophysics Data System (ADS)
Bessaih, Hakima; Olson, Eric; Titi, Edriss S.
2015-03-01
We analyse the performance of a data-assimilation algorithm based on a linear feedback control when used with observational data that contains measurement errors. Our model problem consists of dynamics governed by the two-dimensional incompressible Navier-Stokes equations, observational measurements given by finite volume elements or nodal points of the velocity field and measurement errors which are represented by stochastic noise. Under these assumptions, the data-assimilation algorithm consists of a system of stochastically forced Navier-Stokes equations. The main result of this paper provides explicit conditions on the observation density (resolution) which guarantee explicit asymptotic bounds, as the time tends to infinity, on the error between the approximate solution and the actual solutions which is corresponding to these measurements, in terms of the variance of the noise in the measurements. Specifically, such bounds are given for the limit supremum, as the time tends to infinity, of the expected value of the L2-norm and of the H1 Sobolev norm of the difference between the approximating solution and the actual solution. Moreover, results on the average time error in mean are stated. birthday.
Finding the Way with a Noisy Brain
Cheung, Allen; Vickerstaff, Robert
2010-01-01
Successful navigation is fundamental to the survival of nearly every animal on earth, and achieved by nervous systems of vastly different sizes and characteristics. Yet surprisingly little is known of the detailed neural circuitry from any species which can accurately represent space for navigation. Path integration is one of the oldest and most ubiquitous navigation strategies in the animal kingdom. Despite a plethora of computational models, from equational to neural network form, there is currently no consensus, even in principle, of how this important phenomenon occurs neurally. Recently, all path integration models were examined according to a novel, unifying classification system. Here we combine this theoretical framework with recent insights from directed walk theory, and develop an intuitive yet mathematically rigorous proof that only one class of neural representation of space can tolerate noise during path integration. This result suggests many existing models of path integration are not biologically plausible due to their intolerance to noise. This surprising result imposes significant computational limitations on the neurobiological spatial representation of all successfully navigating animals, irrespective of species. Indeed, noise-tolerance may be an important functional constraint on the evolution of neuroarchitectural plans in the animal kingdom. PMID:21085678
Casting polymer nets to optimize noisy molecular codes
Tlusty, Tsvi
2008-01-01
Life relies on the efficient performance of molecular codes, which relate symbols and meanings via error-prone molecular recognition. We describe how optimizing a code to withstand the impact of molecular recognition noise may be understood from the statistics of a two-dimensional network made of polymers. The noisy code is defined by partitioning the space of symbols into regions according to their meanings. The “polymers” are the boundaries between these regions, and their statistics define the cost and the quality of the noisy code. When the parameters that control the cost–quality balance are varied, the polymer network undergoes a transition, where the number of encoded meanings rises discontinuously. Effects of population dynamics on the evolution of molecular codes are discussed. PMID:18550822
Quantum error correction assisted by two-way noisy communication
Wang, Zhuo; Yu, Sixia; Fan, Heng; Oh, C. H.
2014-01-01
Pre-shared non-local entanglement dramatically simplifies and improves the performance of quantum error correction via entanglement-assisted quantum error-correcting codes (EAQECCs). However, even considering the noise in quantum communication only, the non-local sharing of a perfectly entangled pair is technically impossible unless additional resources are consumed, such as entanglement distillation, which actually compromises the efficiency of the codes. Here we propose an error-correcting protocol assisted by two-way noisy communication that is more easily realisable: all quantum communication is subjected to general noise and all entanglement is created locally without additional resources consumed. In our protocol the pre-shared noisy entangled pairs are purified simultaneously by the decoding process. For demonstration, we first present an easier implementation of the well-known EAQECC [[4, 1, 3; 1
Noisy zigzag transition, fluctuations, and thermal bifurcation threshold.
Delfau, Jean-Baptiste; Coste, Christophe; Saint Jean, Michel
2013-06-01
We study the zigzag transition in a system of particles with screened electrostatic interaction, submitted to a thermal noise. At finite temperature, this configurational phase transition is an example of noisy supercritical pitchfork bifurcation. The measurements of transverse fluctuations allow a complete description of the bifurcation region, which takes place between the deterministic threshold and a thermal threshold beyond which thermal fluctuations do not allow the system to flip between the symmetric zigzag configurations. We show that a divergence of the saturation time for the transverse fluctuations allows a precise and unambiguous definition of this thermal threshold. Its evolution with the temperature is shown to be in good agreement with theoretical predictions from noisy bifurcation theory. PMID:23848655
Noisy zigzag transition, fluctuations, and thermal bifurcation threshold
NASA Astrophysics Data System (ADS)
Delfau, Jean-Baptiste; Coste, Christophe; Saint Jean, Michel
2013-06-01
We study the zigzag transition in a system of particles with screened electrostatic interaction, submitted to a thermal noise. At finite temperature, this configurational phase transition is an example of noisy supercritical pitchfork bifurcation. The measurements of transverse fluctuations allow a complete description of the bifurcation region, which takes place between the deterministic threshold and a thermal threshold beyond which thermal fluctuations do not allow the system to flip between the symmetric zigzag configurations. We show that a divergence of the saturation time for the transverse fluctuations allows a precise and unambiguous definition of this thermal threshold. Its evolution with the temperature is shown to be in good agreement with theoretical predictions from noisy bifurcation theory.
Quantum error correction assisted by two-way noisy communication
NASA Astrophysics Data System (ADS)
Wang, Zhuo; Yu, Sixia; Fan, Heng; Oh, C. H.
2014-11-01
Pre-shared non-local entanglement dramatically simplifies and improves the performance of quantum error correction via entanglement-assisted quantum error-correcting codes (EAQECCs). However, even considering the noise in quantum communication only, the non-local sharing of a perfectly entangled pair is technically impossible unless additional resources are consumed, such as entanglement distillation, which actually compromises the efficiency of the codes. Here we propose an error-correcting protocol assisted by two-way noisy communication that is more easily realisable: all quantum communication is subjected to general noise and all entanglement is created locally without additional resources consumed. In our protocol the pre-shared noisy entangled pairs are purified simultaneously by the decoding process. For demonstration, we first present an easier implementation of the well-known EAQECC [[4, 1, 3; 1
Quantum error correction assisted by two-way noisy communication.
Wang, Zhuo; Yu, Sixia; Fan, Heng; Oh, C H
2014-01-01
Pre-shared non-local entanglement dramatically simplifies and improves the performance of quantum error correction via entanglement-assisted quantum error-correcting codes (EAQECCs). However, even considering the noise in quantum communication only, the non-local sharing of a perfectly entangled pair is technically impossible unless additional resources are consumed, such as entanglement distillation, which actually compromises the efficiency of the codes. Here we propose an error-correcting protocol assisted by two-way noisy communication that is more easily realisable: all quantum communication is subjected to general noise and all entanglement is created locally without additional resources consumed. In our protocol the pre-shared noisy entangled pairs are purified simultaneously by the decoding process. For demonstration, we first present an easier implementation of the well-known EAQECC [[4, 1, 3; 1
Identification and tracking of particular speaker in noisy environment
NASA Astrophysics Data System (ADS)
Sawada, Hideyuki; Ohkado, Minoru
2004-10-01
Human is able to exchange information smoothly using voice under different situations such as noisy environment in a crowd and with the existence of plural speakers. We are able to detect the position of a source sound in 3D space, extract a particular sound from mixed sounds, and recognize who is talking. By realizing this mechanism with a computer, new applications will be presented for recording a sound with high quality by reducing noise, presenting a clarified sound, and realizing a microphone-free speech recognition by extracting particular sound. The paper will introduce a realtime detection and identification of particular speaker in noisy environment using a microphone array based on the location of a speaker and the individual voice characteristics. The study will be applied to develop an adaptive auditory system of a mobile robot which collaborates with a factory worker.
An integrated approach to improving noisy speech perception
NASA Astrophysics Data System (ADS)
Koval, Serguei; Stolbov, Mikhail; Smirnova, Natalia; Khitrov, Mikhail
2002-05-01
For a number of practical purposes and tasks, experts have to decode speech recordings of very poor quality. A combination of techniques is proposed to improve intelligibility and quality of distorted speech messages and thus facilitate their comprehension. Along with the application of noise cancellation and speech signal enhancement techniques removing and/or reducing various kinds of distortions and interference (primarily unmasking and normalization in time and frequency fields), the approach incorporates optimal listener expert tactics based on selective listening, nonstandard binaural listening, accounting for short-term and long-term human ear adaptation to noisy speech, as well as some methods of speech signal enhancement to support speech decoding during listening. The approach integrating the suggested techniques ensures high-quality ultimate results and has successfully been applied by Speech Technology Center experts and by numerous other users, mainly forensic institutions, to perform noisy speech records decoding for courts, law enforcement and emergency services, accident investigation bodies, etc.
Machine printed text and handwriting identification in noisy document images.
Zheng, Yefeng; Li, Huiping; Doermann, David
2004-03-01
In this paper, we address the problem of the identification of text in noisy document images. We are especially focused on segmenting and identifying between handwriting and machine printed text because: 1) Handwriting in a document often indicates corrections, additions, or other supplemental information that should be treated differently from the main content and 2) the segmentation and recognition techniques requested for machine printed and handwritten text are significantly different. A novel aspect of our approach is that we treat noise as a separate class and model noise based on selected features. Trained Fisher classifiers are used to identify machine printed text and handwriting from noise and we further exploit context to refine the classification. A Markov Random Field-based (MRF) approach is used to model the geometrical structure of the printed text, handwriting, and noise to rectify misclassifications. Experimental results show that our approach is robust and can significantly improve page segmentation in noisy document collections. PMID:15376881
Magnitude Estimation with Noisy Integrators Linked by an Adaptive Reference.
Thurley, Kay
2016-01-01
Judgments of physical stimuli show characteristic biases; relatively small stimuli are overestimated whereas relatively large stimuli are underestimated (regression effect). Such biases likely result from a strategy that seeks to minimize errors given noisy estimates about stimuli that itself are drawn from a distribution, i.e., the statistics of the environment. While being conceptually well described, it is unclear how such a strategy could be implemented neurally. The present paper aims toward answering this question. A theoretical approach is introduced that describes magnitude estimation as two successive stages of noisy (neural) integration. Both stages are linked by a reference memory that is updated with every new stimulus. The model reproduces the behavioral characteristics of magnitude estimation and makes several experimentally testable predictions. Moreover, the model identifies the regression effect as a means of minimizing estimation errors and explains how this optimality strategy depends on the subject's discrimination abilities and on the stimulus statistics. The latter influence predicts another property of magnitude estimation, the so-called range effect. Beyond being successful in describing decision-making, the present work suggests that noisy integration may also be important in processing magnitudes. PMID:26909028
Shape Adaptive, Robust Iris Feature Extraction from Noisy Iris Images
Ghodrati, Hamed; Dehghani, Mohammad Javad; Danyali, Habibolah
2013-01-01
In the current iris recognition systems, noise removing step is only used to detect noisy parts of the iris region and features extracted from there will be excluded in matching step. Whereas depending on the filter structure used in feature extraction, the noisy parts may influence relevant features. To the best of our knowledge, the effect of noise factors on feature extraction has not been considered in the previous works. This paper investigates the effect of shape adaptive wavelet transform and shape adaptive Gabor-wavelet for feature extraction on the iris recognition performance. In addition, an effective noise-removing approach is proposed in this paper. The contribution is to detect eyelashes and reflections by calculating appropriate thresholds by a procedure called statistical decision making. The eyelids are segmented by parabolic Hough transform in normalized iris image to decrease computational burden through omitting rotation term. The iris is localized by an accurate and fast algorithm based on coarse-to-fine strategy. The principle of mask code generation is to assign the noisy bits in an iris code in order to exclude them in matching step is presented in details. An experimental result shows that by using the shape adaptive Gabor-wavelet technique there is an improvement on the accuracy of recognition rate. PMID:24696801
Magnitude Estimation with Noisy Integrators Linked by an Adaptive Reference
Thurley, Kay
2016-01-01
Judgments of physical stimuli show characteristic biases; relatively small stimuli are overestimated whereas relatively large stimuli are underestimated (regression effect). Such biases likely result from a strategy that seeks to minimize errors given noisy estimates about stimuli that itself are drawn from a distribution, i.e., the statistics of the environment. While being conceptually well described, it is unclear how such a strategy could be implemented neurally. The present paper aims toward answering this question. A theoretical approach is introduced that describes magnitude estimation as two successive stages of noisy (neural) integration. Both stages are linked by a reference memory that is updated with every new stimulus. The model reproduces the behavioral characteristics of magnitude estimation and makes several experimentally testable predictions. Moreover, the model identifies the regression effect as a means of minimizing estimation errors and explains how this optimality strategy depends on the subject's discrimination abilities and on the stimulus statistics. The latter influence predicts another property of magnitude estimation, the so-called range effect. Beyond being successful in describing decision-making, the present work suggests that noisy integration may also be important in processing magnitudes. PMID:26909028
A reconstruction method for gappy and noisy arterial flow data.
Yakhot, Alexander; Anor, Tomer; Karniadakis, George Em
2007-12-01
Proper orthogonal decomposition (POD), Kriging interpolation, and smoothing are applied to reconstruct gappy and noisy data of blood flow in a carotid artery. While we have applied these techniques to clinical data, in this paper in order to rigorously evaluate their effectiveness we rely on data obtained by computational fluid dynamics (CFD). Specifically, gappy data sets are generated by removing nodal values from high-resolution 3-D CFD data (at random or in a fixed area) while noisy data sets are formed by superimposing speckle noise on the CFD results. A combined POD-Kriging procedure is applied to planar data sets mimicking coarse resolution "ultrasound-like" blood flow images. A method for locating the vessel wall boundary and for calculating the wall shear stress (WSS) is also proposed. The results show good agreement with the original CFD data. The combined POD-Kriging method, enhanced by proper smoothing if needed, holds great potential in dealing effectively with gappy and noisy data reconstruction of in vivo velocity measurements based on color Doppler ultrasound (CDUS) imaging or magnetic resonance angiography (MRA). PMID:18092738
Shape adaptive, robust iris feature extraction from noisy iris images.
Ghodrati, Hamed; Dehghani, Mohammad Javad; Danyali, Habibolah
2013-10-01
In the current iris recognition systems, noise removing step is only used to detect noisy parts of the iris region and features extracted from there will be excluded in matching step. Whereas depending on the filter structure used in feature extraction, the noisy parts may influence relevant features. To the best of our knowledge, the effect of noise factors on feature extraction has not been considered in the previous works. This paper investigates the effect of shape adaptive wavelet transform and shape adaptive Gabor-wavelet for feature extraction on the iris recognition performance. In addition, an effective noise-removing approach is proposed in this paper. The contribution is to detect eyelashes and reflections by calculating appropriate thresholds by a procedure called statistical decision making. The eyelids are segmented by parabolic Hough transform in normalized iris image to decrease computational burden through omitting rotation term. The iris is localized by an accurate and fast algorithm based on coarse-to-fine strategy. The principle of mask code generation is to assign the noisy bits in an iris code in order to exclude them in matching step is presented in details. An experimental result shows that by using the shape adaptive Gabor-wavelet technique there is an improvement on the accuracy of recognition rate. PMID:24696801
Dynamics from noisy data with extreme timing uncertainty.
Fung, R; Hanna, A M; Vendrell, O; Ramakrishna, S; Seideman, T; Santra, R; Ourmazd, A; Ourmazd, A
2016-04-28
Imperfect knowledge of the times at which 'snapshots' of a system are recorded degrades our ability to recover dynamical information, and can scramble the sequence of events. In X-ray free-electron lasers, for example, the uncertainty--the so-called timing jitter--between the arrival of an optical trigger ('pump') pulse and a probing X-ray pulse can exceed the length of the X-ray pulse by up to two orders of magnitude, marring the otherwise precise time-resolution capabilities of this class of instruments. The widespread notion that little dynamical information is available on timescales shorter than the timing uncertainty has led to various hardware schemes to reduce timing uncertainty. These schemes are expensive, tend to be specific to one experimental approach and cannot be used when the record was created under ill-defined or uncontrolled conditions such as during geological events. Here we present a data-analytical approach, based on singular-value decomposition and nonlinear Laplacian spectral analysis, that can recover the history and dynamics of a system from a dense collection of noisy snapshots spanning a sufficiently large multiple of the timing uncertainty. The power of the algorithm is demonstrated by extracting the underlying dynamics on the few-femtosecond timescale from noisy experimental X-ray free-electron laser data recorded with 300-femtosecond timing uncertainty. Using a noisy dataset from a pump-probe experiment on the Coulomb explosion of nitrogen molecules, our analysis reveals vibrational wave-packets consisting of components with periods as short as 15 femtoseconds, as well as more rapid changes, which have yet to be fully explored. Our approach can potentially be applied whenever dynamical or historical information is tainted by timing uncertainty. PMID:27121840
Dynamics from noisy data with extreme timing uncertainty
NASA Astrophysics Data System (ADS)
Fung, R.; Ourmazd, A.; Hanna, A. M.; Vendrell, O.; Ramakrishna, S.; Seideman, T.; Santra, R.; Ourmazd, A.
2016-04-01
Imperfect knowledge of the times at which ‘snapshots’ of a system are recorded degrades our ability to recover dynamical information, and can scramble the sequence of events. In X-ray free-electron lasers, for example, the uncertainty—the so-called timing jitter—between the arrival of an optical trigger (‘pump’) pulse and a probing X-ray pulse can exceed the length of the X-ray pulse by up to two orders of magnitude, marring the otherwise precise time-resolution capabilities of this class of instruments. The widespread notion that little dynamical information is available on timescales shorter than the timing uncertainty has led to various hardware schemes to reduce timing uncertainty. These schemes are expensive, tend to be specific to one experimental approach and cannot be used when the record was created under ill-defined or uncontrolled conditions such as during geological events. Here we present a data-analytical approach, based on singular-value decomposition and nonlinear Laplacian spectral analysis, that can recover the history and dynamics of a system from a dense collection of noisy snapshots spanning a sufficiently large multiple of the timing uncertainty. The power of the algorithm is demonstrated by extracting the underlying dynamics on the few-femtosecond timescale from noisy experimental X-ray free-electron laser data recorded with 300-femtosecond timing uncertainty. Using a noisy dataset from a pump-probe experiment on the Coulomb explosion of nitrogen molecules, our analysis reveals vibrational wave-packets consisting of components with periods as short as 15 femtoseconds, as well as more rapid changes, which have yet to be fully explored. Our approach can potentially be applied whenever dynamical or historical information is tainted by timing uncertainty.
Allard, Rémy; Faubert, Jocelyn
2008-08-01
Visual psychophysics often manipulates the contrast of the image on a digital display screen. Therefore, the limitation of the number of different luminance intensities displayable for most computers (typically, 256) is frequently an issue. To avoid this problem, experimenters generally need to purchase special hardware (graphic cards) and/or develop specific computer programs. Here, we describe an easy-to-implement method, consisting of adding noise to the displayed stimulus, that we call the noisy-bit method. This random dithering method, generalized to 256 luminance intensities, is equivalent to displaying continuous luminance intensities plus a certain amount of noise. Psychophysical testing using a standard spatiotemporal resolution (60 Hz and 1,024 x 768 pixels) demonstrated that the noise introduced by the noisy-bit method has no significant impact on contrast threshold and is not visible. We conclude that the noisy-bit method, combined with the standard 256 luminance levels, is perceptually equivalent to an analog display with a continuous luminance intensity resolution when the spatiotemporal resolution is high enough that the noise becomes negligible (which is easily attainable with the typical spatiotemporal resolutions of present-day computers). PMID:18697669
Direct Characterization of Quantum Dynamics with Noisy Ancilla
NASA Astrophysics Data System (ADS)
Dumitrescu, Eugene; Humble, Travis
We present methods for the direct characterization of quantum dynamics (DCQD) in which both the principal and ancilla systems undergo noisy processes. Using a concatenated error detection code, we discriminate between located and unlocated errors on the principal system in what amounts to filtering of ancilla noise. The example of composite noise involving amplitude damping and depolarizing channels is used to demonstrate the method, while we find the rate of noise filtering is more generally dependent on code distance. Our results indicate the accuracy of quantum process characterization can be greatly improved while remaining within reach of current experimental capabilities. We acknowledge support from the IC postdoctoral research program.
Performance evaluation of antenna arrays with noisy carrier reference
NASA Technical Reports Server (NTRS)
Yan, T. Y.; Clare, L. P.
1981-01-01
The performance evaluation of coherent receivers with noisy carrier references and multiple antennas is presented. The received signal is assumed to be residual carrier BPSK, with a PLL used for extracting the carrier. Explicit relationships between the error probabilities and the various system parameters are given. Specific results are given for the performance gain of combined carrier referencing over baseband only combining when the channel alignment process is ideal. A simple asymptotic expression for the performance gain is determined when the number of antennas used is increased without bound. Examples using Deep Space Network receivers illustrate the performance of each arraying structure.
Direct characterization of quantum dynamics with noisy ancilla
Dumitrescu, Eugene F.; Humble, Travis S.
2015-11-23
We present methods for the direct characterization of quantum dynamics (DCQD) in which both the principal and ancilla systems undergo noisy processes. Using a concatenated error detection code, we discriminate between located and unlocated errors on the principal system in what amounts to filtering of ancilla noise. The example of composite noise involving amplitude damping and depolarizing channels is used to demonstrate the method, while we find the rate of noise filtering is more generally dependent on code distance. Furthermore our results indicate the accuracy of quantum process characterization can be greatly improved while remaining within reach of current experimental capabilities.
Direct characterization of quantum dynamics with noisy ancilla
Dumitrescu, Eugene F.; Humble, Travis S.
2015-11-23
We present methods for the direct characterization of quantum dynamics (DCQD) in which both the principal and ancilla systems undergo noisy processes. Using a concatenated error detection code, we discriminate between located and unlocated errors on the principal system in what amounts to filtering of ancilla noise. The example of composite noise involving amplitude damping and depolarizing channels is used to demonstrate the method, while we find the rate of noise filtering is more generally dependent on code distance. Furthermore our results indicate the accuracy of quantum process characterization can be greatly improved while remaining within reach of current experimentalmore » capabilities.« less
Statistical Analysis of Noisy Signals Using Classification Tools
Thompson, Sandra E.; Heredia-Langner, Alejandro; Johnson, Timothy J.; Foster, Nancy S.; Valentine, Nancy B.; Amonette, James E.
2005-06-04
The potential use of chemicals, biotoxins and biological pathogens are a threat to military and police forces as well as the general public. Rapid identification of these agents is made difficult due to the noisy nature of the signal that can be obtained from portable, in-field sensors. In previously published articles, we created a flowchart that illustrated a method for triaging bacterial identification by combining standard statistical techniques for discrimination and identification with mid-infrared spectroscopic data. The present work documents the process of characterizing and eliminating the sources of the noise and outlines how multidisciplinary teams are necessary to accomplish that goal.
Entanglement and communication-reducing properties of noisy N-qubit states
Laskowski, Wieslaw; Paterek, Tomasz; Brukner, Caslav; Zukowski, Marek
2010-04-15
We consider properties of states of many qubits, which arise after sending certain entangled states via various noisy channels (white noise, colored noise, local depolarization, dephasing, and amplitude damping). Entanglement of these states and their ability to violate certain classes of Bell inequalities are studied. States which violate them allow a higher than classical efficiency in solving related distributed computational tasks with constrained communication. This is a direct property of such states--not requiring their further modification via stochastic local operations and classical communication such as entanglement purification or distillation procedures. We identify families of multiparticle states which are entangled but nevertheless allow the local realistic description of specific Bell experiments. For some of them, the 'gap' between the critical values for entanglement and violation of Bell inequality remains finite even in the limit of infinitely many qubits.
End-to-end quality measure for transmission of compressed imagery over a noisy coded channel
NASA Technical Reports Server (NTRS)
Korwar, V. N.; Lee, P. J.
1981-01-01
For the transmission of imagery at high data rates over large distances with limited power and system gain, it is usually necessary to compress the data before transmitting it over a noisy channel that uses channel coding to reduce the effect of noise introduced errors. Both compression and channel noise introduce distortion into the imagery. In order to design a communication link that provides adequate quality of received images, it is necessary first to define some suitable distortion measure that accounts for both these kinds of distortion and then to perform various tradeoffs to arrive at system parameter values that will provide a sufficiently low level of received image distortion. The overall mean square error is used as the distortion measure and a description of how to perform these tradeoffs are included.
NASA Technical Reports Server (NTRS)
Polites, M. E.
1991-01-01
This paper presents a new approach to processing noisy startracker measurements in spacecraft attitude determination systems. It takes N measurements in each T-second interval and combines them to produce tracker outputs that are estimates of star position at the end of each interval, when the tracker outputs become available. This is an improvement over the standard method, measurement averaging, which generates outputs that are estimates of the average position of the star over each interval. This new scheme is superior to measurement averaging when the spacecraft has some rotation rate as in target tracking or earth pointing. Also, it is not just limited to startracker, but has potential application wherever measurement averaging of sensor outputs is used.
An efficient method for simulation of noisy coupled multi-dimensional oscillators
NASA Astrophysics Data System (ADS)
Stinchcombe, Adam R.; Forger, Daniel B.
2016-09-01
We present an efficient computational method for the study of populations of noisy coupled oscillators. By taking a population density approach in which the probability density of observing an oscillator at a point of state space is the primary variable instead of the states of all of the oscillators, we are able to seamlessly account for intrinsic noise within the oscillators and global coupling within the population. The population is assumed to consist of a large number of oscillators so that the noise process is well sampled over the population. Our numerical method is able to solve the governing equation even in the challenging case of limit cycle oscillators with a large number of state variables. Instead of simulating a prohibitive number of oscillators, our particle method simulates relatively few particles allowing for the efficient solution of the governing equation.
Extensions to minimum relative entropy inversion for noisy data
NASA Astrophysics Data System (ADS)
Ulrych, Tadeusz J.; Woodbury, Allan D.
2003-12-01
Minimum relative entropy (MRE) and Tikhonov regularization (TR) were compared by Neupauer et al. [Water Resour. Res. 36 (2000) 2469] on the basis of an example plume source reconstruction problem originally proposed by Skaggs and Kabala [Water Resour. Res. 30 (1994) 71] and a boxcar-like function. Although Neupauer et al. [Water Resour. Res. 36 (2000) 2469] were careful in their conclusions to note the basis of these comparisons, we show that TR does not perform well on problems in which delta-like sources are convolved with diffuse-groundwater contamination response functions, particularly in the presence of noise. We also show that it is relatively easy to estimate an appropriate value for ɛ, the hyperparameter needed in the minimum relative entropy solution for the inverse problem in the presence of noise. This can be estimated in a variety of ways, including estimation from the data themselves, analysis of data residuals, and a rigorous approach using the real cepstrum and the Akaike Information Criterion (AIC). Regardless of the approach chosen, for the sample problem reported herein, excellent resolution of multiple delta-like spikes is produced from MRE from noisy, diffuse data. The usefulness of MRE for noisy inverse problems has been demonstrated.
AveBoost2: Boosting for Noisy Data
NASA Technical Reports Server (NTRS)
Oza, Nikunj C.
2004-01-01
AdaBoost is a well-known ensemble learning algorithm that constructs its constituent or base models in sequence. A key step in AdaBoost is constructing a distribution over the training examples to create each base model. This distribution, represented as a vector, is constructed to be orthogonal to the vector of mistakes made by the pre- vious base model in the sequence. The idea is to make the next base model's errors uncorrelated with those of the previous model. In previous work, we developed an algorithm, AveBoost, that constructed distributions orthogonal to the mistake vectors of all the previous models, and then averaged them to create the next base model s distribution. Our experiments demonstrated the superior accuracy of our approach. In this paper, we slightly revise our algorithm to allow us to obtain non-trivial theoretical results: bounds on the training error and generalization error (difference between training and test error). Our averaging process has a regularizing effect which, as expected, leads us to a worse training error bound for our algorithm than for AdaBoost but a superior generalization error bound. For this paper, we experimented with the data that we used in both as originally supplied and with added label noise-a small fraction of the data has its original label changed. Noisy data are notoriously difficult for AdaBoost to learn. Our algorithm's performance improvement over AdaBoost is even greater on the noisy data than the original data.
Noisy human neighbours affect where urban monkeys live.
Duarte, Marina H L; Vecci, Marco A; Hirsch, André; Young, Robert J
2011-12-23
Urban areas and many natural habitats are being dominated by a new selection pressure: anthropogenic noise. The ongoing expansion of urban areas, roads and airports throughout the world makes the noise almost omnipresent. Urbanization and the increase of noise levels form a major threat to living conditions in and around cities. Insight into the behavioural strategies of urban survivors may explain the sensitivity of other species to urban selection pressures. Here, we show that urban black-tufted marmosets (Callithrix penicillata) living in noisy urban areas may select their home-range based primarily on ambient noise level. We have tested the hypothesis that the noise from vehicular traffic and visitors in an urban park in Brazil influences the use of home-range (space) by urban marmosets. Marmosets even avoided noisy areas with high food availability. In addition, they systematically preferred the quieter areas even with dynamic changes in the acoustic landscape of the park between weekdays and Sundays (no observations were made on Saturdays). These data provide evidence that the use of home-range by wild animals can be affected by a potential aversive stimulus such as noise pollution. PMID:21715396
Effect of weak measurement on entanglement distribution over noisy channels.
Wang, Xin-Wen; Yu, Sixia; Zhang, Deng-Yu; Oh, C H
2016-01-01
Being able to implement effective entanglement distribution in noisy environments is a key step towards practical quantum communication, and long-term efforts have been made on the development of it. Recently, it has been found that the null-result weak measurement (NRWM) can be used to enhance probabilistically the entanglement of a single copy of amplitude-damped entangled state. This paper investigates remote distributions of bipartite and multipartite entangled states in the amplitudedamping environment by combining NRWMs and entanglement distillation protocols (EDPs). We show that the NRWM has no positive effect on the distribution of bipartite maximally entangled states and multipartite Greenberger-Horne-Zeilinger states, although it is able to increase the amount of entanglement of each source state (noisy entangled state) of EDPs with a certain probability. However, we find that the NRWM would contribute to remote distributions of multipartite W states. We demonstrate that the NRWM can not only reduce the fidelity thresholds for distillability of decohered W states, but also raise the distillation efficiencies of W states. Our results suggest a new idea for quantifying the ability of a local filtering operation in protecting entanglement from decoherence. PMID:26935775
Effect of weak measurement on entanglement distribution over noisy channels
NASA Astrophysics Data System (ADS)
Wang, Xin-Wen; Yu, Sixia; Zhang, Deng-Yu; Oh, C. H.
2016-03-01
Being able to implement effective entanglement distribution in noisy environments is a key step towards practical quantum communication, and long-term efforts have been made on the development of it. Recently, it has been found that the null-result weak measurement (NRWM) can be used to enhance probabilistically the entanglement of a single copy of amplitude-damped entangled state. This paper investigates remote distributions of bipartite and multipartite entangled states in the amplitudedamping environment by combining NRWMs and entanglement distillation protocols (EDPs). We show that the NRWM has no positive effect on the distribution of bipartite maximally entangled states and multipartite Greenberger-Horne-Zeilinger states, although it is able to increase the amount of entanglement of each source state (noisy entangled state) of EDPs with a certain probability. However, we find that the NRWM would contribute to remote distributions of multipartite W states. We demonstrate that the NRWM can not only reduce the fidelity thresholds for distillability of decohered W states, but also raise the distillation efficiencies of W states. Our results suggest a new idea for quantifying the ability of a local filtering operation in protecting entanglement from decoherence.
Optimal block cosine transform image coding for noisy channels
NASA Technical Reports Server (NTRS)
Vaishampayan, V.; Farvardin, N.
1986-01-01
The two dimensional block transform coding scheme based on the discrete cosine transform was studied extensively for image coding applications. While this scheme has proven to be efficient in the absence of channel errors, its performance degrades rapidly over noisy channels. A method is presented for the joint source channel coding optimization of a scheme based on the 2-D block cosine transform when the output of the encoder is to be transmitted via a memoryless design of the quantizers used for encoding the transform coefficients. This algorithm produces a set of locally optimum quantizers and the corresponding binary code assignment for the assumed transform coefficient statistics. To determine the optimum bit assignment among the transform coefficients, an algorithm was used based on the steepest descent method, which under certain convexity conditions on the performance of the channel optimized quantizers, yields the optimal bit allocation. Comprehensive simulation results for the performance of this locally optimum system over noisy channels were obtained and appropriate comparisons against a reference system designed for no channel error were rendered.
Noisy human neighbours affect where urban monkeys live
Duarte, Marina H. L.; Vecci, Marco A.; Hirsch, André; Young, Robert J.
2011-01-01
Urban areas and many natural habitats are being dominated by a new selection pressure: anthropogenic noise. The ongoing expansion of urban areas, roads and airports throughout the world makes the noise almost omnipresent. Urbanization and the increase of noise levels form a major threat to living conditions in and around cities. Insight into the behavioural strategies of urban survivors may explain the sensitivity of other species to urban selection pressures. Here, we show that urban black-tufted marmosets (Callithrix penicillata) living in noisy urban areas may select their home-range based primarily on ambient noise level. We have tested the hypothesis that the noise from vehicular traffic and visitors in an urban park in Brazil influences the use of home-range (space) by urban marmosets. Marmosets even avoided noisy areas with high food availability. In addition, they systematically preferred the quieter areas even with dynamic changes in the acoustic landscape of the park between weekdays and Sundays (no observations were made on Saturdays). These data provide evidence that the use of home-range by wild animals can be affected by a potential aversive stimulus such as noise pollution. PMID:21715396
Identification of Bifurcations from Observations of Noisy Biological Oscillators.
Salvi, Joshua D; Ó Maoiléidigh, Dáibhid; Hudspeth, A J
2016-08-23
Hair bundles are biological oscillators that actively transduce mechanical stimuli into electrical signals in the auditory, vestibular, and lateral-line systems of vertebrates. A bundle's function can be explained in part by its operation near a particular type of bifurcation, a qualitative change in behavior. By operating near different varieties of bifurcation, the bundle responds best to disparate classes of stimuli. We show how to determine the identity of and proximity to distinct bifurcations despite the presence of substantial environmental noise. Using an improved mechanical-load clamp to coerce a hair bundle to traverse different bifurcations, we find that a bundle operates within at least two functional regimes. When coupled to a high-stiffness load, a bundle functions near a supercritical Hopf bifurcation, in which case it responds best to sinusoidal stimuli such as those detected by an auditory organ. When the load stiffness is low, a bundle instead resides close to a subcritical Hopf bifurcation and achieves a graded frequency response-a continuous change in the rate, but not the amplitude, of spiking in response to changes in the offset force-a behavior that is useful in a vestibular organ. The mechanical load in vivo might therefore control a hair bundle's responsiveness for effective operation in a particular receptor organ. Our results provide direct experimental evidence for the existence of distinct bifurcations associated with a noisy biological oscillator, and demonstrate a general strategy for bifurcation analysis based on observations of any noisy system. PMID:27558723
A multistaged automatic restoration of noisy microscopy cell images.
Xu, Jinwei; Hu, Jiankun; Jia, Xiuping
2015-01-01
Automated cell segmentation for microscopy cell images has recently become an initial step for further image analysis in cell biology. However, microscopy cell images are easily degraded by noise during the readout procedure via optical-electronic imaging systems. Such noise degradations result in low signal-to-noise ratio (SNR) and poor image quality for cell identification. In order to improve SNR for subsequent segmentation and image-based quantitative analysis, the commonly used state-of-art restoration techniques are applied but few of them are suitable for corrupted microscopy cell images. In this paper, we propose a multistaged method based on a novel integration of trend surface analysis, quantile-quantile plot, bootstrapping, and the Gaussian spatial kernel for the restoration of noisy microscopy cell images. We show this multistaged approach achieves higher performance compared with other state-of-art restoration techniques in terms of peak signal-to-noise ratio and structure similarity in synthetic noise experiments. This paper also reports an experiment on real noisy microscopy data which demonstrated the advantages of the proposed restoration method for improving segmentation performance. PMID:25291801
Effect of weak measurement on entanglement distribution over noisy channels
Wang, Xin-Wen; Yu, Sixia; Zhang, Deng-Yu; Oh, C. H.
2016-01-01
Being able to implement effective entanglement distribution in noisy environments is a key step towards practical quantum communication, and long-term efforts have been made on the development of it. Recently, it has been found that the null-result weak measurement (NRWM) can be used to enhance probabilistically the entanglement of a single copy of amplitude-damped entangled state. This paper investigates remote distributions of bipartite and multipartite entangled states in the amplitudedamping environment by combining NRWMs and entanglement distillation protocols (EDPs). We show that the NRWM has no positive effect on the distribution of bipartite maximally entangled states and multipartite Greenberger-Horne-Zeilinger states, although it is able to increase the amount of entanglement of each source state (noisy entangled state) of EDPs with a certain probability. However, we find that the NRWM would contribute to remote distributions of multipartite W states. We demonstrate that the NRWM can not only reduce the fidelity thresholds for distillability of decohered W states, but also raise the distillation efficiencies of W states. Our results suggest a new idea for quantifying the ability of a local filtering operation in protecting entanglement from decoherence. PMID:26935775
Forecasting turbulent modes with nonparametric diffusion models: Learning from noisy data
NASA Astrophysics Data System (ADS)
Berry, Tyrus; Harlim, John
2016-04-01
In this paper, we apply a recently developed nonparametric modeling approach, the "diffusion forecast", to predict the time-evolution of Fourier modes of turbulent dynamical systems. While the diffusion forecasting method assumes the availability of a noise-free training data set observing the full state space of the dynamics, in real applications we often have only partial observations which are corrupted by noise. To alleviate these practical issues, following the theory of embedology, the diffusion model is built using the delay-embedding coordinates of the data. We show that this delay embedding biases the geometry of the data in a way which extracts the most stable component of the dynamics and reduces the influence of independent additive observation noise. The resulting diffusion forecast model approximates the semigroup solutions of the generator of the underlying dynamics in the limit of large data and when the observation noise vanishes. As in any standard forecasting problem, the forecasting skill depends crucially on the accuracy of the initial conditions. We introduce a novel Bayesian method for filtering the discrete-time noisy observations which works with the diffusion forecast to determine the forecast initial densities. Numerically, we compare this nonparametric approach with standard stochastic parametric models on a wide-range of well-studied turbulent modes, including the Lorenz-96 model in weakly chaotic to fully turbulent regimes and the barotropic modes of a quasi-geostrophic model with baroclinic instabilities. We show that when the only available data is the low-dimensional set of noisy modes that are being modeled, the diffusion forecast is indeed competitive to the perfect model.
Trading in markets with noisy information: an evolutionary analysis
NASA Astrophysics Data System (ADS)
Bloembergen, Daan; Hennes, Daniel; McBurney, Peter; Tuyls, Karl
2015-07-01
We analyse the value of information in a stock market where information can be noisy and costly, using techniques from empirical game theory. Previous work has shown that the value of information follows a J-curve, where averagely informed traders perform below market average, and only insiders prevail. Here we show that both noise and cost can change this picture, in several cases leading to opposite results where insiders perform below market average, and averagely informed traders prevail. Moreover, we investigate the effect of random explorative actions on the market dynamics, showing how these lead to a mix of traders being sustained in equilibrium. These results provide insight into the complexity of real marketplaces, and show under which conditions a broad mix of different trading strategies might be sustainable.
Reconstruction of pulse noisy images via stochastic resonance
Han, Jing; Liu, Hongjun; Sun, Qibing; Huang, Nan
2015-01-01
We investigate a practical technology for reconstructing nanosecond pulse noisy images via stochastic resonance, which is based on the modulation instability. A theoretical model of this method for optical pulse signal is built to effectively recover the pulse image. The nanosecond noise-hidden images grow at the expense of noise during the stochastic resonance process in a photorefractive medium. The properties of output images are mainly determined by the input signal-to-noise intensity ratio, the applied voltage across the medium, and the correlation length of noise background. A high cross-correlation gain is obtained by optimizing these parameters. This provides a potential method for detecting low-level or hidden pulse images in various imaging applications. PMID:26067911
Inferring the spatiotemporal DNA replication program from noisy data
NASA Astrophysics Data System (ADS)
Baker, A.; Bechhoefer, J.
2014-03-01
We generalize a stochastic model of DNA replication to the case where replication-origin-initiation rates vary locally along the genome and with time. Using this generalized model, we address the inverse problem of inferring initiation rates from experimental data concerning replication in cell populations. Previous work based on curve fitting depended on arbitrarily chosen functional forms for the initiation rate, with free parameters that were constrained by the data. We introduce a nonparametric method of inference that is based on Gaussian process regression. The method replaces specific assumptions about the functional form of the initiation rate with more general prior expectations about the smoothness of variation of this rate, along the genome and in time. Using this inference method, we recover, with high precision, simulated replication schemes from noisy data that are typical of current experiments.
Information jet: Handling noisy big data from weakly disconnected network
NASA Astrophysics Data System (ADS)
Aurongzeb, Deeder
Sudden aggregation (information jet) of large amount of data is ubiquitous around connected social networks, driven by sudden interacting and non-interacting events, network security threat attacks, online sales channel etc. Clustering of information jet based on time series analysis and graph theory is not new but little work is done to connect them with particle jet statistics. We show pre-clustering based on context can element soft network or network of information which is critical to minimize time to calculate results from noisy big data. We show difference between, stochastic gradient boosting and time series-graph clustering. For disconnected higher dimensional information jet, we use Kallenberg representation theorem (Kallenberg, 2005, arXiv:1401.1137) to identify and eliminate jet similarities from dense or sparse graph.
A direct search algorithm for optimization with noisy function evaluations
Anderson, E.; Ferris, M.
1994-12-31
In this paper we describe a new direct search algorithm, reminiscent of the Nelder-Mead method, and related to a more recent pattern search algorithm proposed by Torczon. We believe that this method has applications in situations in which each function evaluation is noisy, but in which repeated function evaluations at the same point can be used to progressively reduce the error. For example, this will occur if the objective function value is given as a result of a simulation experiment. We investigate the convergence behaviour of the new algorithm for problems in which each function evaluation returns the true value of the function plus a random error drawn from a Normal distribution.
Measurement of infinitesimal phase response curves from noisy real neurons
NASA Astrophysics Data System (ADS)
Ota, Keisuke; Omori, Toshiaki; Watanabe, Shigeo; Miyakawa, Hiroyoshi; Okada, Masato; Aonishi, Toru
2011-10-01
We sought to measure infinitesimal phase response curves (iPRCs) from rat hippocampal CA1 pyramidal neurons. It is difficult to measure iPRCs from noisy neurons because of the dilemma that either the linearity or the signal-to-noise ratio of responses to external perturbations must be sacrificed. To overcome this difficulty, we used an iPRC measurement model formulated as the Langevin phase equation (LPE) to extract iPRCs in the Bayesian scheme. We then simultaneously verified the effectiveness of the measurement model and the reliability of the estimated iPRCs by demonstrating that LPEs with the estimated iPRCs could predict the stochastic behaviors of the same neurons, whose iPRCs had been measured, when they were perturbed by periodic stimulus currents. Our results suggest that the LPE is an effective model for real oscillating neurons and that many theoretical frameworks based on it may be applicable to real nerve systems.
Cavity approach to noisy learning in nonlinear perceptrons
NASA Astrophysics Data System (ADS)
Luo, Peixun; Michael Wong, K. Y.
2001-12-01
We analyze the learning of noisy teacher-generated examples by nonlinear and differentiable student perceptrons using the cavity method. The generic activation of an example is a function of the cavity activation of the example, which is its activation in the perceptron that learns without the example. Mean-field equations for the macroscopic parameters and the stability condition yield results consistent with the replica method. When a single value of the cavity activation maps to multiple values of the generic activation, there is a competition in learning strategy between preferentially learning an example and sacrificing it in favor of the background adjustment. We find parameter regimes in which examples are learned preferentially or sacrificially, leading to a gap in the activation distribution. Full phase diagrams of this complex system are presented, and the theory predicts the existence of a phase transition from poor to good generalization states in the system. Simulation results confirm the theoretical predictions.
Symplectic geometry spectrum regression for prediction of noisy time series
NASA Astrophysics Data System (ADS)
Xie, Hong-Bo; Dokos, Socrates; Sivakumar, Bellie; Mengersen, Kerrie
2016-05-01
We present the symplectic geometry spectrum regression (SGSR) technique as well as a regularized method based on SGSR for prediction of nonlinear time series. The main tool of analysis is the symplectic geometry spectrum analysis, which decomposes a time series into the sum of a small number of independent and interpretable components. The key to successful regularization is to damp higher order symplectic geometry spectrum components. The effectiveness of SGSR and its superiority over local approximation using ordinary least squares are demonstrated through prediction of two noisy synthetic chaotic time series (Lorenz and Rössler series), and then tested for prediction of three real-world data sets (Mississippi River flow data and electromyographic and mechanomyographic signal recorded from human body).
Symplectic geometry spectrum regression for prediction of noisy time series.
Xie, Hong-Bo; Dokos, Socrates; Sivakumar, Bellie; Mengersen, Kerrie
2016-05-01
We present the symplectic geometry spectrum regression (SGSR) technique as well as a regularized method based on SGSR for prediction of nonlinear time series. The main tool of analysis is the symplectic geometry spectrum analysis, which decomposes a time series into the sum of a small number of independent and interpretable components. The key to successful regularization is to damp higher order symplectic geometry spectrum components. The effectiveness of SGSR and its superiority over local approximation using ordinary least squares are demonstrated through prediction of two noisy synthetic chaotic time series (Lorenz and Rössler series), and then tested for prediction of three real-world data sets (Mississippi River flow data and electromyographic and mechanomyographic signal recorded from human body). PMID:27300890
Perpendicular diffusion of energetic particles in noisy reduced magnetohydrodynamic turbulence
Shalchi, A.; Hussein, M. E-mail: m_hussein@physics.umanitoba.ca
2014-10-10
A model for noisy reduced magnetohydrodynamic turbulence was recently proposed. This model was already used to study the random walk of magnetic field lines. In the current article we use the same model to investigate the diffusion of energetic particles across the mean magnetic field. To compute the perpendicular diffusion coefficient, two analytical theories are used, namely, the Non-Linear Guiding Center theory and the Unified Non-Linear Transport (UNLT) theory. It is shown that the two theories provide different results for the perpendicular diffusion coefficient. We also perform test-particle simulations for the aforementioned turbulence model. We show that only the UNLT theory describes perpendicular transport accurately, confirming that this is a powerful tool in diffusion theory.
Edge detection of noisy images based on cellular neural networks
NASA Astrophysics Data System (ADS)
Li, Huaqing; Liao, Xiaofeng; Li, Chuandong; Huang, Hongyu; Li, Chaojie
2011-09-01
This paper studies a technique employing both cellular neural networks (CNNs) and linear matrix inequality (LMI) for edge detection of noisy images. Our main work focuses on training templates of noise reduction and edge detection CNNs. Based on the Lyapunov stability theorem, we derive a criterion for global asymptotical stability of a unique equilibrium of the noise reduction CNN. Then we design an approach to train edge detection templates, and this approach can detect the edge precisely and efficiently, i.e., by only one iteration. Finally, we illustrate performance of the proposed methodology from the aspect of peak signal to noise ratio (PSNR) through computer simulations. Moreover, some comparisons are also given to prove that our method outperforms classical operators in gray image edge detection.
Decoding information from noisy, redundant, and intentionally distorted sources
NASA Astrophysics Data System (ADS)
Yu, Yi-Kuo; Zhang, Yi-Cheng; Laureti, Paolo; Moret, Lionel
2006-11-01
Advances in information technology reduce barriers to information propagation, but at the same time they also induce the information overload problem. For the making of various decisions, mere digestion of the relevant information has become a daunting task due to the massive amount of information available. This information, such as that generated by evaluation systems developed by various web sites, is in general useful but may be noisy and may also contain biased entries. In this study, we establish a framework to systematically tackle the challenging problem of information decoding in the presence of massive and redundant data. When applied to a voting system, our method simultaneously ranks the raters and the ratees using only the evaluation data, consisting of an array of scores each of which represents the rating of a ratee by a rater. Not only is our approach effective in decoding information, it is also shown to be robust against various hypothetical types of noise as well as intentional abuses.
Grothendieck's constant and local models for noisy entangled quantum states
Acin, Antonio; Gisin, Nicolas; Toner, Benjamin
2006-06-15
We relate the nonlocal properties of noisy entangled states to Grothendieck's constant, a mathematical constant appearing in Banach space theory. For two-qubit Werner states {rho}{sub p}{sup W}=p|{psi}{sup -}><{psi}{sup -}|+(1-p)1/4, we show that there is a local model for projective measurements if and only if p{<=}1/K{sub G}(3), where K{sub G}(3) is Grothendieck's constant of order 3. Known bounds on K{sub G}(3) prove the existence of this model at least for p < or approx. 0.66, quite close to the current region of Bell violation, p{approx}0.71. We generalize this result to arbitrary quantum states.
On comparison of accuracy of approximate solutions of operator equations with noisy data
NASA Astrophysics Data System (ADS)
Hämarik, Uno
2016-06-01
We consider an operator equation with noisy data where the noise level is given. The case of noisy data is especially actual in ill-posed problems. We formulate a criterion for comparison of accuracy of two approximate solutions get by arbitrary (different) methods. This generalizes previous results about monotonicity of error of approximate solutions generated by the same method but using different parameters.
Evolving Multi Rover Systems in Dynamic and Noisy Environments
NASA Technical Reports Server (NTRS)
Tumer, Kagan; Agogino, Adrian
2005-01-01
In this chapter, we address how to evolve control strategies for a collective: a set of entities that collectively strives to maximize a global evaluation function that rates the performance of the full system. Addressing such problems by directly applying a global evolutionary algorithm to a population of collectives is unworkable because the search space is prohibitively large. Instead, we focus on evolving control policies for each member of the collective, where each member is trying to maximize the fitness of its own population. The main difficulty with this approach is creating fitness evaluation functions for the members of the collective that induce the collective to achieve high performance with respect to the system level goal. To overcome this difficulty, we derive member evaluation functions that are both aligned with the global evaluation function (ensuring that members trying to achieve high fitness results in a collective with high fitness) and sensitive to the fitness of each member (a member's fitness depends more on its own actions than on actions of other members). In a difficult rover coordination problem in dynamic and noisy environments, we show how to construct evaluation functions that lead to good collective behavior. The control policy evolved using aligned and member-sensitive evaluations outperforms global evaluation methods by up to a factor of four. in addition we show that the collective continues to perform well in the presence of high noise levels and when the environment is highly dynamic. More notably, in the presence of a larger number of rovers or rovers with noisy sensors, the improvements due to the proposed method become significantly more pronounced.
Judgements of relative noisiness of a supersonic transport and several commercial-service aircraft
NASA Technical Reports Server (NTRS)
Powell, C. A.
1977-01-01
Two laboratory experiments were conducted on the relative noisiness of takeoff and landing operations of a supersonic transport and several other aircraft in current commercial service. A total of 96 subjects made noisiness judgments on 120 tape-recorded flyover noises in the outdoor-acoustic-simulation experiment; 32 different subjects made judgments on the noises in the indoor-acoustic-simulation experiment. The judgments were made by using the method of numerical category scaling. The effective perceived noise level underestimated the noisiness of the supersonic transport by 3.5 db. For takeoff operations, no difference was found between the noisiness of the supersonic transport and the group of other aircraft for the A-weighted rating scale; however, for landing operations, the noisiness of the supersonic transport was overestimated by 3.7 db. Very high correlation was found between the outdoor-simulation experiment and the indoor-simulation experiment.
Quantum Correlations of Two Relativistic Spin-{1}/{2} Particles Under Noisy Channels
NASA Astrophysics Data System (ADS)
Mahdian, M.; Mojaveri, B.; Dehghani, A.; Makaremi, T.
2016-02-01
We study the quantum correlation dynamics of bipartite spin-{1}/{2} density matrices for two particles under Wigner rotations induced by Lorentz transformations which is transmitted through noisy channels. We compare quantum entanglement, geometric discord(GD), and quantum discord (QD) for bipartite relativistic spin-{1}/{2} states under noisy channels. We find out QD and GD tend to death asymptotically but a sudden change in the decay rate of the entanglement occurs under noisy channels. Also, bipartite relativistic spin density matrices are considered as a quantum channel for teleportation one-qubit state under the influence of depolarizing noise and compare fidelity for various velocities of observers.
Analysis of overlapped and noisy hydrogen/deuterium exchange mass spectra.
Guttman, Miklos; Weis, David D; Engen, John R; Lee, Kelly K
2013-12-01
Noisy and overlapped mass spectrometry data hinder the sequence coverage that can be obtained from hydrogen deuterium exchange analysis, and places a limit on the complexity of the samples that can be studied by this technique. Advances in instrumentation have addressed these limits, but as the complexity of the biological samples under investigation increases, these problems are re-encountered. Here we describe the use of binomial distribution fitting with asymmetric linear squares regression for calculating the accurate deuterium content for mass envelopes of low signal or that contain significant overlap. The approach is demonstrated with a test data set of HIV Env gp140 wherein inclusion of the new analysis regime resulted in obtaining exchange data for 42 additional peptides, improving the sequence coverage by 11%. At the same time, the precision of deuterium uptake measurements was improved for nearly every peptide examined. The improved processing algorithms also provide an efficient method for deconvolution of bimodal mass envelopes and EX1 kinetic signatures. All these functions and visualization tools have been implemented in the new version of the freely available software, HX-Express v2. PMID:24018862
Analysis of Overlapped and Noisy Hydrogen/Deuterium Exchange Mass Spectra
NASA Astrophysics Data System (ADS)
Guttman, Miklos; Weis, David D.; Engen, John R.; Lee, Kelly K.
2013-12-01
Noisy and overlapped mass spectrometry data hinder the sequence coverage that can be obtained from hydrogen deuterium exchange analysis, and places a limit on the complexity of the samples that can be studied by this technique. Advances in instrumentation have addressed these limits, but as the complexity of the biological samples under investigation increases, these problems are re-encountered. Here we describe the use of binomial distribution fitting with asymmetric linear squares regression for calculating the accurate deuterium content for mass envelopes of low signal or that contain significant overlap. The approach is demonstrated with a test data set of HIV Env gp140 wherein inclusion of the new analysis regime resulted in obtaining exchange data for 42 additional peptides, improving the sequence coverage by 11 %. At the same time, the precision of deuterium uptake measurements was improved for nearly every peptide examined. The improved processing algorithms also provide an efficient method for deconvolution of bimodal mass envelopes and EX1 kinetic signatures. All these functions and visualization tools have been implemented in the new version of the freely available software, HX-Express v2.
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.
Reconstructing Breakage Fusion Bridge Architectures Using Noisy Copy Numbers
Bafna, Vineet
2015-01-01
Abstract The Breakage Fusion Bridge (BFB) process is a key marker for genomic instability, producing highly rearranged genomes in relatively small numbers of cell cycles. While the process itself was observed during the late 1930s, little is known about the extent of BFB in tumor genome evolution. Moreover, BFB can dramatically increase copy numbers of chromosomal segments, which in turn hardens the tasks of both reference-assisted and ab initio genome assembly. Based on available data such as Next Generation Sequencing (NGS) and Array Comparative Genomic Hybridization (aCGH) data, we show here how BFB evidence may be identified, and how to enumerate all possible evolutions of the process with respect to observed data. Specifically, we describe practical algorithms that, given a chromosomal arm segmentation and noisy segment copy number estimates, produce all segment count vectors supported by the data that can be produced by BFB, and all corresponding BFB architectures. This extends the scope of analyses described in our previous work, which produced a single count vector and architecture per instance. We apply these analyses to a comprehensive human cancer dataset, demonstrate the effectiveness and efficiency of the computation, and suggest methods for further assertions of candidate BFB samples. Source code of our tool can be found online. PMID:26020441
Improved restoration algorithm for weakly blurred and strongly noisy image
NASA Astrophysics Data System (ADS)
Liu, Qianshun; Xia, Guo; Zhou, Haiyang; Bai, Jian; Yu, Feihong
2015-10-01
In real applications, such as consumer digital imaging, it is very common to record weakly blurred and strongly noisy images. Recently, a state-of-art algorithm named geometric locally adaptive sharpening (GLAS) has been proposed. By capturing local image structure, it can effectively combine denoising and sharpening together. However, there still exist two problems in the practice. On one hand, two hard thresholds have to be constantly adjusted with different images so as not to produce over-sharpening artifacts. On the other hand, the smoothing parameter must be manually set precisely. Otherwise, it will seriously magnify the noise. However, these parameters have to be set in advance and totally empirically. In a practical application, this is difficult to achieve. Thus, it is not easy to use and not smart enough. In an effort to improve the restoration effect of this situation by way of GLAS, an improved GLAS (IGLAS) algorithm by introducing the local phase coherence sharpening Index (LPCSI) metric is proposed in this paper. With the help of LPCSI metric, the two hard thresholds can be fixed at constant values for all images. Compared to the original method, the thresholds in our new algorithm no longer need to change with different images. Based on our proposed IGLAS, its automatic version is also developed in order to compensate for the disadvantages of manual intervention. Simulated and real experimental results show that the proposed algorithm can not only obtain better performances compared with the original method, but it is very easy to apply.
Detecting trends in noisy data series: application to biomarker series.
Bellera, Carine A; Hanley, James A; Joseph, Lawrence; Albertsen, Peter C
2008-05-01
It is common to define a change in health status or in a disease state on the basis of a sustained rise (or decline) in a biomarker over time. However, such observations are often subject to important variability unrelated to the underlying biologic process. The authors propose a method to evaluate rules that define an event on the basis of consecutive increases (or decreases) in the observations, given the presence of random variation. They examine how well these rules correctly identify a truly rising biomarker trajectory and, conversely, how often they can recognize a truly stable series or a slowly rising series. The method relies on simulation of realistic, sophisticated data sets that accurately reflect the systematic and random variations observed in marker series. These flexible, empirically based simulations enable estimation of the sensitivity and specificity of rules of consecutive rises as a function of the underlying trend, amount of random variation, and schedule of measurements (frequency and duration of follow-up). The authors illustrate the approach with postradiotherapy series of prostate-specific antigen, where three consecutive rises in prostate-specific antigen indicate treatment failure; the data are described by using a Bayesian hierarchical changepoint model. The method is particularly flexible and could be applied to evaluate other rules that purport to accurately detect upturns (downturns) in other noisy data series, including other medical data or other application areas. PMID:18303004
Alignment of Noisy and Uniformly Scaled Time Series
NASA Astrophysics Data System (ADS)
Lipowsky, Constanze; Dranischnikow, Egor; Göttler, Herbert; Gottron, Thomas; Kemeter, Mathias; Schömer, Elmar
The alignment of noisy and uniformly scaled time series is an important but difficult task. Given two time series, one of which is a uniformly stretched subsequence of the other, we want to determine the stretching factor and the offset of the second time series within the first one. We adapted and enhanced different methods to address this problem: classical FFT-based approaches to determine the offset combined with a naïve search for the stretching factor or its direct computation in the frequency domain, bounded dynamic time warping and a new approach called shotgun analysis, which is inspired by sequencing and reassembling of genomes in bioinformatics. We thoroughly examined the strengths and weaknesses of the different methods on synthetic and real data sets. The FFT-based approaches are very accurate on high quality data, the shotgun approach is especially suitable for data with outliers. Dynamic time warping is a candidate for non-linear stretching or compression. We successfully applied the presented methods to identify steel coils via their thickness profiles.
Synchronous Generator Model Parameter Estimation Based on Noisy Dynamic Waveforms
NASA Astrophysics Data System (ADS)
Berhausen, Sebastian; Paszek, Stefan
2016-01-01
In recent years, there have occurred system failures in many power systems all over the world. They have resulted in a lack of power supply to a large number of recipients. To minimize the risk of occurrence of power failures, it is necessary to perform multivariate investigations, including simulations, of power system operating conditions. To conduct reliable simulations, the current base of parameters of the models of generating units, containing the models of synchronous generators, is necessary. In the paper, there is presented a method for parameter estimation of a synchronous generator nonlinear model based on the analysis of selected transient waveforms caused by introducing a disturbance (in the form of a pseudorandom signal) in the generator voltage regulation channel. The parameter estimation was performed by minimizing the objective function defined as a mean square error for deviations between the measurement waveforms and the waveforms calculated based on the generator mathematical model. A hybrid algorithm was used for the minimization of the objective function. In the paper, there is described a filter system used for filtering the noisy measurement waveforms. The calculation results of the model of a 44 kW synchronous generator installed on a laboratory stand of the Institute of Electrical Engineering and Computer Science of the Silesian University of Technology are also given. The presented estimation method can be successfully applied to parameter estimation of different models of high-power synchronous generators operating in a power system.
Measuring the robustness of link prediction algorithms under noisy environment.
Zhang, Peng; Wang, Xiang; Wang, Futian; Zeng, An; Xiao, Jinghua
2016-01-01
Link prediction in complex networks is to estimate the likelihood of two nodes to interact with each other in the future. As this problem has applications in a large number of real systems, many link prediction methods have been proposed. However, the validation of these methods is so far mainly conducted in the assumed noise-free networks. Therefore, we still miss a clear understanding of how the prediction results would be affected if the observed network data is no longer accurate. In this paper, we comprehensively study the robustness of the existing link prediction algorithms in the real networks where some links are missing, fake or swapped with other links. We find that missing links are more destructive than fake and swapped links for prediction accuracy. An index is proposed to quantify the robustness of the link prediction methods. Among the twenty-two studied link prediction methods, we find that though some methods have low prediction accuracy, they tend to perform reliably in the "noisy" environment. PMID:26733156
Control of noisy quantum systems: Field-theory approach to error mitigation
NASA Astrophysics Data System (ADS)
Hipolito, Rafael; Goldbart, Paul M.
2016-04-01
We consider the basic quantum-control task of obtaining a target unitary operation (i.e., a quantum gate) via control fields that couple to the quantum system and are chosen to best mitigate errors resulting from time-dependent noise, which frustrate this task. We allow for two sources of noise: fluctuations in the control fields and fluctuations arising from the environment. We address the issue of control-error mitigation by means of a formulation rooted in the Martin-Siggia-Rose (MSR) approach to noisy, classical statistical-mechanical systems. To do this, we express the noisy control problem in terms of a path integral, and integrate out the noise to arrive at an effective, noise-free description. We characterize the degree of success in error mitigation via a fidelity metric, which characterizes the proximity of the sought-after evolution to ones that are achievable in the presence of noise. Error mitigation is then best accomplished by applying the optimal control fields, i.e., those that maximize the fidelity subject to any constraints obeyed by the control fields. To make connection with MSR, we reformulate the fidelity in terms of a Schwinger-Keldysh (SK) path integral, with the added twist that the "forward" and "backward" branches of the time contour are inequivalent with respect to the noise. The present approach naturally and readily allows the incorporation of constraints on the control fields—a useful feature in practice, given that constraints feature in all real experiments. In addition to addressing the noise average of the fidelity, we consider its full probability distribution. The information content present in this distribution allows one to address more complex questions regarding error mitigation, including, in principle, questions of extreme value statistics, i.e., the likelihood and impact of rare instances of the fidelity and how to harness or cope with their influence. We illustrate this MSR-SK reformulation by considering a model
Joint Remote Preparation of an Arbitrary Two-Qubit State in Noisy Environments
NASA Astrophysics Data System (ADS)
Guan, Xiao-Wei; Chen, Xiu-Bo; Wang, Li-Chen; Yang, Yi-Xian
2014-07-01
Utilizing a general joint remote state preparation (JRSP) model, we investigate the JRSP of an arbitrary two-qubit quantum state in noisy environments. Two important decoherence noise models, the amplitude-damping noise and the phase-damping noise, have been considered in our paper. Our investigation of the noisy environment mainly focuses on the process of distributing the channel state. We use fidelity to describe how close the output state with the prepared state are, and how much information has been lost in the transmission. Interestingly, studies show that, if the initial state is successfully prepared, the fidelities in these two cases will only depend on the amplitude parameter of the initial state and the decoherence noisy rate, but have nothing to do with the phase information. Finally, we make some discussions for these two cases to show that in which noisy environment more information will be lost.
[Development of improving speech perception of cochlear implants in noisy environment].
Pan, Haolai; Chen, Zhengnong
2016-01-01
Cochlear implantation has been a standard therapy for treating severe deafness because patients who receive it have better speech perception. However, the hearing performance of cochlear implantation in noisy environment is far from satisfaction. Efforts have been made to reverse such condition, such as EAS, bimodal stimulation, environment-adaptive speech enhancement and multipolar stimulation, and patients who receive it get more or less better speech perception in noisy environment than traditional cochlear implantation. PMID:27192923
Identifying Ionized Regions in Noisy Redshifted 21 cm Data Sets
NASA Astrophysics Data System (ADS)
Malloy, Matthew; Lidz, Adam
2013-04-01
One of the most promising approaches for studying reionization is to use the redshifted 21 cm line. Early generations of redshifted 21 cm surveys will not, however, have the sensitivity to make detailed maps of the reionization process, and will instead focus on statistical measurements. Here, we show that it may nonetheless be possible to directly identify ionized regions in upcoming data sets by applying suitable filters to the noisy data. The locations of prominent minima in the filtered data correspond well with the positions of ionized regions. In particular, we corrupt semi-numeric simulations of the redshifted 21 cm signal during reionization with thermal noise at the level expected for a 500 antenna tile version of the Murchison Widefield Array (MWA), and mimic the degrading effects of foreground cleaning. Using a matched filter technique, we find that the MWA should be able to directly identify ionized regions despite the large thermal noise. In a plausible fiducial model in which ~20% of the volume of the universe is neutral at z ~ 7, we find that a 500-tile MWA may directly identify as many as ~150 ionized regions in a 6 MHz portion of its survey volume and roughly determine the size of each of these regions. This may, in turn, allow interesting multi-wavelength follow-up observations, comparing galaxy properties inside and outside of ionized regions. We discuss how the optimal configuration of radio antenna tiles for detecting ionized regions with a matched filter technique differs from the optimal design for measuring power spectra. These considerations have potentially important implications for the design of future redshifted 21 cm surveys.
Linear Models Based on Noisy Data and the Frisch Scheme*
Ning, Lipeng; Georgiou, Tryphon T.; Tannenbaum, Allen; Boyd, Stephen P.
2016-01-01
We address the problem of identifying linear relations among variables based on noisy measurements. This is a central question in the search for structure in large data sets. Often a key assumption is that measurement errors in each variable are independent. This basic formulation has its roots in the work of Charles Spearman in 1904 and of Ragnar Frisch in the 1930s. Various topics such as errors-in-variables, factor analysis, and instrumental variables all refer to alternative viewpoints on this problem and on ways to account for the anticipated way that noise enters the data. In the present paper we begin by describing certain fundamental contributions by the founders of the field and provide alternative modern proofs to certain key results. We then go on to consider a modern viewpoint and novel numerical techniques to the problem. The central theme is expressed by the Frisch–Kalman dictum, which calls for identifying a noise contribution that allows a maximal number of simultaneous linear relations among the noise-free variables—a rank minimization problem. In the years since Frisch’s original formulation, there have been several insights, including trace minimization as a convenient heuristic to replace rank minimization. We discuss convex relaxations and theoretical bounds on the rank that, when met, provide guarantees for global optimality. A complementary point of view to this minimum-rank dictum is presented in which models are sought leading to a uniformly optimal quadratic estimation error for the error-free variables. Points of contact between these formalisms are discussed, and alternative regularization schemes are presented. PMID:27168672
Noisy Hangul character recognition with fuzzy tree classifier
NASA Astrophysics Data System (ADS)
Lee, Seong-Whan
1992-08-01
Decision trees have been applied to solve a wide range of pattern recognition problems. In a tree classifier, a sequence of decision rules are used to assign an unknown sample to a pattern class. The main advantage of a decision tree over a single stage classifier is that the complex global decision making process can be divided into a number of simpler and local decisions at different levels of the tree. At each stage of the decision process, the feature subset best suited for that classification task can be selected. It can be shown that this approach provides better results than the use of the best feature subset for a single decision classifier. In addition, in large set problems where the number of classes is very large, the tree classifier can make a global decision much more quickly than the single stage classifier. However, a major weak point of a tree classifier is its error accumulation effect when the number of classes is very large. To overcome this difficulty, a fuzzy tree classifier with the following characteristics is implemented: (1) fuzzy logic search is used to find all `possible correct classes,'' and some similarity measures are used to determine the `most probable class;'' (2) global training is applied to generate extended terminals in order to enhance the recognition rate; (3) both the training and search algorithms have been given a lot of flexibility, to provide tradeoffs between error and rejection rates, and between the recognition rate and speed. Experimental results for the recognition of 520 most frequently used noisy Hangul character categories revealed a very high recognition rate of 99.8 percent and very high speed of 100 samples/sec, when the program was written in C and run on general purpose SUN4 SPARCstation
High-dimensional quantum state transfer in a noisy network environment
NASA Astrophysics Data System (ADS)
Qin, Wei; Li, Jun-Lin; Long, Gui-Lu
2015-04-01
We propose and analyze an efficient high-dimensional quantum state transfer protocol in an XX coupling spin network with a hypercube structure or chain structure. Under free spin wave approximation, unitary evolution results in a perfect high-dimensional quantum swap operation requiring neither external manipulation nor weak coupling. Evolution time is independent of either distance between registers or dimensions of sent states, which can improve the computational efficiency. In the low temperature regime and thermodynamic limit, the decoherence caused by a noisy environment is studied with a model of an antiferromagnetic spin bath coupled to quantum channels via an Ising-type interaction. It is found that while the decoherence reduces the fidelity of state transfer, increasing intra-channel coupling can strongly suppress such an effect. These observations demonstrate the robustness of the proposed scheme. Project supported by the National Natural Science Foundation of China (Grant Nos. 11175094 and 91221205) and the National Basic Research Program of China (Grant No. 2011CB9216002). Long Gui-Lu also thanks the support of Center of Atomic and Molecular Nanoscience of Tsinghua University, China.
Deterministic joint remote preparation of an arbitrary two-qubit state in noisy environments
NASA Astrophysics Data System (ADS)
Li, Jin-Fang; Liu, Jin-Ming; Xu, Xin-Ye
2015-09-01
Using four Einstein-Podolsky-Rosen (EPR) states as the shared quantum channel, we investigate the deterministic joint remote preparation of an arbitrary two-qubit state in the presence of noisy environments through the analytical solution of the master equation in the Lindblad form. By means of unitary matrix decomposition method, quantum logic circuit for the deterministic joint remote state preparation (JRSP) protocol is first constructed. Then, we analytically derive the average fidelities of the deterministic JRSP process under the influence of Pauli noises, zero-temperature and high-temperature reservoirs acting on the four EPR pairs. It is found that the average fidelities under the action of different noises display different evolution behaviors. Moreover, for the specific noises examined in this paper, in the long-time limit, the dephasing noise and the zero-temperature environment have the relatively weak effect on their respective average fidelities, whereas the isotropic noise and the high-temperature environment have the relatively strong effect.
Methodology to estimate the relative pressure field from noisy experimental velocity data
NASA Astrophysics Data System (ADS)
Bolin, C. D.; Raguin, L. G.
2008-11-01
The determination of intravascular pressure fields is important to the characterization of cardiovascular pathology. We present a two-stage method that solves the inverse problem of estimating the relative pressure field from noisy velocity fields measured by phase contrast magnetic resonance imaging (PC-MRI) on an irregular domain with limited spatial resolution, and includes a filter for the experimental noise. For the pressure calculation, the Poisson pressure equation is solved by embedding the irregular flow domain into a regular domain. To lessen the propagation of the noise inherent to the velocity measurements, three filters - a median filter and two physics-based filters - are evaluated using a 2-D Couette flow. The two physics-based filters outperform the median filter for the estimation of the relative pressure field for realistic signal-to-noise ratios (SNR = 5 to 30). The most accurate pressure field results from a filter that applies in a least-squares sense three constraints simultaneously: consistency between measured and filtered velocity fields, divergence-free and additional smoothness conditions. This filter leads to a 5-fold gain in accuracy for the estimated relative pressure field compared to without noise filtering, in conditions consistent with PC-MRI of the carotid artery: SNR = 5, 20 x 20 discretized flow domain (25 X 25 computational domain).
Noise cross correlation functions in a noisy region
NASA Astrophysics Data System (ADS)
Gaudot, I.; Beucler, E.; Mocquet, A.; Schimmel, M.; Le Feuvre, M.; Leparoux, D.; Côte, P.
2013-12-01
the strong directivity of the noise and the seismicity. Rapid changes in the noise directivity are also studied since they appear to deteriorate the reconstruction of the NCFs. The NCFs are computed using different schemes and the convergence toward an empirical Green's function is analyzed using two criteria of quality: the signal to noise ratio and the similarity. The objective is to explore the existing correlation techniques in a noisy region.
A variational ensemble scheme for noisy image data assimilation
NASA Astrophysics Data System (ADS)
Yang, Yin; Robinson, Cordelia; Heitz, Dominique; Mémin, Etienne
2014-05-01
Data assimilation techniques aim at recovering a system state variables trajectory denoted as X, along time from partially observed noisy measurements of the system denoted as Y. These procedures, which couple dynamics and noisy measurements of the system, fulfill indeed a twofold objective. On one hand, they provide a denoising - or reconstruction - procedure of the data through a given model framework and on the other hand, they provide estimation procedures for unknown parameters of the dynamics. A standard variational data assimilation problem can be formulated as the minimization of the following objective function with respect to the initial discrepancy, η, from the background initial guess: δ« J(η(x)) = 1∥Xb (x) - X (t ,x)∥2 + 1 tf∥H(X (t,x ))- Y (t,x)∥2dt. 2 0 0 B 2 t0 R (1) where the observation operator H links the state variable and the measurements. The cost function can be interpreted as the log likelihood function associated to the a posteriori distribution of the state given the past history of measurements and the background. In this work, we aim at studying ensemble based optimal control strategies for data assimilation. Such formulation nicely combines the ingredients of ensemble Kalman filters and variational data assimilation (4DVar). It is also formulated as the minimization of the objective function (1), but similarly to ensemble filter, it introduces in its objective function an empirical ensemble-based background-error covariance defined as: B ≡ <(Xb -
Fuzzy Logic Based Edge Detection in Smooth and Noisy Clinical Images
Haq, Izhar
2015-01-01
Edge detection has beneficial applications in the fields such as machine vision, pattern recognition and biomedical imaging etc. Edge detection highlights high frequency components in the image. Edge detection is a challenging task. It becomes more arduous when it comes to noisy images. This study focuses on fuzzy logic based edge detection in smooth and noisy clinical images. The proposed method (in noisy images) employs a 3×3 mask guided by fuzzy rule set. Moreover, in case of smooth clinical images, an extra mask of contrast adjustment is integrated with edge detection mask to intensify the smooth images. The developed method was tested on noise-free, smooth and noisy images. The results were compared with other established edge detection techniques like Sobel, Prewitt, Laplacian of Gaussian (LOG), Roberts and Canny. When the developed edge detection technique was applied to a smooth clinical image of size 270×290 pixels having 24 dB ‘salt and pepper’ noise, it detected very few (22) false edge pixels, compared to Sobel (1931), Prewitt (2741), LOG (3102), Roberts (1451) and Canny (1045) false edge pixels. Therefore it is evident that the developed method offers improved solution to the edge detection problem in smooth and noisy clinical images. PMID:26407133
Do Quiet Areas Afford Greater Health-Related Quality of Life than Noisy Areas?
Shepherd, Daniel; Welch, David; Dirks, Kim N.; McBride, David
2013-01-01
People typically choose to live in quiet areas in order to safeguard their health and wellbeing. However, the benefits of living in quiet areas are relatively understudied compared to the burdens associated with living in noisy areas. Additionally, research is increasingly focusing on the relationship between the human response to noise and measures of health and wellbeing, complementing traditional dose-response approaches, and further elucidating the impact of noise and health by incorporating human factors as mediators and moderators. To further explore the benefits of living in quiet areas, we compared the results of health-related quality of life (HRQOL) questionnaire datasets collected from households in localities differentiated by their soundscapes and population density: noisy city, quiet city, quiet rural, and noisy rural. The dose-response relationships between noise annoyance and HRQOL measures indicated an inverse relationship between the two. Additionally, quiet areas were found to have higher mean HRQOL domain scores than noisy areas. This research further supports the protection of quiet locales and ongoing noise abatement in noisy areas. PMID:23535280
Characterization of emergent synaptic topologies in noisy neural networks
NASA Astrophysics Data System (ADS)
Miller, Aaron James
of a LIF neuron subjected to Gaussian white noise (GWN). The system reduces to the Ornstein-Uhlenbeck first passage time problem, the solution of which we build into the mapping method of Chapter 2. We demonstrate that simulations using the stochastic mapping have reduced computation time compared to traditional Runge-Kutta methods by more than a factor of 150. In Chapter 4, we use the stochastic mapping to study the dynamics of emerging synaptic topologies in noisy networks. With the addition of membrane noise, networks with dynamical synapses can admit states in which the distribution of the synaptic weights is static under spontaneous activity, but the random connectivity between neurons is dynamical. The widely cited problem of instabilities in networks with STDP is avoided with the implementation of a synaptic decay and an activation threshold on each synapse. When such networks are presented with stimulus modeled by a focused excitatory current, chain-like networks can emerge with the addition of an axon-remodeling plasticity rule, a topological constraint on the connectivity modeling the finite resources available to each neuron. The emergent topologies are the result of an iterative stochastic process. The dynamics of the growth process suggest a strong interplay between the network topology and the spike sequences they produce during development. Namely, the existence of an embedded spike sequence alters the distribution of synaptic weights through the entire network. The roles of model parameters that affect the interplay between network structure and activity are elucidated. Finally, we propose two mathematical growth models, which are complementary, that capture the essence of the growth dynamics observed in simulations. In Chapter 5, we present an extension of the stochastic mapping that allows the possibility of neuronal cooperation. We demonstrate that synaptic topologies admitting stereotypical sequences can emerge in yet higher, biologically
Quantum Dynamics in Noisy Backgrounds: from Sampling to Dissipation and Fluctuations
NASA Astrophysics Data System (ADS)
Oliveira, O.; Paula, W. de; Frederico, T.; Hussein, M. S.
2016-08-01
We investigate the dynamics of a quantum system coupled linearly to Gaussian white noise using functional methods. By performing the integration over the noisy field in the evolution operator, we get an equivalent non-Hermitian Hamiltonian, which evolves the quantum state with a dissipative dynamics. We also show that if the integration over the noisy field is done for the time evolution of the density matrix, a gain contribution from the fluctuations can be accessed in addition to the loss one from the non-hermitian Hamiltonian dynamics. We illustrate our study by computing analytically the effective non-Hermitian Hamiltonian, which we found to be the complex frequency harmonic oscillator, with a known evolution operator. It leads to space and time localisation, a common feature of noisy quantum systems in general applications.
Park, Jinsoo; Kim, Wooil; Han, David K.; Ko, Hanseok
2014-01-01
A new voice activity detector for noisy environments is proposed. In conventional algorithms, the endpoint of speech is found by applying an edge detection filter that finds the abrupt changing point in a feature domain. However, since the frame energy feature is unstable in noisy environments, it is difficult to accurately find the endpoint of speech. Therefore, a novel feature extraction algorithm based on the double-combined Fourier transform and envelope line fitting is proposed. It is combined with an edge detection filter for effective detection of endpoints. Effectiveness of the proposed algorithm is evaluated and compared to other VAD algorithms using two different databases, which are AURORA 2.0 database and SITEC database. Experimental results show that the proposed algorithm performs well under a variety of noisy conditions. PMID:25170520
NASA Astrophysics Data System (ADS)
Jiang, Li-Nan; Ma, Jing; Yu, Si-Yuan; Tan, Li-Ying; Ran, Qi-Wen
2015-02-01
The entanglement evolution of the bipartite quantum system which is initially prepared in extended Werner-like state under the influence of independent or collective noisy channels are investigated by solving the master equation in Lindblad form. With the aid of the concurrence, we find that the initial state can preserve more entanglement in certain region when it is transmitted through the collective Pauli σ x or σ y noisy channel than the corresponding independent noisy channel. For the Pauli σ z or the depolarizing channel, however, the collective decoherence can speed up the process of entanglement decay. Meanwhile, we show that the purity of initial state has a great influence on the region which the entanglement can be preserved.
Noisy galvanic vestibular stimulation modulates the amplitude of EEG synchrony patterns.
Kim, Diana J; Yogendrakumar, Vignan; Chiang, Joyce; Ty, Edna; Wang, Z Jane; McKeown, Martin J
2013-01-01
Noisy galvanic vestibular stimulation has been associated with numerous cognitive and behavioural effects, such as enhancement of visual memory in healthy individuals, improvement of visual deficits in stroke patients, as well as possibly improvement of motor function in Parkinson's disease; yet, the mechanism of action is unclear. Since Parkinson's and other neuropsychiatric diseases are characterized by maladaptive dynamics of brain rhythms, we investigated whether noisy galvanic vestibular stimulation was associated with measurable changes in EEG oscillatory rhythms within theta (4-7.5 Hz), low alpha (8-10 Hz), high alpha (10.5-12 Hz), beta (13-30 Hz) and gamma (31-50 Hz) bands. We recorded the EEG while simultaneously delivering noisy bilateral, bipolar stimulation at varying intensities of imperceptible currents - at 10, 26, 42, 58, 74 and 90% of sensory threshold - to ten neurologically healthy subjects. Using standard spectral analysis, we investigated the transient aftereffects of noisy stimulation on rhythms. Subsequently, using robust artifact rejection techniques and the Least Absolute Shrinkage Selection Operator regression and cross-validation, we assessed the combinations of channels and power spectral features within each EEG frequency band that were linearly related with stimulus intensity. We show that noisy galvanic vestibular stimulation predominantly leads to a mild suppression of gamma power in lateral regions immediately after stimulation, followed by delayed increase in beta and gamma power in frontal regions approximately 20-25 s after stimulation ceased. Ongoing changes in the power of each oscillatory band throughout frontal, central/parietal, occipital and bilateral electrodes predicted the intensity of galvanic vestibular stimulation in a stimulus-dependent manner, demonstrating linear effects of stimulation on brain rhythms. We propose that modulation of neural oscillations is a potential mechanism for the previously-described cognitive
NASA Technical Reports Server (NTRS)
Layland, J. W.
1974-01-01
An approximate analysis of the effect of a noisy carrier reference on the performance of sequential decoding is presented. The analysis uses previously developed techniques for evaluating noisy reference performance for medium-rate uncoded communications adapted to sequential decoding for data rates of 8 to 2048 bits/s. In estimating the ten to the minus fourth power deletion probability thresholds for Helios, the model agrees with experimental data to within the experimental tolerances. The computational problem involved in sequential decoding, carrier loop effects, the main characteristics of the medium-rate model, modeled decoding performance, and perspectives on future work are discussed.
Effects of quantum noises and noisy quantum operations on entanglement and special dense coding
Quek, Sylvanus; Li Ziang; Yeo Ye
2010-02-15
We show how noncommuting noises could cause a Bell state {chi}{sub 0} to suffer entanglement sudden death (ESD). ESD may similarly occur when a noisy operation acts, if the corresponding Hamiltonian and Lindblad operator do not commute. We study the implications of these in special dense coding S. When noises that cause ESD act, we show that {chi}{sub 0} may lose its capacity for S before ESD occurs. Similarly, {chi}{sub 0} may fail to yield information transfer better than classically possible when the encoding operations are noisy, though entanglement is not destroyed in the process.
Lasko, Thomas A; Denny, Joshua C; Levy, Mia A
2013-01-01
Inferring precise phenotypic patterns from population-scale clinical data is a core computational task in the development of precision, personalized medicine. The traditional approach uses supervised learning, in which an expert designates which patterns to look for (by specifying the learning task and the class labels), and where to look for them (by specifying the input variables). While appropriate for individual tasks, this approach scales poorly and misses the patterns that we don't think to look for. Unsupervised feature learning overcomes these limitations by identifying patterns (or features) that collectively form a compact and expressive representation of the source data, with no need for expert input or labeled examples. Its rising popularity is driven by new deep learning methods, which have produced high-profile successes on difficult standardized problems of object recognition in images. Here we introduce its use for phenotype discovery in clinical data. This use is challenging because the largest source of clinical data - Electronic Medical Records - typically contains noisy, sparse, and irregularly timed observations, rendering them poor substrates for deep learning methods. Our approach couples dirty clinical data to deep learning architecture via longitudinal probability densities inferred using Gaussian process regression. From episodic, longitudinal sequences of serum uric acid measurements in 4368 individuals we produced continuous phenotypic features that suggest multiple population subtypes, and that accurately distinguished (0.97 AUC) the uric-acid signatures of gout vs. acute leukemia despite not being optimized for the task. The unsupervised features were as accurate as gold-standard features engineered by an expert with complete knowledge of the domain, the classification task, and the class labels. Our findings demonstrate the potential for achieving computational phenotype discovery at population scale. We expect such data
Lasko, Thomas A.; Denny, Joshua C.; Levy, Mia A.
2013-01-01
Inferring precise phenotypic patterns from population-scale clinical data is a core computational task in the development of precision, personalized medicine. The traditional approach uses supervised learning, in which an expert designates which patterns to look for (by specifying the learning task and the class labels), and where to look for them (by specifying the input variables). While appropriate for individual tasks, this approach scales poorly and misses the patterns that we don’t think to look for. Unsupervised feature learning overcomes these limitations by identifying patterns (or features) that collectively form a compact and expressive representation of the source data, with no need for expert input or labeled examples. Its rising popularity is driven by new deep learning methods, which have produced high-profile successes on difficult standardized problems of object recognition in images. Here we introduce its use for phenotype discovery in clinical data. This use is challenging because the largest source of clinical data – Electronic Medical Records – typically contains noisy, sparse, and irregularly timed observations, rendering them poor substrates for deep learning methods. Our approach couples dirty clinical data to deep learning architecture via longitudinal probability densities inferred using Gaussian process regression. From episodic, longitudinal sequences of serum uric acid measurements in 4368 individuals we produced continuous phenotypic features that suggest multiple population subtypes, and that accurately distinguished (0.97 AUC) the uric-acid signatures of gout vs. acute leukemia despite not being optimized for the task. The unsupervised features were as accurate as gold-standard features engineered by an expert with complete knowledge of the domain, the classification task, and the class labels. Our findings demonstrate the potential for achieving computational phenotype discovery at population scale. We expect such data
Aliabadi, Mohsen; Golmohammadi, Rostam; Mansoorizadeh, Muharram
2014-03-01
It is highly important to analyze the acoustic properties of workrooms in order to identify best noise control measures from the standpoint of noise exposure limits. Due to the fact that sound pressure is dependent upon environments, it cannot be a suitable parameter for determining the share of workroom acoustic characteristics in producing noise pollution. This paper aims to empirically analyze noise source characteristics and acoustic properties of noisy embroidery workrooms based on special parameters. In this regard, reverberation time as the special room acoustic parameter in 30 workrooms was measured based on ISO 3382-2. Sound power quantity of embroidery machines was also determined based on ISO 9614-3. Multiple linear regression was employed for predicting reverberation time based on acoustic features of the workrooms using MATLAB software. The results showed that the measured reverberation times in most of the workrooms were approximately within the ranges recommended by ISO 11690-1. Similarity between reverberation time values calculated by the Sabine formula and measured values was relatively poor (R (2) = 0.39). This can be due to the inaccurate estimation of the acoustic influence of furniture and formula preconditions. Therefore, this value cannot be considered representative of an actual acoustic room. However, the prediction performance of the regression method with root mean square error (RMSE) = 0.23 s and R (2) = 0.69 is relatively acceptable. Because the sound power of the embroidery machines was relatively high, these sources get the highest priority when it comes to applying noise controls. Finally, an objective approach for the determination of the share of workroom acoustic characteristics in producing noise could facilitate the identification of cost-effective noise controls. PMID:24214295
Automated marker tracking using noisy X-ray images degraded by the treatment beam.
Wisotzky, E; Fast, M F; Oelfke, U; Nill, S
2015-06-01
This study demonstrates the feasibility of automated marker tracking for the real-time detection of intrafractional target motion using noisy kilovoltage (kV) X-ray images degraded by the megavoltage (MV) treatment beam. The authors previously introduced the in-line imaging geometry, in which the flat-panel detector (FPD) is mounted directly underneath the treatment head of the linear accelerator. They found that the 121 kVp image quality was severely compromised by the 6 MV beam passing through the FPD at the same time. Specific MV-induced artefacts present a considerable challenge for automated marker detection algorithms. For this study, the authors developed a new imaging geometry by re-positioning the FPD and the X-ray tube. This improved the contrast-to-noise-ratio between 40% and 72% at the 1.2 mAs/image exposure setting. The increase in image quality clearly facilitates the quick and stable detection of motion with the aid of a template matching algorithm. The setup was tested with an anthropomorphic lung phantom (including an artificial lung tumour). In the tumour one or three Calypso beacons were embedded to achieve better contrast during MV radiation. For a single beacon, image acquisition and automated marker detection typically took around 76 ± 6 ms. The success rate was found to be highly dependent on imaging dose and gantry angle. To eliminate possible false detections, the authors implemented a training phase prior to treatment beam irradiation and also introduced speed limits for motion between subsequent images. PMID:25280891
Lowry, Hélène; Lill, Alan; Wong, Bob B. M.
2012-01-01
Background Urban environments generate constant loud noise, which creates a formidable challenge for many animals relying on acoustic communication. Some birds make vocal adjustments that reduce auditory masking by altering, for example, the frequency (kHz) or timing of vocalizations. Another adjustment, well documented for birds under laboratory and natural field conditions, is a noise level-dependent change in sound signal amplitude (the ‘Lombard effect’). To date, however, field research on amplitude adjustments in urban environments has focused exclusively on bird song. Methods We investigated amplitude regulation of alarm calls using, as our model, a successful urban ‘adapter’ species, the Noisy miner, Manorina melanocephala. We compared several different alarm calls under contrasting noise conditions. Results Individuals at noisier locations (arterial roads) alarm called significantly more loudly than those at quieter locations (residential streets). Other mechanisms known to improve sound signal transmission in ‘noise’, namely use of higher perches and in-flight calling, did not differ between site types. Intriguingly, the observed preferential use of different alarm calls by Noisy miners inhabiting arterial roads and residential streets was unlikely to have constituted a vocal modification made in response to sound-masking in the urban environment because the calls involved fell within the main frequency range of background anthropogenic noise. Conclusions The results of our study suggest that a species, which has the ability to adjust the amplitude of its signals, might have a ‘natural’ advantage in noisy urban environments. PMID:22238684
Dutta, Anirban; Rahmani, Armin; Del Campo, Adolfo
2016-08-19
We show that a thermally isolated system driven across a quantum phase transition by a noisy control field exhibits anti-Kibble-Zurek behavior, whereby slower driving results in higher excitations. We characterize the density of excitations as a function of the ramping rate and the noise strength. The optimal driving time to minimize excitations is shown to scale as a universal power law of the noise strength. Our findings reveal the limitations of adiabatic protocols such as quantum annealing and demonstrate the universality of the optimal ramping rate. PMID:27588838
Near-optimal assembly for shotgun sequencing with noisy reads
2014-01-01
Recent work identified the fundamental limits on the information requirements in terms of read length and coverage depth required for successful de novo genome reconstruction from shotgun sequencing data, based on the idealistic assumption of no errors in the reads (noiseless reads). In this work, we show that even when there is noise in the reads, one can successfully reconstruct with information requirements close to the noiseless fundamental limit. A new assembly algorithm, X-phased Multibridging, is designed based on a probabilistic model of the genome. It is shown through analysis to perform well on the model, and through simulations to perform well on real genomes. PMID:25252708
Quantum correlation dynamics of two qubits in noisy environments: The factorization law and beyond
Zhang, Guo-Feng; Ji, Ai-Ling; Fan, Heng; Liu, Wu-Ming
2012-09-15
We investigate the quantum correlations of two qubits under conditions of single-sided and two-sided noisy channels when the initial state of the system belongs to a subclass of X structured ones in terms of measurement-induced nonlocality, measurement-induced disturbance and quantum discord. The results show that measurement-induced nonlocality has a factorization law, regardless of whether there are single-sided or two-sided noisy channels. However, there is no simple factorization relation for measurement-induced disturbance and quantum discord. Also, we compare the evolution of these quantum correlations as functions of time. For the four Bell initial states, we find that the measurement-induced disturbance evolution equations are the same when the channel is single-sided, but they will be divided into two categories when the channel is two-sided. Quantum correlations decay more quickly when the channel is two-sided. Furthermore, quantum discord presents sudden change in the derivative of its time evolution. - Highlights: Black-Right-Pointing-Pointer The quantum correlation dynamics of two qubits under noisy environmental conditions is investigated. Black-Right-Pointing-Pointer Measurement-induced nonlocality has a factorization law, regardless of whether there are single-sided or two-sided noisy channels. Black-Right-Pointing-Pointer There is no simple factorization relation for measurement-induced disturbance and quantum discord.
ERIC Educational Resources Information Center
Winstone, Naomi; Davis, Alyson; De Bruyn, Bart
2012-01-01
Young children are frequently exposed to sounds such as speech and music in noisy listening conditions, which have the potential to disrupt their learning. Missing input that is masked by louder sounds can, under the right conditions, be "filled in" by the perceptual system using a process known as perceptual restoration. This experiment…
FALSE DETERMINATIONS OF CHAOS IN SHORT NOISY TIME SERIES. (R828745)
A method (NEMG) proposed in 1992 for diagnosing chaos in noisy time series with 50 or fewer observations entails fitting the time series with an empirical function which predicts an observation in the series from previous observations, and then estimating the rate of divergenc...
Probabilistic inference of molecular networks from noisy data sources.
Iossifov, Ivan; Krauthammer, Michael; Friedman, Carol; Hatzivassiloglou, Vasileios; Bader, Joel S; White, Kevin P; Rzhetsky, Andrey
2004-05-22
Information on molecular networks, such as networks of interacting proteins, comes from diverse sources that contain remarkable differences in distribution and quantity of errors. Here, we introduce a probabilistic model useful for predicting protein interactions from heterogeneous data sources. The model describes stochastic generation of protein-protein interaction networks with real-world properties, as well as generation of two heterogeneous sources of protein-interaction information: research results automatically extracted from the literature and yeast two-hybrid experiments. Based on the domain composition of proteins, we use the model to predict protein interactions for pairs of proteins for which no experimental data are available. We further explore the prediction limits, given experimental data that cover only part of the underlying protein networks. This approach can be extended naturally to include other types of biological data sources. PMID:14871876
Dynamical decoupling leads to improved scaling in noisy quantum metrology
NASA Astrophysics Data System (ADS)
Sekatski, Pavel; Skotiniotis, Michalis; Dür, Wolfgang
2016-07-01
We consider the usage of dynamical decoupling in quantum metrology, where the joint evolution of system plus environment is described by a Hamiltonian. We show that by ultra-fast unitary control operations acting locally only on system qubits, noise can be eliminated while the desired evolution is only reduced by at most a constant factor, leading to Heisenberg scaling. We identify all kinds of noise where such an approach is applicable. Only noise that is generated by the Hamiltonian to be estimated itself cannot be altered. However, even for such parallel noise, one can achieve an improved scaling as compared to the standard quantum limit for any local noise by means of symmetrization. Our results are also applicable in other schemes based on dynamical decoupling, e.g. the generation of high-fidelity entangling gates.
Multiscale Morphological Filtering for Analysis of Noisy and Complex Images
NASA Technical Reports Server (NTRS)
Kher, A.; Mitra, S.
1993-01-01
Images acquired with passive sensing techniques suffer from illumination variations and poor local contrasts that create major difficulties in interpretation and identification tasks. On the other hand, images acquired with active sensing techniques based on monochromatic illumination are degraded with speckle noise. Mathematical morphology offers elegant techniques to handle a wide range of image degradation problems. Unlike linear filters, morphological filters do not blur the edges and hence maintain higher image resolution. Their rich mathematical framework facilitates the design and analysis of these filters as well as their hardware implementation. Morphological filters are easier to implement and are more cost effective and efficient than several conventional linear filters. Morphological filters to remove speckle noise while maintaining high resolution and preserving thin image regions that are particularly vulnerable to speckle noise were developed and applied to SAR imagery. These filters used combination of linear (one-dimensional) structuring elements in different (typically four) orientations. Although this approach preserves more details than the simple morphological filters using two-dimensional structuring elements, the limited orientations of one-dimensional elements approximate the fine details of the region boundaries. A more robust filter designed recently overcomes the limitation of the fixed orientations. This filter uses a combination of concave and convex structuring elements. Morphological operators are also useful in extracting features from visible and infrared imagery. A multiresolution image pyramid obtained with successive filtering and a subsampling process aids in the removal of the illumination variations and enhances local contrasts. A morphology-based interpolation scheme was also introduced to reduce intensity discontinuities created in any morphological filtering task. The generality of morphological filtering techniques in
Smartphone-based hearing screening in noisy environments.
Na, Youngmin; Joo, Hyo Sung; Yang, Hyejin; Kang, Soojin; Hong, Sung Hwa; Woo, Jihwan
2014-01-01
It is important and recommended to detect hearing loss as soon as possible. If it is found early, proper treatment may help improve hearing and reduce the negative consequences of hearing loss. In this study, we developed smartphone-based hearing screening methods that can ubiquitously test hearing. However, environmental noise generally results in the loss of ear sensitivity, which causes a hearing threshold shift (HTS). To overcome this limitation in the hearing screening location, we developed a correction algorithm to reduce the HTS effect. A built-in microphone and headphone were calibrated to provide the standard units of measure. The HTSs in the presence of either white or babble noise were systematically investigated to determine the mean HTS as a function of noise level. When the hearing screening application runs, the smartphone automatically measures the environmental noise and provides the HTS value to correct the hearing threshold. A comparison to pure tone audiometry shows that this hearing screening method in the presence of noise could closely estimate the hearing threshold. We expect that the proposed ubiquitous hearing test method could be used as a simple hearing screening tool and could alert the user if they suffer from hearing loss. PMID:24926692
Cicadas impact bird communication in a noisy tropical rainforest
Hall, Robert; Ray, William; Beck, Angela; Zook, James
2015-01-01
Many animals communicate through acoustic signaling, and “acoustic space” may be viewed as a limited resource that organisms compete for. If acoustic signals overlap, the information in them is masked, so there should be selection toward strategies that reduce signal overlap. The extent to which animals are able to partition acoustic space in acoustically diverse habitats such as tropical forests is poorly known. Here, we demonstrate that a single cicada species plays a major role in the frequency and timing of acoustic communication in a neotropical wet forest bird community. Using an automated acoustic monitor, we found that cicadas vary the timing of their signals throughout the day and that the frequency range and timing of bird vocalizations closely track these signals. Birds significantly avoid temporal overlap with cicadas by reducing and often shutting down vocalizations at the onset of cicada signals that utilize the same frequency range. When birds do vocalize at the same time as cicadas, the vocalizations primarily occur at nonoverlapping frequencies with cicada signals. Our results greatly improve our understanding of the community dynamics of acoustic signaling and reveal how patterns in biotic noise shape the frequency and timing of bird vocalizations in tropical forests. PMID:26023277
Quantum gates with optimal bandwidth in noisy environments
NASA Astrophysics Data System (ADS)
Low, Guang Hao; Theodore, Yoder; Chuang, Isaac
The traditional approach of open-loop quantum error correction suppresses certain systematic imperfections ɛ in quantum control to higher orders ɛ (L) by a well-designed sequence of L imperfect quantum gates. However, this philosophy of maximal flatness leads to an ɛ-bandwidth that scales poorly with length and a residual that is easily overwhelmed by unaccounted sources of noise. We advance the paradigm of equiripple compensated gates that directly optimize for bandwidth given the limitations imposed by noise of magnitude δ, leading to dramatically improved performance. Where ɛ represent amplitude errors, we provide a formalism that generalizes both approaches and is effective at finding such gates. With it, we provide in closed-form the phase angles for an optimal family of population inversion gates with an ɛ -bandwidth of (logδ-1/L) - a quadratic improvement over optimal maximally flat variants. We also construct optimal NOT gates and discuss extensions to other gates and error models.
Smartphone-Based Hearing Screening in Noisy Environments
Na, Youngmin; Joo, Hyo Sung; Yang, Hyejin; Kang, Soojin; Hong, Sung Hwa; Woo, Jihwan
2014-01-01
It is important and recommended to detect hearing loss as soon as possible. If it is found early, proper treatment may help improve hearing and reduce the negative consequences of hearing loss. In this study, we developed smartphone-based hearing screening methods that can ubiquitously test hearing. However, environmental noise generally results in the loss of ear sensitivity, which causes a hearing threshold shift (HTS). To overcome this limitation in the hearing screening location, we developed a correction algorithm to reduce the HTS effect. A built-in microphone and headphone were calibrated to provide the standard units of measure. The HTSs in the presence of either white or babble noise were systematically investigated to determine the mean HTS as a function of noise level. When the hearing screening application runs, the smartphone automatically measures the environmental noise and provides the HTS value to correct the hearing threshold. A comparison to pure tone audiometry shows that this hearing screening method in the presence of noise could closely estimate the hearing threshold. We expect that the proposed ubiquitous hearing test method could be used as a simple hearing screening tool and could alert the user if they suffer from hearing loss. PMID:24926692
Wireless medical ultrasound video transmission through noisy channels.
Panayides, A; Pattichis, M S; Pattichis, C S
2008-01-01
Recent advances in video compression such as the current state-of-the-art H.264/AVC standard in conjunction with increasingly available bitrate through new technologies like 3G, and WiMax have brought mobile health (m-Health) healthcare systems and services closer to reality. Despite this momentum towards m-Health systems and especially e-Emergency systems, wireless channels remain error prone, while the absence of objective quality metrics limits the ability of providing medical video of adequate diagnostic quality at a required bitrate. In this paper we investigate different encoding schemes and loss rates in medical ultrasound video transmission and come to conclusions involving efficiency, the trade-off between bitrate and quality, while we highlight the relationship linking video quality and the error ratio of corrupted P and B frames. More specifically, we investigate IPPP, IBPBP and IBBPBBP coding structures under packet loss rates of 2%, 5%, 8% and 10% and derive that the latter attains higher SNR ratings in all tested cases. A preliminary clinical evaluation shows that for SNR ratings higher than 30 db, video diagnostic quality may be adequate, while above 30.5 db the diagnostic information available in the reconstructed ultrasound video is close to that of the original. PMID:19163920
NASA Astrophysics Data System (ADS)
Schöniger, Anneli; Wöhling, Thomas; Nowak, Wolfgang
2014-05-01
Bayesian model averaging ranks the predictive capabilities of alternative conceptual models based on Bayes' theorem. The individual models are weighted with their posterior probability to be the best one in the considered set of models. Finally, their predictions are combined into a robust weighted average and the predictive uncertainty can be quantified. This rigorous procedure does, however, not yet account for possible instabilities due to measurement noise in the calibration data set. This is a major drawback, since posterior model weights may suffer a lack of robustness related to the uncertainty in noisy data, which may compromise the reliability of model ranking. We present a new statistical concept to account for measurement noise as source of uncertainty for the weights in Bayesian model averaging. Our suggested upgrade reflects the limited information content of data for the purpose of model selection. It allows us to assess the significance of the determined posterior model weights, the confidence in model selection, and the accuracy of the quantified predictive uncertainty. Our approach rests on a brute-force Monte Carlo framework. We determine the robustness of model weights against measurement noise by repeatedly perturbing the observed data with random realizations of measurement error. Then, we analyze the induced variability in posterior model weights and introduce this "weighting variance" as an additional term into the overall prediction uncertainty analysis scheme. We further determine the theoretical upper limit in performance of the model set which is imposed by measurement noise. As an extension to the merely relative model ranking, this analysis provides a measure of absolute model performance. To finally decide, whether better data or longer time series are needed to ensure a robust basis for model selection, we resample the measurement time series and assess the convergence of model weights for increasing time series length. We illustrate
Statistics of actin-propelled trajectories in noisy environments
NASA Astrophysics Data System (ADS)
Wen, Fu-Lai; Chen, Hsuan-Yi; Leung, Kwan-tai
2016-06-01
Actin polymerization is ubiquitously utilized to power the locomotion of eukaryotic cells and pathogenic bacteria in living systems. Inevitably, actin polymerization and depolymerization proceed in a fluctuating environment that renders the locomotion stochastic. Previously, we have introduced a deterministic model that manages to reproduce actin-propelled trajectories in experiments, but not to address fluctuations around them. To remedy this, here we supplement the deterministic model with noise terms. It enables us to compute the effects of fluctuating actin density and forces on the trajectories. Specifically, the mean-squared displacement (MSD) of the trajectories is computed and found to show a super-ballistic scaling with an exponent 3 in the early stage, followed by a crossover to a normal, diffusive scaling of exponent 1 in the late stage. For open-end trajectories such as straights and S-shaped curves, the time of crossover matches the decay time of orientational order of the velocities along trajectories, suggesting that it is the spreading of velocities that leads to the crossover. We show that the super-ballistic scaling of MSD arises from the initial, linearly increasing correlation of velocities, before time translational symmetry is established. When the spreading of velocities reaches a steady state in the long-time limit, short-range correlation then yields a diffusive scaling in MSD. In contrast, close-loop trajectories like circles exhibit localized periodic motion, which inhibits spreading. The initial super-ballistic scaling of MSD arises from velocity correlation that both linearly increases and oscillates in time. Finally, we find that the above statistical features of the trajectories transcend the nature of noises, be it additive or multiplicative, and generalize to other self-propelled systems that are not necessarily actin based.
Noisy transport in reaction-diffusion systems with quenched disorder
NASA Astrophysics Data System (ADS)
Missel, Andrew Royce
Reaction-diffusion (RD) models are useful tools for studying a wide variety of natural phenomena. The effects of quenched disorder in the reaction rates on RD models is not completely understood, especially in parameter regimes where internal noise or stochasticity is also important. In the first part of this dissertation, I will examine an RD model in which both quenched disorder and stochasticity are important. The model consists of particles (labeled A) which diffuse around space and reproduce (A → 2A), die (A → 0), and compete with one another (2A → A) with rates that depend on position. Specifically, birth is only allowed in localized patches called "oases," while death is allowed in the "desert" that comprises the rest of space. In the limit of low oasis density, transport through the system is achieved via rare "hopping" events when small concentrations of particles make it through the desert from one oasis to another. To correctly account for this hopping---and to accurately describe the nature of transport in the system---it is necessary to take stochasticity into account. In order to determine the nature of transport in this system analytically, I will use a variety of tools drawn from disparate sources, including the theory of hopping conduction in doped semiconductors and first passage percolation. These tools will allow for predictions to be made for a number of important transport-related features: the infection time, or time needed for the population to traverse the system; the velocity of the front moving through the system; and the dynamic roughening of the front. I will also present the results of simulations of the system that largely confirm the analytical predictions. Finally, in the second part of the dissertation I will study a pair of closely related RD models, one of which exhibits an active to absorbing state phase transition.
Statistics of actin-propelled trajectories in noisy environments.
Wen, Fu-Lai; Chen, Hsuan-Yi; Leung, Kwan-Tai
2016-06-01
Actin polymerization is ubiquitously utilized to power the locomotion of eukaryotic cells and pathogenic bacteria in living systems. Inevitably, actin polymerization and depolymerization proceed in a fluctuating environment that renders the locomotion stochastic. Previously, we have introduced a deterministic model that manages to reproduce actin-propelled trajectories in experiments, but not to address fluctuations around them. To remedy this, here we supplement the deterministic model with noise terms. It enables us to compute the effects of fluctuating actin density and forces on the trajectories. Specifically, the mean-squared displacement (MSD) of the trajectories is computed and found to show a super-ballistic scaling with an exponent 3 in the early stage, followed by a crossover to a normal, diffusive scaling of exponent 1 in the late stage. For open-end trajectories such as straights and S-shaped curves, the time of crossover matches the decay time of orientational order of the velocities along trajectories, suggesting that it is the spreading of velocities that leads to the crossover. We show that the super-ballistic scaling of MSD arises from the initial, linearly increasing correlation of velocities, before time translational symmetry is established. When the spreading of velocities reaches a steady state in the long-time limit, short-range correlation then yields a diffusive scaling in MSD. In contrast, close-loop trajectories like circles exhibit localized periodic motion, which inhibits spreading. The initial super-ballistic scaling of MSD arises from velocity correlation that both linearly increases and oscillates in time. Finally, we find that the above statistical features of the trajectories transcend the nature of noises, be it additive or multiplicative, and generalize to other self-propelled systems that are not necessarily actin based. PMID:27415296
Simple protocols for oblivious transfer and secure identification in the noisy-quantum-storage model
Schaffner, Christian
2010-09-15
We present simple protocols for oblivious transfer and password-based identification which are secure against general attacks in the noisy-quantum-storage model as defined in R. Koenig, S. Wehner, and J. Wullschleger [e-print arXiv:0906.1030]. We argue that a technical tool from Koenig et al. suffices to prove security of the known protocols. Whereas the more involved protocol for oblivious transfer from Koenig et al. requires less noise in storage to achieve security, our ''canonical'' protocols have the advantage of being simpler to implement and the security error is easier control. Therefore, our protocols yield higher OT rates for many realistic noise parameters. Furthermore, a proof of security of a direct protocol for password-based identification against general noisy-quantum-storage attacks is given.
Noisy image magnification with total variation regularization and order-changed dictionary learning
NASA Astrophysics Data System (ADS)
Xu, Jian; Chang, Zhiguo; Fan, Jiulun; Zhao, Xiaoqiang; Wu, Xiaomin; Wang, Yanzi
2015-12-01
Noisy low resolution (LR) images are always obtained in real applications, but many existing image magnification algorithms can not get good result from a noisy LR image. We propose a two-step image magnification algorithm to solve this problem. The proposed algorithm takes the advantages of both regularization-based method and learning-based method. The first step is based on total variation (TV) regularization and the second step is based on sparse representation. In the first step, we add a constraint on the TV regularization model to magnify the LR image and at the same time to suppress the noise in it. In the second step, we propose an order-changed dictionary training algorithm to train the dictionaries which is dominated by texture details. Experimental results demonstrate that the proposed algorithm performs better than many other algorithms when the noise is not serious. The proposed algorithm can also provide better visual quality on natural LR images.
NASA Astrophysics Data System (ADS)
Deng, Xiaowei; Hao, Shuhong; Tian, Caixing; Su, Xiaolong; Xie, Changde; Peng, Kunchi
2016-02-01
Squeezed state can increase the signal-to-noise ratio in quantum communication and quantum measurement. However, losses and noises existing in real communication channels will reduce or even totally destroy the squeezing. The phenomenon of disappearance of the squeezing will result in the failure of quantum communication. In this letter, we present the experimental demonstrations on the disappearance and revival of the squeezing in quantum communication with squeezed state. The experimental results show that the squeezed light is robust (squeezing never disappears) in a pure lossy but noiseless channel. While in a noisy channel, the excess noise will lead to the disappearance of the squeezing, and the squeezing can be revived by the use of a correlated noisy channel (non-Markovian environment). The channel capacity of quantum communication is increased after the squeezing is revived. The presented results provide useful technical references for quantum communication with squeezed light.
Sensing of Particular Speakers for the Construction of Voice Interface Utilized in Noisy Environment
NASA Astrophysics Data System (ADS)
Sawada, Hideyuki; Ohkado, Minoru
Human is able to exchange information smoothly using voice under different situations such as noisy environment in a crowd and with the existence of plural speakers. We are able to detect the position of a source sound in 3D space, extract a particular sound from mixed sounds, and recognize who is talking. By realizing this mechanism with a computer, new applications will be presented for recording a sound with high quality by reducing noise, presenting a clarified sound, and realizing a microphone-free speech recognition by extracting particular sound. The paper will introduce a realtime detection and identification of particular speaker in noisy environment using a microphone array based on the location of a speaker and the individual voice characteristics. The study will be applied to develop an adaptive auditory system of a mobile robot which collaborates with a factory worker.
Simple protocols for oblivious transfer and secure identification in the noisy-quantum-storage model
NASA Astrophysics Data System (ADS)
Schaffner, Christian
2010-09-01
We present simple protocols for oblivious transfer and password-based identification which are secure against general attacks in the noisy-quantum-storage model as defined in R. König, S. Wehner, and J. Wullschleger [e-print arXiv:0906.1030]. We argue that a technical tool from König suffices to prove security of the known protocols. Whereas the more involved protocol for oblivious transfer from König requires less noise in storage to achieve security, our “canonical” protocols have the advantage of being simpler to implement and the security error is easier control. Therefore, our protocols yield higher OT rates for many realistic noise parameters. Furthermore, a proof of security of a direct protocol for password-based identification against general noisy-quantum-storage attacks is given.
Pairwise Quantum Discord for a Symmetric Multi-Qubit System in Different Types of Noisy Channels
NASA Astrophysics Data System (ADS)
Guo, You-Neng; Zeng, Ke; Wang, Guo-You
2016-06-01
We study the pairwise quantum discord (QD) for a symmetric multi-qubit system in different types of noisy channels, such as phase-flip, amplitude damping, phase-damping, and depolarizing channels. Using the QD and geometric quantum discord (GMQD) to quantify quantum correlations, some analytical and numerical results are presented. The results show that, the QD dynamics is strongly related to the number of spin particles N as well as the initial parameter 𝜃 of the one-axis twisting collective state. With the number of spin particles N increasing, the amount of the QD increases. However, when the amount of the QD arrives at a stable maximal value, the QD is independence of the number of spin particles N increasing. The behavior of the QD is symmetrical during a period 0 ≤ 𝜃 ≤ 2 π. Moreover, we compare the QD dynamics with the GMQD for a symmetric multi-qubit system in different types of noisy channels.
Security of modified Ping-Pong protocol in noisy and lossy channel
NASA Astrophysics Data System (ADS)
Han, Yun-Guang; Yin, Zhen-Qiang; Li, Hong-Wei; Chen, Wei; Wang, Shuang; Guo, Guang-Can; Han, Zheng-Fu
2014-05-01
The ``Ping-Pong'' (PP) protocol is a two-way quantum key protocol based on entanglement. In this protocol, Bob prepares one maximally entangled pair of qubits, and sends one qubit to Alice. Then, Alice performs some necessary operations on this qubit and sends it back to Bob. Although this protocol was proposed in 2002, its security in the noisy and lossy channel has not been proven. In this report, we add a simple and experimentally feasible modification to the original PP protocol, and prove the security of this modified PP protocol against collective attacks when the noisy and lossy channel is taken into account. Simulation results show that our protocol is practical.
NASA Astrophysics Data System (ADS)
Mendonça, J. Ricardo G.
2016-07-01
We investigate the inactive-active phase transition in an array of additive (exclusive-or) cellular automata (CA) under noise. The model is closely related with the Domany-Kinzel (DK) probabilistic cellular automaton (PCA), for which there are rigorous as well as numerical estimates on the transition probabilities. Here, we characterize the critical behavior of the noisy additive cellular automaton by mean field analysis and finite-size scaling and show that its phase transition belongs to the directed percolation universality class of critical behavior. As a by-product of our analysis, we argue that the critical behavior of the noisy elementary CA 90 and 102 (in Wolfram’s enumeration scheme) must be the same. We also perform an empirical investigation of the mean field equations to assess their quality and find that away from the critical point (but not necessarily very far away) the mean field approximations provide a reasonably good description of the dynamics of the PCA.
Bidirectional controlled teleportation by using nine-qubit entangled state in noisy environments
NASA Astrophysics Data System (ADS)
Li, Yuan-hua; Jin, Xian-min
2016-02-01
A theoretical scheme is proposed to implement bidirectional quantum controlled teleportation (BQCT) by using a nine-qubit entangled state as a quantum channel, where Alice may transmit an arbitrary two-qubit state called qubits A_1 and A_2 to Bob; and at the same time, Bob may also transmit an arbitrary two-qubit state called qubits B_1 and B_2 to Alice via the control of the supervisor Charlie. Based on our channel, we explicitly show how the bidirectional quantum controlled teleportation protocol works. And we show this bidirectional quantum controlled teleportation scheme may be determinate and secure. Taking the amplitude-damping noise and the phase-damping noise as typical noisy channels, we analytically derive the fidelities of the BQCT process and show that the fidelities in these two cases only depend on the amplitude parameter of the initial state and the decoherence noisy rate.
Which verification qubits perform best for secure communication in noisy channel?
NASA Astrophysics Data System (ADS)
Sharma, Rishi Dutt; Thapliyal, Kishore; Pathak, Anirban; Pan, Alok Kumar; De, Asok
2016-04-01
In secure quantum communication protocols, a set of single qubits prepared using 2 or more mutually unbiased bases or a set of n-qubit (n≥ 2) entangled states of a particular form are usually used to form a verification string which is subsequently used to detect traces of eavesdropping. The qubits that form a verification string are referred to as decoy qubits, and there exists a large set of different quantum states that can be used as decoy qubits. In the absence of noise, any choice of decoy qubits provides equivalent security. In this paper, we examine such equivalence for noisy environment (e.g., in amplitude damping, phase damping, collective dephasing and collective rotation noise channels) by comparing the decoy-qubit-assisted schemes of secure quantum communication that use single-qubit states as decoy qubits with the schemes that use entangled states as decoy qubits. Our study reveals that the single- qubit-assisted scheme performs better in some noisy environments, while some entangled-qubit-assisted schemes perform better in other noisy environments. Specifically, single-qubit-assisted schemes perform better in amplitude damping and phase damping noisy channels, whereas a few Bell-state-based decoy schemes are found to perform better in the presence of the collective noise. Thus, if the kind of noise present in a communication channel (i.e., the characteristics of the channel) is known or measured, then the present study can provide the best choice of decoy qubits required for implementation of schemes of secure quantum communication through that channel.
Clustering of noisy image data using an adaptive neuro-fuzzy system
NASA Technical Reports Server (NTRS)
Pemmaraju, Surya; Mitra, Sunanda
1992-01-01
Identification of outliers or noise in a real data set is often quite difficult. A recently developed adaptive fuzzy leader clustering (AFLC) algorithm has been modified to separate the outliers from real data sets while finding the clusters within the data sets. The capability of this modified AFLC algorithm to identify the outliers in a number of real data sets indicates the potential strength of this algorithm in correct classification of noisy real data.
Lee, Soojin; Kim, Diana J; Svenkeson, Daniel; Parras, Gabriel; Oishi, Meeko Mitsuko K; McKeown, Martin J
2015-01-01
Parkinson's disease (PD) is a neurodegenerative movement disorder that is characterized clinically by slowness of movement, rigidity, tremor, postural instability, and often cognitive impairments. Recent studies have demonstrated altered cortico-basal ganglia rhythms in PD, which raises the possibility of a role for non-invasive stimulation therapies such as noisy galvanic vestibular stimulation (GVS). We applied noisy GVS to 12 mild-moderately affected PD subjects (Hoehn and Yahr 1.5-2.5) off medication while they performed a sinusoidal visuomotor joystick tracking task, which alternated between 2 task conditions depending on whether the displayed cursor position underestimated the actual error by 30% ('Better') or overestimated by 200% ('Worse'). Either sham or subthreshold, noisy GVS (0.1-10 Hz, 1/f-type power spectrum) was applied in pseudorandom order. We used exploratory (linear discriminant analysis with bootstrapping) and confirmatory (robust multivariate linear regression) methods to determine if the presence of GVS significantly affected our ability to predict cursor position based on target variables. Variables related to displayed error were robustly seen to discriminate GVS in all subjects particularly in the Worse condition. If we considered higher frequency components of the cursor trajectory as "noise," the signal-to-noise ratio of cursor trajectory was significantly increased during the GVS stimulation. The results suggest that noisy GVS influenced motor performance of the PD subjects, and we speculate that they were elicited through a combination of mechanisms: enhanced cingulate activity resulting in modulation of frontal midline theta rhythms, improved signal processing in neuromotor system via stochastic facilitation and/or enhanced "vigor" known to be deficient in PD subjects. Further work is required to determine if GVS has a selective effect on corrective submovements that could not be detected by the current analyses. PMID:25698944
Sequence-Based Pronunciation Variation Modeling for Spontaneous ASR Using a Noisy Channel Approach
NASA Astrophysics Data System (ADS)
Hofmann, Hansjörg; Sakti, Sakriani; Hori, Chiori; Kashioka, Hideki; Nakamura, Satoshi; Minker, Wolfgang
The performance of English automatic speech recognition systems decreases when recognizing spontaneous speech mainly due to multiple pronunciation variants in the utterances. Previous approaches address this problem by modeling the alteration of the pronunciation on a phoneme to phoneme level. However, the phonetic transformation effects induced by the pronunciation of the whole sentence have not yet been considered. In this article, the sequence-based pronunciation variation is modeled using a noisy channel approach where the spontaneous phoneme sequence is considered as a “noisy” string and the goal is to recover the “clean” string of the word sequence. Hereby, the whole word sequence and its effect on the alternation of the phonemes will be taken into consideration. Moreover, the system not only learns the phoneme transformation but also the mapping from the phoneme to the word directly. In this study, first the phonemes will be recognized with the present recognition system and afterwards the pronunciation variation model based on the noisy channel approach will map from the phoneme to the word level. Two well-known natural language processing approaches are adopted and derived from the noisy channel model theory: Joint-sequence models and statistical machine translation. Both of them are applied and various experiments are conducted using microphone and telephone of spontaneous speech.
New approach for T-wave end detection on electrocardiogram: Performance in noisy conditions
2011-01-01
Background The detection of T-wave end points on electrocardiogram (ECG) is a basic procedure for ECG processing and analysis. Several methods have been proposed and tested, featuring high accuracy and percentages of correct detection. Nevertheless, their performance in noisy conditions remains an open problem. Methods A new approach and algorithm for T-wave end location based on the computation of Trapezium's areas is proposed and validated (in terms of accuracy and repeatability), using signals from the Physionet QT Database. The performance of the proposed algorithm in noisy conditions has been tested and compared with one of the most used approaches for estimating the T-wave end point: the method based on the threshold on the first derivative. Results The results indicated that the proposed approach based on Trapezium's areas outperformed the baseline method with respect to accuracy and repeatability. Also, the proposed method is more robust to wideband noise. Conclusions The trapezium-based approach has a good performance in noisy conditions and does not rely on any empirical threshold. It is very adequate for use in scenarios where the levels of broadband noise are significant. PMID:21906317
Ma, Jianfen; Hu, Yi; Loizou, Philipos C.
2009-01-01
The articulation index (AI), speech-transmission index (STI), and coherence-based intelligibility metrics have been evaluated primarily in steady-state noisy conditions and have not been tested extensively in fluctuating noise conditions. The aim of the present work is to evaluate the performance of new speech-based STI measures, modified coherence-based measures, and AI-based measures operating on short-term (30 ms) intervals in realistic noisy conditions. Much emphasis is placed on the design of new band-importance weighting functions which can be used in situations wherein speech is corrupted by fluctuating maskers. The proposed measures were evaluated with intelligibility scores obtained by normal-hearing listeners in 72 noisy conditions involving noise-suppressed speech (consonants and sentences) corrupted by four different maskers (car, babble, train, and street interferences). Of all the measures considered, the modified coherence-based measures and speech-based STI measures incorporating signal-specific band-importance functions yielded the highest correlations (r=0.89–0.94). The modified coherence measure, in particular, that only included vowel∕consonant transitions and weak consonant information yielded the highest correlation (r=0.94) with sentence recognition scores. The results from this study clearly suggest that the traditional AI and STI indices could benefit from the use of the proposed signal- and segment-dependent band-importance functions. PMID:19425678
Blind noisy image quality evaluation using a deformable ant colony algorithm
NASA Astrophysics Data System (ADS)
Chen, Li; Huang, Xiaotong; Tian, Jing; Fu, Xiaowei
2014-04-01
The objective of blind noisy image quality assessment is to evaluate the quality of the degraded noisy image without the knowledge of the ground truth image. Its performance relies on the accuracy of the noise statistics estimated from homogenous blocks. The major challenge of block-based approaches lies in the block size selection, as it affects the local noise derivation. To tackle this challenge, a deformable ant colony optimization (DACO) approach is proposed in this paper to adaptively adjust the ant size for image block selection. The proposed DACO approach considers that the size of the ant is adjustable during foraging. For the smooth image blocks, more pheromone is deposited, and then the size of ant is increased. Therefore, this strategy enables the ants to have dynamic food-search capability, leading to more accurate selection of homogeneous blocks. Furthermore, the regression analysis is used to obtain image quality score by exploiting the above-estimated noise statistics. Experimental results are provided to justify that the proposed approach outperforms conventional approaches to provide more accurate noise statistics estimation and achieve a consistent image quality evaluation performance for both the artificially generated and real-world noisy images.
Marching along to an Offbeat Drum: Entrainment of Synthetic Gene Oscillators by a Noisy Stimulus.
Butzin, Nicholas C; Hochendoner, Philip; Ogle, Curtis T; Hill, Paul; Mather, William H
2016-02-19
Modulation of biological oscillations by stimuli lies at the root of many phenomena, including maintenance of circadian rhythms, propagation of neural signals, and somitogenesis. While it is well established that regular periodic modulation can entrain an oscillator, an aperiodic (noisy) modulation can also robustly entrain oscillations. This latter scenario may describe, for instance, the effect of irregular weather patterns on circadian rhythms, or why irregular neural stimuli can still reliably transmit information. A synthetic gene oscillator approach has already proven to be useful in understanding the entrainment of biological oscillators by periodic signaling, mimicking the entrainment of a number of noisy oscillating systems. We similarly seek to use synthetic biology as a platform to understand how aperiodic signals can strongly correlate the behavior of cells. This study should lead to a deeper understanding of how fluctuations in our environment and even within our body may promote substantial synchrony among our cells. Specifically, we investigate experimentally and theoretically the entrainment of a synthetic gene oscillator in E. coli by a noisy stimulus. This phenomenon was experimentally studied and verified by a combination of microfluidics and microscopy using the real synthetic circuit. Stochastic simulation of an associated model further supports that the synthetic gene oscillator can be strongly entrained by aperiodic signals, especially telegraph noise. Finally, widespread applicability of aperiodic entrainment beyond the synthetic gene oscillator is supported by results derived from both a model for a natural oscillator in D. discoideum and a model for predator-prey oscillations. PMID:26524465
Time-bin-encoding-based remote states generation of nitrogen-vacancy centers through noisy channels
NASA Astrophysics Data System (ADS)
Su, Shi-Lei; Chen, Li; Guo, Qi; Wang, Hong-Fu; Zhu, Ai-Dong; Zhang, Shou
2015-02-01
We design proposals to generate a remote Greenberger-Horne-Zeilinger (GHZ) state and a W state of nitrogen-vacancy (NV) centers coupled to microtoroidal resonators (MTRs) through noisy channels by utilizing time-bin encoding processes and fast-optical-switch-based polarization rotation operations. The polarization and phase noise induced by noisy channels generally affect the time of state generation but not its success probability and fidelity. Besides, the above proposals can be generalized to n-qubit between two or among n remote nodes with success probability unity under ideal conditions. Furthermore, the proposals are robust for regular noise-changeable channels for the n-node case. This method is also useful in other remote quantum information processing tasks through noisy channels. Project supported by the National Natural Science Foundation of China (Grant Nos. 11264042, 61465013, 11465020, and 11165015), the Program for Chun Miao Excellent Talents of Jilin Provincial Department of Education (Grant No. 201316), and the Talent Program of Yanbian University of China (Grant No. 950010001).
Does finite-temperature decoding deliver better optima for noisy Hamiltonians?
NASA Astrophysics Data System (ADS)
Ochoa, Andrew J.; Nishimura, Kohji; Nishimori, Hidetoshi; Katzgraber, Helmut G.
The minimization of an Ising spin-glass Hamiltonian is an NP-hard problem. Because many problems across disciplines can be mapped onto this class of Hamiltonian, novel efficient computing techniques are highly sought after. The recent development of quantum annealing machines promises to minimize these difficult problems more efficiently. However, the inherent noise found in these analog devices makes the minimization procedure difficult. While the machine might be working correctly, it might be minimizing a different Hamiltonian due to the inherent noise. This means that, in general, the ground-state configuration that correctly minimizes a noisy Hamiltonian might not minimize the noise-less Hamiltonian. Inspired by rigorous results that the energy of the noise-less ground-state configuration is equal to the expectation value of the energy of the noisy Hamiltonian at the (nonzero) Nishimori temperature [J. Phys. Soc. Jpn., 62, 40132930 (1993)], we numerically study the decoding probability of the original noise-less ground state with noisy Hamiltonians in two space dimensions, as well as the D-Wave Inc. Chimera topology. Our results suggest that thermal fluctuations might be beneficial during the optimization process in analog quantum annealing machines.
Nath, Audrey R.; Beauchamp, Michael S.
2011-01-01
Humans are remarkably adept at understanding speech, even when it is contaminated by noise. Multisensory integration may explain some of this ability: combining independent information from the auditory modality (vocalizations) and the visual modality (mouth movements) reduces noise and increases accuracy. Converging evidence suggests that the superior temporal sulcus (STS) is a critical brain area for multisensory integration, but little is known about its role in the perception of noisy speech. Behavioral studies have shown that perceptual judgments are weighted by the reliability of the sensory modality: more reliable modalities are weighted more strongly, even if the reliability changes rapidly. We hypothesized that changes in the functional connectivity of STS with auditory and visual cortex could provide a neural mechanism for perceptual reliability-weighting. To test this idea, we performed five blood oxygenation level dependent (BOLD) fMRI and behavioral experiments in 34 healthy subjects. We found increased functional connectivity between the STS and auditory cortex when the auditory modality was more reliable (less noisy) and increased functional connectivity between the STS and visual cortex when the visual modality was more reliable, even when the reliability changed rapidly during presentation of successive words. This finding matched the results of a behavioral experiment in which the perception of incongruent audiovisual syllables was biased toward the more reliable modality, even with rapidly changing reliability. Changes in STS functional connectivity may be an important neural mechanism underlying the perception of noisy speech. PMID:21289179
A rating scale experiment on loudness, noisiness and annoyance of environmental sounds
NASA Astrophysics Data System (ADS)
Hiramatsu, K.; Takagi, K.; Yamamoto, T.
1988-12-01
How people judge loudness, noisiness and annoyance of sounds was investigated by using a variety of environmental sounds. Fifty male and female subjects, aged from 18 to 60 years, heard 59 environmental sounds as well as seven kinds of white noise and judged their loudness, noisiness and annoyance on rating scales. Average scores on the three concepts given to the steady white noises are approximately in linear proportion to the level of the noise, with high correlation coefficients. The relationships were used to convert the scores given to the sounds to the levels of white noise which would have the same scores and can be regarded as points of subjective equality ( PSE's) of the sounds. It is found that the PSE thus obtained concerning loudness is best correlated among the three with Perceived Level and that concerning annoyance is least correlated with the level. Scattergrams of PSE's between the three concepts plotted against each other showed considerably high correlations. They are more correlated when sounds such as music, church bell, birds, etc., being on average judged pleasant or neutral, are excluded. This suggests that the human responses concerning those three concepts of auditory sensation and/or perception are mutually correlated. Lower correlation between loudness and annoyance, however, suggests sounds heard as equally loud could be differently annoying. More detailed analysis of the results showed that the judgement of loudness was not independent of noisiness and/or annoyance of the sound.
Location of Microearthquakes in Various Noisy Environments Using Envelope Stacking
NASA Astrophysics Data System (ADS)
Oye, V.; Gharti, H.
2009-12-01
Monitoring of microearthquakes is routinely conducted in various environments such as hydrocarbon and geothermal reservoirs, mines, dams, seismically active faults, volcanoes, nuclear power plants and CO2 storages. In many of these cases the handled data is sensitive and the interpretation of the data may be vital. In some cases, such as during mining or hydraulic fracturing activities, the number of microearthquakes is very large with tens to thousands of events per hour. In others, almost no events occur during a week and furthermore, it might not be anticipated that many events occur at all. However, the general setup of seismic networks, including surface and downhole stations, is usually optimized to record as many microearthquakes as possible, thereby trying to lower the detection threshold of the network. This process is obviously limited to some extent. Most microearthquake location techniques take advantage of a combination of P- and S-wave onset times that often can be picked reliably in an automatic mode. Moreover, when using seismic wave onset times, sometimes in combination with seismic wave polarization, these methods are more accurate compared to migration-based location routines. However, many events cannot be located because their magnitude is too small, i.e. the P- and/or S-wave onset times cannot be picked accurately on a sufficient number of receivers. Nevertheless, these small events are important for the interpretation of the processes that are monitored and even an inferior estimate of event locations and strengths is valuable information. Moreover, the smaller the event the more often such events statistically occur and the more important such additional information becomes. In this study we try to enhance the performance of any microseismic network, providing additional estimates of event locations below the actual detection threshold. We present a migration-based event location method, where we project the recorded seismograms onto the ray
The Noisiness of Low-Frequency One-Third Octave Bands of Noise. M.S. Thesis - Southampton Univ.
NASA Technical Reports Server (NTRS)
Lawton, B. W.
1975-01-01
This study examined the relative noisiness of low frequency one-third octave bands of noise bounded by the bands centered at 25 Hz and 200 Hz, with intensities ranging from 50 db sound pressure level (SPL) to 95 db SPL. The thirty-two subjects used a method-of-adjustment technique, producing comparison-band intensities as noisy as standard bands centered at 100 Hz and 200 Hz with intensities of 60 db SPL and 72 db SPL. Four contours of equal noisiness were developed for one-third octave bands, extending down to 25 Hz and ranging in intensity from approximately 58 db SPL to 86 db SPL. These curves were compared with the contours of equal noisiness of Kryter and Pearsons. In the region of overlap (between 50 Hz and 200 Hz) the agreement was good.
NASA Astrophysics Data System (ADS)
Araújo, Mario; Areán, Daniel; Lizana, Javier M.
2016-07-01
We study the effects of disorder on strongly coupled compressible matter in 2+1 dimensions. Our system consists of a D3/D5 intersection at finite temperature and in the presence of a disordered chemical potential. We first study the impact of disorder on the charge density and the quark condensate. Next, we focus on the DC conductivity and derive analytic expressions for the corrections induced by weak disorder. It is found that disorder enhances the DC conductivity at low charge density, while for large charge density the conductivity is reduced. We present numerical simulations both for weak and strong disorder. Finally, we show how disorder gives rise to a sublinear behavior for the conductivity as a function of the charge density, a behavior qualitatively similar to predictions and observations for electric transport in graphene.
Lauzeral, Christine; Grenouillet, Gaël; Brosse, Sébastien
2012-01-01
Species distribution models (SDMs) are widespread in ecology and conservation biology, but their accuracy can be lowered by non-environmental (noisy) absences that are common in species occurrence data. Here we propose an iterative ensemble modelling (IEM) method to deal with noisy absences and hence improve the predictive reliability of ensemble modelling of species distributions. In the IEM approach, outputs of a classical ensemble model (EM) were used to update the raw occurrence data. The revised data was then used as input for a new EM run. This process was iterated until the predictions stabilized. The outputs of the iterative method were compared to those of the classical EM using virtual species. The IEM process tended to converge rapidly. It increased the consensus between predictions provided by the different methods as well as between those provided by different learning data sets. Comparing IEM and EM showed that for high levels of non-environmental absences, iterations significantly increased prediction reliability measured by the Kappa and TSS indices, as well as the percentage of well-predicted sites. Compared to EM, IEM also reduced biases in estimates of species prevalence. Compared to the classical EM method, IEM improves the reliability of species predictions. It particularly deals with noisy absences that are replaced in the data matrices by simulated presences during the iterative modelling process. IEM thus constitutes a promising way to increase the accuracy of EM predictions of difficult-to-detect species, as well as of species that are not in equilibrium with their environment. PMID:23166691
Dendritic tree extraction from noisy maximum intensity projection images in C. elegans
2014-01-01
Background Maximum Intensity Projections (MIP) of neuronal dendritic trees obtained from confocal microscopy are frequently used to study the relationship between tree morphology and mechanosensory function in the model organism C. elegans. Extracting dendritic trees from noisy images remains however a strenuous process that has traditionally relied on manual approaches. Here, we focus on automated and reliable 2D segmentations of dendritic trees following a statistical learning framework. Methods Our dendritic tree extraction (DTE) method uses small amounts of labelled training data on MIPs to learn noise models of texture-based features from the responses of tree structures and image background. Our strategy lies in evaluating statistical models of noise that account for both the variability generated from the imaging process and from the aggregation of information in the MIP images. These noisy models are then used within a probabilistic, or Bayesian framework to provide a coarse 2D dendritic tree segmentation. Finally, some post-processing is applied to refine the segmentations and provide skeletonized trees using a morphological thinning process. Results Following a Leave-One-Out Cross Validation (LOOCV) method for an MIP databse with available “ground truth” images, we demonstrate that our approach provides significant improvements in tree-structure segmentations over traditional intensity-based methods. Improvements for MIPs under various imaging conditions are both qualitative and quantitative, as measured from Receiver Operator Characteristic (ROC) curves and the yield and error rates in the final segmentations. In a final step, we demonstrate our DTE approach on previously unseen MIP samples including the extraction of skeletonized structures, and compare our method to a state-of-the art dendritic tree tracing software. Conclusions Overall, our DTE method allows for robust dendritic tree segmentations in noisy MIPs, outperforming traditional intensity
[Application of a modified method of wavelet noise removing to noisy ICP-AES spectra].
Ma, Xiao-guo; Zhang, Zhan-xia
2003-06-01
A new method for noise removal from signal by the wavelet transform was developed. Compared with analytical signal, noise has higher frequency and smaller amplitude. By the new wavelet filtering method, the high frequency components were first removed, and then the small ones in the remaining transformed vectors were discarded. The proposed approach was evaluated by the processing of simulated and experimental noisy ICP-AES spectra. Different amounts of noise were added to a Gaussian peak to obtain a series of noisy ICP spectra. The simulated noisy spectra with R (signal to noise ratio) = 6 and N (data number) = 51, and with R = 6 and N = 17 were used to illustrate the feasibility of the proposed method. The performances of noise removal by the wavelet smoothing, the wavelet denoising and the proposed technique were compared. It was found that using the new approach, the relative errors of peak height would be no more than 5% for spectra with normal sampling points and R > or = 2. Moreover, the baseline could be easily defined, which was helpful to the accurate measurement of peak height. Experimental spectra of Al and V at low concentrations were processed by the proposed method. Intense noises were efficiently removed and the spectra became smoother without underestimating the analytical signal. The distortion of V 303.310 nm line was substantially rectified. The linear correlation coefficients between the peak heights in the reconstructed spectra and the concentrations were found to be 0.9953 for Al and 0.9836 for V, respectively. PMID:12953539
Limitations on quantum key repeaters.
Bäuml, Stefan; Christandl, Matthias; Horodecki, Karol; Winter, Andreas
2015-01-01
A major application of quantum communication is the distribution of entangled particles for use in quantum key distribution. Owing to noise in the communication line, quantum key distribution is, in practice, limited to a distance of a few hundred kilometres, and can only be extended to longer distances by use of a quantum repeater, a device that performs entanglement distillation and quantum teleportation. The existence of noisy entangled states that are undistillable but nevertheless useful for quantum key distribution raises the question of the feasibility of a quantum key repeater, which would work beyond the limits of entanglement distillation, hence possibly tolerating higher noise levels than existing protocols. Here we exhibit fundamental limits on such a device in the form of bounds on the rate at which it may extract secure key. As a consequence, we give examples of states suitable for quantum key distribution but unsuitable for the most general quantum key repeater protocol. PMID:25903096
A Statistical and Spectral Model for Representing Noisy Sounds with Short-Time Sinusoids
NASA Astrophysics Data System (ADS)
Hanna, Pierre; Desainte-Catherine, Myriam
2005-12-01
We propose an original model for noise analysis, transformation, and synthesis: the CNSS model. Noisy sounds are represented with short-time sinusoids whose frequencies and phases are random variables. This spectral and statistical model represents information about the spectral density of frequencies. This perceptually relevant property is modeled by three mathematical parameters that define the distribution of the frequencies. This model also represents the spectral envelope. The mathematical parameters are defined and the analysis algorithms to extract these parameters from sounds are introduced. Then algorithms for generating sounds from the parameters of the model are presented. Applications of this model include tools for composers, psychoacoustic experiments, and pedagogy.
Self-calibration of a noisy multiple-sensor system with genetic algorithms
NASA Astrophysics Data System (ADS)
Brooks, Richard R.; Iyengar, S. Sitharama; Chen, Jianhua
1996-01-01
This paper explores an image processing application of optimization techniques which entails interpreting noisy sensor data. The application is a generalization of image correlation; we attempt to find the optimal gruence which matches two overlapping gray-scale images corrupted with noise. Both taboo search and genetic algorithms are used to find the parameters which match the two images. A genetic algorithm approach using an elitist reproduction scheme is found to provide significantly superior results. The presentation includes a graphic presentation of the paths taken by tabu search and genetic algorithms when trying to find the best possible match between two corrupted images.
Frequency-Zooming ARMA Modeling for Analysis of Noisy String Instrument Tones
NASA Astrophysics Data System (ADS)
Esquef, Paulo A. A.; Karjalainen, Matti; Välimäki, Vesa
2003-12-01
This paper addresses model-based analysis of string instrument sounds. In particular, it reviews the application of autoregressive (AR) modeling to sound analysis/synthesis purposes. Moreover, a frequency-zooming autoregressive moving average (FZ-ARMA) modeling scheme is described. The performance of the FZ-ARMA method on modeling the modal behavior of isolated groups of resonance frequencies is evaluated for both synthetic and real string instrument tones immersed in background noise. We demonstrate that the FZ-ARMA modeling is a robust tool to estimate the decay time and frequency of partials of noisy tones. Finally, we discuss the use of the method in synthesis of string instrument sounds.
Study and Simulation of Enhancements for TCP Performance Over Noisy High Latency Links
NASA Technical Reports Server (NTRS)
Partridge, Craig
1999-01-01
The goal of this study is to better understand how TCP behaves over noisy, high-latency links such as satellite links and propose improvements to TCP implementations such that TCP might better handle such links. This report is comprised of a series of smaller reports, presentations and recommendations. Included in these documents are a summary of the TCP enhancement techniques for large windows, protect against wrap around (PAWS), use of selective acknowledgements (SACK), increasing TCP's initial window and recommendations to implement TCP pacing.
Critical avalanches and subsampling in map-based neural networks coupled with noisy synapses.
Girardi-Schappo, M; Kinouchi, O; Tragtenberg, M H R
2013-08-01
Many different kinds of noise are experimentally observed in the brain. Among them, we study a model of noisy chemical synapse and obtain critical avalanches for the spatiotemporal activity of the neural network. Neurons and synapses are modeled by dynamical maps. We discuss the relevant neuronal and synaptic properties to achieve the critical state. We verify that networks of functionally excitable neurons with fast synapses present power-law avalanches, due to rebound spiking dynamics. We also discuss the measuring of neuronal avalanches by subsampling our data, shedding light on the experimental search for self-organized criticality in neural networks. PMID:24032969
Romano, Raffaele; Loock, Peter van
2010-07-15
Quantum teleportation enables deterministic and faithful transmission of quantum states, provided a maximally entangled state is preshared between sender and receiver, and a one-way classical channel is available. Here, we prove that these resources are not only sufficient, but also necessary, for deterministically and faithfully sending quantum states through any fixed noisy channel of maximal rank, when a single use of the cannel is admitted. In other words, for this family of channels, there are no other protocols, based on different (and possibly cheaper) sets of resources, capable of replacing quantum teleportation.
Design of source coders and joint source/channel coders for noisy channels
NASA Technical Reports Server (NTRS)
Sayood, Khalid; Rost, Martin C.; Michels, Alan
1987-01-01
A theory behind a proposed joint source/channel coding approach is developed and a variable rate design approach which provides substantial improvement over current joint source/channel coder designs is obtained. The Rice algorithm as applied to the output of the Gamma Ray Detector of the Mars Orbiter is evaluated. An alternative algorithm is obtained which outperforms the Rice both in terms of data compression and noisy channel performance. A high-fidelity low-rate image compression algorithm is developed which provides almost distortionless compression of high resolution images.
Symbolic dynamics-based error analysis on chaos synchronization via noisy channels
NASA Astrophysics Data System (ADS)
Lin, Da; Zhang, Fuchen; Liu, Jia-Ming
2014-07-01
In this study, symbolic dynamics is used to research the error of chaos synchronization via noisy channels. The theory of symbolic dynamics reduces chaos to a shift map that acts on a discrete set of symbols, each of which contains information about the system state. Using this transformation, a coder-decoder scheme is proposed. A model for the relationship among word length, region number of a partition, and synchronization error is provided. According to the model, the fundamental trade-off between word length and region number can be optimized to minimize the synchronization error. Numerical simulations provide support for our results.
Noisy bases in Hilbert space: A new class of thermal coherent states and their properties
NASA Technical Reports Server (NTRS)
Vourdas, A.; Bishop, R. F.
1995-01-01
Coherent mixed states (or thermal coherent states) associated with the displaced harmonic oscillator at finite temperature, are introduced as a 'random' (or 'thermal' or 'noisy') basis in Hilbert space. A resolution of the identity for these states is proved and used to generalize the usual coherent state formalism for the finite temperature case. The Bargmann representation of an operator is introduced and its relation to the P and Q representations is studied. Generalized P and Q representations for the finite temperature case are also considered and several interesting relations among them are derived.
Variable-order fractional numerical differentiation for noisy signals by wavelet denoising
NASA Astrophysics Data System (ADS)
Chen, Yi-Ming; Wei, Yan-Qiao; Liu, Da-Yan; Boutat, Driss; Chen, Xiu-Kai
2016-04-01
In this paper, a numerical method is proposed to estimate the variable-order fractional derivatives of an unknown signal in noisy environment. Firstly, the wavelet denoising process is adopted to reduce the noise effect for the signal. Secondly, polynomials are constructed to fit the denoised signal in a set of overlapped subintervals of a considered interval. Thirdly, the variable-order fractional derivatives of these fitting polynomials are used as the estimations of the unknown ones, where the values obtained near the boundaries of each subinterval are ignored in the overlapped parts. Finally, numerical examples are presented to demonstrate the efficiency and robustness of the proposed method.
Intelligibility Assessment of Ideal Binary-Masked Noisy Speech with Acceptance of Room Acoustic
NASA Astrophysics Data System (ADS)
Vladimír, Sedlak; Daniela, Durackova; Roman, Zalusky; Tomas, Kovacik
2015-01-01
In this paper the intelligibility of ideal binary-masked noisy signal is evaluated for different signal to noise ratio (SNR), mask error, masker types, distance between source and receiver, reverberation time and local criteria for forming the binary mask. The ideal binary mask is computed from time-frequency decompositions of target and masker signals by thresholding the local SNR within time-frequency units. The intelligibility of separated signal is measured using different objective measures computed in frequency and perceptual domain. The present study replicates and extends the findings which were already presented but mainly shows impact of room acoustic on the intelligibility performance of IBM technique.
Noisy transcription factor NF-κB oscillations stabilize and sensitize cytokine signaling in space
NASA Astrophysics Data System (ADS)
Gangstad, Sirin W.; Feldager, Cilie W.; Juul, Jeppe; Trusina, Ala
2013-02-01
NF-κB is a major transcription factor mediating inflammatory response. In response to a pro-inflammatory stimulus, it exhibits a characteristic response—a pulse followed by noisy oscillations in concentrations of considerably smaller amplitude. NF-κB is an important mediator of cellular communication, as it is both activated by and upregulates production of cytokines, signals used by white blood cells to find the source of inflammation. While the oscillatory dynamics of NF-κB has been extensively investigated both experimentally and theoretically, the role of the noise and the lower secondary amplitude has not been addressed. We use a cellular automaton model to address these issues in the context of spatially distributed communicating cells. We find that noisy secondary oscillations stabilize concentric wave patterns, thus improving signal quality. Furthermore, both lower secondary amplitude as well as noise in the oscillation period might be working against chronic inflammation, the state of self-sustained and stimulus-independent excitations. Our findings suggest that the characteristic irregular secondary oscillations of lower amplitude are not accidental. On the contrary, they might have evolved to increase robustness of the inflammatory response and the system's ability to return to a pre-stimulated state.
Accurate estimation of motion blur parameters in noisy remote sensing image
NASA Astrophysics Data System (ADS)
Shi, Xueyan; Wang, Lin; Shao, Xiaopeng; Wang, Huilin; Tao, Zhong
2015-05-01
The relative motion between remote sensing satellite sensor and objects is one of the most common reasons for remote sensing image degradation. It seriously weakens image data interpretation and information extraction. In practice, point spread function (PSF) should be estimated firstly for image restoration. Identifying motion blur direction and length accurately is very crucial for PSF and restoring image with precision. In general, the regular light-and-dark stripes in the spectrum can be employed to obtain the parameters by using Radon transform. However, serious noise existing in actual remote sensing images often causes the stripes unobvious. The parameters would be difficult to calculate and the error of the result relatively big. In this paper, an improved motion blur parameter identification method to noisy remote sensing image is proposed to solve this problem. The spectrum characteristic of noisy remote sensing image is analyzed firstly. An interactive image segmentation method based on graph theory called GrabCut is adopted to effectively extract the edge of the light center in the spectrum. Motion blur direction is estimated by applying Radon transform on the segmentation result. In order to reduce random error, a method based on whole column statistics is used during calculating blur length. Finally, Lucy-Richardson algorithm is applied to restore the remote sensing images of the moon after estimating blur parameters. The experimental results verify the effectiveness and robustness of our algorithm.
A hybrid algorithm for robust acoustic source localization in noisy and reverberant environments
NASA Astrophysics Data System (ADS)
Rajagopalan, Ramesh; Dessonville, Timothy
2014-09-01
Acoustic source localization using microphone arrays is widely used in videoconferencing and surveillance systems. However, it still remains a challenging task to develop efficient algorithms for accurate estimation of source location using distributed data processing. In this work, we propose a new algorithm for efficient localization of a speaker in noisy and reverberant environments such as videoconferencing. We propose a hybrid algorithm that combines generalized cross correlation based phase transform method (GCC-PHAT) and Tabu search to obtain a robust and accurate estimate of the speaker location. The Tabu Search algorithm iteratively improves the time difference of arrival (TDOA) estimate of GCC-PHAT by examining the neighboring solutions until a convergence in the TDOA value is obtained. Experiments were performed based on real world data recorded from a meeting room in the presence of noise such as computer and fans. Our results demonstrate that the proposed hybrid algorithm outperforms GCC-PHAT especially when the noise level is high. This shows the robustness of the proposed algorithm in noisy and realistic videoconferencing systems.
Localization of a sound source in a noisy environment by hyperbolic curves in quefrency domain
NASA Astrophysics Data System (ADS)
Park, Choon-Su; Jeon, Jong-Hoon; Kim, Yang-Hann
2014-10-01
Time Difference of Arrivals (TDOAs) of sound waves between microphones have to do with source localization. How well a sound source can be localized depends on how precisely the TDOAs are estimated. Although many ways to estimate TDOA have been proposed, noise always prevents us from finding exact time differences more or less in practice. Cross correlation has been the most prevalent way to estimate time difference, and various cross correlations robust to noise have also been developed. Nevertheless, much remains to be done for exact TDOA estimation under noisy environments. A novel way to show time delays in quefrency domain by removing noise has been proposed, which is called Minimum Variance Cepstrum (MVC). In particular, it is practically desirable to visualize source position with as few number of sensors as possible. Once TDOAs are obtained precisely, it is enough to show the source position in a 2-D plane using hyperbolic curves with only three sensors. In this work, the MVC is adopted to accurately estimate TDOAs under noise, and a way to localize an acoustic source by intersecting hyperbolic curves using the TDOAs between three microphones is proposed. Numerical simulations on TDOA estimation and source localization with white Gaussian noise demonstrated that the proposed method worked well under the noisy environment, and we compared the results with those of other old but well-established cross correlation estimators. In addition, experiments to detect a leaking point on a pipe successfully showed where the leak sound was generated.
Bass, Ellen J.; Baumgart, Leigh A.; Shepley, Kathryn Klein
2014-01-01
Displaying both the strategy that information analysis automation employs to makes its judgments and variability in the task environment may improve human judgment performance, especially in cases where this variability impacts the judgment performance of the information analysis automation. This work investigated the contribution of providing either information analysis automation strategy information, task environment information, or both, on human judgment performance in a domain where noisy sensor data are used by both the human and the information analysis automation to make judgments. In a simplified air traffic conflict prediction experiment, 32 participants made probability of horizontal conflict judgments under different display content conditions. After being exposed to the information analysis automation, judgment achievement significantly improved for all participants as compared to judgments without any of the automation's information. Participants provided with additional display content pertaining to cue variability in the task environment had significantly higher aided judgment achievement compared to those provided with only the automation's judgment of a probability of conflict. When designing information analysis automation for environments where the automation's judgment achievement is impacted by noisy environmental data, it may be beneficial to show additional task environment information to the human judge in order to improve judgment performance. PMID:24847184
Daily Sleep Changes in a Noisy Environment Assessed by Subjective and Polygraphic Sleep Parameters
NASA Astrophysics Data System (ADS)
Kawada, T.; Sasazawa, Y.; Kiryu, Y.; Suzuki, S.
1997-08-01
Habituation of sleep to a noisy environment was investigated by self-rated sleep scores, polygraphic sleep parameters, and a performance test on the following morning. The self-rated sleep questionaire, OSA, includes five factors of subjective sleep quality: sleepiness, sleep maintenance, worry, integrated sleep feeling and sleep initiation. The polygraphic sleep parameters were six sleep stages in minutes, sleep latency, REM latency, REM cycle, REM duration, frequency and duration in minutes of awakening during sleep, total sleep time, number of sleep stage shifts, sleep efficiency, number of sleep spindles and density. The differences between reaction times before sleep that night and the following morning were also examined. The subjects were twelve students aged 19 to 21 who were tested a total of 96 nights. Each subject slept in an experimental room and was exposed to recorded passing truck noise with peak levels of 45, 50, 55 and 60 dB(A) at intervals of 15 min. Significant changes were recognized in Stage 1, MT, frequency of awakening and number of sleep stage shifts. The authors speculate that the decrease in the shallow stage as noisy nights were repeated reflects habituation of night sleep to repeated passing truck noise, whose interval, duration and nature was constant.
NASA Astrophysics Data System (ADS)
Ji, S.; Yuan, X.
2016-06-01
A generic probabilistic model, under fundamental Bayes' rule and Markov assumption, is introduced to integrate the process of mobile platform localization with optical sensors. And based on it, three relative independent solutions, bundle adjustment, Kalman filtering and particle filtering are deduced under different and additional restrictions. We want to prove that first, Kalman filtering, may be a better initial-value supplier for bundle adjustment than traditional relative orientation in irregular strips and networks or failed tie-point extraction. Second, in high noisy conditions, particle filtering can act as a bridge for gap binding when a large number of gross errors fail a Kalman filtering or a bundle adjustment. Third, both filtering methods, which help reduce the error propagation and eliminate gross errors, guarantee a global and static bundle adjustment, who requires the strictest initial values and control conditions. The main innovation is about the integrated processing of stochastic errors and gross errors in sensor observations, and the integration of the three most used solutions, bundle adjustment, Kalman filtering and particle filtering into a generic probabilistic localization model. The tests in noisy and restricted situations are designed and examined to prove them.
Semi-supervised learning for detecting text-lines in noisy document images
NASA Astrophysics Data System (ADS)
Liu, Zongyi; Zhou, Hanning
2010-01-01
Document layout analysis is a key step in document image understanding with wide applications in document digitization and reformatting. Identifying correct layout from noisy scanned images is especially challenging. In this paper, we introduce a semi-supervised learning framework to detect text-lines from noisy document images. Our framework consists of three steps. The first step is the initial segmentation that extracts text-lines and images using simple morphological operations. The second step is a grouping-based layout analysis that identifies text-lines, image zones, column separator and vertical border noise. It is able to efficiently remove the vertical border noises from multi-column pages. The third step is an online classifier that is trained with the high confidence line detection results from Step Two, and filters out noise from low confidence lines. The classifier effectively removes speckle noises embedded inside the content zones. We compare the performance of our algorithm to the state-of-the-art work in the field on the UW-III database. We choose the results reported by the Image Understanding Pattern Recognition Research (IUPR) and Scansoft Omnipage SDK 15.5. We evaluate the performances at both the page frame level and the text-line level. The result shows that our system has much lower false-alarm rate, while maintains similar content detection rate. In addition, we also show that our online training model generalizes better than algorithms depending on offline training.
Noisy decision thresholds can account for suboptimal detection of low coherence motion.
Price, Nicholas S C; VanCuylenberg, John B
2016-01-01
Noise in sensory signals can vary over both space and time. Moving random dot stimuli are commonly used to quantify how the visual system accounts for spatial noise. In these stimuli, a fixed proportion of "signal" dots move in the same direction and the remaining "noise" dots are randomly replotted. The spatial coherence, or proportion of signal versus noise dots, is fixed across time; however, this means that little is known about how temporally-noisy signals are integrated. Here we use a stimulus with low temporal coherence; the signal direction is only presented on a fraction of frames. Human observers are able to reliably detect and discriminate the direction of a 200 ms motion pulse, even when just 25% of frames within the pulse move in the signal direction. Using psychophysical reverse-correlation analyses, we show that observers are strongly influenced by the number of near-target directions spread throughout the pulse, and that consecutive signal frames have only a small additional influence on perception. Finally, we develop a model inspired by the leaky integration of the responses of direction-selective neurons, which reliably represents motion direction, and which can account for observers' sub-optimal detection of motion pulses by incorporating a noisy decision threshold. PMID:26726736
Noisy decision thresholds can account for suboptimal detection of low coherence motion
Price, Nicholas S. C.; VanCuylenberg, John B.
2016-01-01
Noise in sensory signals can vary over both space and time. Moving random dot stimuli are commonly used to quantify how the visual system accounts for spatial noise. In these stimuli, a fixed proportion of “signal” dots move in the same direction and the remaining “noise” dots are randomly replotted. The spatial coherence, or proportion of signal versus noise dots, is fixed across time; however, this means that little is known about how temporally-noisy signals are integrated. Here we use a stimulus with low temporal coherence; the signal direction is only presented on a fraction of frames. Human observers are able to reliably detect and discriminate the direction of a 200 ms motion pulse, even when just 25% of frames within the pulse move in the signal direction. Using psychophysical reverse-correlation analyses, we show that observers are strongly influenced by the number of near-target directions spread throughout the pulse, and that consecutive signal frames have only a small additional influence on perception. Finally, we develop a model inspired by the leaky integration of the responses of direction-selective neurons, which reliably represents motion direction, and which can account for observers’ sub-optimal detection of motion pulses by incorporating a noisy decision threshold. PMID:26726736
NASA Astrophysics Data System (ADS)
Rfifi, Saad
2016-06-01
The eavesdropping attacks applied in the quantum secret sharing (QSS) protocols through a phase-damping noisy environment are very easy to be realized. In fact, the QSS fidelity has an ordinary behaviour with just one peak according to the noise rate value for many values of the quantum message amplitude. The present work employs a Fock cavity field in such protocols to complicate any eavesdropping attacks through a phase-damping noisy environment. Indeed, only the legitimate users who can adjust the cavity parameters to reach periodically the fidelity peaks.
Implementation of two-party protocols in the noisy-storage model
Wehner, Stephanie; Curty, Marcos; Schaffner, Christian; Lo, Hoi-Kwong
2010-05-15
The noisy-storage model allows the implementation of secure two-party protocols under the sole assumption that no large-scale reliable quantum storage is available to the cheating party. No quantum storage is thereby required for the honest parties. Examples of such protocols include bit commitment, oblivious transfer, and secure identification. Here, we provide a guideline for the practical implementation of such protocols. In particular, we analyze security in a practical setting where the honest parties themselves are unable to perform perfect operations and need to deal with practical problems such as errors during transmission and detector inefficiencies. We provide explicit security parameters for two different experimental setups using weak coherent, and parametric down-conversion sources. In addition, we analyze a modification of the protocols based on decoy states.
Purity of Gaussian states: Measurement schemes and time evolution in noisy channels
Paris, Matteo G.A.; Illuminati, Fabrizio; Serafini, Alessio; De Siena, Silvio
2003-07-01
We present a systematic study of the purity for Gaussian states of single-mode continuous variable systems. We prove the connection of purity to observable quantities for these states, and show that the joint measurement of two conjugate quadratures is necessary and sufficient to determine the purity at any time. The statistical reliability and the range of applicability of the proposed measurement scheme are tested by means of Monte Carlo simulated experiments. We then consider the dynamics of purity in noisy channels. We derive an evolution equation for the purity of general Gaussian states both in thermal and in squeezed thermal baths. We show that purity is maximized at any given time for an initial coherent state evolving in a thermal bath, or for an initial squeezed state evolving in a squeezed thermal bath whose asymptotic squeezing is orthogonal to that of the input state.
Mackey-Glass noisy chaotic time series prediction by a swarm-optimized neural network
NASA Astrophysics Data System (ADS)
López-Caraballo, C. H.; Salfate, I.; Lazzús, J. A.; Rojas, P.; Rivera, M.; Palma-Chilla, L.
2016-05-01
In this study, an artificial neural network (ANN) based on particle swarm optimization (PSO) was developed for the time series prediction. The hybrid ANN+PSO algorithm was applied on Mackey-Glass noiseless chaotic time series in the short-term and long-term prediction. The performance prediction is evaluated and compared with similar work in the literature, particularly for the long-term forecast. Also, we present properties of the dynamical system via the study of chaotic behaviour obtained from the time series prediction. Then, this standard hybrid ANN+PSO algorithm was complemented with a Gaussian stochastic procedure (called stochastic hybrid ANN+PSO) in order to obtain a new estimator of the predictions that also allowed us compute uncertainties of predictions for noisy Mackey-Glass chaotic time series. We study the impact of noise for three cases with a white noise level (σ N ) contribution of 0.01, 0.05 and 0.1.
An efficient technique for the performance evaluation of antenna arrays with noisy carrier reference
NASA Technical Reports Server (NTRS)
Yan, T. Y.; Clare, L.
1981-01-01
An efficient computational technique is developed to evaluate the performance of coherent receivers with noisy carrier reference and multiple antennas. The received signal is assumed to be uncoded residual carrier BPSK (binary phase shift keying), with a PLL (phase locked loop) used for extracting the carrier. Explicit relationships between the error probabilities and the various system parameters are given. Specific results are given for the performance gain of combined carrier referencing over baseband only combining when the channel alignment process is ideal. A simple asymptotic expression for the performance gain is determined when the number of antennas used is increased without bound. An example using a Block 3 Deep Space Network PLL illustrates the performance of each arraying structure. The technique used is applicable to the performance evaluation for other receivers having similar decision statistics.
Theory of magnetic field line random walk in noisy reduced magnetohydrodynamic turbulence
Ruffolo, D.; Matthaeus, W. H.
2013-01-15
When a magnetic field consists of a mean part and fluctuations, the stochastic wandering of its field lines is often treated as a diffusive process. Under suitable conditions, a stable value is found for the mean square transverse displacement per unit parallel displacement relative to the mean field. Here, we compute the associated field line diffusion coefficient for a highly anisotropic 'noisy' reduced magnetohydrodynamic model of the magnetic field, which is useful in describing low frequency turbulence in the presence of a strong applied DC mean magnetic field, as may be found, for example, in the solar corona, or in certain laboratory devices. Our approach is nonperturbative, based on Corrsin's independence hypothesis, and makes use of recent advances in understanding factors that control decorrelation over a range of parameters described by the Kubo number. Both Bohm and quasilinear regimes are identified.
Local homogeneity combined with DCT statistics to blind noisy image quality assessment
NASA Astrophysics Data System (ADS)
Yang, Lingxian; Chen, Li; Chen, Heping
2015-03-01
In this paper a novel method for blind noisy image quality assessment is proposed. First, it is believed that human visual system (HVS) is more sensitive to the local smoothness area in a noise image, an adaptively local homogeneous block selection algorithm is proposed to construct a new homogeneous image named as homogeneity blocks (HB) based on computing each pixel characteristic. Second, applying the discrete cosine transform (DCT) for each HB and using high frequency component to evaluate image noise level. Finally, a modified peak signal to noise ratio (MPSNR) image quality assessment approach is proposed based on analysis DCT kurtosis distributions change and noise level above-mentioned. Simulations show that the quality scores that produced from the proposed algorithm are well correlated with the human perception of quality and also have a stability performance.
Analytically exact correction scheme for signal extraction from noisy magnitude MR signals
NASA Astrophysics Data System (ADS)
Koay, Cheng Guan; Basser, Peter J.
2006-04-01
An analytically exact method is proposed to extract the signal intensity and the noise variance simultaneously from noisy magnitude MR signals. This method relies on a fixed point formula of signal-to-noise ratio (SNR) and a correction factor. The correction factor, which is a function of SNR, establishes a fundamental link between the variance of the magnitude MR signal and the variance of the underlying Gaussian noise in the two quadrature channels. A more general but very similar method is developed for parallel signal acquisitions with multiple receiver coils. In the context of MR imaging, the proposed method can be carried out on a pixel-by-pixel basis if the mean and the standard deviation of the magnitude signal are available.
Mobile robot trajectory tracking using noisy RSS measurements: an RFID approach.
Miah, M Suruz; Gueaieb, Wail
2014-03-01
Most RF beacons-based mobile robot navigation techniques rely on approximating line-of-sight (LOS) distances between the beacons and the robot. This is mostly performed using the robot's received signal strength (RSS) measurements from the beacons. However, accurate mapping between the RSS measurements and the LOS distance is almost impossible to achieve in reverberant environments. This paper presents a partially-observed feedback controller for a wheeled mobile robot where the feedback signal is in the form of noisy RSS measurements emitted from radio frequency identification (RFID) tags. The proposed controller requires neither an accurate mapping between the LOS distance and the RSS measurements, nor the linearization of the robot model. The controller performance is demonstrated through numerical simulations and real-time experiments. PMID:24268746
NASA Astrophysics Data System (ADS)
Wirz, V.; Beutel, J.; Gruber, S.; Gubler, S.; Purves, R. S.
2014-09-01
Detecting and monitoring of moving and potentially hazardous slopes requires reliable estimations of velocities. Separating any movement signal from measurement noise is crucial for understanding the temporal variability of slope movements and detecting changes in the movement regime, which may be important indicators of the process. Thus, methods capable of estimating velocity and its changes reliably are required. In this paper we develop and test a method for deriving velocities based on noisy GPS (Global Positioning System) data, suitable for various movement patterns and variable signal-to-noise-ratios (SNR). We tested this method on synthetic data, designed to mimic the characteristics of diverse processes, but where we have full knowledge of the underlying velocity patterns, before applying it to explore data collected.
NASA Astrophysics Data System (ADS)
Salehi, Mohammad Reza; Abiri, Ebrahim; Dehyadegari, Louiza
2013-10-01
This paper seeks to investigate an approach of photonic reservoir computing for optical speech recognition on an examination isolated digit recognition task. An analytical approach in photonic reservoir computing is further drawn on to decrease time consumption, compared to numerical methods; which is very important in processing large signals such as speech recognition. It is also observed that adjusting reservoir parameters along with a good nonlinear mapping of the input signal into the reservoir, analytical approach, would boost recognition accuracy performance. Perfect recognition accuracy (i.e. 100%) can be achieved for noiseless speech signals. For noisy signals with 0-10 db of signal to noise ratios, however, the accuracy ranges observed varied between 92% and 98%. In fact, photonic reservoir application demonstrated 9-18% improvement compared to classical reservoir networks with hyperbolic tangent nodes.
Signal detection via residence-time asymmetry in noisy bistable devices.
Bulsara, A R; Seberino, C; Gammaitoni, L; Karlsson, M F; Lundqvist, B; Robinson, J W C
2003-01-01
We introduce a dynamical readout description for a wide class of nonlinear dynamic sensors operating in a noisy environment. The presence of weak unknown signals is assessed via the monitoring of the residence time in the metastable attractors of the system, in the presence of a known, usually time-periodic, bias signal. This operational scenario can mitigate the effects of sensor noise, providing a greatly simplified readout scheme, as well as significantly reduced processing procedures. Such devices can also show a wide variety of interesting dynamical features. This scheme for quantifying the response of a nonlinear dynamic device has been implemented in experiments involving a simple laboratory version of a fluxgate magnetometer. We present the results of the experiments and demonstrate that they match the theoretical predictions reasonably well. PMID:12636577
An Efficient Method for Noisy Cell Image Segmentation Using Generalized α-Entropy
NASA Astrophysics Data System (ADS)
Sadek, Samy; Al-Hamadi, Ayoub; Michaelis, Bernd; Sayed, Usama
In 1953, a functional extension by A. Rènyi to generalize traditional Shannon's entropy known as α-entropies was proposed. The functionalities of α-entropies share the major properties of Shannon's entropy. Moreover, these entropies can be easily estimated using a kernel estimate. This makes their use by many researchers in computer vision community highly appealing . In this paper, an efficient and fast entropic method for noisy cell image segmentation is presented. The method utilizes generalized α-entropy to measure the maximum structural information of image and to locate the optimal threshold desired by segmentation. To speed up the proposed method, computations are carried out on 1D histograms of image. Experimental results show that the proposed method is efficient and much more tolerant to noise than other state-of-the-art segmentation techniques.
Antithetic Integral Feedback Ensures Robust Perfect Adaptation in Noisy Biomolecular Networks.
Briat, Corentin; Gupta, Ankit; Khammash, Mustafa
2016-01-27
The ability to adapt to stimuli is a defining feature of many biological systems and critical to maintaining homeostasis. While it is well appreciated that negative feedback can be used to achieve homeostasis when networks behave deterministically, the effect of noise on their regulatory function is not understood. Here, we combine probability and control theory to develop a theory of biological regulation that explicitly takes into account the noisy nature of biochemical reactions. We introduce tools for the analysis and design of robust homeostatic circuits and propose a new regulation motif, which we call antithetic integral feedback. This motif exploits stochastic noise, allowing it to achieve precise regulation in scenarios where similar deterministic regulation fails. Specifically, antithetic integral feedback preserves the stability of the overall network, steers the population of any regulated species to a desired set point, and adapts perfectly. We suggest that this motif may be prevalent in endogenous biological circuits and useful when creating synthetic circuits. PMID:27136686
Phase estimation from noisy phase fringe patterns using linearly independent basis functions
NASA Astrophysics Data System (ADS)
Kulkarni, Rishikesh; Rastogi, Pramod
2015-12-01
A novel technique is proposed for obtaining unwrapped phase estimation from a highly noisy exponential phase field. In this technique, the interference phase is represented as a linear combination of linearly independent and pre-defined basis functions along each row/column of the phase field at a time. Consequently, the problem of phase estimation is converted into the problem of the estimation of the weights of the basis functions. The extended Kalman filter formulation allows for the accurate estimation of these weights. The simulation results indicate that the formulation offers a strong noise robustness in the phase estimation. Experimental results obtained using digital holographic interferometry and digital speckle pattern interferometry set-ups are provided to demonstrate the practical applicability of the proposed method.
Detecting nonlocality of noisy multipartite states with the Clauser-Horne-Shimony-Holt inequality
NASA Astrophysics Data System (ADS)
Chaves, Rafael; Acín, Antonio; Aolita, Leandro; Cavalcanti, Daniel
2014-04-01
The Clauser-Horne-Shimony-Holt inequality was originally proposed as a Bell inequality to detect nonlocality in bipartite systems. However, it can also be used to certify the nonlocality of multipartite quantum states. We apply this to study the nonlocality of multipartite Greenberger-Horne-Zeilinger (GHZ), W, and graph states under local decoherence processes. We derive lower bounds on the critical local-noise strength tolerated by the states before becoming local. In addition, for the whole noisy dynamics, we derive lower bounds on the corresponding nonlocal content for the three classes of states. All the bounds presented can be calculated efficiently and, in some cases, provide significantly tighter estimates than with any other known method. For example, they reveal that N -qubit GHZ states undergoing local dephasing are, for all N , nonlocal throughout all the dephasing dynamics.
The lower bound to the concurrence for four-qubit W state under noisy channels
NASA Astrophysics Data System (ADS)
Espoukeh, Pakhshan; Pedram, Pouria
2015-02-01
We study the dynamics of four-qubit W state under various noisy environments by solving analytically the master equation in the Lindblad form in which the Lindblad operators correspond to the Pauli matrices and describe the decoherence of states. Also, we investigate the dynamics of the entanglement using the lower bound to the concurrence. It is found that while the entanglement decreases monotonically for Pauli-Z noise, it decays suddenly for other three noises. Moreover, by studying the time evolution of entanglement of various maximally entangled four-qubit states, we indicate that the four-qubit W state is more robust under same-axis Pauli channels. Furthermore, three-qubit W state preserves more entanglement with respect to the four-qubit W state, except for the Pauli-Z noise.
Graph-regularized 3D shape reconstruction from highly anisotropic and noisy images
Heinrich, Stephanie; Drewe, Philipp; Lou, Xinghua; Umrania, Shefali; Rätsch, Gunnar
2014-01-01
Analysis of microscopy images can provide insight into many biological processes. One particularly challenging problem is cellular nuclear segmentation in highly anisotropic and noisy 3D image data. Manually localizing and segmenting each and every cellular nucleus is very time-consuming, which remains a bottleneck in large-scale biological experiments. In this work, we present a tool for automated segmentation of cellular nuclei from 3D fluorescent microscopic data. Our tool is based on state-of-the-art image processing and machine learning techniques and provides a user-friendly graphical user interface. We show that our tool is as accurate as manual annotation and greatly reduces the time for the registration. PMID:25866587
Parameter estimation of the FitzHugh-Nagumo model using noisy measurements for membrane potential.
Che, Yanqiu; Geng, Li-Hui; Han, Chunxiao; Cui, Shigang; Wang, Jiang
2012-06-01
This paper proposes an identification method to estimate the parameters of the FitzHugh-Nagumo (FHN) model for a neuron using noisy measurements available from a voltage-clamp experiment. By eliminating an unmeasurable recovery variable from the FHN model, a parametric second order ordinary differential equation for the only measurable membrane potential variable can be obtained. In the presence of the measurement noise, a simple least squares method is employed to estimate the associated parameters involved in the FHN model. Although the available measurements for the membrane potential are contaminated with noises, the proposed identification method aided by wavelet denoising can also give the FHN model parameters with satisfactory accuracy. Finally, two simulation examples demonstrate the effectiveness of the proposed method. PMID:22757546
Model-based failure detection for cylindrical shells from noisy vibration measurements.
Candy, J V; Fisher, K A; Guidry, B L; Chambers, D H
2014-12-01
Model-based processing is a theoretically sound methodology to address difficult objectives in complex physical problems involving multi-channel sensor measurement systems. It involves the incorporation of analytical models of both physical phenomenology (complex vibrating structures, noisy operating environment, etc.) and the measurement processes (sensor networks and including noise) into the processor to extract the desired information. In this paper, a model-based methodology is developed to accomplish the task of online failure monitoring of a vibrating cylindrical shell externally excited by controlled excitations. A model-based processor is formulated to monitor system performance and detect potential failure conditions. The objective of this paper is to develop a real-time, model-based monitoring scheme for online diagnostics in a representative structural vibrational system based on controlled experimental data. PMID:25480059
Implementation of two-party protocols in the noisy-storage model
NASA Astrophysics Data System (ADS)
Wehner, Stephanie; Curty, Marcos; Schaffner, Christian; Lo, Hoi-Kwong
2010-05-01
The noisy-storage model allows the implementation of secure two-party protocols under the sole assumption that no large-scale reliable quantum storage is available to the cheating party. No quantum storage is thereby required for the honest parties. Examples of such protocols include bit commitment, oblivious transfer, and secure identification. Here, we provide a guideline for the practical implementation of such protocols. In particular, we analyze security in a practical setting where the honest parties themselves are unable to perform perfect operations and need to deal with practical problems such as errors during transmission and detector inefficiencies. We provide explicit security parameters for two different experimental setups using weak coherent, and parametric down-conversion sources. In addition, we analyze a modification of the protocols based on decoy states.
Nonparametric Bayesian Dictionary Learning for Analysis of Noisy and Incomplete Images
Zhou, Mingyuan; Chen, Haojun; Paisley, John; Ren, Lu; Li, Lingbo; Xing, Zhengming; Dunson, David; Sapiro, Guillermo; Carin, Lawrence
2013-01-01
Nonparametric Bayesian methods are considered for recovery of imagery based upon compressive, incomplete, and/or noisy measurements. A truncated beta-Bernoulli process is employed to infer an appropriate dictionary for the data under test and also for image recovery. In the context of compressive sensing, significant improvements in image recovery are manifested using learned dictionaries, relative to using standard orthonormal image expansions. The compressive-measurement projections are also optimized for the learned dictionary. Additionally, we consider simpler (incomplete) measurements, defined by measuring a subset of image pixels, uniformly selected at random. Spatial interrelationships within imagery are exploited through use of the Dirichlet and probit stick-breaking processes. Several example results are presented, with comparisons to other methods in the literature. PMID:21693421