Ultimate Precision Limits for Noisy Frequency Estimation.
Smirne, Andrea; Kołodyński, Jan; Huelga, Susana F; Demkowicz-Dobrzański, Rafał
2016-03-25
Quantum metrology protocols allow us to surpass precision limits typical to classical statistics. However, in recent years, no-go theorems have been formulated, which state that typical forms of uncorrelated noise can constrain the quantum enhancement to a constant factor and, thus, bound the error to the standard asymptotic scaling. In particular, that is the case of time-homogeneous (Lindbladian) dephasing and, more generally, all semigroup dynamics that include phase covariant terms, which commute with the system Hamiltonian. We show that the standard scaling can be surpassed when the dynamics is no longer ruled by a semigroup and becomes time inhomogeneous. In this case, the ultimate precision is determined by the system short-time behavior, which when exhibiting the natural Zeno regime leads to a nonstandard asymptotic resolution. In particular, we demonstrate that the relevant noise feature dictating the precision is the violation of the semigroup property at short time scales, while non-Markovianity does not play any specific role.
Limiting hazardous noise exposure from noisy toys: simple, sticky solutions.
Weinreich, Heather M; Jabbour, Noel; Levine, Samuel; Yueh, Bevan
2013-09-01
To assess noise levels of toys from the Sight & Hearing Association (SHA) 2010 Noisy Toys List and evaluate the change in noise of these toys after covering the speakers with tape or glue. One Group Pretest-Posttest Design. SHA 2010 Toys List (n = 18) toys were tested at distances of 0 and 25 cm from sound source in a soundproof booth using a digital sound-level meter. The dBA level of sound produced by toy was obtained. Toys with speakers (n = 16) were tested before and after altering speakers with plastic packing tape or nontoxic glue. Mean noise level for non-taped toys at 0 and 25 cm was 107.6 dBA (SD ± 8.5) and 82.5 dBA (SD ± 8.8), respectively. With tape, there was a statistically significant decrease in noise level at 0 and 25 cm: 84.2 dBA and 68.2 dBA (P <0.001). With glue, there was a statistically significant decrease in noise level at 0 cm and 25 cm: 79.7 dBA and 66.4 dBA (P <0.001). Both tape and glue significantly decreased the noise level produced by the toys. However, there was no significant difference between tape or glue. Overall, altering the toy can significantly decrease the sound a child may experience when playing with toys. However, some toys, even after altering, still produce sound levels that may be considered dangerous. Copyright © 2013 The American Laryngological, Rhinological and Otological Society, Inc.
Distributed Compressive CSIT Estimation and Feedback for FDD Multi-User Massive MIMO Systems
NASA Astrophysics Data System (ADS)
Rao, Xiongbin; Lau, Vincent K. N.
2014-06-01
To fully utilize the spatial multiplexing gains or array gains of massive MIMO, the channel state information must be obtained at the transmitter side (CSIT). However, conventional CSIT estimation approaches are not suitable for FDD massive MIMO systems because of the overwhelming training and feedback overhead. In this paper, we consider multi-user massive MIMO systems and deploy the compressive sensing (CS) technique to reduce the training as well as the feedback overhead in the CSIT estimation. The multi-user massive MIMO systems exhibits a hidden joint sparsity structure in the user channel matrices due to the shared local scatterers in the physical propagation environment. As such, instead of naively applying the conventional CS to the CSIT estimation, we propose a distributed compressive CSIT estimation scheme so that the compressed measurements are observed at the users locally, while the CSIT recovery is performed at the base station jointly. A joint orthogonal matching pursuit recovery algorithm is proposed to perform the CSIT recovery, with the capability of exploiting the hidden joint sparsity in the user channel matrices. We analyze the obtained CSIT quality in terms of the normalized mean absolute error, and through the closed-form expressions, we obtain simple insights into how the joint channel sparsity can be exploited to improve the CSIT recovery performance.
Well-posedness of the limiting equation of a noisy consensus model in opinion dynamics
NASA Astrophysics Data System (ADS)
Chazelle, Bernard; Jiu, Quansen; Li, Qianxiao; Wang, Chu
2017-07-01
This paper establishes the global well-posedness of the nonlinear Fokker-Planck equation for a noisy version of the Hegselmann-Krause model. The equation captures the mean-field behavior of a classic multiagent system for opinion dynamics. We prove the global existence, uniqueness, nonnegativity and regularity of the weak solution. We also exhibit a global stability condition, which delineates a forbidden region for consensus formation. This is the first nonlinear stability result derived for the Hegselmann-Krause model.
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.
Robust THP Transceiver Designs for Multiuser MIMO Downlink with Imperfect CSIT
NASA Astrophysics Data System (ADS)
Ubaidulla, P.; Chockalingam, A.
2009-12-01
We present robust joint nonlinear transceiver designs for multiuser multiple-input multiple-output (MIMO) downlink in the presence of imperfections in the channel state information at the transmitter (CSIT). The base station (BS) is equipped with multiple transmit antennas, and each user terminal is equipped with one or more receive antennas. The BS employs Tomlinson-Harashima precoding (THP) for interuser interference precancellation at the transmitter. We consider robust transceiver designs that jointly optimize the transmit THP filters and receive filter for two models of CSIT errors. The first model is a stochastic error (SE) model, where the CSIT error is Gaussian-distributed. This model is applicable when the CSIT error is dominated by channel estimation error. In this case, the proposed robust transceiver design seeks to minimize a stochastic function of the sum mean square error (SMSE) under a constraint on the total BS transmit power. We propose an iterative algorithm to solve this problem. The other model we consider is a norm-bounded error (NBE) model, where the CSIT error can be specified by an uncertainty set. This model is applicable when the CSIT error is dominated by quantization errors. In this case, we consider a worst-case design. For this model, we consider robust (i) minimum SMSE, (ii) MSE-constrained, and (iii) MSE-balancing transceiver designs. We propose iterative algorithms to solve these problems, wherein each iteration involves a pair of semidefinite programs (SDPs). Further, we consider an extension of the proposed algorithm to the case with per-antenna power constraints. We evaluate the robustness of the proposed algorithms to imperfections in CSIT through simulation, and show that the proposed robust designs outperform nonrobust designs as well as robust linear transceiver designs reported in the recent literature.
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
Achievable degrees of freedom of MIMO two-way relay interference channel with delayed CSIT
NASA Astrophysics Data System (ADS)
Li, Qingyun; Wu, Gang; Li, Shaoqian
2016-10-01
In this paper, assuming each node has delayed channel state information at the transmitter (CSIT), we investigate the achievable degrees of freedom (DOF) of MIMO two-way relay interference channel in frequency division duplex (FDD) systems, where there are K user pairs (i.e., 2K users) and each user in a user pair exchanges messages with the other user in the same user pair simultaneously via an intermediate relay. We propose a two-stage transmission scheme and derive the closed-form expressions for its achievable DOF.
Vinciarelli, Alessandro
2005-12-01
This work presents categorization experiments performed over noisy texts. By noisy, we mean any text obtained through an extraction process (affected by errors) from media other than digital texts (e.g., transcriptions of speech recordings extracted with a recognition system). The performance of a categorization system over the clean and noisy (Word Error Rate between approximately 10 and approximately 50 percent) versions of the same documents is compared. The noisy texts are obtained through handwriting recognition and simulation of optical character recognition. The results show that the performance loss is acceptable for Recall values up to 60-70 percent depending on the noise sources. New measures of the extraction process performance, allowing a better explanation of the categorization results, are proposed.
NoisyGOA: Noisy GO annotations prediction using taxonomic and semantic similarity.
Lu, Chang; Wang, Jun; Zhang, Zili; Yang, Pengyi; Yu, Guoxian
2016-12-01
Gene Ontology (GO) provides GO annotations (GOA) that associate gene products with GO terms that summarize their cellular, molecular and functional aspects in the context of biological pathways. GO Consortium (GOC) resorts to various quality assurances to ensure the correctness of annotations. Due to resources limitations, only a small portion of annotations are manually added/checked by GO curators, and a large portion of available annotations are computationally inferred. While computationally inferred annotations provide greater coverage of known genes, they may also introduce annotation errors (noise) that could mislead the interpretation of the gene functions and their roles in cellular and biological processes. In this paper, we investigate how to identify noisy annotations, a rarely addressed problem, and propose a novel approach called NoisyGOA. NoisyGOA first measures taxonomic similarity between ontological terms using the GO hierarchy and semantic similarity between genes. Next, it leverages the taxonomic similarity and semantic similarity to predict noisy annotations. We compare NoisyGOA with other alternative methods on identifying noisy annotations under different simulated cases of noisy annotations, and on archived GO annotations. NoisyGOA achieved higher accuracy than other alternative methods in comparison. These results demonstrated both taxonomic similarity and semantic similarity contribute to the identification of noisy annotations. Our study shows that annotation errors are predictable and removing noisy annotations improves the performance of gene function prediction. This study can prompt the community to study methods for removing inaccurate annotations, a critical step for annotating gene and pathway functions. Copyright Â© 2016 Elsevier Ltd. All rights reserved.
Learning With Auxiliary Less-Noisy Labels.
Duan, Yunyan; Wu, Ou
2016-04-06
Obtaining a sufficient number of accurate labels to form a training set for learning a classifier can be difficult due to the limited access to reliable label resources. Instead, in real-world applications, less-accurate labels, such as labels from nonexpert labelers, are often used. However, learning with less-accurate labels can lead to serious performance deterioration because of the high noise rate. Although several learning methods (e.g., noise-tolerant classifiers) have been advanced to increase classification performance in the presence of label noise, only a few of them take the noise rate into account and utilize both noisy but easily accessible labels and less-noisy labels, a small amount of which can be obtained with an acceptable added time cost and expense. In this brief, we propose a learning method, in which not only noisy labels but also auxiliary less-noisy labels, which are available in a small portion of the training data, are taken into account. Based on a flipping probability noise model and a logistic regression classifier, this method estimates the noise rate parameters, infers ground-truth labels, and learns the classifier simultaneously in a maximum likelihood manner. The proposed method yields three learning algorithms, which correspond to three prior knowledge states regarding the less-noisy labels. The experiments show that the proposed method is tolerant to label noise, and outperforms classifiers that do not explicitly consider the auxiliary less-noisy labels.
Reentrant transition in coupled noisy oscillators
NASA Astrophysics Data System (ADS)
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.
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.
Cryptography from noisy storage.
Wehner, Stephanie; Schaffner, Christian; Terhal, Barbara M
2008-06-06
We show how to implement cryptographic primitives based on the realistic assumption that quantum storage of qubits is noisy. We thereby consider individual-storage attacks; i.e., the dishonest party attempts to store each incoming qubit separately. Our model is similar to the model of bounded-quantum storage; however, we consider an explicit noise model inspired by present-day technology. To illustrate the power of this new model, we show that a protocol for oblivious transfer is secure for any amount of quantum-storage noise, as long as honest players can perform perfect quantum operations. Our model also allows us to show the security of protocols that cope with noise in the operations of the honest players and achieve more advanced tasks such as secure identification.
Purification of noisy quantum measurements
Dall'Arno, Michele; D'Ariano, Giacomo Mauro; Sacchi, Massimiliano F.
2010-10-15
We consider the problem of improving noisy quantum measurements by suitable preprocessing strategies making many noisy detectors equivalent to a single ideal detector. For observables pertaining to finite-dimensional systems (e.g., qubits or spins) we consider preprocessing strategies that are reminiscent of quantum error correction procedures and allow one to perfectly measure an observable on a single quantum system for increasing number of inefficient detectors. For measurements of observables with an unbounded spectrum (e.g., photon number and homodyne and heterodyne detection), the purification of noisy quantum measurements can be achieved by preamplification as suggested by Yuen [Opt. Lett. 12, 789 (1987)].
Communicating in a Noisy World.
1983-04-18
among us; we could not band together in groups to coprt nachieving mutual goals. The following words encapsulate this important fact, "With communication ...AD-AI72 754 COMMUNICATING IN A NOISY WQRLD(U) ARMY WAR CO LL CARLISLE BARRACKS PA P M GAYNOR 18 APR 83 U LNCLASSIFIED FG52 N 1 j 2.2 11111111111.8...TITLE (and Subtitle) 3. TYPE OF REPORT & PERIOD COVERED COMMUNICATING IN A NOISY WORLD Student Essay 6. PERFORMING ORG. REPORT NUMBER 7. AUTHOR(&) S
Pros and cons of swimming in a noisy environment.
Olla, Piero
2014-03-01
The problem of optimal microscopic swimming in a noisy environment is analyzed. A simplified model in which propulsion is generated by the relative motion of three spheres connected by immaterial links has been considered. We show that an optimized noisy microswimmer requires less power for propulsion (on average) than an optimal noiseless counterpart migrating with identical mean velocity and swimming stroke amplitude. We also show that noise can be used to overcome some of the limitations of the scallop theorem and have a swimmer that is able to propel itself with control over just one degree of freedom.
Pros and cons of swimming in a noisy environment
NASA Astrophysics Data System (ADS)
Olla, Piero
2014-03-01
The problem of optimal microscopic swimming in a noisy environment is analyzed. A simplified model in which propulsion is generated by the relative motion of three spheres connected by immaterial links has been considered. We show that an optimized noisy microswimmer requires less power for propulsion (on average) than an optimal noiseless counterpart migrating with identical mean velocity and swimming stroke amplitude. We also show that noise can be used to overcome some of the limitations of the scallop theorem and have a swimmer that is able to propel itself with control over just one degree of freedom.
Abnormality detection in noisy biosignals.
Kaya, Emine Merve; Elhilali, Mounya
2013-01-01
Although great strides have been achieved in computer-aided diagnosis (CAD) research, a major remaining problem is the ability to perform well under the presence of significant noise. In this work, we propose a mechanism to find instances of potential interest in time series for further analysis. Adaptive Kalman filters are employed in parallel among different feature axes. Lung sounds recorded in noisy conditions are used as an example application, with spectro-temporal feature extraction to capture the complex variabilities in sound. We demonstrate that both disease indicators and distortion events can be detected, reducing long time series signals into a sparse set of relevant events.
Distilling entanglement with noisy operations
NASA Astrophysics Data System (ADS)
Chang, Jinho; Bae, Joonwoo; Kwon, Younghun
Entanglement distillation is a fundamental task in quantum information processing. It not only extracts entanglement out of corrupted systems but also leads to protecting systems of interest against intervention with environment. In this work, we consider a realistic scenario of entanglement distillation where noisy quantum operations are applied. In particular, the two-way distillation protocol that tolerates the highest error rate is considered. We show that among all types of noise there are only four equivalence classes according to the distillability condition. Since the four classes are connected by local unitary transformations, our results can be used to improve entanglement distillability in practice when entanglement distillation is performed in a realistic setting.
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.
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.
Quantum error correction via less noisy qubits.
Fujiwara, Yuichiro
2013-04-26
Known quantum error correction schemes are typically able to take advantage of only a limited class of classical error-correcting codes. Entanglement-assisted quantum error correction is a partial solution which made it possible to exploit any classical linear codes over the binary or quaternary finite field. However, the known entanglement-assisted scheme requires noiseless qubits that help correct quantum errors on noisy qubits, which can be too severe an assumption. We prove that a more relaxed and realistic assumption is sufficient by presenting encoding and decoding operations assisted by qubits on which quantum errors of one particular kind may occur. As in entanglement assistance, our scheme can import any binary or quaternary linear codes. If the auxiliary qubits are noiseless, our codes become entanglement-assisted codes, and saturate the quantum Singleton bound when the underlying classical codes are maximum distance separable.
Additive Classical Capacity of Quantum Channels Assisted by Noisy Entanglement
NASA Astrophysics Data System (ADS)
Zhuang, Quntao; Zhu, Elton Yechao; Shor, Peter W.
2017-05-01
We give a capacity formula for the classical information transmission over a noisy quantum channel, with separable encoding by the sender and limited resources provided by the receiver's preshared ancilla. Instead of a pure state, we consider the signal-ancilla pair in a mixed state, purified by a "witness." Thus, the signal-witness correlation limits the resource available from the signal-ancilla correlation. Our formula characterizes the utility of different forms of resources, including noisy or limited entanglement assistance, for classical communication. With separable encoding, the sender's signals across multiple channel uses are still allowed to be entangled, yet our capacity formula is additive. In particular, for generalized covariant channels, our capacity formula has a simple closed form. Moreover, our additive capacity formula upper bounds the general coherent attack's information gain in various two-way quantum key distribution protocols. For Gaussian protocols, the additivity of the formula indicates that the collective Gaussian attack is the most powerful.
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.
Sparse Poisson noisy image deblurring.
Carlavan, Mikael; Blanc-Féraud, Laure
2012-04-01
Deblurring noisy Poisson images has recently been a subject of an increasing amount of works in many areas such as astronomy and biological imaging. In this paper, we focus on confocal microscopy, which is a very popular technique for 3-D imaging of biological living specimens that gives images with a very good resolution (several hundreds of nanometers), although degraded by both blur and Poisson noise. Deconvolution methods have been proposed to reduce these degradations, and in this paper, we focus on techniques that promote the introduction of an explicit prior on the solution. One difficulty of these techniques is to set the value of the parameter, which weights the tradeoff between the data term and the regularizing term. Only few works have been devoted to the research of an automatic selection of this regularizing parameter when considering Poisson noise; therefore, it is often set manually such that it gives the best visual results. We present here two recent methods to estimate this regularizing parameter, and we first propose an improvement of these estimators, which takes advantage of confocal images. Following these estimators, we secondly propose to express the problem of the deconvolution of Poisson noisy images as the minimization of a new constrained problem. The proposed constrained formulation is well suited to this application domain since it is directly expressed using the antilog likelihood of the Poisson distribution and therefore does not require any approximation. We show how to solve the unconstrained and constrained problems using the recent alternating-direction technique, and we present results on synthetic and real data using well-known priors, such as total variation and wavelet transforms. Among these wavelet transforms, we specially focus on the dual-tree complex wavelet transform and on the dictionary composed of curvelets and an undecimated wavelet transform.
Noisy continuous time random walks
NASA Astrophysics Data System (ADS)
Jeon, Jae-Hyung; Barkai, Eli; Metzler, Ralf
2013-09-01
Experimental studies of the diffusion of biomolecules within biological cells are routinely confronted with multiple sources of stochasticity, whose identification renders the detailed data analysis of single molecule trajectories quite intricate. Here, we consider subdiffusive continuous time random walks that represent a seminal model for the anomalous diffusion of tracer particles in complex environments. This motion is characterized by multiple trapping events with infinite mean sojourn time. In real physical situations, however, instead of the full immobilization predicted by the continuous time random walk model, the motion of the tracer particle shows additional jiggling, for instance, due to thermal agitation of the environment. We here present and analyze in detail an extension of the continuous time random walk model. Superimposing the multiple trapping behavior with additive Gaussian noise of variable strength, we demonstrate that the resulting process exhibits a rich variety of apparent dynamic regimes. In particular, such noisy continuous time random walks may appear ergodic, while the bare continuous time random walk exhibits weak ergodicity breaking. Detailed knowledge of this behavior will be useful for the truthful physical analysis of experimentally observed subdiffusion.
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.
Auditory Modeling for Noisy Speech Recognition.
2000-01-01
recognition, audio signal processing, and multilingual language translation to design and demonstrate an advanced audio interface for speech recognition...and provides applications to multilingual spoken language translation. As a future Phase III commercial product, this system will perform real time... multilingual speech recognition in noisy vehicles, offices and factories. The potential market for this technology includes any commercial speech and translation application in noisy environments.
Quantum walks with coins undergoing different quantum noisy channels
NASA Astrophysics Data System (ADS)
Hao, Qin; Xue, Peng
2016-01-01
Quantum walks have significantly different properties compared to classical random walks, which have potential applications in quantum computation and quantum simulation. We study Hadamard quantum walks with coins undergoing different quantum noisy channels and deduce the analytical expressions of the first two moments of position in the long-time limit. Numerical simulations have been done, the results are compared with the analytical results, and they match extremely well. We show that the variance of the position distributions of the walks grows linearly with time when enough steps are taken and the linear coefficient is affected by the strength of the quantum noisy channels. Project supported by the National Natural Science Foundation of China (Grant Nos. 11174052 and 11474049) and the CAST Innovation Fund, China.
NoGOA: predicting noisy GO annotations using evidences and sparse representation.
Yu, Guoxian; Lu, Chang; Wang, Jun
2017-07-21
Gene Ontology (GO) is a community effort to represent functional features of gene products. GO annotations (GOA) provide functional associations between GO terms and gene products. Due to resources limitation, only a small portion of annotations are manually checked by curators, and the others are electronically inferred. Although quality control techniques have been applied to ensure the quality of annotations, the community consistently report that there are still considerable noisy (or incorrect) annotations. Given the wide application of annotations, however, how to identify noisy annotations is an important but yet seldom studied open problem. We introduce a novel approach called NoGOA to predict noisy annotations. NoGOA applies sparse representation on the gene-term association matrix to reduce the impact of noisy annotations, and takes advantage of sparse representation coefficients to measure the semantic similarity between genes. Secondly, it preliminarily predicts noisy annotations of a gene based on aggregated votes from semantic neighborhood genes of that gene. Next, NoGOA estimates the ratio of noisy annotations for each evidence code based on direct annotations in GOA files archived on different periods, and then weights entries of the association matrix via estimated ratios and propagates weights to ancestors of direct annotations using GO hierarchy. Finally, it integrates evidence-weighted association matrix and aggregated votes to predict noisy annotations. Experiments on archived GOA files of six model species (H. sapiens, A. thaliana, S. cerevisiae, G. gallus, B. Taurus and M. musculus) demonstrate that NoGOA achieves significantly better results than other related methods and removing noisy annotations improves the performance of gene function prediction. The comparative study justifies the effectiveness of integrating evidence codes with sparse representation for predicting noisy GO annotations. Codes and datasets are available at http://mlda.swu.edu.cn/codes.php?name=NoGOA .
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.
Robust information propagation through noisy neural circuits
Pouget, Alexandre
2017-01-01
Sensory neurons give highly variable responses to stimulation, which can limit the amount of stimulus information available to downstream circuits. Much work has investigated the factors that affect the amount of information encoded in these population responses, leading to insights about the role of covariability among neurons, tuning curve shape, etc. However, the informativeness of neural responses is not the only relevant feature of population codes; of potentially equal importance is how robustly that information propagates to downstream structures. For instance, to quantify the retina’s performance, one must consider not only the informativeness of the optic nerve responses, but also the amount of information that survives the spike-generating nonlinearity and noise corruption in the next stage of processing, the lateral geniculate nucleus. Our study identifies the set of covariance structures for the upstream cells that optimize the ability of information to propagate through noisy, nonlinear circuits. Within this optimal family are covariances with “differential correlations”, which are known to reduce the information encoded in neural population activities. Thus, covariance structures that maximize information in neural population codes, and those that maximize the ability of this information to propagate, can be very different. Moreover, redundancy is neither necessary nor sufficient to make population codes robust against corruption by noise: redundant codes can be very fragile, and synergistic codes can—in some cases—optimize robustness against noise. PMID:28419098
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.
Consolidation of visuomotor adaptation memory with consistent and noisy environments.
Maeda, Rodrigo S; McGee, Steven E; Marigold, Daniel S
2017-01-01
Our understanding of how we learn and retain motor behaviors is still limited. For instance, there is conflicting evidence as to whether the memory of a learned visuomotor perturbation consolidates; i.e., the motor memory becomes resistant to interference from learning a competing perturbation over time. Here, we sought to determine the factors that influence consolidation during visually guided walking. Subjects learned a novel mapping relationship, created by prism lenses, between the perceived location of two targets and the motor commands necessary to direct the feet to their positions. Subjects relearned this mapping 1 wk later. Different groups experienced protocols with or without a competing mapping (and with and without washout trials), presented either on the same day as initial learning or before relearning on day 2 We tested identical protocols under constant and noisy mapping structures. In the latter, we varied, on a trial-by-trial basis, the strength of prism lenses around a non-zero mean. We found that a novel visuomotor mapping is retained at least 1 wk after initial learning. We also found reduced foot-placement error with relearning in constant and noisy mapping groups, despite learning a competing mapping beforehand, and with the exception of one protocol, with and without washout trials. Exposure to noisy mappings led to similar performance on relearning compared with the equivalent constant mapping groups for most protocols. Overall, our results support the idea of motor memory consolidation during visually guided walking and suggest that constant and noisy practices are effective for motor learning.
Hearing impaired speech in noisy classrooms
NASA Astrophysics Data System (ADS)
Shahin, Kimary; McKellin, William H.; Jamieson, Janet; Hodgson, Murray; Pichora-Fuller, M. Kathleen
2005-04-01
Noisy classrooms have been shown to induce among students patterns of interaction similar to those used by hearing impaired people [W. H. McKellin et al., GURT (2003)]. In this research, the speech of children in a noisy classroom setting was investigated to determine if noisy classrooms have an effect on students' speech. Audio recordings were made of the speech of students during group work in their regular classrooms (grades 1-7), and of the speech of the same students in a sound booth. Noise level readings in the classrooms were also recorded. Each student's noisy and quiet environment speech samples were acoustically analyzed for prosodic and segmental properties (f0, pitch range, pitch variation, phoneme duration, vowel formants), and compared. The analysis showed that the students' speech in the noisy classrooms had characteristics of the speech of hearing-impaired persons [e.g., R. O'Halpin, Clin. Ling. and Phon. 15, 529-550 (2001)]. Some educational implications of our findings were identified. [Work supported by the Peter Wall Institute for Advanced Studies, University of British Columbia.
Critical fluctuations of noisy period-doubling maps
NASA Astrophysics Data System (ADS)
Noble, Andrew E.; Karimeddiny, Saba; Hastings, Alan; Machta, Jonathan
2017-01-01
We extend the theory of quasipotentials in dynamical systems by calculating, within a broad class of period-doubling maps, an exact potential for the critical fluctuations of pitchfork bifurcations in the weak noise limit. These far-from-equilibrium fluctuations are described by finite-size mean field theory, placing their static properties in the same universality class as the Ising model on a complete graph. We demonstrate that the effective system size of noisy period-doubling bifurcations exhibits universal scaling behavior along period-doubling routes to chaos.
Array Imaging of Noisy Materials
NASA Astrophysics Data System (ADS)
Wilcox, P. D.
2011-06-01
The ultimate limit on ultrasonic defect detectability is the coherent noise due to material backscatter. A model of such noise in ultrasonic array images is developed based on the single scattering assumption. The implications of the model are discussed and supported with some experimental examples. In the case of a copper specimen, it is shown that an improvement in signal to coherent noise ratio of over 30 dB can be obtained by optimization of imaging parameters.
Badapple: promiscuity patterns from noisy evidence.
Yang, Jeremy J; Ursu, Oleg; Lipinski, Christopher A; Sklar, Larry A; Oprea, Tudor I; Bologa, Cristian G
2016-01-01
Bioassay data analysis continues to be an essential, routine, yet challenging task in modern drug discovery and chemical biology research. The challenge is to infer reliable knowledge from big and noisy data. Some aspects of this problem are general with solutions informed by existing and emerging data science best practices. Some aspects are domain specific, and rely on expertise in bioassay methodology and chemical biology. Testing compounds for biological activity requires complex and innovative methodology, producing results varying widely in accuracy, precision, and information content. Hit selection criteria involve optimizing such that the overall probability of success in a project is maximized, and resource-wasteful "false trails" are avoided. This "fail-early" approach is embraced both in pharmaceutical and academic drug discovery, since follow-up capacity is resource-limited. Thus, early identification of likely promiscuous compounds has practical value. Here we describe an algorithm for identifying likely promiscuous compounds via associated scaffolds which combines general and domain-specific features to assist and accelerate drug discovery informatics, called Badapple: bioassay-data associative promiscuity pattern learning engine. Results are described from an analysis using data from MLP assays via the BioAssay Research Database (BARD) http://bard.nih.gov. Specific examples are analyzed in the context of medicinal chemistry, to illustrate associations with mechanisms of promiscuity. Badapple has been developed at UNM, released and deployed for public use two ways: (1) BARD plugin, integrated into the public BARD REST API and BARD web client; and (2) public web app hosted at UNM. Badapple is a method for rapidly identifying likely promiscuous compounds via associated scaffolds. Badapple generates a score associated with a pragmatic, empirical definition of promiscuity, with the overall goal to identify "false trails" and streamline workflows. Unlike
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.
Neural network approaches for noisy language modeling.
Li, Jun; Ouazzane, Karim; Kazemian, Hassan B; Afzal, Muhammad Sajid
2013-11-01
Text entry from people is not only grammatical and distinct, but also noisy. For example, a user's typing stream contains all the information about the user's interaction with computer using a QWERTY keyboard, which may include the user's typing mistakes as well as specific vocabulary, typing habit, and typing performance. In particular, these features are obvious in disabled users' typing streams. This paper proposes a new concept called noisy language modeling by further developing information theory and applies neural networks to one of its specific application-typing stream. This paper experimentally uses a neural network approach to analyze the disabled users' typing streams both in general and specific ways to identify their typing behaviors and subsequently, to make typing predictions and typing corrections. In this paper, a focused time-delay neural network (FTDNN) language model, a time gap model, a prediction model based on time gap, and a probabilistic neural network model (PNN) are developed. A 38% first hitting rate (HR) and a 53% first three HR in symbol prediction are obtained based on the analysis of a user's typing history through the FTDNN language modeling, while the modeling results using the time gap prediction model and the PNN model demonstrate that the correction rates lie predominantly in between 65% and 90% with the current testing samples, and 70% of all test scores above basic correction rates, respectively. The modeling process demonstrates that a neural network is a suitable and robust language modeling tool to analyze the noisy language stream. The research also paves the way for practical application development in areas such as informational analysis, text prediction, and error correction by providing a theoretical basis of neural network approaches for noisy language modeling.
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.
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.
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.
Robust vector quantization for noisy channels
NASA Technical Reports Server (NTRS)
Demarca, J. R. B.; Farvardin, N.; Jayant, N. S.; Shoham, Y.
1988-01-01
The paper briefly discusses techniques for making vector quantizers more tolerant to tranmsission errors. Two algorithms are presented for obtaining an efficient binary word assignment to the vector quantizer codewords without increasing the transmission rate. It is shown that about 4.5 dB gain over random assignment can be achieved with these algorithms. It is also proposed to reduce the effects of error propagation in vector-predictive quantizers by appropriately constraining the response of the predictive loop. The constrained system is shown to have about 4 dB of SNR gain over an unconstrained system in a noisy channel, with a small loss of clean-channel performance.
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.
Normal and Feature Approximations from Noisy Point Clouds
2005-02-01
Normal and Feature Approximations from Noisy Point Clouds Tamal K. Dey Jian Sun Abstract We consider the problem of approximating normal and...normal and, in partic- ular, feature size approximations for noisy point clouds . In the noise-free case the choice of the Delaunay balls is not an issue...axis from noisy point clouds ex- ists [7]. This algorithm approximates the medial axis with Voronoi faces under a stringent uniform sampling
Simulation and analysis about noisy range images of laser radar
NASA Astrophysics Data System (ADS)
Zhao, Mingbo; He, Jun; Fu, Qiang; Xi, Dan
2011-06-01
A measured range image of imaging laser radar (ladar) is usually disturbed by dropouts and outliers. For the difficulty of obtaining measured data and controlling noise level of dropouts and outliers, a new simulation method for range image with noise is proposed. Based on the noise formation mechanism of ladar range image, an accurate ladar range imaging model is formulated, including three major influencing factors: speckle, atmospheric turbulence and receiver noise. The noisy range images under different scenarios are obtained using MATLABTM. Analysis on simulation results reveals that: (1) Despite of detection strategy, the speckle, the atmospheric turbulence and the receiver noise are major factors which cause dropouts and outliers. (2) The receiver noise itself has limited effect on outliers. However, if other factors (speckle, atmospheric turbulence, etc.) also exist, the effect will be sharply enhanced. (3) Both dropouts and outliers exist in background and target regions.
Quantum amplification and purification of noisy coherent states
NASA Astrophysics Data System (ADS)
Zhao, Xiaobin; Chiribella, Giulio
2017-04-01
Quantum-limited amplifiers increase the amplitude of quantum signals at the price of introducing additional noise. Quantum purification protocols operate in the reverse way, by reducing the noise while attenuating the signal. Here we investigate a scenario that interpolates between these two extremes. We search for the optimal physical process that generates M approximate copies of a pure and amplified coherent state, starting from N copies of a noisy coherent state with Gaussian modulation. We prove that the optimal deterministic processes are always Gaussian, whereas non-Gaussianity powers up probabilistic advantages in suitable parameter regimes. The optimal processes are experimentally realizable with current technology, both in the deterministic and in the probabilistic scenario. In view of this fact, we provide benchmarks that can be used to certify the experimental demonstration of the quantum-enhanced amplification and purification of coherent states.
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.
Stabilized quasi-Newton optimization of noisy potential energy surfaces
NASA Astrophysics Data System (ADS)
Schaefer, Bastian; Alireza Ghasemi, S.; Roy, Shantanu; Goedecker, Stefan
2015-01-01
Optimizations of atomic positions belong to the most commonly performed tasks in electronic structure calculations. Many simulations like global minimum searches or characterizations of chemical reactions require performing hundreds or thousands of minimizations or saddle computations. 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. We here present a technique that allows obtaining significant curvature information of noisy potential energy surfaces. We use this technique to construct both, a stabilized quasi-Newton minimization method and a stabilized quasi-Newton saddle finding approach. We demonstrate with the help of benchmarks that both the minimizer and the saddle finding approach are superior to comparable existing methods.
Stabilized quasi-Newton optimization of noisy potential energy surfaces
Schaefer, Bastian; Goedecker, Stefan; Alireza Ghasemi, S.; Roy, Shantanu
2015-01-21
Optimizations of atomic positions belong to the most commonly performed tasks in electronic structure calculations. Many simulations like global minimum searches or characterizations of chemical reactions require performing hundreds or thousands of minimizations or saddle computations. 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. We here present a technique that allows obtaining significant curvature information of noisy potential energy surfaces. We use this technique to construct both, a stabilized quasi-Newton minimization method and a stabilized quasi-Newton saddle finding approach. We demonstrate with the help of benchmarks that both the minimizer and the saddle finding approach are superior to comparable existing methods.
Rigid body constrained noisy point pattern matching.
Morgera, S D; Cheong, P C
1995-01-01
Noisy pattern matching problems arise in many areas, e.g., computational vision, robotics, guidance and control, stereophotogrammetry, astronomy, genetics, and high-energy physics. Least-squares pattern matching over the Euclidean space E(n) for unordered sets of cardinalities p and q is commonly formulated as a combinatorial optimization problem having complexity p(p-1)...(p-q+1), q=/
Engineered noisy environment for studying decoherence
NASA Astrophysics Data System (ADS)
Iwakura, Ai; Matsuzaki, Yuichiro; Kondo, Yasushi
2017-09-01
The largest obstacle to perform quantum information processing is decoherence of a system. In order to overcome this, various techniques, such as dynamical decoupling and quantum Zeno effects, have been proposed and demonstrated. Here, we present an NMR model with which various decoherence suppression techniques can experimentally be evaluated. By changing the conditions in the sample preparation, we can engineer an environment to interact the system that contains the information. Moreover, we can efficiently describe the dynamics by the operator-sum representation due to the simplicity of our model. As concrete examples, we have investigated the performance of dynamical decoupling with several molecules. Our model provides a useful test bench to understand the mechanism of decoherence induced by a noisy environment and to examine various ideas of decoherence suppression techniques.
A segmentation algorithm for noisy images
Xu, Y.; Olman, V.; Uberbacher, E.C.
1996-12-31
This paper presents a 2-D image segmentation algorithm and addresses issues related to its performance on noisy images. The algorithm segments an image by first constructing a minimum spanning tree representation of the image and then partitioning the spanning tree into sub-trees representing different homogeneous regions. The spanning tree is partitioned in such a way that the sum of gray-level variations over all partitioned subtrees is minimized under the constraints that each subtree has at least a specified number of pixels and two adjacent subtrees have significantly different ``average`` gray-levels. Two types of noise, transmission errors and Gaussian additive noise. are considered and their effects on the segmentation algorithm are studied. Evaluation results have shown that the segmentation algorithm is robust in the presence of these two types of noise.
Learning from Weak and Noisy Labels for Semantic Segmentation.
Lu, Zhiwu; Fu, Zhenyong; Xiang, Tao; Han, Peng; Wang, Liwei; Gao, Xin
2016-04-08
A weakly supervised semantic segmentation (WSSS) method aims to learn a segmentation model from weak (image-level) as opposed to strong (pixel-level) labels. By avoiding the tedious pixel-level annotation process, it can exploit the unlimited supply of user-tagged images from media-sharing sites such as Flickr for large scale applications. However, these 'free' tags/labels are often noisy and few existing works address the problem of learning with both weak and noisy labels. In this work, we cast the WSSS problem into a label noise reduction problem. Specifically, after segmenting each image into a set of superpixels, the weak and potentially noisy image-level labels are propagated to the superpixel level resulting in highly noisy labels; the key to semantic segmentation is thus to identify and correct the superpixel noisy labels. To this end, a novel L1-optimisation based sparse learning model is formulated to directly and explicitly detect noisy labels. To solve the L1-optimisation problem, we further develop an efficient learning algorithm by introducing an intermediate labelling variable. Extensive experiments on three benchmark datasets show that our method yields state-of-the-art results given noise-free labels, whilst significantly outperforming the existing methods when the weak labels are also noisy.
A Statistical Detection of an Anomaly from a Few Noisy Tomographic Projections
NASA Astrophysics Data System (ADS)
Fillatre, Lionel; Nikiforov, Igor
2005-12-01
The problem of detecting an anomaly/target from a very limited number of noisy tomographic projections is addressed from the statistical point of view. The imaged object is composed of an environment, considered as a nuisance parameter, with a possibly hidden anomaly/target. The GLR test is used to solve the problem. When the projection linearly depends on the nuisance parameters, the GLR test coincides with an optimal statistical invariant test.
Entanglement verification of noisy NOON states
NASA Astrophysics Data System (ADS)
Bohmann, M.; Sperling, J.; Vogel, W.
2017-07-01
Entangled quantum states, such as NOON states, are of major importance for quantum technologies due to their quantum-enhanced performance. At the same time, their quantum correlations are relatively vulnerable when they are subjected to imperfections. Therefore, it is crucial to determine under which circumstances their distinct quantum features can be exploited. In this paper, we study the entanglement property of noisy NOON states. This class of states is a generalization of NOON states including various attenuation effects, such as mixing, constant or fluctuating losses, and dephasing. To verify their entanglement, we pursue two strategies: detection-based entanglement witnesses and entanglement quasiprobabilities. Both methods result from our solution of so-called separability eigenvalue equations. In particular, the entanglement quasiprobabilities allow for a full entanglement characterization. As examples of our general treatment, the cases of NOON states subjected to Gaussian dephasing and fluctuating atmospheric losses are explicitly studied. In any correlated fluctuating loss channel, entanglement is found to survive for nonzero transmissivity. In addition, an extension of our approach to multipartite systems is given, and the relation to the quantum-optical nonclassicality in phase space is discussed.
Neural networks optimally trained with noisy data
NASA Astrophysics Data System (ADS)
Wong, K. Y. Michael; Sherrington, David
1993-06-01
We study the retrieval behaviors of neural networks which are trained to optimize their performance for an ensemble of noisy example patterns. In particular, we consider (1) the performance overlap, which reflects the performance of the network in an operating condition identical to the training condition; (2) the storage overlap, which reflects the ability of the network to merely memorize the stored information; (3) the attractor overlap, which reflects the precision of retrieval for dilute feedback networks; and (4) the boundary overlap, which defines the boundary of the basin of attraction, and hence the associative ability for dilute feedback networks. We find that for sufficiently low training noise, the network optimizes its overall performance by sacrificing the individual performance of a minority of patterns, resulting in a two-band distribution of the aligning fields. For a narrow range of storage level, the network loses and then regains its retrieval capability when the training noise level increases, and we interpret that this reentrant retrieval behavior is related to competing tendencies in structuring the basins of attraction for the stored patterns. Reentrant behavior is also observed in the space of synaptic interactions, in which the replica symmetric solution of the optimal network destabilizes and then restabilizes when the training noise level increases. We summarize these observations by picturing training noises as an instrument for widening the basins of attractions of the stored patterns at the expense of reducing the precision of retrieval.
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.
Quantum computing with realistically noisy devices.
Knill, E
2005-03-03
In theory, quantum computers offer a means of solving problems that would be intractable on conventional computers. Assuming that a quantum computer could be constructed, it would in practice be required to function with noisy devices called 'gates'. These gates cause decoherence of the fragile quantum states that are central to the computer's operation. The goal of so-called 'fault-tolerant quantum computing' is therefore to compute accurately even when the error probability per gate (EPG) is high. Here we report a simple architecture for fault-tolerant quantum computing, providing evidence that accurate quantum computing is possible for EPGs as high as three per cent. Such EPGs have been experimentally demonstrated, but to avoid excessive resource overheads required by the necessary architecture, lower EPGs are needed. Assuming the availability of quantum resources comparable to the digital resources available in today's computers, we show that non-trivial quantum computations at EPGs of as high as one per cent could be implemented.
Optimal control in a noisy system
NASA Astrophysics Data System (ADS)
Asenjo, F.; Toledo, B. A.; Muñoz, V.; Rogan, J.; Valdivia, J. A.
2008-09-01
We describe a simple method to control a known unstable periodic orbit (UPO) in the presence of noise. The strategy is based on regarding the control method as an optimization problem, which allows us to calculate a control matrix A. We illustrate the idea with the Rossler system, the Lorenz system, and a hyperchaotic system that has two exponents with positive real parts. Initially, a UPO and the corresponding control matrix are found in the absence of noise in these systems. It is shown that the strategy is useful even if noise is added as control is applied. For low noise, it is enough to find a control matrix such that the maximum Lyapunov exponent λmax<0, and with a single non-null entry. If noise is increased, however, this is not the case, and the full control matrix A may be required to keep the UPO under control. Besides the Lyapunov spectrum, a characterization of the control strategies is given in terms of the average distance to the UPO and the control effort required to keep the orbit under control. Finally, particular attention is given to the problem of handling noise, which can affect considerably the estimation of the UPO itself and its exponents, and a cleaning strategy based on singular value decomposition was developed. This strategy gives a consistent manner to approach noisy systems, and may be easily adapted as a parametric control strategy, and to experimental situations, where noise is unavoidable.
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.
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
Quantum steganography with noisy quantum channels
NASA Astrophysics Data System (ADS)
Shaw, Bilal A.; Brun, Todd A.
2011-02-01
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.
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.
Dead regions and noisiness of pure tones.
Huss, Martina; Moore, Brian C J
2005-10-01
Some hearing-impaired subjects report pure tones as sounding highly distorted and noise-like. We assessed whether such reports indicate that the tone frequency falls inside a dead region (DR). Nine hearing-impaired and four normally hearing subjects rated pure tones on a scale from 1 to 7, where 1 indicates clear tone and 7 indicates noise. A white noise was presented as a reference for a sound that should be rated as 7. Stimuli covered the whole audible range of frequencies and levels. The noisiness ratings were, on average, higher for hearing-impaired subjects than for normally hearing subjects. For the former, the ratings were not markedly different for tones with frequencies just outside or inside a DR. However, ratings always exceeded 3 for tones falling more than 1.5 octaves inside a DR. The results indicate that judgement of a tone as sounding noise-like does not reliably indicate that the tone frequency falls in a DR. Both normally hearing and hearing-impaired subjects rated 0.125 kHz and 12 kHz tones as somewhat noise-like, independently of the existence of a DR.
Maeda, Shin-ichi; Song, Wen-Jie; Ishii, Shin
2005-01-01
In this letter, we propose a noisy nonlinear version of independent component analysis (ICA). Assuming that the probability density function (p. d. f.) of sources is known, a learning rule is derived based on maximum likelihood estimation (MLE). Our model involves some algorithms of noisy linear ICA (e. g., Bermond & Cardoso, 1999) or noise-free nonlinear ICA (e. g., Lee, Koehler, & Orglmeister, 1997) as special cases. Especially when the nonlinear function is linear, the learning rule derived as a generalized expectation-maximization algorithm has a similar form to the noisy ICA algorithm previously presented by Douglas, Cichocki, and Amari (1998). Moreover, our learning rule becomes identical to the standard noise-free linear ICA algorithm in the noiseless limit, while existing MLE-based noisy ICA algorithms do not rigorously include the noise-free ICA. We trained our noisy nonlinear ICA by using acoustic signals such as speech and music. The model after learning successfully simulates virtual pitch phenomena, and the existence region of virtual pitch is qualitatively similar to that observed in a psychoacoustic experiment. Although a linear transformation hypothesized in the central auditory system can account for the pitch sensation, our model suggests that the linear transformation can be acquired through learning from actual acoustic signals. Since our model includes a cepstrum analysis in a special case, it is expected to provide a useful feature extraction method that has often been given by the cepstrum analysis.
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.
Phase and amplitude imaging from noisy images by Kalman filtering.
Waller, Laura; Tsang, Mankei; Ponda, Sameera; Yang, Se Young; Barbastathis, George
2011-01-31
We propose and demonstrate a computational method for complex-field imaging from many noisy intensity images with varying defocus, using an extended complex Kalman filter. The technique offers dynamic smoothing of noisy measurements and is recursive rather than iterative, so is suitable for adaptive measurements. The Kalman filter provides near-optimal results in very low-light situations and may be adapted to propagation through turbulent, scattering, or nonlinear media.
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.
Fujii, Keisuke; Tamate, Shuhei
2016-05-18
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
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.
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.
Joint Segmentation and Recognition of Categorized Objects from Noisy Web Image Collection.
Wang, Le; Hua, Gang; Xue, Jianru; Gao, Zhanning; Zheng, Nanning
2014-07-14
The segmentation of categorized objects addresses the problem of joint segmentation of a single category of object across a collection of images, where categorized objects are referred to objects in the same category. Most existing methods of segmentation of categorized objects made the assumption that all images in the given image collection contain the target object. In other words, the given image collection is noise free. Therefore, they may not work well when there are some noisy images which are not in the same category, such as those image collections gathered by a text query from modern image search engines. To overcome this limitation, we propose a method for automatic segmentation and recognition of categorized objects from noisy Web image collections. This is achieved by cotraining an automatic object segmentation algorithm that operates directly on a collection of images, and an object category recognition algorithm that identifies which images contain the target object. The object segmentation algorithm is trained on a subset of images from the given image collection which are recognized to contain the target object with high confidence, while training the object category recognition model is guided by the intermediate segmentation results obtained from the object segmentation algorithm. This way, our co-training algorithm automatically identifies the set of true positives in the noisy Web image collection, and simultaneously extracts the target objects from all the identified images. Extensive experiments validated the efficacy of our proposed approach on four datasets: 1) the Weizmann horse dataset, 2) the MSRC object category dataset, 3) the iCoseg dataset, and 4) a new 30-categories dataset including 15,634 Web images with both hand-annotated category labels and ground truth segmentation labels. It is shown that our method compares favorably with the state-of-the-art, and has the ability to deal with noisy image collections.
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
Smoothing of, and Parameter Estimation from, Noisy Biophysical Recordings
Huys, Quentin J. M.; Paninski, Liam
2009-01-01
Biophysically detailed models of single cells are difficult to fit to real data. Recent advances in imaging techniques allow simultaneous access to various intracellular variables, and these data can be used to significantly facilitate the modelling task. These data, however, are noisy, and current approaches to building biophysically detailed models are not designed to deal with this. We extend previous techniques to take the noisy nature of the measurements into account. Sequential Monte Carlo (“particle filtering”) methods, in combination with a detailed biophysical description of a cell, are used for principled, model-based smoothing of noisy recording data. We also provide an alternative formulation of smoothing where the neural nonlinearities are estimated in a non-parametric manner. Biophysically important parameters of detailed models (such as channel densities, intercompartmental conductances, input resistances, and observation noise) are inferred automatically from noisy data via expectation-maximisation. Overall, we find that model-based smoothing is a powerful, robust technique for smoothing of noisy biophysical data and for inference of biophysical parameters in the face of recording noise. PMID:19424506
Active learning for noisy oracle via density power divergence.
Sogawa, Yasuhiro; Ueno, Tsuyoshi; Kawahara, Yoshinobu; Washio, Takashi
2013-10-01
The accuracy of active learning is critically influenced by the existence of noisy labels given by a noisy oracle. In this paper, we propose a novel pool-based active learning framework through robust measures based on density power divergence. By minimizing density power divergence, such as β-divergence and γ-divergence, one can estimate the model accurately even under the existence of noisy labels within data. Accordingly, we develop query selecting measures for pool-based active learning using these divergences. In addition, we propose an evaluation scheme for these measures based on asymptotic statistical analyses, which enables us to perform active learning by evaluating an estimation error directly. Experiments with benchmark datasets and real-world image datasets show that our active learning scheme performs better than several baseline methods. Copyright © 2013 Elsevier Ltd. All rights reserved.
Noisy traveling waves: Effect of selection on genealogies
NASA Astrophysics Data System (ADS)
Brunet, E.; Derrida, B.; Mueller, A. H.; Munier, S.
2006-10-01
For a family of models of evolving population under selection, which can be described by noisy traveling-wave equations, the coalescence times along the genealogical tree scale like ln αN, where N is the size of the population, in contrast with neutral models for which they scale like N. An argument relating this time scale to the diffusion constant of the noisy traveling wave leads to a prediction for α which agrees with our simulations. An exactly soluble case gives trees with statistics identical to those predicted for mean-field spin glasses by Parisi's theory.
Modified correlation entropy estimation for a noisy chaotic time series.
Jayawardena, A W; Xu, Pengcheng; Li, W K
2010-06-01
A method of estimating the Kolmogorov-Sinai (KS) entropy, herein referred to as the modified correlation entropy, is presented. The method can be applied to both noise-free and noisy chaotic time series. It has been applied to some clean and noisy data sets and the numerical results show that the modified correlation entropy is closer to the KS entropy of the nonlinear system calculated by the Lyapunov spectrum than the general correlation entropy. Moreover, the modified correlation entropy is more robust to noise than the correlation entropy.
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.
Extortion under uncertainty: Zero-determinant strategies in noisy games.
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.
Noisy threshold in neuronal models: connections with the noisy leaky integrate-and-fire model.
Dumont, G; Henry, J; Tarniceriu, C O
2016-12-01
Providing an analytical treatment to the stochastic feature of neurons' dynamics is one of the current biggest challenges in mathematical biology. The noisy leaky integrate-and-fire model and its associated Fokker-Planck equation are probably the most popular way to deal with neural variability. Another well-known formalism is the escape-rate model: a model giving the probability that a neuron fires at a certain time knowing the time elapsed since its last action potential. This model leads to a so-called age-structured system, a partial differential equation with non-local boundary condition famous in the field of population dynamics, where the age of a neuron is the amount of time passed by since its previous spike. In this theoretical paper, we investigate the mathematical connection between the two formalisms. We shall derive an integral transform of the solution to the age-structured model into the solution of the Fokker-Planck equation. This integral transform highlights the link between the two stochastic processes. As far as we know, an explicit mathematical correspondence between the two solutions has not been introduced until now.
Discovering Knowledge from Noisy Databases Using Genetic Programming.
ERIC Educational Resources Information Center
Wong, Man Leung; Leung, Kwong Sak; Cheng, Jack C. Y.
2000-01-01
Presents a framework that combines Genetic Programming and Inductive Logic Programming, two approaches in data mining, to induce knowledge from noisy databases. The framework is based on a formalism of logic grammars and is implemented as a data mining system called LOGENPRO (Logic Grammar-based Genetic Programming System). (Contains 34…
Detection and identification of substances using noisy THz signal
NASA Astrophysics Data System (ADS)
Trofimov, Vyacheslav A.; Zakharova, Irina G.; Zagursky, Dmitry Yu.; Varentsova, Svetlana A.
2017-05-01
We discuss an effective method for the detection and identification of substances using a high noisy THz signal. In order to model such a noisy signal, we add to the THz signal transmitted through a pure substance, a noisy THz signal obtained in real conditions at a long distance (more than 3.5 m) from the receiver in air. The insufficiency of the standard THz-TDS method is demonstrated. The method discussed in the paper is based on time-dependent integral correlation criteria calculated using spectral dynamics of medium response. A new type of the integral correlation criterion, which is less dependent on spectral characteristics of the noisy signal under investigation, is used for the substance identification. To demonstrate the possibilities of the integral correlation criteria in real experiment, they are applied for the identification of explosive HMX in the reflection mode. To explain the physical mechanism for the false absorption frequencies appearance in the signal we make a computer simulation using 1D Maxwell's equations and density matrix formalism. We propose also new method for the substance identification by using the THz pulse frequency up-conversion and discuss an application of the cascade mechanism of molecules high energy levels excitation for the substance identification.
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…
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 }
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 and stability in noisy population dynamics.
Araujo, Sabrina B L; de Aguiar, M A M
2008-02-01
We study the stability and synchronization of predator-prey populations subjected to noise. The system is described by patches of local populations coupled by migration and predation over a neighborhood. When a single patch is considered, random perturbations tend to destabilize the populations, leading to extinction. If the number of patches is small, stabilization in the presence of noise is maintained at the expense of synchronization. As the number of patches increases, both the stability and the synchrony among patches increase. However, a residual asynchrony, large compared with the noise amplitude, seems to persist even in the limit of an infinite number of patches. Therefore, the mechanism of stabilization by asynchrony recently proposed by Abta [Phys. Rev. Lett. 98, 098104 (2007)], combining noise, diffusion, and nonlinearities, seems to be more general than first proposed.
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
Desert ants achieve reliable recruitment across noisy interactions.
Razin, Nitzan; Eckmann, Jean-Pierre; Feinerman, Ofer
2013-05-06
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 our
Identification of determinism in noisy neuronal systems.
Slutzky, Marc W; Cvitanovic, Predrag; Mogul, David J
2002-08-30
Most neuronal ensembles are nonlinear excitable systems. Thus it is becoming common to apply principles derived from nonlinear dynamics to characterize neuronal systems. One important characterization is whether such systems contain deterministic behavior or are purely stochastic. Unfortunately, many methods used to make this distinction do not perform well when both determinism and high-amplitude noise are present which is often the case in physiological systems. Therefore, we propose two novel techniques for identifying determinism in experimental systems. The first, called short-time expansion analysis, examines the expansion rate of small groups of points in state space. The second, called state point forcing, derives from the technique of chaos control. The system state is forced onto a fixed point, and the subsequent behavior is analyzed. This technique can be used to verify the presence of fixed points (or unstable periodic orbits) and to assess stationarity. If these are present, it implies that the system contains determinism. We demonstrate the use and possible limitations of these two techniques in two systems: the Hénon map, a classic example of a chaotic system, and spontaneous epileptiform bursting in the rat hippocampal slice. Identifying the presence of determinism in a physiological system assists in the understanding of the system's dynamics and provides a mechanism for manipulating this behavior.
Quantum states tomography with noisy measurement channels
NASA Astrophysics Data System (ADS)
Bogdanov, Yu. I.; Bantysh, B. I.; Bogdanova, N. A.; Kvasnyy, A. B.; Lukichev, V. F.
2016-12-01
We consider realistic measurement systems, where measurements are accompanied by decoherence processes. The aim of this work is the construction of methods and algorithms for precise quantum measurements with fidelity close to the fundamental limit. In the present work the notions of ideal and non-ideal quantum measurements are strictly formalized. It is shown that non-ideal quantum measurements could be represented as a mixture of ideal measurements. Based on root approach the quantum state reconstruction method is developed. Informational accuracy theory of non-ideal quantum measurements is proposed. The monitoring of the amount of information about the quantum state parameters is examined, including the analysis of the information degradation under the noise influence. The study of achievable fidelity in non-ideal quantum measurements is performed. The results of simulation of fidelity characteristics of a wide class of quantum protocols based on polyhedrons geometry with high level of symmetry are presented. The impact of different decoherence mechanisms, including qubit amplitude and phase relaxation, bit-flip and phase-flip, is considered.
Quantum state transfer through noisy quantum cellular automata
NASA Astrophysics Data System (ADS)
Avalle, Michele; Genoni, Marco G.; Serafini, Alessio
2015-05-01
We model the transport of an unknown quantum state on one dimensional qubit lattices by means of a quantum cellular automata (QCA) evolution. We do this by first introducing a class of discrete noisy dynamics, in the first excitation sector, in which a wide group of classical stochastic dynamics is embedded within the more general formalism of quantum operations. We then extend the Hilbert space of the system to accommodate a global vacuum state, thus allowing for the transport of initial on-site coherences besides excitations, and determine the dynamical constraints that define the class of noisy QCA in this subspace. We then study the transport performance through numerical simulations, showing that for some instances of the dynamics perfect quantum state transfer is attainable. Our approach provides one with a natural description of both unitary and open quantum evolutions, where the homogeneity and locality of interactions allow one to take into account several forms of quantum noise in a plausible scenario.
Quantum error correction assisted by two-way noisy communication.
Wang, Zhuo; Yu, Sixia; Fan, Heng; Oh, C H
2014-11-26
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.
Noisy Oscillations in the Actin Cytoskeleton of Chemotactic Amoeba
NASA Astrophysics Data System (ADS)
Negrete, Jose; Pumir, Alain; Hsu, Hsin-Fang; Westendorf, Christian; Tarantola, Marco; Beta, Carsten; Bodenschatz, Eberhard
2016-09-01
Biological systems with their complex biochemical networks are known to be intrinsically noisy. Here we investigate the dynamics of actin polymerization of amoeboid cells, which are close to the onset of oscillations. We show that the large phenotypic variability in the polymerization dynamics can be accurately captured by a generic nonlinear oscillator model in the presence of noise. We determine the relative role of the noise with a single dimensionless, experimentally accessible parameter, thus providing a quantitative description of the variability in a population of cells. Our approach, which rests on a generic description of a system close to a Hopf bifurcation and includes the effect of noise, can characterize the dynamics of a large class of noisy systems close to an oscillatory instability.
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
Emergence of a negative resistance in noisy coupled linear oscillators
NASA Astrophysics Data System (ADS)
Quiroz-Juárez, M. A.; Aragón, J. L.; León-Montiel, R. de J.; Vázquez-Medina, R.; Domínguez-Juárez, J. L.; Quintero-Torres, R.
2016-12-01
We report on the experimental observation of an emerging negative resistance in a system of coupled linear electronic RLC harmonic oscillators under the influence of multiplicative noise with long correlation time. When two oscillators are coupled by a noisy inductor, an analysis in the Fourier space of the electrical variables unveils the presence of an effective negative resistance, which acts as an energy transport facilitator. This might constitute a simple explanation of the now fashionable problem of energy transport assisted by noise in classical systems. The experimental setup is based on the working principle of an analog computer and by itself constitutes a versatile platform for studying energy transport in noisy systems by means of coupled electrical oscillator systems.
Restoration of noisy blurred images by a smoothing spline filter.
Peyrovian, M J; Sawchuk, A A
1977-12-01
For the restoration of noisy blurred images, a controllable smoothing criterion based on the locally variable statistics and minimization of the second derivative is defined, and the corresponding filter, applicable to both space-variant and space-invariant degradations, is obtained. The output of this filter is a cubic spline function. The parameters of the filter determine the local smoothing window and over-all extent of smoothing, and thus the tradeoff between resolution and smoothing is controllable in a spatially nonstationary manner. The interesting properties of this filter have made it capable of restoring signal-dependent noisy images, and it has been successfully applied for filtering images degraded by film-grain noise. Since the matrices of this filter are banded circulant or Toeplitz, efficient algorithms are used for matrix manipulations.
Nonlinear dynamics approach to speech detection in noisy signals
NASA Astrophysics Data System (ADS)
Bronakowski, Lukasz J.
2009-06-01
The presented paper describes a novel approach to detection of speech corrupted by noise. The proposed procedure is based on fractal dimension, which is being evaluated directly from speech signal samples using two different methods: box-counting and the approach proposed by Katz. The recordings, taken from TIMIT database, were corrupted by five different types of noise (white, pink, hf-channel, babble and factory) with four noise amplitudes (5,10,15,20 dB). The resulting noisy speech was the subject of the analysis. The Otsu's method was used to determine a threshold value for differentiating between noise-only and noisy-speech segments. It has been shown that fractal dimension-based approach provides good basis for detecting speech under a presence of noise.
Excitation of coherent oscillations in a noisy medium
NASA Astrophysics Data System (ADS)
Köhler, Jan; Mayer, Jörg; Schuster, Heinz Georg
2008-02-01
We numerically study the influence of neuronal threshold modulation on the properties of cortical traveling waves. For that reason we simplify a Wilson-Cowan-type integrodifferential equation model of propagating neocortical activity to a spatially discrete version. Further we introduce a noisy threshold. Depending on the noise level we find different states of the network activity, ranging from asynchronous oscillations, traveling waves, to synchronous oscillations. Finally, we induce the transition between these different states by an external modulation.
Excitation of coherent oscillations in a noisy medium
Koehler, Jan; Mayer, Joerg; Schuster, Heinz Georg
2008-02-15
We numerically study the influence of neuronal threshold modulation on the properties of cortical traveling waves. For that reason we simplify a Wilson-Cowan-type integrodifferential equation model of propagating neocortical activity to a spatially discrete version. Further we introduce a noisy threshold. Depending on the noise level we find different states of the network activity, ranging from asynchronous oscillations, traveling waves, to synchronous oscillations. Finally, we induce the transition between these different states by an external modulation.
Noisy fluctuation of heart rate indicates cardiovascular system instability.
Fortrat, Jacques-Olivier; Baum, Charlotte; Jeanguillaume, Christian; Custaud, Marc-Antoine
2013-09-01
Heart rate spontaneously fluctuates despite homeostatic regulatory mechanisms to stabilize it. Harmonic and fractal fluctuations have been described. Non-harmonic non-fractal fluctuation has not been studied because it is usually thought that it is caused by apparatus noise. We hypothesized that this fluctuation looking like apparatus noise (that we call "noisy fluctuation") is linked to challenged blood pressure stabilization and not to apparatus noise. We assessed noisy fluctuation by quantifying the small and fastest beat-to-beat fluctuation of RR-interval by means of spectral analysis (Nyquist power of heart rate variability: nyHRV) after filtering out its fractal component. We observed nyHRV in healthy supine subjects and in patients with vasovagal symptoms. We challenged stabilization of blood pressure by upright posture (by means of a head-up tilt table test). Head-up position on the tilt table dramatically decreased nyHRV (0.128 ± 0.063 vs. 0.004 ± 0.002, p < 0.01) in healthy subjects (n = 12). Head-up position also decreased nyHRV in patients without vasovagal symptoms (n = 24; 0.220 ± 0.058 vs. 0.034 ± 0.015, p < 0.05), but not in patients with vasovagal symptoms during a head-up tilt table test (age and sex paired, 0.103 ± 0.041 vs. 0.122 ± 0.069, not significant). Heart rate variability includes a physiological non-harmonic non-fractal noisy fluctuation. This noisy fluctuation indicates low engagement of regulatory mechanisms because it disappears when the cardiovascular system is challenged (upright posture). It also indicates cardiovascular instability because it does not disappear in upright patients before vasovagal syncope, a transient failure of cardiovascular regulation.
Noisy covariance matrices and portfolio optimization II
NASA Astrophysics Data System (ADS)
Pafka, Szilárd; Kondor, Imre
2003-03-01
Recent studies inspired by results from random matrix theory (Galluccio et al.: Physica A 259 (1998) 449; Laloux et al.: Phys. Rev. Lett. 83 (1999) 1467; Risk 12 (3) (1999) 69; Plerou et al.: Phys. Rev. Lett. 83 (1999) 1471) found that covariance matrices determined from empirical financial time series appear to contain such a high amount of noise that their structure can essentially be regarded as random. This seems, however, to be in contradiction with the fundamental role played by covariance matrices in finance, which constitute the pillars of modern investment theory and have also gained industry-wide applications in risk management. Our paper is an attempt to resolve this embarrassing paradox. The key observation is that the effect of noise strongly depends on the ratio r= n/ T, where n is the size of the portfolio and T the length of the available time series. On the basis of numerical experiments and analytic results for some toy portfolio models we show that for relatively large values of r (e.g. 0.6) noise does, indeed, have the pronounced effect suggested by Galluccio et al. (1998), Laloux et al. (1999) and Plerou et al. (1999) and illustrated later by Laloux et al. (Int. J. Theor. Appl. Finance 3 (2000) 391), Plerou et al. (Phys. Rev. E, e-print cond-mat/0108023) and Rosenow et al. (Europhys. Lett., e-print cond-mat/0111537) in a portfolio optimization context, while for smaller r (around 0.2 or below), the error due to noise drops to acceptable levels. Since the length of available time series is for obvious reasons limited in any practical application, any bound imposed on the noise-induced error translates into a bound on the size of the portfolio. In a related set of experiments we find that the effect of noise depends also on whether the problem arises in asset allocation or in a risk measurement context: if covariance matrices are used simply for measuring the risk of portfolios with a fixed composition rather than as inputs to optimization, the
Sciancalepore, M; Coslovich, T; Lorenzon, P; Ziraldo, G; Taccola, G
2015-10-01
Electrical stimulation (ES) of skeletal muscle partially mimics the benefits of physical activity. However, the stimulation protocols applied clinically to date, often cause unpleasant symptoms and muscle fatigue. Here, we compared the efficiency of a "noisy" stimulus waveform derived from human electromyographic (EMG) muscle patterns, with stereotyped 45 and 1 Hz electrical stimulations applied to mouse myotubes in vitro. Human gastrocnemius medialis electromyograms recorded from volunteers during real locomotor activity were used as a template for a noisy stimulation, called EMGstim. The stimulus-induced electrical activity, intracellular Ca(2+) dynamics and mechanical twitches in the myotubes were assessed using whole-cell perforated patch-clamp, Ca(2+) imaging and optical visualization techniques. EMGstim was more efficient in inducing myotube cell firing, [Ca(2+)]i changes and contractions compared with more conventional electrical stimulation. Its stimulation strength was also much lower than the minimum required to induce contractions via stereotyped stimulation protocols. We conclude that muscle cells in vitro can be more efficiently depolarized using the "noisy" stochastic stimulation pattern, EMGstim, a finding that suggests a way to favor a higher level of electrical activity in a larger number of cells.
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.
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.
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
Predictors of noise annoyance in noisy and quiet urban streets.
Paunović, Katarina; Jakovljević, Branko; Belojević, Goran
2009-06-01
Although noise annoyance is a major public health problem in urban areas, there is a lack of published data on predictors for noise annoyance in acoustically different urban environments. The aim of the study was to assess the predictive value of various factors on noise annoyance in noisy and quiet urban streets. Equivalent noise levels [Leq (dBA)] were measured during day, evening and night times in all of the streets of a central Belgrade municipality. Based on 24-hour noise levels, the streets were denoted as noisy (24-hour Leq over 65 dBA), or quiet (24-hour Leq under 55 dBA). A cross-sectional study was performed on 1954 adult residents (768 men and 1186 women), aged 18-80 years. Noise annoyance was estimated using a self-report five-graded scale. In both areas, two multivariate logistic regression models were fitted: the first one with nighttime noise indicators and the other one with parameters for 24-hour noise exposure. In noisy streets, the relevant predictors of high annoyance were: the orientation of living room/bedroom toward the street, noise annoyance at workplace, and noise sensitivity. Significant acoustical factors for high noise annoyance were: nighttime noise level [OR=1.02, 95%CI=1.00-1.04 (per decibel)], nighttime heavy traffic [OR=1.01, 95%CI=1.00-1.02 (per vehicle)]; or day-evening-night noise level (Lden) [OR=1.03, 95%CI=1.00-1.07 (per decibel)]. In quiet streets, the significant predictors were: noise sensitivity, the time spent at home daily, light vehicles at nighttime or heavy vehicles at daytime. Our study identified subjective noise sensitivity as a common annoyance predictor, regardless of noise exposure. Noise levels were important indicators of annoyance only in noisy streets, both for nighttime and 24-hour exposure. We propose that noise sensitivity is the most relevant personal trait for future studies and that nighttime noise levels might be as good as Lden in predicting annoyance in noisy urban areas.
Quantum resource control for noisy Einstein-Podolsky-Rosen steering with qubit measurements
NASA Astrophysics Data System (ADS)
Kiukas, Jukka; Burgarth, Daniel
2016-03-01
We demonstrate how quantum optimal control can be used to enhance quantum resources for bipartite one-way protocols, specifically Einstein-Podolsky-Rosen steering with qubit measurements. Steering is relevant for one-sided device-independent key distribution, the realistic implementations of which necessitate the study of noisy scenarios. So far, mainly the case of imperfect detection efficiency has been considered; here we look at the effect of dynamical noise responsible for decoherence and dissipation. In order to set up the optimization, we map the steering problem into the equivalent joint measurability problem and employ quantum resource-theoretic robustness monotones from that context. The advantage is that incompatibility (hence steerability) with arbitrary pairs of noisy qubit measurements has been completely characterized through an analytical expression, which can be turned into a computable cost function with exact gradient. Furthermore, dynamical loss of incompatibility has recently been illustrated by using these monotones. We demonstrate resource control numerically by using a special gradient-based software showing, in particular, the advantage over naive control with cost function chosen as a fidelity in relation to a specific target. We subsequently illustrate the complexity of the control landscapes with a simplified two-variable scheme. The results contribute to the theoretical understanding of the limitations in realistic implementations of quantum information protocols, also paving the way to practical use of the rather abstract quantum resource theories.
Variability and coding efficiency of noisy neural spike encoders.
Steinmetz, P N; Manwani, A; Koch, C
2001-01-01
Encoding synaptic inputs as a train of action potentials is a fundamental function of nerve cells. Although spike trains recorded in vivo have been shown to be highly variable, it is unclear whether variability in spike timing represents faithful encoding of temporally varying synaptic inputs or noise inherent in the spike encoding mechanism. It has been reported that spike timing variability is more pronounced for constant, unvarying inputs than for inputs with rich temporal structure. This could have significant implications for the nature of neural coding, particularly if precise timing of spikes and temporal synchrony between neurons is used to represent information in the nervous system. To study the potential functional role of spike timing variability, we estimate the fraction of spike timing variability which conveys information about the input for two types of noisy spike encoders--an integrate and fire model with randomly chosen thresholds and a model of a patch of neuronal membrane containing stochastic Na(+) and K(+) channels obeying Hodgkin-Huxley kinetics. The quality of signal encoding is assessed by reconstructing the input stimuli from the output spike trains using optimal linear mean square estimation. A comparison of the estimation performance of noisy neuronal models of spike generation enables us to assess the impact of neuronal noise on the efficacy of neural coding. The results for both models suggest that spike timing variability reduces the ability of spike trains to encode rapid time-varying stimuli. Moreover, contrary to expectations based on earlier studies, we find that the noisy spike encoding models encode slowly varying stimuli more effectively than rapidly varying ones.
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.
NASA Astrophysics Data System (ADS)
La Cour, Brian R.; Ostrove, Corey I.
2017-01-01
This paper describes a novel approach to solving unstructured search problems using a classical, signal-based emulation of a quantum computer. The classical nature of the representation allows one to perform subspace projections in addition to the usual unitary gate operations. Although bandwidth requirements will limit the scale of problems that can be solved by this method, it can nevertheless provide a significant computational advantage for problems of limited size. In particular, we find that, for the same number of noisy oracle calls, the proposed subspace projection method provides a higher probability of success for finding a solution than does an single application of Grover's algorithm on the same device.
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.
Noisy Quantum Cellular Automata for Quantum versus Classical Excitation Transfer
NASA Astrophysics Data System (ADS)
Avalle, Michele; Serafini, Alessio
2014-05-01
We introduce a class of noisy quantum cellular automata on a qubit lattice that includes all classical Markov chains, as well as maps where quantum coherence between sites is allowed to build up over time. We apply such a construction to the problem of excitation transfer through 1D lattices, and compare the performance of classical and quantum dynamics with equal local transition probabilities. Our discrete approach has the merits of stripping down the complications of the open system dynamics, of clearly isolating coherent effects, and of allowing for an exact treatment of conditional dynamics, all while capturing a rich variety of dynamical behaviors.
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.
Particle model for optical noisy image recovery via stochastic resonance
NASA Astrophysics Data System (ADS)
Zhang, Yongbin; Liu, Hongjun; Huang, Nan; Wang, Zhaolu; Han, Jing
2017-10-01
We propose a particle model for investigating the optical noisy image recovery via stochastic resonance. The light propagating in nonlinear media is regarded as moving particles, which are used for analyzing the nonlinear coupling of signal and noise. Owing to nonlinearity, a signal seeds a potential to reinforce itself at the expense of noise. The applied electric field, noise intensity, and correlation length are important parameters that influence the recovery effects. The noise-hidden image with the signal-to-noise intensity ratio of 1:30 is successfully restored and an optimal cross-correlation gain of 6.1 is theoretically obtained.
Noisy quantum cellular automata for quantum versus classical excitation transfer.
Avalle, Michele; Serafini, Alessio
2014-05-02
We introduce a class of noisy quantum cellular automata on a qubit lattice that includes all classical Markov chains, as well as maps where quantum coherence between sites is allowed to build up over time. We apply such a construction to the problem of excitation transfer through 1D lattices, and compare the performance of classical and quantum dynamics with equal local transition probabilities. Our discrete approach has the merits of stripping down the complications of the open system dynamics, of clearly isolating coherent effects, and of allowing for an exact treatment of conditional dynamics, all while capturing a rich variety of dynamical behaviors.
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
Fast Object Recognition in Noisy Images Using Simulated Annealing.
1994-12-01
correlation coefficient is used as a measure of the match between a hypothesized object and an image. Templates are generated on-line during the search by transforming model images. Simulated annealing reduces the search time by orders of magnitude with respect to an exhaustive search. The algorithm is applied to the problem of how landmarks, for example, traffic signs, can be recognized by an autonomous vehicle or a navigating robot. The algorithm works well in noisy, real-world images of complicated scenes for model images with high information
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.
Rotation Matrix Method for Analyzing Noisy Nonlinear Data
NASA Astrophysics Data System (ADS)
Chu, P. C.; Ivanov, L. M.; Margolina, T. M.
2005-12-01
Analysis on noisy nonlinear data is to solve a set of algebraic equations. Three factors affect the accuracy of reconstruction: (a) large condition number of the coefficient matrix, (b) high noise-to-signal ratio in the source term, and (c) no a-priori knowledge of noise statistics. To improve the reconstruction accuracy, the set of linear algebraic equations is transformed into a new one with minimum condition number and noise-to-signal ratio using the rotation matrix. The procedure does not require any knowledge of low-order statistics of noises. Several examples including highly distorted Lorenz attractor, Black Sea circulations illustrate the benefit of using this procedure.
Teleportation in a noisy environment: a quantum trajectories approach.
Carlo, Gabriel G; Benenti, Giuliano; Casati, Giulio
2003-12-19
We study the fidelity of quantum teleportation for the situation in which quantum logic gates are used to provide the long distance entanglement required in the protocol, and where the effect of a noisy environment is modeled by means of a generalized amplitude damping channel. Our results demonstrate the effectiveness of the quantum trajectories approach, which allows the simulation of open systems with a large number of qubits (up to 24). This shows that the method is suitable for modeling quantum information protocols in realistic environments.
Experimental Extraction of Secure Correlations from a Noisy Private State
NASA Astrophysics Data System (ADS)
Dobek, K.; Karpiński, M.; Demkowicz-Dobrzański, R.; Banaszek, K.; Horodecki, P.
2011-01-01
We report experimental generation of a noisy entangled four-photon state that exhibits a separation between the secure key contents and distillable entanglement, a hallmark feature of the recently established quantum theory of private states. The privacy analysis, based on the full tomographic reconstruction of the prepared state, is utilized in a proof-of-principle key generation. The inferiority of distillation-based strategies to extract the key is exposed by an implementation of an entanglement distillation protocol for the produced state.
NASA Astrophysics Data System (ADS)
Nayak, Anantha S.; Sudha; Usha Devi, A. R.; Rajagopal, A. K.
2017-02-01
We employ the conditional version of sandwiched Tsallis relative entropy to determine 1:N-1 separability range in the noisy one-parameter families of pseudopure and Werner-like N-qubit W, GHZ states. The range of the noisy parameter, for which the conditional sandwiched Tsallis relative entropy is positive, reveals perfect agreement with the necessary and sufficient criteria for separability in the 1:N-1 partition of these one parameter noisy states.
Objectivity in a Noisy Photonic Environment through Quantum State Information Broadcasting
NASA Astrophysics Data System (ADS)
Korbicz, J. K.; Horodecki, P.; Horodecki, R.
2014-03-01
Recently, the emergence of classical objectivity as a property of a quantum state has been explicitly derived for a small object embedded in a photonic environment in terms of a spectrum broadcast form—a specific classically correlated state, redundantly encoding information about the preferred states of the object in the environment. However, the environment was in a pure state and the fundamental problem was how generic and robust is the conclusion. Here, we prove that despite the initial environmental noise, the emergence of the broadcast structure still holds, leading to the perceived objectivity of the state of the object. We also show how this leads to a quantum Darwinism-type condition, reflecting the classicality of proliferated information in terms of a limit behavior of the mutual information. Quite surprisingly, we find "singular points" of the decoherence, which can be used to faithfully broadcast a specific classical message through the noisy environment.
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.
Extreme fluctuations in noisy task-completion landscapes on scale-free networks.
Guclu, H; Korniss, G; Toroczkai, Z
2007-06-01
We study the statistics and scaling of extreme fluctuations in noisy task-completion landscapes, such as those emerging in synchronized distributed-computing networks, or generic causally constrained queuing networks, with scale-free topology. In these networks the average size of the fluctuations becomes finite (synchronized state) and the extreme fluctuations typically diverge only logarithmically in the large system-size limit ensuring synchronization in a practical sense. Provided that local fluctuations in the network are short tailed, the statistics of the extremes are governed by the Gumbel distribution. We present large-scale simulation results using the exact algorithmic rules, supported by mean-field arguments based on a coarse-grained description.
Objectivity in a noisy photonic environment through quantum state information broadcasting.
Korbicz, J K; Horodecki, P; Horodecki, R
2014-03-28
Recently, the emergence of classical objectivity as a property of a quantum state has been explicitly derived for a small object embedded in a photonic environment in terms of a spectrum broadcast form-a specific classically correlated state, redundantly encoding information about the preferred states of the object in the environment. However, the environment was in a pure state and the fundamental problem was how generic and robust is the conclusion. Here, we prove that despite the initial environmental noise, the emergence of the broadcast structure still holds, leading to the perceived objectivity of the state of the object. We also show how this leads to a quantum Darwinism-type condition, reflecting the classicality of proliferated information in terms of a limit behavior of the mutual information. Quite surprisingly, we find "singular points" of the decoherence, which can be used to faithfully broadcast a specific classical message through the noisy environment.
NASA Astrophysics Data System (ADS)
Aguirre, Luis Antonio; Billings, S. A.
This paper investigates the identification of global models from chaotic data corrupted by additive noise. It is verified that noise has a strong influence on the identification of chaotic systems. In particular, there seems to be a critical noise level beyond which the accurate estimation of polynomial models from chaotic data becomes very difficult. Similarities with the estimation of the largest Lyapunov exponent from noisy data suggest that part of the problem might be related to the limited ability of predicting the data records when these are chaotic. A nonlinear filtering scheme is suggested in order to reduce the noise in the data and thereby enable the estimation of good models. This prediction-based filtering incorporates a resetting mechanism which enables the filtering of chaotic data and which is also applicable to non-chaotic data.
NASA Astrophysics Data System (ADS)
Gurov, Igor P.; Volkov, Mikhail V.
2002-04-01
Image enhancement and evaluation play an important role in modern information and measurement technologies. An important image kind is obtained in coherent systems in holography and interferometry in the form of fringe patterns. Because of the physical and technical limitations fringe patterns are often distorted under the noise influence. It is proposed new noise-immune method for fringe pattern enhancement and evaluation. Unlike conventional filtering methods, in this method a filter impulse response is formed by the local empirical histogram modification with the spatial weighting function inside a dimensionally-varied area dependent on the local fringe intensity distribution. High efficiency of the method was verified experimentally when processing real noisy distorted fringe patterns.
NASA Astrophysics Data System (ADS)
Sajeeb, R.; Manohar, C. S.; Roy, D.
2007-09-01
The problem of active control of nonlinear structural dynamical systems, in the presence of both process and measurement noises, is considered. The focus of the study is on the use of particle filters for state estimation in feedback control algorithms for nonlinear structures, when a limited number of noisy output measurements are available. The control design is done using the state-dependent Riccati equation (SDRE) method. The stochastic differential equations (SDEs) governing the dynamical systems are discretized using explicit forms of Ito-Taylor expansions. The Bayesian bootstrap filter and that based on sequential important sampling (SIS) are employed for state estimation. The simulation results show the feasibility of using particle filters and SDRE techniques in control of nonlinear structural dynamical systems.
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.
The dynamic mechanism of noisy signal decoding in gene regulation
Liu, Peijiang; Wang, Haohua; Huang, Lifang; Zhou, Tianshou
2017-01-01
Experimental evidence supports that signaling pathways can induce different dynamics of transcription factor (TF) activation, but how an input signal is encoded by such a dynamic, noisy TF and further decoded by downstream genes remains largely unclear. Here, using a system of stochastic transcription with signal regulation, we show that (1) keeping the intensity of the signal noise invariant but prolonging the signal duration can both enhance the mutual information (MI) and reduce the energetic cost (EC); (2) if the signal duration is fixed, the larger MI needs the larger EC, but if the signal period is fixed, there is an optimal time that the signal spends at one lower branch, such that MI reaches the maximum; (3) if both the period and the duration are simultaneously fixed, increasing the input noise can always enhance MI in the case of transcription regulation rather than in the case of degradation regulation. In addition, we find that the input noise can induce stochastic focusing in a regulation-dependent manner. These results reveal not only the dynamic mechanism of noisy signal decoding in gene regulation but also the essential role of external noise in controlling gene expression levels. PMID:28176840
Nonlinear spectral correlation for fatigue crack detection under noisy environments
NASA Astrophysics Data System (ADS)
Liu, Peipei; Sohn, Hoon; Jeon, Ikgeun
2017-07-01
When ultrasonic waves at two distinct frequencies are applied to a structure with a fatigue crack, crack-induced nonlinearity creates nonlinear ultrasonic modulations at the sum and difference of the two input frequencies. The amplitude of the nonlinear modulation components is typically one or two orders of magnitude smaller than that of the primary linear components. Therefore, the modulation components can be easily buried under noise levels and it becomes difficult to extract the nonlinear modulation components under noisy environments using a conventional spectral density function. In this study, nonlinear spectral correlation, which calculates the spectral correlation between nonlinear modulation components, is proposed to isolate the nonlinear modulation components from noisy environments and used for fatigue crack detection. The proposed nonlinear spectral correlation offers the following benefits: (1) Stationary noises have little effect on nonlinear spectral correlation; (2) By using a wideband high-frequency input and a single low-frequency input, the contrast of nonlinear spectral correlation between damage and intact conditions can be enhanced; and (3) The test efficiency can be also improved via reducing the data collection time. Validation tests are performed on aluminum plates and scaled steel shafts with real fatigue cracks. The experimental results demonstrate that the proposed nonlinear spectral correlation owns a higher sensitivity to fatigue crack than the classical nonlinear coefficient estimated from the spectral density function, and the usage of nonlinear spectral correlation allows the detection of fatigue crack even using noncontact air-coupled transducers with a low signal-to-noise ratio.
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.
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.
Extensions to minimum relative entropy inversion for noisy data.
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 epsilon, 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.
Graph ensemble boosting for imbalanced noisy graph stream classification.
Pan, Shirui; Wu, Jia; Zhu, Xingquan; Zhang, Chengqi
2015-05-01
Many applications involve stream data with structural dependency, graph representations, and continuously increasing volumes. For these applications, it is very common that their class distributions are imbalanced with minority (or positive) samples being only a small portion of the population, which imposes significant challenges for learning models to accurately identify minority samples. This problem is further complicated with the presence of noise, because they are similar to minority samples and any treatment for the class imbalance may falsely focus on the noise and result in deterioration of accuracy. In this paper, we propose a classification model to tackle imbalanced graph streams with noise. Our method, graph ensemble boosting, employs an ensemble-based framework to partition graph stream into chunks each containing a number of noisy graphs with imbalanced class distributions. For each individual chunk, we propose a boosting algorithm to combine discriminative subgraph pattern selection and model learning as a unified framework for graph classification. To tackle concept drifting in graph streams, an instance level weighting mechanism is used to dynamically adjust the instance weight, through which the boosting framework can emphasize on difficult graph samples. The classifiers built from different graph chunks form an ensemble for graph stream classification. Experiments on real-life imbalanced graph streams demonstrate clear benefits of our boosting design for handling imbalanced noisy graph stream.
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
The dynamic mechanism of noisy signal decoding in gene regulation.
Liu, Peijiang; Wang, Haohua; Huang, Lifang; Zhou, Tianshou
2017-02-08
Experimental evidence supports that signaling pathways can induce different dynamics of transcription factor (TF) activation, but how an input signal is encoded by such a dynamic, noisy TF and further decoded by downstream genes remains largely unclear. Here, using a system of stochastic transcription with signal regulation, we show that (1) keeping the intensity of the signal noise invariant but prolonging the signal duration can both enhance the mutual information (MI) and reduce the energetic cost (EC); (2) if the signal duration is fixed, the larger MI needs the larger EC, but if the signal period is fixed, there is an optimal time that the signal spends at one lower branch, such that MI reaches the maximum; (3) if both the period and the duration are simultaneously fixed, increasing the input noise can always enhance MI in the case of transcription regulation rather than in the case of degradation regulation. In addition, we find that the input noise can induce stochastic focusing in a regulation-dependent manner. These results reveal not only the dynamic mechanism of noisy signal decoding in gene regulation but also the essential role of external noise in controlling gene expression levels.
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.
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
Blur kernel estimate in single noisy image deblurring
NASA Astrophysics Data System (ADS)
Sun, Shijie; Zhao, Huaici; Li, Bo
2014-11-01
Restoring blurred images is challenging because both the blur kernel and the sharp image are unknown, which makes this problem severely under constrained. Recently many single image blind deconvolution methods have been proposed, but these state-of-the-art single image deblurring techniques are still sensitive to image noise, and can degrade their performance rapidly especially when the noise level of the input blurred images increases. In this work, we estimate the blur kernel accurately by applying a series of directional low-pass filters in different orientations to the input blurred image, and effectively constructing the Radon transform of the blur kernel from each filtered image. Finally, we use a robust non-blind deconvolution method with outlier handling, which can effectively reduce ringing artifacts, to generate the final results. Our experimental results on both synthetic and real-world examples show that our method achieves comparable quality to existing approaches on blurry noisy-free images, and higher quality outputs than previous approaches on blurry and noisy images.
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.
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.
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.
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.
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.
Modulated noisy light propagated on dispersive fiber in optical links
NASA Astrophysics Data System (ADS)
Salehi, M. R.; Dehghani, M. J.
2008-12-01
The intensity spectrum of modulated noisy light on optical microwave signal processing and on conversion of FM noise to intensity noise in optical links is investigated theoretically and experimentally with a good agreement. We have applied a model that uses a 1550 nm distributed feedback (DFB) laser and an unbalanced Mach-Zehnder interferometer (UMZI) considering the external phase modulator. Numerical calculations show the influence of the phase modulation index, modulation frequency, and interferometric delay in the phase-to-intensity noise conversion by lowest-order group-velocity dispersion in optical fiber. The results can be employed to estimate the influence of the chromatic dispersion in phase-to-intensity noise conversion, which use either self-delayed interferences or interferometers.
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.
Inferring the spatiotemporal DNA replication program from noisy data.
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.
Stimulus sensitivity and neuromodulatory properties of noisy intrinsic neuronal oscillators.
Huber, M T; Krieg, J C; Dewald, M; Voigt, K; Braun, H A
1998-01-01
Intrinsic subthreshold oscillations in the membrane potential are a common property of many neurons in the peripheral and central nervous system. When such oscillations are combined with noise, interesting signal encoding and neuromodulatory properties are obtained which allow, for example, sensitivity adjustment or differential encoding of stimuli. Here we demonstrate that a noisy Hodgkin/Huxley-model for subthreshold oscillations, when tuned to maximum sensitivity, can be significantly modulated by even minor physiological changes in the oscillation parameters amplitude or frequency. Given the ubiquity of subthreshold oscillating neurons, it can be assumed that these findings reflect principle encoding properties which are relevant for an understanding of sensitivity and neuromodulation in peripheral and central neurons.
The annoyance of multiple noisy events. [ratings for simulated flyovers
NASA Technical Reports Server (NTRS)
Ahumada, A., Jr.; Nagel, D. C.
1979-01-01
A total of 24 subjects (17 M, 7 F) was tested in an experimental study of annoyance rating of multiple noisy events (30 sets of noise bursts). The scaling technique known as functional measurement was used to determine whether annoyance integrates additively over events and if so, to measure the power law exponent which relates the levels of the events to the additive scale values. To this end, groups of three noises were presented at three levels in a factorial arrangement to check the additivity hypothesis and to estimate the scaling function. Also, a series of sets of noises of constant level but varying in set size were considered. The functional measurement of annoyance ratings of sets of three simulated flyovers showed that the integration of annoyance can be represented as an additive process in terms of scale values that are power functions of the sound power with a power-law exponent near 0.7.
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.
Noisy random Boolean formulae: a statistical physics perspective.
Mozeika, Alexander; Saad, David; Raymond, Jack
2010-10-01
Properties of computing Boolean circuits composed of noisy logical gates are studied using the statistical physics methodology. A formula-growth model that gives rise to random Boolean functions is mapped onto a spin system, which facilitates the study of their typical behavior in the presence of noise. Bounds on their performance, derived in the information theory literature for specific gates, are straightforwardly retrieved, generalized and identified as the corresponding macroscopic phase transitions. The framework is employed for deriving results on error-rates at various function-depths and function sensitivity, and their dependence on the gate-type and noise model used. These are difficult to obtain via the traditional methods used in this field.
Traveling phase waves in asymmetric networks of noisy chaotic attractors
NASA Astrophysics Data System (ADS)
Peron, Thomas K. DM.; Kurths, Jürgen; Rodrigues, Francisco A.; Schimansky-Geier, Lutz; Sonnenschein, Bernard
2016-10-01
We explore identical Rössler systems organized into two equally sized groups, among which differing positive and negative in- and out-coupling strengths are allowed. With this asymmetric coupling, we analyze patterns in the phase dynamics that coexist with chaotic amplitudes. We specifically investigate traveling phase waves where the oscillators settle on a new rhythm different from their own. We show that these waves are possible even without coherence in the phase angles. It is further demonstrated that the emergence of these incoherent traveling waves depends on the type of coupling, not on the individual dynamics of the Rössler systems. Together with the study of noise effects, our results suggest a promising new avenue toward the interplay of chaotic, noisy, coherent, and incoherent collective dynamics.
Noisy quantum walks of two indistinguishable interacting particles
NASA Astrophysics Data System (ADS)
Siloi, Ilaria; Benedetti, Claudia; Piccinini, Enrico; Piilo, Jyrki; Maniscalco, Sabrina; Paris, Matteo G. A.; Bordone, Paolo
2017-02-01
We investigate the dynamics of continuous-time two-particle quantum walks on a one-dimensional noisy lattice. Depending on the initial condition, we show how the interplay between particle indistinguishability and interaction determines distinct propagation regimes. A realistic model for the environment is considered by introducing non-Gaussian noise as time-dependent fluctuations of the tunneling amplitudes between adjacent sites. We observe that the combined effect of particle interaction and fast noise (weak coupling with the environment) provides a faster propagation compared to the noiseless case. This effect can be understood in terms of the band structure of the Hubbard model, and a detailed analysis as a function of both noise and system parameters is presented.
Genetic Redundancies Enhance Information Transfer in Noisy Regulatory Circuits
Rodrigo, Guillermo; Poyatos, Juan F.
2016-01-01
Cellular decision making is based on regulatory circuits that associate signal thresholds to specific physiological actions. This transmission of information is subjected to molecular noise what can decrease its fidelity. Here, we show instead how such intrinsic noise enhances information transfer in the presence of multiple circuit copies. The result is due to the contribution of noise to the generation of autonomous responses by each copy, which are altogether associated with a common decision. Moreover, factors that correlate the responses of the redundant units (extrinsic noise or regulatory cross-talk) contribute to reduce fidelity, while those that further uncouple them (heterogeneity within the copies) can lead to stronger information gain. Overall, our study emphasizes how the interplay of signal thresholding, redundancy, and noise influences the accuracy of cellular decision making. Understanding this interplay provides a basis to explain collective cell signaling mechanisms, and to engineer robust decisions with noisy genetic circuits. PMID:27741249
Real time speech enhancement for the noisy MRI environment.
Pathak, Nishank; Panahi, Issa; Devineni, P; Briggs, Richard
2009-01-01
Performance of two Adaptive (nLMS and Normalized Sign-error LMS) and a single channel (LogMMSE) speech enhancement algorithms are tested on a floating point DSP to reveal their effectiveness in enhancing speech corrupted in noisy MRI environment with very low SNR. The purpose of experiments is to reduce the fatigue of the listener by eliminating the strong MRI noise. The experiments use actual data set collected from a 3-Tesla MRI machine. Results of the experiments and performance of the speech enhancement system are presented in this paper. The speech enhancement system is automated. Our experiments reveal that after enhancement of the speech signal using Sign-Error LMS, the residual noise shows characteristics of white noise in contrast to the residual noise of the other algorithms which is more structured. It is also shown that the Sign-Error LMS offers fast convergence in comparison to the other two methods.
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.
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).
Traveling phase waves in asymmetric networks of noisy chaotic attractors.
Peron, Thomas K Dm; Kurths, Jürgen; Rodrigues, Francisco A; Schimansky-Geier, Lutz; Sonnenschein, Bernard
2016-10-01
We explore identical Rössler systems organized into two equally sized groups, among which differing positive and negative in- and out-coupling strengths are allowed. With this asymmetric coupling, we analyze patterns in the phase dynamics that coexist with chaotic amplitudes. We specifically investigate traveling phase waves where the oscillators settle on a new rhythm different from their own. We show that these waves are possible even without coherence in the phase angles. It is further demonstrated that the emergence of these incoherent traveling waves depends on the type of coupling, not on the individual dynamics of the Rössler systems. Together with the study of noise effects, our results suggest a promising new avenue toward the interplay of chaotic, noisy, coherent, and incoherent collective dynamics.
Statistical Mechanics of Node-perturbation Learning with Noisy Baseline
NASA Astrophysics Data System (ADS)
Hara, Kazuyuki; Katahira, Kentaro; Okada, Masato
2017-02-01
Node-perturbation learning is a type of statistical gradient descent algorithm that can be applied to problems where the objective function is not explicitly formulated, including reinforcement learning. It estimates the gradient of an objective function by using the change in the object function in response to the perturbation. The value of the objective function for an unperturbed output is called a baseline. Cho et al. proposed node-perturbation learning with a noisy baseline. In this paper, we report on building the statistical mechanics of Cho's model and on deriving coupled differential equations of order parameters that depict learning dynamics. We also show how to derive the generalization error by solving the differential equations of order parameters. On the basis of the results, we show that Cho's results are also apply in general cases and show some general performances of Cho's model.
Trust based Fusion over Noisy Channels through Anomaly Detection in Cognitive Radio Networks
2011-11-01
Trust based Fusion over Noisy Channels through Anomaly Detection in Cognitive Radio Networks∗ Shameek Bhattacharjee Department of EECS University of...of Systems]: Fault Tolerance General Terms Algorithms, Performance, Security, Theory Keywords Cognitive radio networks, attacks, anomaly detection , trust...TYPE N/A 3. DATES COVERED - 4. TITLE AND SUBTITLE Trust based Fusion over Noisy Channels through Anomaly Detection in Cognitive Radio
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.
Multimode entanglement and telecloning in a noisy environment
Ferraro, Alessandro; Paris, Matteo G.A.
2005-09-15
We address the generation, propagation, and application of multipartite continuous variable entanglement in a noisy environment. In particular, we focus our attention on the multimode entangled states achievable by second-order nonlinear crystals--i.e., coherent states of the SU(m,1) group--which provide a generalization of the twin-beam state of a bipartite system. The full inseparability in the ideal case is shown, whereas thresholds for separability are given for the tripartite case in the presence of noise. We find that entanglement of tripartite states is robust against thermal noise, both in the generation process and during propagation. We then consider coherent states of SU(m,1) as a resource for multipartite distribution of quantum information and analyze a specific protocol for telecloning, proving its optimality in the case of symmetric cloning of pure Gaussian states. We show that the proposed protocol also provides the first example of a completely asymmetric 1{yields}m telecloning and derive explicitly the optimal relation among the different fidelities of the m clones. The effect of noise in the various stages of the protocol is taken into account, and the fidelities of the clones are analytically obtained as a function of the noise parameters. In turn, this permits the optimization of the telecloning protocol, including its adaptive modifications to the noisy environment. In the optimized scheme the clones' fidelity remains maximal even in the presence of losses (in the absence of thermal noise), for propagation times that diverge as the number of modes increases. In the optimization procedure the prominent role played by the location of the entanglement source is analyzed in details. Our results indicate that, when only losses are present, telecloning is a more effective way to distribute quantum information than direct transmission followed by local cloning.
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.
Synchronization of coupled noisy oscillators: Coarse graining from continuous to discrete phases
NASA Astrophysics Data System (ADS)
Escaff, Daniel; Rosas, Alexandre; Toral, Raúl; Lindenberg, Katja
2016-11-01
The theoretical description of synchronization phenomena often relies on coupled units of continuous time noisy Markov chains with a small number of states in each unit. It is frequently assumed, either explicitly or implicitly, that coupled discrete-state noisy Markov units can be used to model mathematically more complex coupled noisy continuous phase oscillators. In this work we explore conditions that justify this assumption by coarse graining continuous phase units. In particular, we determine the minimum number of states necessary to justify this correspondence for Kuramoto-like oscillators.
Synchronization of coupled noisy oscillators: Coarse graining from continuous to discrete phases.
Escaff, Daniel; Rosas, Alexandre; Toral, Raúl; Lindenberg, Katja
2016-11-01
The theoretical description of synchronization phenomena often relies on coupled units of continuous time noisy Markov chains with a small number of states in each unit. It is frequently assumed, either explicitly or implicitly, that coupled discrete-state noisy Markov units can be used to model mathematically more complex coupled noisy continuous phase oscillators. In this work we explore conditions that justify this assumption by coarse graining continuous phase units. In particular, we determine the minimum number of states necessary to justify this correspondence for Kuramoto-like oscillators.
Secret sharing of a known arbitrary quantum state with noisy environment
NASA Astrophysics Data System (ADS)
Wang, Ming-Ming; Wang, Wei; Chen, Jin-Guang; Farouk, Ahmed
2015-11-01
We study quantum state sharing (QSTS) with noisy environment in this paper. As an example, we present a QSTS scheme of a known state whose information is hold by the dealer and then investigate the noisy influence process of the scheme. Taking the amplitude-damping noise and the phase-damping noise as typical noisy channels, we show that the secret state can be shared among agents with some information lost. Our research connects the areas of quantum state sharing and remote state preparation.
1984-04-01
CIR (3.2) *. where B(v) is a finite or infinite product of Blaschke factors, i.e. V-v* B(v) = TI B (v) where B lV ) = ( 3.3) i=l k Zk v~vk Furthermore...language, it is: f-t Given the sets {Ti1 with associated projections Pi =P1 i=l 1 T.iM4 1 find G such that GE n T.i=l I_ Gubin, Polyak and Raik 137] have...36. J.R. Fienup, "Phase retrieval algorithms: a comparison." Appl. Opt., 21, 2758-2769 (1982). 37. L. Gubin, B. Polyak , and E. Raik, "The method of
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.
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.
Retrieval of noisy fingerprint patterns using metric attractor networks.
González, Mario; Dominguez, David; Rodríguez, Francisco B; Sánchez, Ángel
2014-11-01
This work experimentally analyzes the learning and retrieval capabilities of the diluted metric attractor neural network when applied to collections of fingerprint images. The computational cost of the network decreases with the dilution, so we can increase the region of interest to cover almost the complete fingerprint. The network retrieval was successfully tested for different noisy configurations of the fingerprints, and proved to be robust with a large basin of attraction. We showed that network topologies with a 2D-Grid arrangement adapt better to the fingerprints spatial structure, outperforming the typical 1D-Ring configuration. An optimal ratio of local connections to random shortcuts that better represent the intrinsic spatial structure of the fingerprints was found, and its influence on the retrieval quality was characterized in a phase diagram. Since the present model is a set of nonlinear equations, it is possible to go beyond the naïve static solution (consisting in matching two fingerprints using a fixed distance threshold value), and a crossing evolution of similarities was shown, leading to the retrieval of the right fingerprint from an apparently more distant candidate. This feature could be very useful for fingerprint verification to discriminate between fingerprints pairs.
Stochastic perturbations in open chaotic systems: random versus noisy maps.
Bódai, Tamás; Altmann, Eduardo G; Endler, Antonio
2013-04-01
We investigate the effects of random perturbations on fully chaotic open systems. Perturbations can be applied to each trajectory independently (white noise) or simultaneously to all trajectories (random map). We compare these two scenarios by generalizing the theory of open chaotic systems and introducing a time-dependent conditionally-map-invariant measure. For the same perturbation strength we show that the escape rate of the random map is always larger than that of the noisy map. In random maps we show that the escape rate κ and dimensions D of the relevant fractal sets often depend nonmonotonically on the intensity of the random perturbation. We discuss the accuracy (bias) and precision (variance) of finite-size estimators of κ and D, and show that the improvement of the precision of the estimations with the number of trajectories N is extremely slow ([proportionality]1/lnN). We also argue that the finite-size D estimators are typically biased. General theoretical results are combined with analytical calculations and numerical simulations in area-preserving baker maps.
Hybrid system architecture for reasoning in noisy domains
NASA Astrophysics Data System (ADS)
Melvin, David G.; Spracklen, C. T.
1992-09-01
Neural network techniques and those used in conventional artificial intelligence systems show promise for solving complex real world problems. The strengths and weaknesses of the separate techniques are well known, for example the former is capable of reasoning on noisy or incomplete data but has poor facilities for eliciting input/output correlations. On the other hand, the latter has poor domain knowledge elicitation but is much better at explaining the correlation between its input data and its output response. In certain valuable aspects the two techniques are complementary and this paper reports on the characteristics exhibited by a hybrid system formed from a set of neural networks and a classical expert system. The paper describes how a hybrid system based upon a number of artificial neural network subsystems (ANNS), each implementing a knowledge source, is attached to a rule based system. By fusing these neural networks into the knowledge based system in a transparent way a new architecture is formed which performs markedly better than a conventional rule based system while retaining the explanation facilities of the rule based approach. The paper discusses in detail a prototype system which operates in the domain of optical character recognition. The paper highlights the advantages and disadvantages of such a technique in terms of concepts that are applicable to many other real world problem domains.
Convexity, Jensen's inequality and benefits of noisy mechanical ventilation.
Brewster, John F; Graham, M Ruth; Mutch, W Alan C
2005-09-22
Mechanical ventilators breathe for you when you cannot or when your lungs are too sick to do their job. Most ventilators monotonously deliver the same-sized breaths, like clockwork; however, healthy people do not breathe this way. This has led to the development of a biologically variable ventilator--one that incorporates noise. There are indications that such a noisy ventilator may be beneficial for patients with very sick lungs. In this paper we use a probabilistic argument, based on Jensen's inequality, to identify the circumstances in which the addition of noise may be beneficial and, equally important, the circumstances in which it may not be beneficial. Using the local convexity of the relationship between airway pressure and tidal volume in the lung, we show that the addition of noise at low volume or low pressure results in higher mean volume (at the same mean pressure) or lower mean pressure (at the same mean volume). The consequence is enhanced gas exchange or less stress on the lungs, both clinically desirable. The argument has implications for other life support devices, such as cardiopulmonary bypass pumps. This paper illustrates the benefits of research that takes place at the interface between mathematics and medicine.
The noisy Hegselmann-Krause model for opinion dynamics
NASA Astrophysics Data System (ADS)
Pineda, Miguel; Toral, Raúl; Hernández-García, Emilio
2013-12-01
In the model for continuous opinion dynamics introduced by Hegselmann and Krause, each individual moves to the average opinion of all individuals within an area of confidence. In this work we study the effects of noise in this system. With certain probability, individuals are given the opportunity to change spontaneously their opinion to another one selected randomly inside the opinion space with different rules. If the random jump does not occur, individuals interact through the Hegselmann-Krause's rule. We analyze two cases, one where individuals can carry out opinion random jumps inside the whole opinion space, and other where they are allowed to perform jumps just inside a small interval centered around the current opinion. We found that these opinion random jumps change the model behavior inducing interesting phenomena. Using pattern formation techniques, we obtain approximate analytical results for critical conditions of opinion cluster formation. Finally, we compare the results of this work with the noisy version of the Deffuant et al. model [G. Deffuant, D. Neu, F. Amblard, G. Weisbuch, Adv. Compl. Syst. 3, 87 (2000)] for continuous-opinion dynamics.
Ergodicity breaking and particle spreading in noisy heterogeneous diffusion processes
NASA Astrophysics Data System (ADS)
Cherstvy, Andrey G.; Metzler, Ralf
2015-04-01
We study noisy heterogeneous diffusion processes with a position dependent diffusivity of the form D(x) ˜ D0|x|α0 in the presence of annealed and quenched disorder of the environment, corresponding to an effective variation of the exponent α in time and space. In the case of annealed disorder, for which effectively α0 = α0(t), we show how the long time scaling of the ensemble mean squared displacement (MSD) and the amplitude variation of individual realizations of the time averaged MSD are affected by the disorder strength. For the case of quenched disorder, the long time behavior becomes effectively Brownian after a number of jumps between the domains of a stratified medium. In the latter situation, the averages are taken over both an ensemble of particles and different realizations of the disorder. As physical observables, we analyze in detail the ensemble and time averaged MSDs, the ergodicity breaking parameter, and higher order moments of the time averages.
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.
Friction-induced Resonance in a Noisy Fractional Oscillator
NASA Astrophysics Data System (ADS)
Laas, K.; Mankin, R.
2010-11-01
The influence of the friction coefficient on the long-time behavior of the spectral amplification, variance, and signal-to-noise ratio (SNR) found for the output signal of a fractional oscillator with fluctuating eigenfrequency subjected to a periodic force is considered. The influence of the fluctuating environment is modeled by a multiplicative white noise and by an additive noise with a zero mean. The viscoelastic friction kernel with memory is assumed as a power-law function of time. The study is a follow-up of a previous investigation of a noisy fractional oscillator [Phys. Rev. E 81, 041122 (2010)]. On the basis of exact formulas it is demonstrated that an interplay of multiplicative noise and memory can generate a multiresonance of SNR versus the friction coefficient. The necessary and sufficient conditions for such a resonance effect are also discussed. Particularly, it is shown that resonance-like behavior of SNR versus the friction coefficient is qualitatively different in the cases of external and internal additive noises.
Spectra of delay-coupled heterogeneous noisy nonlinear oscillators
NASA Astrophysics Data System (ADS)
Vüllings, Andrea; Schöll, Eckehard; Lindner, Benjamin
2014-02-01
Nonlinear oscillators that are subject to noise and delayed interaction have been used to describe a number of dynamical phenomena in Physics and beyond. Here we study the spectral statistics (power and cross-spectral densities) of a small number of noisy nonlinear oscillators and derive analytical approximations for these spectra. In our paper, individual oscillators are described by the normal form of a supercritical or subcritical Hopf bifurcation supplemented by Gaussian white noise. Oscillators can be distinguished from each other by their frequency, bifurcation parameter, and noise intensity. Extending previous results from the literature, we first calculate in linear response theory the power spectral density and response function of the single oscillator in both super- and subcritical parameter regime and test them against numerical simulations. For small heterogeneous groups of oscillators (N = 2 or 3), which are coupled by a delayed linear term, we use a linear response ansatz to derive approximations for the power and cross-spectral densities of the oscillators within this small network. These approximations are confirmed by comparison with extensive numerical simulations. Using the theory we relate the peaks in the spectra of the homogeneous system (identical oscillators) to periodic solutions of the deterministic (noiseless) system. For two delay-coupled subcritical Hopf oscillators, we show that the coupling can enhance the coherence resonance effect, which is known to occur for the single subcritical oscillator. In the case of heterogeneous oscillators, we find that the delay-induced characteristic profile of the spectra is conserved for moderate frequency detuning.
Blurred and noisy image pairs in parallel optics.
Klapp, Iftach; Sochen, Nir; Mendlovic, David
2014-11-01
In previous works we have shown that parallel optics (PO) architecture can be used to improve the system matrix condition, which results in improving its immunity to additive noise in the image restoration process. PO is composed of a "main" system and an "auxiliary" system. Previously, we suggested the "trajectories" method to realize PO. In that method, a required auxiliary system is composed from auxiliary optics with a pixel confined response, followed by signal processing. In this paper, we emphasize the important secondary effects of the trajectories method. We show that in such a system, where the postprocessing comes after the detection, the postprocessing acts as a noise filter, hence allowing us to work with noisy data in the auxiliary channel. Roughly speaking, the SNR of an imaging system depends on the numerical aperture (NA). It follows that the main system, which typically has a higher NA, also has a higher SNR. Hence in the PO system, the ratio between the NA values of the main and auxiliary systems is expected to dictate the gap between their SNR values. In this paper, we show that when the system is implemented by the trajectories method, this expectation is too conservative. It is shown that due to the noise filtering, the auxiliary system can be noisier than expected. This claim is proved analytically and verified and exemplified by using experimental measurements.
Optimal block cosine transform image coding for noisy channels
NASA Technical Reports Server (NTRS)
Vaishampayan, Vinay A.; Farvardin, Nariman
1990-01-01
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 optimiaation of a scheme based on the 2-D block cosine transorm 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 noise channels were obtained and appropriate comparisons against a reference system designed for no channel error were rendered.
Genetic programming model for forecast of short and noisy data
NASA Astrophysics Data System (ADS)
Sivapragasam, C.; Vincent, P.; Vasudevan, G.
2007-01-01
Though forecasting of river flow has received a great deal of attention from engineers and researchers throughout the world, this still continues to be a challenging task owing to the complexity of the process. In the last decade or so, artificial neural networks (ANNs) have been widely applied, and their ability to model complex phenomena has been clearly demonstrated. However, the success of ANNs depends very crucially on having representative records of sufficient length. Further, the forecast accuracy decreases rapidly with an increase in the forecast horizon. In this study, the use of the Darwinian theory-based recent evolutionary technique of genetic programming (GP) is suggested to forecast fortnightly flow up to 4-lead. It is demonstrated that short lead predictions can be significantly improved from a short and noisy time series if the stochastic (noise) component is appropriately filtered out. The deterministic component can then be easily modelled. Further, only the immediate antecedent exogenous and/or non-exogenous inputs can be assumed to control the process. With an increase in the forecast horizon, the stochastic components also play an important role in the forecast, besides the inherent difficulty in ascertaining the appropriate input variables which can be assumed to govern the underlying process. GP is found to be an efficient tool to identify the most appropriate input variables to achieve reasonable prediction accuracy for higher lead-period forecasts. A comparison with ANNs suggests that though there is no significant difference in the prediction accuracy, GP does offer some unique advantages. Copyright
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.
Optimal block cosine transform image coding for noisy channels
NASA Technical Reports Server (NTRS)
Vaishampayan, Vinay A.; Farvardin, Nariman
1990-01-01
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 optimiaation of a scheme based on the 2-D block cosine transorm 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 noise channels were obtained and appropriate comparisons against a reference system designed for no channel error were rendered.
An edge detection method for strong noisy image using shearlets
NASA Astrophysics Data System (ADS)
Li, Yuming; Cao, Hanqiang; Xu, Zijian
2011-11-01
Numerous edge detection methods have been proposed to detect image edges. However, these methods are not very effective in detecting edges in strong noisy images. Recent years, multiscale analysis has been introduced to the realm of image processing. As the third generation wavelet, shearlets have their own superiority. Anisotropic dilation operator and shear operator are introduced to overcome the shortcomings of traditional wavelets. Because of their sensitivity to directions, shearlets are apt to do the job of edge detection. Based on shearlets, in this paper, a new edge detection method is proposed. The main idea about this new method is combining the shearlet denoising method with the edge detecting method based on shearlets. Analyzing results show that edges are characterized as zerocrossing points in shearlet domain and can be extracted from shearlet transform coefficients by detecting zero crossing points and using boundary tracking method. Many experiments are conducted to test this novel approach and we also compare Sobel, Log and Canny operators with this new method. Experiments demonstrate that when an image existing high deviation Gaussian noise, this method are much better than ordinary edge detection operators in time domain.
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
Noisy scattering dynamics in the randomly driven Hénon-Heiles oscillator
NASA Astrophysics Data System (ADS)
Gan, Chunbiao; Yang, Shixi; Lei, Hua
2010-12-01
Noisy scattering dynamics in the randomly driven Hénon-Heiles oscillator is investigated when the energy is above the threshold to permit particles to escape from the scattering region. First, some basic simulation procedures are briefly introduced and the fractal exit basins appear to be robust when the bounded noisy excitation is imposed on the oscillator. Second, several key fractal characteristics of the sample basin boundaries, such as the delay-time function and the uncertainty dimension, are estimated from which this oscillator is found to be structurally unstable against the bounded noisy excitation. Moreover, the stable and unstable manifolds of some sample chaotic invariant sets are estimated and illustrated in a special two-dimensional Poincaré section. Lastly, several previous methods are developed to identify three arbitrarily chosen noisy scattering time series of the randomly driven Hénon-Heiles oscillator, from which the quasiperiodic-dominant and the chaotic-dominant dynamical behaviors are distinguished.
Quantum Cryptography, Quantum Communication, and Quantum Computer in a Noisy Environment
NASA Astrophysics Data System (ADS)
Nagata, Koji; Nakamura, Tadao
2017-07-01
First, we study several information theories based on quantum computing in a desirable noiseless situation. (1) We present quantum key distribution based on Deutsch's algorithm using an entangled state. (2) We discuss the fact that the Bernstein-Vazirani algorithm can be used for quantum communication including an error correction. Finally, we discuss the main result. We study the Bernstein-Vazirani algorithm in a noisy environment. The original algorithm determines a noiseless function. Here we consider the case that the function has an environmental noise. We introduce a noise term into the function f( x). So we have another noisy function g( x). The relation between them is g( x) = f( x) ± O( 𝜖). Here O( 𝜖) ≪ 1 is the noise term. The goal is to determine the noisy function g( x) with a success probability. The algorithm overcomes classical counterpart by a factor of N in a noisy environment.
2010-12-01
R. M. Murray, “ Consensus problems in networks of agents with switching topology and time -delays,” IEEE Trans. Autom. Control, vol. 49, no. 9, pp... Distributed Tracking with Consensus on Noisy Time -varying Graphs: Convergence Results and Applications Sudharman K. Jayaweera and Y. Ruan ECE... distributed tracking with consensus on a time -varying graph with noisy communications links and sensing constraints. We develop a framework to handle the
NASA Astrophysics Data System (ADS)
Liao, Xiang-Ping; Fang, Mao-Fa; Zhou, Xin
2017-10-01
An efficient method is proposed to enhance the parameter-estimation precision for noisy quantum channels based on measurement reversal from partial-collapse measurement. It is shown that the quantum Fisher information can be distinctly improved for amplitude-damping channel, phase-damping channel and depolarizing channel with partial-collapse measurement. This also means that choosing the appropriate measurement strengths can lead to higher precision of estimation on noisy quantum channels.
The evolution of cooperation by negotiation in a noisy world.
Ito, K; McNamara, J M; Yamauchi, A; Higginson, A D
2017-03-01
Cooperative interactions among individuals are ubiquitous despite the possibility of exploitation by selfish free riders. One mechanism that may promote cooperation is 'negotiation': individuals altering their behaviour in response to the behaviour of others. Negotiating individuals decide their actions through a recursive process of reciprocal observation, thereby reducing the possibility of free riding. Evolutionary games with response rules have shown that infinitely many forms of the rule can be evolutionarily stable simultaneously, unless there is variation in individual quality. This potentially restricts the conditions under which negotiation could maintain cooperation. Organisms interact with one another in a noisy world in which cooperative effort and the assessment of effort may be subject to error. Here, we show that such noise can make the number of evolutionarily stable rules finite, even without quality variation, and so noise could help maintain cooperative behaviour. We show that the curvature of the benefit function is the key factor determining whether individuals invest more or less as their partner's investment increases, investing less when the benefit to investment has diminishing returns. If the benefits of low investment are very small then behavioural flexibility tends to promote cooperation, because negotiation enables cooperators to reach large benefits. Under some conditions, this leads to a repeating cycle in which cooperative behaviour rises and falls over time, which may explain between-population differences in cooperative behaviour. In other conditions, negotiation leads to extremely high levels of cooperative behaviour, suggesting that behavioural flexibility could facilitate the evolution of eusociality in the absence of high relatedness. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.
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.
Estimating signal features from noisy images with stochastic backgrounds
NASA Astrophysics Data System (ADS)
Whitaker, Meredith Kathryn
Imaging is often used in scientific applications as a measurement tool. The location of a target, brightness of a star, and size of a tumor are all examples of object features that are sought after in various imaging applications. A perfect measurement of these quantities from image data is impossible because of, most notably, detector noise fluctuations, finite resolution, sensitivity of the imaging instrument, and obscuration by undesirable object structures. For these reasons, sophisticated image-processing techniques are designed to treat images as random variables. Quantities calculated from an image are subject to error and fluctuation; implied by calling them estimates of object features. This research focuses on estimator error for tasks common to imaging applications. Computer simulations of imaging systems are employed to compare the estimates to the true values. These computations allow for algorithm performance tests and subsequent development. Estimating the location, size, and strength of a signal embedded in a background structure from noisy image data is the basic task of interest. The estimation task's degree of difficulty is adjusted to discover the simplest data-processing necessary to yield successful estimates. Even when using an idealized imaging model, linear Wiener estimation was found to be insufficient for estimating signal location and shape. These results motivated the investigation of more complex data processing. A new method (named the scanning-linear estimator because it maximizes a linear functional) is successful in cases where linear estimation fails. This method has also demonstrated positive results when tested in realistic simulations of tomographic SPECT imaging systems. A comparison to a model of current clinical estimation practices found that the scanning-linear method offers substantial gains in performance.
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
NASA Astrophysics Data System (ADS)
Brunet, Éric; Derrida, Bernard
2004-07-01
We calculate exactly the velocity and diffusion constant of a microscopic stochastic model of N evolving particles which can be described by a noisy traveling-wave equation with a noise of order N-1/2 . Our model can be viewed as the infinite range limit of a directed polymer in random medium with N sites in the transverse direction. Despite some peculiarities of the traveling-wave equations in the absence of noise, our exact solution allows us to test the validity of a simple cutoff approximation and to show that, in the weak noise limit, the position of the front can be completely described by the effect of the noise on the first particle.
Brunet, Eric; Derrida, Bernard
2004-01-01
We calculate exactly the velocity and diffusion constant of a microscopic stochastic model of N evolving particles which can be described by a noisy traveling-wave equation with a noise of order N(-1/2). Our model can be viewed as the infinite range limit of a directed polymer in random medium with N sites in the transverse direction. Despite some peculiarities of the traveling-wave equations in the absence of noise, our exact solution allows us to test the validity of a simple cutoff approximation and to show that, in the weak noise limit, the position of the front can be completely described by the effect of the noise on the first particle.
Optimum Mixed-State Discrimination for Noisy Entanglement-Enhanced Sensing
NASA Astrophysics Data System (ADS)
Zhuang, Quntao; Zhang, Zheshen; Shapiro, Jeffrey H.
2017-01-01
Quantum metrology utilizes nonclassical resources, such as entanglement or squeezed light, to realize sensors whose performance exceeds that afforded by classical-state systems. Environmental loss and noise, however, easily destroy nonclassical resources and, thus, nullify the performance advantages of most quantum-enhanced sensors. Quantum illumination (QI) is different. It is a robust entanglement-enhanced sensing scheme whose 6 dB performance advantage over a coherent-state sensor of the same average transmitted photon number survives the initial entanglement's eradication by loss and noise. Unfortunately, an implementation of the optimum quantum receiver that would reap QI's full performance advantage has remained elusive, owing to its having to deal with a huge number of very noisy optical modes. We show how sum-frequency generation (SFG) can be fruitfully applied to optimum multimode Gaussian-mixed-state discrimination. Applied to QI, our analysis and numerical evaluations demonstrate that our SFG receiver saturates QI's quantum Chernoff bound. Moreover, augmenting our SFG receiver with a feedforward (FF) mechanism pushes its performance to the Helstrom bound in the limit of low signal brightness. The FF-SFG receiver, thus, opens the door to optimum quantum-enhanced imaging, radar detection, state and channel tomography, and communication in practical Gaussian-state situations.
Köndgen, Harold; Geisler, Caroline; Fusi, Stefano; Wang, Xiao-Jing; Lüscher, Hans-Rudolf; Giugliano, Michele
2008-09-01
Cortical neurons are often classified by current-frequency relationship. Such a static description is inadequate to interpret neuronal responses to time-varying stimuli. Theoretical studies suggested that single-cell dynamical response properties are necessary to interpret ensemble responses to fast input transients. Further, it was shown that input-noise linearizes and boosts the response bandwidth, and that the interplay between the barrage of noisy synaptic currents and the spike-initiation mechanisms determine the dynamical properties of the firing rate. To test these model predictions, we estimated the linear response properties of layer 5 pyramidal cells by injecting a superposition of a small-amplitude sinusoidal wave and a background noise. We characterized the evoked firing probability across many stimulation trials and a range of oscillation frequencies (1-1000 Hz), quantifying response amplitude and phase-shift while changing noise statistics. We found that neurons track unexpectedly fast transients, as their response amplitude has no attenuation up to 200 Hz. This cut-off frequency is higher than the limits set by passive membrane properties (approximately 50 Hz) and average firing rate (approximately 20 Hz) and is not affected by the rate of change of the input. Finally, above 200 Hz, the response amplitude decays as a power-law with an exponent that is independent of voltage fluctuations induced by the background noise.
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 -
Quantum teleportation through noisy channels with multi-qubit GHZ states
NASA Astrophysics Data System (ADS)
Espoukeh, Pakhshan; Pedram, Pouria
2014-08-01
We investigate two-party quantum teleportation through noisy channels for multi-qubit Greenberger-Horne-Zeilinger (GHZ) states and find which state loses less quantum information in the process. The dynamics of states is described by the master equation with the noisy channels that lead to the quantum channels to be mixed states. We analytically solve the Lindblad equation for -qubit GHZ states where Lindblad operators correspond to the Pauli matrices and describe the decoherence of states. Using the average fidelity, we show that 3GHZ state is more robust than GHZ state under most noisy channels. However, GHZ state preserves same quantum information with respect to Einstein-Podolsky-Rosen and 3GHZ states where the noise is in direction in which the fidelity remains unchanged. We explicitly show that Jung et al.'s conjecture (Phys Rev A 78:012312, 2008), namely "average fidelity with same-axis noisy channels is in general larger than average fidelity with different-axes noisy channels," is not valid for 3GHZ and 4GHZ states.
Fuzzy Logic Based Edge Detection in Smooth and Noisy Clinical Images.
Haq, Izhar; Anwar, Shahzad; Shah, Kamran; Khan, Muhammad Tahir; Shah, Shaukat Ali
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.
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
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
Generation of entanglement and its decay in a noisy environment
NASA Astrophysics Data System (ADS)
Huang, Jiehui
Entanglement plays a central role in distinguishing quantum mechanics from classical physics. Due to its fantastic properties and many potential applications in quantum information science, entanglement is attracting more and more attention. This thesis focuses on the generation of entanglement and its decay in a noisy environment. In the first experimental scheme to entangle two thermal fields, an atomic ensemble, composed of many identical four-level atoms, is employed. In the first Raman scattering, this atomic ensemble emits write signal photons after the pumping by a weak write pulse, accompanied by the transfer from one lower level to the other for some atoms. Similarly, the atomic ensemble emits read signal photons after the driving by a strong read pulse, and the ensemble turns back to its ground state after the second Raman scattering. The coherence between the two lower atomic levels plays a key role in establishing the quantum correlation between two emission fields, which is verified through the violation of Cauchy-Schwarz inequality. In particular, the controllable time delay between the two emission fields actually means the storage time of photonic information in this system, which sheds light on some potential applications, such as quantum memory. In the second experimental scheme for the generation of spatially separated multiphoton entanglement, two or more identical optical cavities are aligned along a bee-line, and a four-level atom runs through these cavities sequentially. By appropriately adjusting the passage time of the atom in each cavity or the Rabi frequency of the classical pumping laser, a photon can be generated via the interaction between the excited atom and the cavity modes. This adiabatic passage model is an effective method to map atomic coherence to photonic state in cavity QED, thus all photons in different cavities quantum-mechanically correlate with the moving atom. When a final detection is made on this atom, a generalized n
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.
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.
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
Mildren, Robyn L; Peters, Ryan M; Hill, Aimee J; Blouin, Jean-Sébastien; Carpenter, Mark G; Inglis, J Timothy
2017-05-01
Noisy stimuli, along with linear systems analysis, have proven to be effective for mapping functional neural connections. We explored the use of noisy (10-115 Hz) Achilles tendon vibration to examine somatosensory reflexes in the triceps surae muscles in standing healthy young adults (n = 8). We also examined the association between noisy vibration and electrical activity recorded over the sensorimotor cortex using electroencephalography. We applied 2 min of vibration and recorded ongoing muscle activity of the soleus and gastrocnemii using surface electromyography (EMG). Vibration amplitude was varied to characterize reflex scaling and to examine how different stimulus levels affected postural sway. Muscle activity from the soleus and gastrocnemii was significantly correlated with the tendon vibration across a broad frequency range (~10-80 Hz), with a peak located at ~40 Hz. Vibration-EMG coherence positively scaled with stimulus amplitude in all three muscles, with soleus displaying the strongest coupling and steepest scaling. EMG responses lagged the vibration by ~38 ms, a delay that paralleled observed response latencies to tendon taps. Vibration-evoked cortical oscillations were observed at frequencies ~40-70 Hz (peak ~54 Hz) in most subjects, a finding in line with previous reports of sensory-evoked γ-band oscillations. Further examination of the method revealed 1) accurate reflex estimates could be obtained with <60 s of low-level (root mean square = 10 m/s(2)) vibration; 2) responses did not habituate over 2 min of exposure; and importantly, 3) noisy vibration had a minimal influence on standing balance. Our findings suggest noisy tendon vibration is an effective novel approach to characterize somatosensory reflexes during standing.NEW & NOTEWORTHY We applied noisy (10-115 Hz) vibration to the Achilles tendon to examine the frequency characteristics of lower limb somatosensory reflexes during standing. Ongoing muscle activity was coherent with the
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.
Correspondence between a noisy sample-space-reducing process and records in correlated random events
NASA Astrophysics Data System (ADS)
Yadav, Avinash Chand
2017-09-01
We study survival time statistics in a noisy sample-space-reducing (SSR) process. Our simulations suggest that both the mean and standard deviation scale as ˜N /Nλ , where N is the system size and λ is a tunable parameter that characterizes the process. The survival time distribution has the form PN(τ ) ˜N-θJ (τ /Nθ) , where J is a universal scaling function and θ =1 -λ . Analytical insight is provided by a conjecture for the equivalence between the survival time statistics in the noisy SSR process and the record statistics in a correlated time series modeled as a drifted random walk with Cauchy distributed jumps.
On extending the complex FastICA algorithms to noisy data.
Ruan, Zongli; Li, Liping; Qian, Guobing
2014-12-01
Independent component analysis (ICA) methods are widely applied to modern digital signal processing. The complex-valued FastICA algorithms are one type of the most significant methods. However, the complex ICA model usually omits the noise. In this paper, we discuss two complex FastICA algorithms for noisy data, where the cost functions are based on kurtosis and negentropy respectively. The nc-FastICA and KM-F algorithms are modified to separate noisy data. At the same time, we also give the stability conditions of cost functions. Simulations are presented to illustrate the effectiveness of our methods. Copyright © 2014 Elsevier Ltd. All rights reserved.
Noisy-flow-induced instability in a reaction-diffusion system
NASA Astrophysics Data System (ADS)
Paul, Shibashis; Ghosh, Shyamolina; Ray, Deb Shankar
2016-12-01
We consider a generic reaction-diffusion-advection system where the flow velocity of the advection term is subjected to dichotomous noise with zero mean and Ornstein-Zernike correlation. A general condition for noisy-flow-induced instability is derived in the flow velocity-correlation rate parameter plane. Full numerical simulations on Gierer-Meinhardt model with activator-inhibitor kinetics have been performed to show how noisy differential flow can lead to symmetry breaking of a homogeneous stable state in the presence of noise resulting in traveling waves.
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
Optimized control of quantum state transfer from noisy to quiet qubits
NASA Astrophysics Data System (ADS)
Escher, B. M.; Bensky, G.; Clausen, J.; Kurizki, G.
2011-08-01
Existing optimal control methods of open quantum systems rely on extensive numerical simulations of the dynamics in the presence of a bath, or alternatively ignore the exact bath dynamics. If the bath effects are to be treated properly on both Markovian and non-Markovian timescales using numerical simulations, the number of bath modes cannot be large. This may affect the ability to simulate realistic scenarios. Even if realistic, such simulations are hard to interpret physically. An alternative approach advocated here is to resort to a perturbative analysis provided the system-bath coupling is weak. This analysis would allow for the effects of any given bath (finite or infinite, Markovian or non-Markovian) and any control at our disposal. This poses the challenge of constructing a method for the optimization of various operations requiring proper manipulation of the system, based on a general perturbative treatment to second order in the system-bath coupling. This proposed treatment yields a universal tool for optimizing the fidelity of a given operation. It involves a fidelity-control matrix: a construct that allows us to prioritize the use of available control resources so as to maximize the operation fidelity in any given bath. As an analytically solvable example of this general method, we analyse quantum state-transfer optimization, from a 'noisy' (write-in) qubit to its 'quiet' counterpart (storage qubit). Intriguing interplay is revealed between our ability to avoid bath-induced errors that profoundly depend on the bath-memory time and the limitations imposed by leakage out of the operational subspace. Counterintuitively, under no circumstances is the fastest transfer optimal (for a given transfer energy).
Stochastic P-bifurcation and stochastic resonance in a noisy bistable fractional-order system
NASA Astrophysics Data System (ADS)
Yang, J. H.; Sanjuán, Miguel A. F.; Liu, H. G.; Litak, G.; Li, X.
2016-12-01
We investigate the stochastic response of a noisy bistable fractional-order system when the fractional-order lies in the interval (0, 2]. We focus mainly on the stochastic P-bifurcation and the phenomenon of the stochastic resonance. We compare the generalized Euler algorithm and the predictor-corrector approach which are commonly used for numerical calculations of fractional-order nonlinear equations. Based on the predictor-corrector approach, the stochastic P-bifurcation and the stochastic resonance are investigated. Both the fractional-order value and the noise intensity can induce an stochastic P-bifurcation. The fractional-order may lead the stationary probability density function to turn from a single-peak mode to a double-peak mode. However, the noise intensity may transform the stationary probability density function from a double-peak mode to a single-peak mode. The stochastic resonance is investigated thoroughly, according to the linear and the nonlinear response theory. In the linear response theory, the optimal stochastic resonance may occur when the value of the fractional-order is larger than one. In previous works, the fractional-order is usually limited to the interval (0, 1]. Moreover, the stochastic resonance at the subharmonic frequency and the superharmonic frequency are investigated respectively, by using the nonlinear response theory. When it occurs at the subharmonic frequency, the resonance may be strong and cannot be ignored. When it occurs at the superharmonic frequency, the resonance is weak. We believe that the results in this paper might be useful for the signal processing of nonlinear systems.
The estimation of time-invariant parameters of noisy nonlinear oscillatory systems
NASA Astrophysics Data System (ADS)
Khalil, Mohammad; Sarkar, Abhijit; Adhikari, Sondipon; Poirel, Dominique
2015-05-01
The inverse problem of estimating time-invariant (static) parameters of a nonlinear system exhibiting noisy oscillation is considered in this paper. Firstly, a Markov Chain Monte Carlo (MCMC) simulation is used for the time-invariant parameter estimation which exploits a non-Gaussian filter, namely the Ensemble Kalman Filter (EnKF) for state estimation required to compute the likelihood function. Secondly, a recently proposed Particle Filter (PF) (that uses the EnKF for its proposal density for the state estimation) has been adapted for combined state and parameter estimation. Numerical illustrations highlight the strengths and limitations of the MCMC, EnKF and PF algorithms for time-invariant parameter estimation. For low measurement noise and dense measurement data, the performances of the MCMC, EnKF and PF algorithms are comparable. For high measurement noise and sparse observational data, the EnKF fails to provide accurate parameter estimates. Hence the adapted PF algorithm becomes necessary in order to obtain parameter estimates comparable in accuracy to the MCMC simulation with EnKF. It highlights the fact that the augmented state space model for the combined state and parameter estimation contains stronger nonlinearity than the original state space model. Hence the EnKF effectively handles the state estimation of the original state space model, but it fails for the combined state and parameter estimation using the augmented system. The effectiveness of the EnKF for the state estimation is therefore leveraged in the MCMC simulation for the time-invariant parameter estimation. In order to obtain accurate parameter estimates using the augmented system, the adapted PF becomes necessary to match the parameter estimates obtained using the MCMC simulation complemented by EnKF for likelihood function computation.
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
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. Copyright © 2014. Published by Elsevier GmbH.
Boström, Jan; Elger, Christian E.; Mormann, Florian
2016-01-01
Recording extracellulary from neurons in the brains of animals in vivo is among the most established experimental techniques in neuroscience, and has recently become feasible in humans. Many interesting scientific questions can be addressed only when extracellular recordings last several hours, and when individual neurons are tracked throughout the entire recording. Such questions regard, for example, neuronal mechanisms of learning and memory consolidation, and the generation of epileptic seizures. Several difficulties have so far limited the use of extracellular multi-hour recordings in neuroscience: Datasets become huge, and data are necessarily noisy in clinical recording environments. No methods for spike sorting of such recordings have been available. Spike sorting refers to the process of identifying the contributions of several neurons to the signal recorded in one electrode. To overcome these difficulties, we developed Combinato: a complete data-analysis framework for spike sorting in noisy recordings lasting twelve hours or more. Our framework includes software for artifact rejection, automatic spike sorting, manual optimization, and efficient visualization of results. Our completely automatic framework excels at two tasks: It outperforms existing methods when tested on simulated and real data, and it enables researchers to analyze multi-hour recordings. We evaluated our methods on both short and multi-hour simulated datasets. To evaluate the performance of our methods in an actual neuroscientific experiment, we used data from from neurosurgical patients, recorded in order to identify visually responsive neurons in the medial temporal lobe. These neurons responded to the semantic content, rather than to visual features, of a given stimulus. To test our methods with multi-hour recordings, we made use of neurons in the human medial temporal lobe that respond selectively to the same stimulus in the evening and next morning. PMID:27930664
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.
Information transduction capacity of noisy biochemical signaling networks
Cheong, Raymond; Rhee, Alex; Wang, Chiaochun Joanne; Nemenman, Ilya; Levchenko, Andre
2014-01-01
Molecular noise restricts the ability of an individual cell to resolve input signals of different strengths and gather information about the external environment. Transmitting information through complex signaling networks with redundancies can overcome this limitation. We developed an integrative theoretical and experimental framework, based on the formalism of information theory, to quantitatively predict and measure the amount of information transduced by molecular and cellular networks. Analyzing tumor necrosis factor (TNF) signaling revealed that individual TNF signaling pathways transduce information sufficient for accurate binary decisions, and an upstream bottleneck limits the information gained via multiple pathways together. Negative feedback to this bottleneck could both alleviate and enhance its limiting effect, despite decreasing noise. Bottlenecks likewise constrain information attained by networks signaling through multiple genes or cells. PMID:21921160
Kaptein, Maurits; van Emden, Robin; Iannuzzi, Davide
2017-01-01
Due to the ubiquitous presence of treatment heterogeneity, measurement error, and contextual confounders, numerous social phenomena are hard to study. Precise control of treatment variables and possible confounders is often key to the success of studies in the social sciences, yet often proves out of the realm of control of the experimenter. To amend this situation we propose a novel approach coined "lock-in feedback" which is based on a method that is routinely used in high-precision physics experiments to extract small signals out of a noisy environment. Here, we adapt the method to noisy social signals in multiple dimensions and evaluate it by studying an inherently noisy topic: the perception of (subjective) beauty. We show that the lock-in feedback approach allows one to select optimal treatment levels despite the presence of considerable noise. Furthermore, through the introduction of an external contextual shock we demonstrate that we can find relationships between noisy variables that were hitherto unknown. We therefore argue that lock-in methods may provide a valuable addition to the social scientist's experimental toolbox and we explicitly discuss a number of future applications.
Rational integration of noisy evidence and prior semantic expectations in sentence interpretation
Gibson, Edward; Bergen, Leon; Piantadosi, Steven T.
2013-01-01
Sentence processing theories typically assume that the input to our language processing mechanisms is an error-free sequence of words. However, this assumption is an oversimplification because noise is present in typical language use (for instance, due to a noisy environment, producer errors, or perceiver errors). A complete theory of human sentence comprehension therefore needs to explain how humans understand language given imperfect input. Indeed, like many cognitive systems, language processing mechanisms may even be “well designed”–in this case for the task of recovering intended meaning from noisy utterances. In particular, comprehension mechanisms may be sensitive to the types of information that an idealized statistical comprehender would be sensitive to. Here, we evaluate four predictions about such a rational (Bayesian) noisy-channel language comprehender in a sentence comprehension task: (i) semantic cues should pull sentence interpretation towards plausible meanings, especially if the wording of the more plausible meaning is close to the observed utterance in terms of the number of edits; (ii) this process should asymmetrically treat insertions and deletions due to the Bayesian “size principle”; such nonliteral interpretation of sentences should (iii) increase with the perceived noise rate of the communicative situation and (iv) decrease if semantically anomalous meanings are more likely to be communicated. These predictions are borne out, strongly suggesting that human language relies on rational statistical inference over a noisy channel. PMID:23637344
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…
An Empirical Validation of Recursive Noisy OR (RNOR) Rule for Asthma Prediction.
Anand, Vibha; Downs, Stephen M
2010-11-13
In 2004, an extension of the Noisy-OR formalism termed the Recursive Noisy-OR (RNOR) rule was published for estimating complex probabilistic interactions in a Bayesian Network (BN). The RNOR rule presents an algorithm to construct a complete conditional probability distribution (CPD) of a node while allowing domain causal relationships over and above causal independence to be tractably captured in a semantically meaningful way. However, to the best of our knowledge, the accuracy of this rule has not been tested empirically. In this paper, we report the results of a study that compares the performance of a data-trained expert BN (empiric BN) with the reformulated BN, using the RNOR rule. The original empiric BN was trained with a large dataset from the Regenstrief Medical Record System (RMRS). Furthermore, we evaluate conditions in our dataset which render the RNOR rule inapplicable and discuss our use of Noisy-OR calculations in such situations. We call this approach "Adaptive Recursive Noisy-OR".
2017-01-01
Due to the ubiquitous presence of treatment heterogeneity, measurement error, and contextual confounders, numerous social phenomena are hard to study. Precise control of treatment variables and possible confounders is often key to the success of studies in the social sciences, yet often proves out of the realm of control of the experimenter. To amend this situation we propose a novel approach coined “lock-in feedback” which is based on a method that is routinely used in high-precision physics experiments to extract small signals out of a noisy environment. Here, we adapt the method to noisy social signals in multiple dimensions and evaluate it by studying an inherently noisy topic: the perception of (subjective) beauty. We show that the lock-in feedback approach allows one to select optimal treatment levels despite the presence of considerable noise. Furthermore, through the introduction of an external contextual shock we demonstrate that we can find relationships between noisy variables that were hitherto unknown. We therefore argue that lock-in methods may provide a valuable addition to the social scientist’s experimental toolbox and we explicitly discuss a number of future applications. PMID:28306728
Analog circuit for the measurement of phase difference between two noisy sine-wave signals
NASA Technical Reports Server (NTRS)
Shakkottai, P.; Kwack, E. Y.; Back, L. H.
1989-01-01
A simple circuit was designed to measure the phase difference between two noisy sine waves. It locks over a wide range of frequencies and produces an output proportional to the phase difference of rapidly varying signals. A square wave locked in frequency and phase to the first signal is produced by a phase-locked loop and is amplified by an operational amplifier.
On the judgment of loudness, noisiness and annoyance with actual and artificial noises
NASA Astrophysics Data System (ADS)
Kuwano, S.; Namba, S.; Fastl, H.
1988-12-01
Loudness, noisiness and annoyance were judged for 36 stimuli by Japanese and German subjects. In experiment 1, actual noises such as aircraft and road traffic noise were used. In experiment 2, artificial noises were used. Their level patterns were simulated to correspond to the actual sound sources used in experiment 1, and the carrier was pink noise. Absolute magnitude estimation was used for making judgments. Eight German subjects and eight Japanese subjects participated. Judgments of loudness, noisiness and annoyance were made for actual and for simulated sounds. Results showed the following. (1) The concepts "loudness", "noisiness" and "annoyance" have rather different implications; various factors, such as the temporal pattern of the stimulus, frequency components, duration and subjective meaning, contribute to the differences. (2) Differences in the subjective meaning of sounds may have an important effect on judgments of noisiness and annoyance. (3) German subjects seem to be more sensitive to level fluctuation; they tend to judge sound on the basis of its maximum level, whereas Japanese do so on the basis of its energy. (4) In the case of traffic noise, there was little difference in the evaluation of the three aspects by the German and Japanese subjects; it therefore seems appropriate to evaluate these sounds by LA eq.
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...
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...
Analog circuit for the measurement of phase difference between two noisy sine-wave signals
NASA Technical Reports Server (NTRS)
Shakkottai, P.; Kwack, E. Y.; Back, L. H.
1989-01-01
A simple circuit was designed to measure the phase difference between two noisy sine waves. It locks over a wide range of frequencies and produces an output proportional to the phase difference of rapidly varying signals. A square wave locked in frequency and phase to the first signal is produced by a phase-locked loop and is amplified by an operational amplifier.
Lee, Norman; Ward, Jessica L; Vélez, Alejandro; Micheyl, Christophe; Bee, Mark A
2017-03-06
Noise is a ubiquitous source of errors in all forms of communication [1]. Noise-induced errors in speech communication, for example, make it difficult for humans to converse in noisy social settings, a challenge aptly named the "cocktail party problem" [2]. Many nonhuman animals also communicate acoustically in noisy social groups and thus face biologically analogous problems [3]. However, we know little about how the perceptual systems of receivers are evolutionarily adapted to avoid the costs of noise-induced errors in communication. In this study of Cope's gray treefrog (Hyla chrysoscelis; Hylidae), we investigated whether receivers exploit a potential statistical regularity present in noisy acoustic scenes to reduce errors in signal recognition and discrimination. We developed an anatomical/physiological model of the peripheral auditory system to show that temporal correlation in amplitude fluctuations across the frequency spectrum ("comodulation") [4-6] is a feature of the noise generated by large breeding choruses of sexually advertising males. In four psychophysical experiments, we investigated whether females exploit comodulation in background noise to mitigate noise-induced errors in evolutionarily critical mate-choice decisions. Subjects experienced fewer errors in recognizing conspecific calls and in selecting the calls of high-quality mates in the presence of simulated chorus noise that was comodulated. These data show unequivocally, and for the first time, that exploiting statistical regularities present in noisy acoustic scenes is an important biological strategy for solving cocktail-party-like problems in nonhuman animal communication.
Automatic detection of noisy channels in fNIRS signal based on correlation analysis.
Guerrero-Mosquera, Carlos; Borragán, Guillermo; Peigneux, Philippe
2016-09-15
fNIRS signals can be contaminated by distinct sources of noise. While most of the noise can be corrected using digital filters, optimized experimental paradigms or pre-processing methods, few approaches focus on the automatic detection of noisy channels. In the present study, we propose a new method that detect automatically noisy fNIRS channels by combining the global correlations of the signal obtained from sliding windows (Cui et al., 2010) with correlation coefficients extracted experimental conditions defined by triggers. The validity of the method was evaluated on test data from 17 participants, for a total of 16 NIRS channels per subject, positioned over frontal, dorsolateral prefrontal, parietal and occipital areas. Additionally, the detection of noisy channels was tested in the context of different levels of cognitive requirement in a working memory N-back paradigm. Bad channels detection accuracy, defined as the proportion of bad NIRS channels correctly detected among the total number of channels examined, was close to 91%. Under different cognitive conditions the area under the Receiver Operating Curve (AUC) increased from 60.5% (global correlations) to 91.2% (local correlations). Our results show that global correlations are insufficient for detecting potentially noisy channels when the whole data signal is included in the analysis. In contrast, adding specific local information inherent to the experimental paradigm (e.g., cognitive conditions in a block or event-related design), improved detection performance for noisy channels. Also, we show that automated fNIRS channel detection can be achieved with high accuracy at low computational cost. Copyright © 2016 Elsevier B.V. All rights reserved.
Optimal efficiency of a noisy quantum heat engine.
Stefanatos, Dionisis
2014-07-01
In this article we use optimal control to maximize the efficiency of a quantum heat engine executing the Otto cycle in the presence of external noise. We optimize the engine performance for both amplitude and phase noise. In the case of phase damping we additionally show that the ideal performance of a noiseless engine can be retrieved in the adiabatic (long time) limit. The results obtained here are useful in the quest for absolute zero, the design of quantum refrigerators that can cool a physical system to the lowest possible temperature. They can also be applied to the optimal control of a collection of classical harmonic oscillators sharing the same time-dependent frequency and subjected to similar noise mechanisms. Finally, our methodology can be used for the optimization of other interesting thermodynamic processes.
Noisy inverted pendulums with time-delayed feedback: Statistical Dynamics
NASA Astrophysics Data System (ADS)
Milton, John G.
2001-03-01
The question of how an inverted pendulum can be stabilized has puzzled scientists for over 300 years. Studies of postural sway and stick balancing at the fingertip provide insights into how the human nervous system solves this problem. Time delays and noise are intrinsic features of the neural control and thus models are in the form of stochastic delay-differential equations. Examples are presented to show that the statistical properties of the fluctuations in posture and stick balancing are dominated by noise-dependent, nonlinear phenomena: noise-induced switching between limit cycle attractors (postural sway) and "on-off intermittency" arising from the stochastic forcing of a control parameter across a stability boundary (stick balancing). The existence of these phenomena is difficult to reconcile with classical concepts of neural feedback control.
Noisy metrology: a saturable lower bound on quantum Fisher information
NASA Astrophysics Data System (ADS)
Yousefjani, R.; Salimi, S.; Khorashad, A. S.
2017-06-01
In order to provide a guaranteed precision and a more accurate judgement about the true value of the Cramér-Rao bound and its scaling behavior, an upper bound (equivalently a lower bound on the quantum Fisher information) for precision of estimation is introduced. Unlike the bounds previously introduced in the literature, the upper bound is saturable and yields a practical instruction to estimate the parameter through preparing the optimal initial state and optimal measurement. The bound is based on the underling dynamics, and its calculation is straightforward and requires only the matrix representation of the quantum maps responsible for encoding the parameter. This allows us to apply the bound to open quantum systems whose dynamics are described by either semigroup or non-semigroup maps. Reliability and efficiency of the method to predict the ultimate precision limit are demonstrated by three main examples.
Accuracy of the box-counting algorithm for noisy fractals
NASA Astrophysics Data System (ADS)
Górski, A. Z.; Stróż, M.; Oświȩcimka, P.; Skrzat, J.
2016-04-01
The box-counting (BC) algorithm is applied to calculate fractal dimensions of four fractal sets. The sets are contaminated with an additive noise with amplitude γ=10-5-10-1. The accuracy of calculated numerical values of the fractal dimensions is analyzed as a function of γ for different sizes of the data sample. In particular, it has been found that even in case of pure fractals (γ=0) as well as for tiny noise (γ≈10-5) one has considerable error for the calculated exponents of order 0.01. For larger noise the error is growing up to 0.1 and more, with natural saturation limited by the embedding dimension. This prohibits the power-like scaling of the error. Moreover, the noise effect cannot be cured by taking larger data samples.
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
NASA Astrophysics Data System (ADS)
Khan, Shiraj; Bandyopadhyay, Sharba; Ganguly, Auroop R.; Saigal, Sunil; Erickson, David J., III; Protopopescu, Vladimir; Ostrouchov, George
2007-08-01
Commonly used dependence measures, such as linear correlation, cross-correlogram, or Kendall’s τ , cannot capture the complete dependence structure in data unless the structure is restricted to linear, periodic, or monotonic. Mutual information (MI) has been frequently utilized for capturing the complete dependence structure including nonlinear dependence. Recently, several methods have been proposed for the MI estimation, such as kernel density estimators (KDEs), k -nearest neighbors (KNNs), Edgeworth approximation of differential entropy, and adaptive partitioning of the XY plane. However, outstanding gaps in the current literature have precluded the ability to effectively automate these methods, which, in turn, have caused limited adoptions by the application communities. This study attempts to address a key gap in the literature—specifically, the evaluation of the above methods to choose the best method, particularly in terms of their robustness for short and noisy data, based on comparisons with the theoretical MI estimates, which can be computed analytically, as well with linear correlation and Kendall’s τ . Here we consider smaller data sizes, such as 50, 100, and 1000, and within this study we characterize 50 and 100 data points as very short and 1000 as short. We consider a broader class of functions, specifically linear, quadratic, periodic, and chaotic, contaminated with artificial noise with varying noise-to-signal ratios. Our results indicate KDEs as the best choice for very short data at relatively high noise-to-signal levels whereas the performance of KNNs is the best for very short data at relatively low noise levels as well as for short data consistently across noise levels. In addition, the optimal smoothing parameter of a Gaussian kernel appears to be the best choice for KDEs while three nearest neighbors appear optimal for KNNs. Thus, in situations where the approximate data sizes are known in advance and exploratory data analysis and
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.
Estimating random signal parameters from noisy images with nuisance parameters
Whitaker, Meredith Kathryn; Clarkson, Eric; Barrett, Harrison H.
2008-01-01
In a pure estimation task, an object of interest is known to be present, and we wish to determine numerical values for parameters that describe the object. This paper compares the theoretical framework, implementation method, and performance of two estimation procedures. We examined the performance of these estimators for tasks such as estimating signal location, signal volume, signal amplitude, or any combination of these parameters. The signal is embedded in a random background to simulate the effect of nuisance parameters. First, we explore the classical Wiener estimator, which operates linearly on the data and minimizes the ensemble mean-squared error. The results of our performance tests indicate that the Wiener estimator can estimate amplitude and shape once a signal has been located, but is fundamentally unable to locate a signal regardless of the quality of the image. Given these new results on the fundamental limitations of Wiener estimation, we extend our methods to include more complex data processing. We introduce and evaluate a scanning-linear estimator that performs impressively for location estimation. The scanning action of the estimator refers to seeking a solution that maximizes a linear metric, thereby requiring a global-extremum search. The linear metric to be optimized can be derived as a special case of maximum a posteriori (MAP) estimation when the likelihood is Gaussian and a slowly varying covariance approximation is made. PMID:18545527
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
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
NASA Astrophysics Data System (ADS)
Beitone, C.; Balandraud, X.; Delpueyo, D.; Grédiac, M.
2017-01-01
This paper presents a post-processing technique for noisy temperature maps based on a gradient anisotropic diffusion (GAD) filter in the context of heat source reconstruction. The aim is to reconstruct heat source maps from temperature maps measured using infrared (IR) thermography. Synthetic temperature fields corrupted by added noise are first considered. The GAD filter, which relies on a diffusion process, is optimized to retrieve as well as possible a heat source concentration in a two-dimensional plate. The influence of the dimensions and the intensity of the heat source concentration are discussed. The results obtained are also compared with two other types of filters: averaging filter and Gaussian derivative filter. The second part of this study presents an application for experimental temperature maps measured with an IR camera. The results demonstrate the relevancy of the GAD filter in extracting heat sources from noisy temperature fields.
Chen, Yuhang
2016-01-01
Quantitative evaluation of dimensional parameters from noisy atomic force microscopy (AFM) images was investigated. Non-local means (NLM) denoising was adopted to reduce noise and maintain fine image structures. Major tuning parameters in NLM filtering, such as the patch size and the window size, were optimized on simulated surface structures. The ability of dimensional evaluation from noisy data was demonstrated to be improved by almost 15 times. Finally, NLM filtering with optimal settings was applied on experimental AFM images, which were scanned on a patterned few-layer graphene specimen. Evaluations of the step height and the pattern size were verified to be much more accurate and robust. Such a data processing method can enhance the AFM dimensional measurements, particularly when the noise-level is reached.
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.
Avoiding disentanglement of multipartite entangled optical beams with a correlated noisy channel
Deng, Xiaowei; Tian, Caixing; Su, Xiaolong; Xie, Changde
2017-01-01
A quantum communication network can be constructed by distributing a multipartite entangled state to space-separated nodes. Entangled optical beams with highest flying speed and measurable brightness can be used as carriers to convey information in quantum communication networks. Losses and noises existing in real communication channels will reduce or even totally destroy entanglement. The phenomenon of disentanglement will result in the complete failure of quantum communication. Here, we present the experimental demonstrations on the disentanglement and the entanglement revival of tripartite entangled optical beams used in a quantum network. We experimentally demonstrate that symmetric tripartite entangled optical beams are robust in pure lossy but noiseless channels. In a noisy channel, the excess noise will lead to the disentanglement and the destroyed entanglement can be revived by the use of a correlated noisy channel (non-Markovian environment). The presented results provide useful technical references for establishing quantum networks. PMID:28295024
Stochastic error whitening algorithm for linear filter estimation with noisy data.
Rao, Yadunandana N; Erdogmus, Deniz; Rao, Geetha Y; Principe, Jose C
2003-01-01
Mean squared error (MSE) has been the most widely used tool to solve the linear filter estimation or system identification problem. However, MSE gives biased results when the input signals are noisy. This paper presents a novel stochastic gradient algorithm based on the recently proposed error whitening criterion (EWC) to tackle the problem of linear filter estimation in the presence of additive white disturbances. We will briefly motivate the theory behind the new criterion and derive an online stochastic gradient algorithm. Convergence proof of the stochastic gradient algorithm is derived making mild assumptions. Further, we will propose some extensions to the stochastic gradient algorithm to ensure faster, step-size independent convergence. We will perform extensive simulations and compare the results with MSE as well as total-least squares in a parameter estimation problem. The stochastic EWC algorithm has many potential applications. We will use this in designing robust inverse controllers with noisy data.
Security of modified Ping-Pong protocol in noisy and lossy channel
Han, Yun-Guang; Yin, Zhen-Qiang; Li, Hong-Wei; Chen, Wei; Wang, Shuang; Guo, Guang-Can; Han, Zheng-Fu
2014-01-01
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. PMID:24816899
Scared and less noisy: glucocorticoids are associated with alarm call entropy
Blumstein, Daniel T.; Chi, Yvonne Y.
2012-01-01
The nonlinearity and arousal hypothesis predicts that highly aroused mammals will produce nonlinear, noisy vocalizations. We tested this prediction by measuring faecal glucocorticoid metabolites (GCMs) in adult yellow-bellied marmots (Marmota flaviventris), and asking if variation in GCMs was positively correlated with Wiener entropy—a measure of noise. Contrary to our prediction, we found a significant negative relationship: marmots with more faecal GCMs produced calls with less noise than those with lower levels of GCMs. A previous study suggested that glucocorticoids modulate the probability that a marmot will emit a call. This study suggests that, like some other species, calls emitted from highly aroused individuals are less noisy. Glucocorticoids thus play an important, yet underappreciated role, in alarm call production. PMID:21976625
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.
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.
Full Bell locality of a noisy state for N ⩾ 3 nonlocally entangled qudits
NASA Astrophysics Data System (ADS)
Loubenets, Elena R.
2017-10-01
Bounds, expressed in terms of d and N, on full Bell locality of a quantum state for N≥slant 3 nonlocally entangled qudits (of a dimension d≥slant 2 ) mixed with white noise are known, to our knowledge, only within full separability of this noisy N-qudit state. For the maximal violation of general Bell inequalities by an N-partite quantum state, we specify the analytical upper bound expressed in terms of dilation characteristics of this state, and this allows us to find new general bounds in d, N, valid for all d≥slant 2 and all N≥slant 3, on full Bell locality under generalized quantum measurements of (i) the N-qudit GHZ state mixed with white noise and (ii) an arbitrary N-qudit state mixed with white noise. The new full Bell locality bounds are beyond the known ranges for full separability of these noisy N-qudit states.
Avoiding disentanglement of multipartite entangled optical beams with a correlated noisy channel
NASA Astrophysics Data System (ADS)
Deng, Xiaowei; Tian, Caixing; Su, Xiaolong; Xie, Changde
2017-03-01
A quantum communication network can be constructed by distributing a multipartite entangled state to space-separated nodes. Entangled optical beams with highest flying speed and measurable brightness can be used as carriers to convey information in quantum communication networks. Losses and noises existing in real communication channels will reduce or even totally destroy entanglement. The phenomenon of disentanglement will result in the complete failure of quantum communication. Here, we present the experimental demonstrations on the disentanglement and the entanglement revival of tripartite entangled optical beams used in a quantum network. We experimentally demonstrate that symmetric tripartite entangled optical beams are robust in pure lossy but noiseless channels. In a noisy channel, the excess noise will lead to the disentanglement and the destroyed entanglement can be revived by the use of a correlated noisy channel (non-Markovian environment). The presented results provide useful technical references for establishing quantum networks.
Koutsoumanis, Konstantinos P; Aspridou, Zafiro
2017-01-02
Gene expression is a fundamentally noisy process giving rise to a significant cell to cell variability at the phenotype level. The phenotypic noise is manifested in a wide range of microbial traits. Heterogeneous behavior of individual cells is observed at the growth, survival and inactivation responses and should be taken into account in the context of Predictive Food Microbiology (PMF). Recent methodological advances can be employed for the study and modeling of single cell dynamics leading to a new generation of mechanistic models which can provide insight into the link between phenotype, gene-expression, protein and metabolic functional units at the single cell level. Such models however, need to deal with an enormous amount of interactions and processes that influence each other, forming an extremely complex system. In this review paper, we discuss the importance of noise and present the future challenges in predicting the "noisy" microbial responses in foods.
Rectification-adapted snake for complex-boundary segmentation in noisy images
NASA Astrophysics Data System (ADS)
Chan, Din-Yuen; Hsu, Roy C.; Wu, Pang-Hao; Liu, Cheng-Ting
2013-03-01
In this paper, a contour-fitness improved adaptive snake, namely, edge-conducted rectification-adapted snake (ECRA-snake) is proposed for segmenting complex-boundary objects in the noisy image. The ECRA-snake includes a main ingredient called edge-conducted evolution (ECE), where the adaptations of model coefficients can accommodate ECE itself to the characteristics of salient edges for better curve fitting in tracking. Following ECE, a direction-induced rectification evolution (DIRE) will correct boundary-unmatched snake fragments by handling the initial direction and the tensile-force weighting of unqualified snaxels in this snake re-evolution. Simulation results demonstrate that the proposed ECRA-snake can obtain better object-boundary coincidence than the Gradient Vector Flow (GVF) model in segmenting the complex-boundary object from noisy images.
Perceived noisiness under anechoic, semi-reverberant and earphone listening conditions
NASA Technical Reports Server (NTRS)
Clarke, F. R.; Kryter, K. D.
1972-01-01
Magnitude estimates by each of 31 listeners were obtained for a variety of noise sources under three methods of stimuli presentation: loudspeaker presentation in an anechoic chamber, loudspeaker presentation in a normal semi-reverberant room, and earphone presentation. Comparability of ratings obtained in these environments were evaluated with respect to predictability of ratings from physical measures, reliability of ratings, and to the scale values assigned to various noise stimuli. Acoustic environment was found to have little effect upon physical predictive measures and ratings of perceived noisiness were little affected by the acoustic environment in which they were obtained. The need for further study of possible differing interactions between judged noisiness of steady state sound and the methods of magnitude estimation and paired comparisons is indicated by the finding that in these tests the subjects, though instructed otherwise, apparently judged the maximum rather than the effective magnitude of steady-state noises.
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.
Computational Experience with the Spectral Smoothing Method for Differentiating Noisy Data
NASA Astrophysics Data System (ADS)
Baart, M. L.
1981-07-01
When applied to non-exact (noisy) data, numerical methods for calculating derivatives, in particular- derivatives of order higher than the first, based on model, functions fitted to exact data, become unsatisfactory . The spectral smoothing method of Anderssen and Bloomfield, developed to solve this problem, entails calculation of a smoothing parameter and the choice of an optimal-order Sobolev norm that is used as regularizer. This method is used to differentiate, smooth and integrate noisy data. A likelihood function is minimized to determine the smoothing parameter. We present numerical results suggesting that this function can be jointly minimized with respect to the smoothing parameter and the order of the regularizing norm, thus yielding a fully automatic numerical differentiation procedure.
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.
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.
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.
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
Zhang, T; Godavarthi, C; Chaumet, P C; Maire, G; Giovannini, H; Talneau, A; Prada, C; Sentenac, A; Belkebir, K
2015-02-15
Tomographic diffractive microscopy is a marker-free optical digital imaging technique in which three-dimensional samples are reconstructed from a set of holograms recorded under different angles of incidence. We show experimentally that, by processing the holograms with singular value decomposition, it is possible to image objects in a noisy background that are invisible with classical wide-field microscopy and conventional tomographic reconstruction procedure. The targets can be further characterized with a selective quantitative inversion.
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.
Noisy face recognition using compression-based joint wavelet-transform correlator
NASA Astrophysics Data System (ADS)
Widjaja, Joewono
2012-03-01
A new method for noisy face recognition by incorporating wavelet filter into compression-based joint transform correlator (JTC) is proposed. The simulation results show that the proposed method has advantages over the conventional compression-based JTC in that regardless of the contrast and the noise level of the target, the wavelet filter can optimize the recognition performance to be higher than the classical JTC, provided compressed references have high contrast.
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.
Operator quantum Zeno effect: protecting quantum information with noisy two-qubit interactions.
Wang, Shu-Chao; Li, Ying; Wang, Xiang-Bin; Kwek, Leong Chuan
2013-03-08
The time evolution of some quantum states can be slowed down or even stopped under frequent measurements. This is the usual quantum Zeno effect. Here, we report an operator quantum Zeno effect, in which the evolution of some physical observables is slowed down through measurements even though the quantum state changes randomly with time. Based on the operator quantum Zeno effect, we show how we can protect quantum information from decoherence with two-qubit measurements, realizable with noisy two-qubit interactions.
SVD-Based Passive Bistatic Radar Detection with Noisy Reference Signal (PREPRINT)
2016-11-01
signal-plus-noise matrices of the reference and surveillance channels. In the presence of a noisy reference channel, the hypothesis testing problem...the principal left singular vectors of the signal-plus-noise matrices of the reference and surveillance channels. This detector exploits the low rank...structure inherent to the signal matrices in settings where the transmitted signals are assumed to be a weighted periodic summation of several
3D Modeling of Interior Building Environments and Objects from Noisy Sensor Suites
2015-05-14
3D Modeling of Interior Building Environments and Objects from Noisy Sensor Suites Eric Turner Electrical Engineering and Computer Sciences ... Computer Sciences ,Berkeley,CA,94720 8. PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10. SPONSOR/MONITOR’S...Philosophy in Engineering – Electrical Engineering and Computer Sciences in the Graduate Division of the University of California, Berkeley Committee in
Estimation of Speech Components by Acf Analysis in a Noisy Environment
NASA Astrophysics Data System (ADS)
Kazama, M.; Tohyama, M.
2001-03-01
A speech signal can be decomposed into the fundamental frequency and harmonics, and the autocorrelation function (ACF) is an effective tool for identifying the fundamental frequency and the harmonics. This paper, thus, explains how ACF harmonic analysis can be applied to speech detection and reconstruction when speech communication technologies are used in noisy environments. The dominant sinusoidal components used for the ACF analysis can be picked out from the short-time Fourier spectrum records of a noisy speech signal by using a peak-picking method. Because the number of components usable for speech reconstruction depends on the signal-to-noise (S/N) ratio, we authors developed new methods for peak-picking method and for harmonic sieving. The number of components picked out is adjusted frame by frame depending on the short-time S/N ratio, and harmonics are extracted from the short-time Fourier spectrum record by changing the frame length adaptively according to the fundamental frequency. Consequently, intelligible speech without 'musical noise' could be reconstructed from noisy speech signals.
Lu, Wenlong; Xie, Junwei; Wang, Heming; Sheng, Chuan
2016-01-01
Inspired by track-before-detection technology in radar, a novel time-frequency transform, namely polynomial chirping Fourier transform (PCFT), is exploited to extract components from noisy multicomponent signal. The PCFT combines advantages of Fourier transform and polynomial chirplet transform to accumulate component energy along a polynomial chirping curve in the time-frequency plane. The particle swarm optimization algorithm is employed to search optimal polynomial parameters with which the PCFT will achieve a most concentrated energy ridge in the time-frequency plane for the target component. The component can be well separated in the polynomial chirping Fourier domain with a narrow-band filter and then reconstructed by inverse PCFT. Furthermore, an iterative procedure, involving parameter estimation, PCFT, filtering and recovery, is introduced to extract components from a noisy multicomponent signal successively. The Simulations and experiments show that the proposed method has better performance in component extraction from noisy multicomponent signal as well as provides more time-frequency details about the analyzed signal than conventional methods.
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
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
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.
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).
A noisy linear map underlies oscillations in cell size and gene expression in bacteria.
Tanouchi, Yu; Pai, Anand; Park, Heungwon; Huang, Shuqiang; Stamatov, Rumen; Buchler, Nicolas E; You, Lingchong
2015-07-16
During bacterial growth, a cell approximately doubles in size before division, after which it splits into two daughter cells. This process is subjected to the inherent perturbations of cellular noise and thus requires regulation for cell-size homeostasis. The mechanisms underlying the control and dynamics of cell size remain poorly understood owing to the difficulty in sizing individual bacteria over long periods of time in a high-throughput manner. Here we measure and analyse long-term, single-cell growth and division across different Escherichia coli strains and growth conditions. We show that a subset of cells in a population exhibit transient oscillations in cell size with periods that stretch across several (more than ten) generations. Our analysis reveals that a simple law governing cell-size control-a noisy linear map-explains the origins of these cell-size oscillations across all strains. This noisy linear map implements a negative feedback on cell-size control: a cell with a larger initial size tends to divide earlier, whereas one with a smaller initial size tends to divide later. Combining simulations of cell growth and division with experimental data, we demonstrate that this noisy linear map generates transient oscillations, not just in cell size, but also in constitutive gene expression. Our work provides new insights into the dynamics of bacterial cell-size regulation with implications for the physiological processes involved.
Effects of listening to music with headphones on hearing--especially under noisy conditions.
Miyake, S; Kumashiro, M
1986-12-01
The purpose of this experiment was to clarify the effects of exposure to music using headphones under noisy conditions on hearing. The most comfortable loudness (MCL) for three kinds of music (Rock, Popular, Japanese songs) decided by two normal hearing subjects was measured under 6 noisy conditions (Train, Subway, Tram, Bus, Underground, Street) in a soundproof room. In the same manner, the MCL of favorite tunes of five subjects were measured. Temporary threshold shift 2 min after exposure (TTS2) to music for 30 min at the highest MCL was obtained. Furthermore, the characteristics such as spectral structures in one-third octave band or level fluctuations (coefficient of variation) were obtained for noise and music and compared. Statistical analysis revealed that MCL in Street was significantly higher than under other conditions and there was no significant differences in MCL among the various types of music. However, the highest MCL was found for Rock. About 20 dB of TTS was observed in one ear and the hazardous of headphones use in noisy conditions was suggested.
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.
Fuzzy difference-of-Gaussian-based iris recognition method for noisy iris images
NASA Astrophysics Data System (ADS)
Kang, Byung Jun; Park, Kang Ryoung; Yoo, Jang-Hee; Moon, Kiyoung
2010-06-01
Iris recognition is used for information security with a high confidence level because it shows outstanding recognition accuracy by using human iris patterns with high degrees of freedom. However, iris recognition accuracy can be reduced by noisy iris images with optical and motion blurring. We propose a new iris recognition method based on the fuzzy difference-of-Gaussian (DOG) for noisy iris images. This study is novel in three ways compared to previous works: (1) The proposed method extracts iris feature values using the DOG method, which is robust to local variations of illumination and shows fine texture information, including various frequency components. (2) When determining iris binary codes, image noises that cause the quantization error of the feature values are reduced with the fuzzy membership function. (3) The optimal parameters of the DOG filter and the fuzzy membership function are determined in terms of iris recognition accuracy. Experimental results showed that the performance of the proposed method was better than that of previous methods for noisy iris images.
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.
Robust optical flow using adaptive Lorentzian filter for image reconstruction under noisy condition
NASA Astrophysics Data System (ADS)
Kesrarat, Darun; Patanavijit, Vorapoj
2017-02-01
In optical flow for motion allocation, the efficient result in Motion Vector (MV) is an important issue. Several noisy conditions may cause the unreliable result in optical flow algorithms. We discover that many classical optical flows algorithms perform better result under noisy condition when combined with modern optimized model. This paper introduces effective robust models of optical flow by using Robust high reliability spatial based optical flow algorithms using the adaptive Lorentzian norm influence function in computation on simple spatial temporal optical flows algorithm. Experiment on our proposed models confirm better noise tolerance in optical flow's MV under noisy condition when they are applied over simple spatial temporal optical flow algorithms as a filtering model in simple frame-to-frame correlation technique. We illustrate the performance of our models by performing an experiment on several typical sequences with differences in movement speed of foreground and background where the experiment sequences are contaminated by the additive white Gaussian noise (AWGN) at different noise decibels (dB). This paper shows very high effectiveness of noise tolerance models that they are indicated by peak signal to noise ratio (PSNR).
Dictionary learning based noisy image super-resolution via distance penalty weight model
Han, Yulan; Zhao, Yongping; Wang, Qisong
2017-01-01
In this study, we address the problem of noisy image super-resolution. Noisy low resolution (LR) image is always obtained in applications, while most of the existing algorithms assume that the LR image is noise-free. As to this situation, we present an algorithm for noisy image super-resolution which can achieve simultaneously image super-resolution and denoising. And in the training stage of our method, LR example images are noise-free. For different input LR images, even if the noise variance varies, the dictionary pair does not need to be retrained. For the input LR image patch, the corresponding high resolution (HR) image patch is reconstructed through weighted average of similar HR example patches. To reduce computational cost, we use the atoms of learned sparse dictionary as the examples instead of original example patches. We proposed a distance penalty model for calculating the weight, which can complete a second selection on similar atoms at the same time. Moreover, LR example patches removed mean pixel value are also used to learn dictionary rather than just their gradient features. Based on this, we can reconstruct initial estimated HR image and denoised LR image. Combined with iterative back projection, the two reconstructed images are applied to obtain final estimated HR image. We validate our algorithm on natural images and compared with the previously reported algorithms. Experimental results show that our proposed method performs better noise robustness. PMID:28759633
Ma, Jianfen; Hu, Yi; Loizou, Philipos C
2009-05-01
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.
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.
A noisy linear map underlies oscillations in cell size and gene expression in bacteria
Tanouchi, Yu; Pai, Anand; Park, Heungwon; Huang, Shuqiang; Stamatov, Rumen; Buchler, Nicolas E.; You, Lingchong
2016-01-01
During bacterial growth, a cell approximately doubles in size prior to division, upon which it splits into two daughter cells. This process is subjected to the inherent perturbations of cellular noise1,2 and thus requires regulation for cell-size homeostasis. The mechanisms underlying cell-size control and their dynamics consequences remain poorly understood due to the difficulty in sizing individual bacteria over long periods of time in a high-throughput manner. Here, we measured and analyzed long-term, single-cell growth and division across different Escherichia coli strains and growth conditions3. We found that a subset of cells in a population exhibited transient oscillations in cell size with periods that stretch across multiple (>10) generations. Our analysis revealed that a simple law governing cell size control – a noisy linear map – explains the origins of these cell-size oscillations across all strains. This noisy linear map implements a negative feedback on cell-size control: a cell with a larger initial size tends to divide earlier, whereas one with a smaller initial size tends to divide later. Combining simulations of cell growth and division with experimental data, we demonstrate that this noisy linear map generates transient oscillations, not just in cell size, but also in constitutive gene expression. Our work provides new insights into the dynamics of bacterial cell-size regulation with implications for the physiological processes involved. PMID:26040722
Dictionary learning based noisy image super-resolution via distance penalty weight model.
Han, Yulan; Zhao, Yongping; Wang, Qisong
2017-01-01
In this study, we address the problem of noisy image super-resolution. Noisy low resolution (LR) image is always obtained in applications, while most of the existing algorithms assume that the LR image is noise-free. As to this situation, we present an algorithm for noisy image super-resolution which can achieve simultaneously image super-resolution and denoising. And in the training stage of our method, LR example images are noise-free. For different input LR images, even if the noise variance varies, the dictionary pair does not need to be retrained. For the input LR image patch, the corresponding high resolution (HR) image patch is reconstructed through weighted average of similar HR example patches. To reduce computational cost, we use the atoms of learned sparse dictionary as the examples instead of original example patches. We proposed a distance penalty model for calculating the weight, which can complete a second selection on similar atoms at the same time. Moreover, LR example patches removed mean pixel value are also used to learn dictionary rather than just their gradient features. Based on this, we can reconstruct initial estimated HR image and denoised LR image. Combined with iterative back projection, the two reconstructed images are applied to obtain final estimated HR image. We validate our algorithm on natural images and compared with the previously reported algorithms. Experimental results show that our proposed method performs better noise robustness.
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.
Tracking multiple-sized objects in low resolution and noisy images
NASA Astrophysics Data System (ADS)
Akhloufi, Moulay
2009-05-01
In recent years, we see an increase of interest for efficient tracking systems in surveillance applications. Many of the proposed techniques work well for good quality images and when objects are within a certain size. When dealing with UAV or surveillance cameras, the images are noisy and many techniques fail to detect and track the real moving objects. This work presents a tracking technique based on a combined spatial and temporal wavelet processing of the image sequence. For sequences coming from an UAV, images are rectified using detected features in the scene. A modified Harris corner detector is used to select points of interest. Regions around these points are matched in successive frames in order to find the transformations between successive images. These transformations are used to stabilize the images and to build a complete scene mosaic from the original sequence during the object tracking. A spatial discrete wavelet transform is then used to extract potential target regions. These detections are refined using a temporal wavelet transform. Mathematical morphology is then used to eliminate targets resulting from image noise. The remaining targets are further processed using Kalman filter. A refinement selection strategy is then performed to keep only the targets obtaining the highest scores. The obtained results are promising and show the possibility of efficiently tracking moving objects in noisy images captured by a moving camera. Also, the proposed technique works efficiently with noisy infrared sequences captured by a surveillance system.
The methods of paired comparisons and magnitude estimation in judging the noisiness of aircraft
NASA Technical Reports Server (NTRS)
Clarke, F. R.; Kryter, K. D.
1972-01-01
The point of subjective equality in regard to perceived noisiness for each of 14 pairs of aircraft noises was obtained using both magnitude estimation technique and the method of paired comparisons. Both methods gave approximately the same estimates of the points of subjective equality for the noise pairs, and both showed similar correspondence to predictive physical measures. Nevertheless, the two methods appear to have greater face validity to the listeners. However, the magnitude estimation technique appears to be more efficient; for a given level of reliability it requires approximately 50% of the testing time required by the paired comparison method. The functions relating physical intensity to the estimated magnitude of subjective noisiness had slopes ranging from about .61 to .29 for the aircraft noises employed in this study, indicating a required change of about 5 to 10 db for a doubling in subjective magnitude. Some physical units of noise measurement were found to be very predictive (standard errors of estimate as low as 1.9 db) of the subjective judgements of noisiness.
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.
Limitations on quantum key repeaters
NASA Astrophysics Data System (ADS)
Bäuml, Stefan; Christandl, Matthias; Horodecki, Karol; Winter, Andreas
2015-04-01
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.
Limitations on quantum key repeaters.
Bäuml, Stefan; Christandl, Matthias; Horodecki, Karol; Winter, Andreas
2015-04-23
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.
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.
NASA Astrophysics Data System (ADS)
Thees, Barnim; Buras, Allan; Jetschke, Gottfried; Kutzbach, Lars; Zorita, Eduardo; Wilmking, Martin
2014-05-01
In paleoclimatology, reconstructions of environmental conditions play a significant role. Such reconstructions rely on the relationship between proxies (e.g. tree-rings, lake sediments) and the processes which are to be reconstructed (e.g. temperature, precipitation, solar activity). However, both of these variable types in general are noisy. For instance, ring-width is only a proxy for tree growth and further determined by several other environmental signals (e.g. precipitation, length of growing season, competition). On the other hand, records of process data that are to be reconstructed are mostly available for too short periods (too short in terms of calibration) at the particular site at which the proxy data have been sampled. The resulting 'spatial' noise (e.g. by using climate station data not situated at the proxy site) causes additional errors in the relationship between measured proxy data and available process data (e.g. Kutzbach et al., 2011). If deriving models from such noisy data, Thees et al. (2009) and Kutzbach et al. (2011) could show (amongst others), that model slopes (the factor with which the one variable is multiplied to predict the other variable) in most cases are misestimated - depending on the ratio of the variances of the respective variable noises. Despite these facts, many recent reconstructions are based on ordinary least squares regressions, which underestimate model slopes as they do not account for the noise in the predictor variable (Kutzbach et al., 2011). This is because there yet only are few methodological approaches available to treat noisy data in terms of modeling, and for those methods additional information (e.g. a good estimate of the error noise ratio) which often is impossible to acquire is needed. Here we introduce the Sequential Iterative NOise Matching Algorithm - SINOMA - with which we are able to derive good estimates for model slopes between noisy time series. The mathematical background of SINOMA is described
Rodriguez, Jose A; Xu, Rui; Chen, Chien-Chun; Zou, Yunfei; Miao, Jianwei
2013-04-01
Coherent diffraction imaging (CDI) is high-resolution lensless microscopy that has been applied to image a wide range of specimens using synchrotron radiation, X-ray free-electron lasers, high harmonic generation, soft X-ray lasers and electrons. Despite recent rapid advances, it remains a challenge to reconstruct fine features in weakly scattering objects such as biological specimens from noisy data. Here an effective iterative algorithm, termed oversampling smoothness (OSS), for phase retrieval of noisy diffraction intensities is presented. OSS exploits the correlation information among the pixels or voxels in the region outside of a support in real space. By properly applying spatial frequency filters to the pixels or voxels outside the support at different stages of the iterative process (i.e. a smoothness constraint), OSS finds a balance between the hybrid input-output (HIO) and error reduction (ER) algorithms to search for a global minimum in solution space, while reducing the oscillations in the reconstruction. Both numerical simulations with Poisson noise and experimental data from a biological cell indicate that OSS consistently outperforms the HIO, ER-HIO and noise robust (NR)-HIO algorithms at all noise levels in terms of accuracy and consistency of the reconstructions. It is expected that OSS will find application in the rapidly growing CDI field, as well as other disciplines where phase retrieval from noisy Fourier magnitudes is needed. The MATLAB (The MathWorks Inc., Natick, MA, USA) source code of the OSS algorithm is freely available from http://www.physics.ucla.edu/research/imaging.
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.
Greenblum, Ayala; Sznitman, Raphael; Fua, Pascal; Arratia, Paulo E; Oren, Meital; Podbilewicz, Benjamin; Sznitman, Josué
2014-06-12
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. 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. 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. Overall, our DTE method allows for robust dendritic tree segmentations in noisy MIPs, outperforming traditional intensity-based methods. Such approach provides a
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.
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.
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.
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.
Critical avalanches and subsampling in map-based neural networks coupled with noisy synapses
NASA Astrophysics Data System (ADS)
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.
Performance of unbalanced QPSK in the presence of noisy reference and crosstalk
NASA Technical Reports Server (NTRS)
Divsalar, D.; Yuen, J. H.
1979-01-01
The problem of transmitting two telemetry data streams having different rates and different powers using unbalanced quadriphase shift keying (UQPSK) signaling is considered. It is noted that the presence of a noisy carrier phase reference causes a degradation in detection performance in coherent communications systems and that imperfect carrier synchronization not only attenuates the main demodulated signal voltage in UQPSK but also produces interchannel interference (crosstalk) which degrades the performance still further. Exact analytical expressions for symbol error probability of UQPSK in the presence of noise phase reference are derived.
NASA Astrophysics Data System (ADS)
Estrada, Antonio; Efimov, Denis; Perruquetti, Wilfrid
2016-09-01
The present work focuses on the problem of velocity and position estimation. A solution is presented for a class of oscillating systems in which position, velocity and acceleration are zero mean signals. The proposed scheme considers that the dynamic model of the system is unknown. Only noisy acceleration measurements, that may be contaminated by zero mean noise and constant bias, are considered to be available. The proposal uses the periodic nature of the signals obtaining finite-time estimations while tackling integration drift accumulation.
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.
Robust layered image transmission based on genetic programming for noisy channels
NASA Astrophysics Data System (ADS)
Hwang, Wen-Jyi; Lin, Ray-Shine; Wu, Chung-Kun
2001-02-01
We present a novel robust layered image transmission design algorithm for noisy channels. In the algorithm, the layered embedded zerotree wavelet coding technique is used to encode the images for the transmission of each layer. A new error protection allocation scheme based on genetic programming is then employed to determine the degree of protection for each layer so that the average distortion of the reconstructed images after transmission can be minimized. Simulation results show that, subject to the same amount of redundancy bits for error protection, the new algorithm outperforms other existing algorithms where equal- protection schemes are adopted.
Retrieving squeezing from classically noisy light in second-harmonic generation
NASA Astrophysics Data System (ADS)
Ralph, T. C.; White, A. G.
1995-05-01
We report the results of a study of the quantum noise properties of a squeezing system involving a three-level laser pumping two similar second-harmonic-generating crystals. We show that squeezing that has been obscured by intensity and phase noise from the pump laser may be retrieved by difference detection of both second-harmonic outputs. Similarly, the squeezed vacuum formed by combining the two outputs on a 50/50 beam splitter will be squeezed at frequencies that are classically noisy in the individual beams.
NASA Astrophysics Data System (ADS)
Treacy, Michael M. J.; Gibson, J. M.
2003-05-01
Flunctuation microscopy is a hybrid diffraction-imaging technique that yields information about higher-order correlations between structural units in materials. It has been shown to be well suited for detecting medium rangeorder in atomic positions in amorphous materials. This article presents a review of flunctuation microscopy as employed in a transmission electron microscope for the study of amorphous tetrahedral semiconductors. Possible extensions of the technique to other radiations such as x-rays, and for other structurally noisy materials such as polymers and starches, are discussed.
2012-03-30
procedure for parameter estimation from noisy data. To cite this article: A.T. Patera, E.M. Rønquist, C. R. Acad. Sci. Paris, Ser . I XXX (2012...une formulation moindres carrés. Les erreurs induites par les données bruitées dans les coefficients EIM aussi bien que les sorties fonctionelle...Paris, Ser . I XXX (2012). Email addresses: patera@mit.edu (Anthony T. Patera), ronquist@math.ntnu.no (Einar M. Rønquist). Preprint submitted to the
Robustness of non-Gaussian entanglement against noisy amplifier and attenuator environments.
Sabapathy, Krishna Kumar; Ivan, J Solomon; Simon, R
2011-09-23
The recently developed Kraus representation for bosonic Gaussian channels is employed to study analytically the robustness of non-Gaussian entanglement against evolution under noisy attenuator and amplifier environments, and compare it with the robustness of Gaussian entanglement. Our results show that some non-Gaussian states with one ebit of entanglement are more robust than all Gaussian states, even the ones with arbitrarily large entanglement, a conclusion of direct consequence to the recent conjecture by Allegra et al. [Phys. Rev. Lett. 105, 100503 (2010)].
Dynamical complexity of short and noisy time series - Compression-Complexity vs. Shannon entropy
NASA Astrophysics Data System (ADS)
Nagaraj, Nithin; Balasubramanian, Karthi
2017-01-01
Shannon entropy has been extensively used for characterizing complexity of time series arising from chaotic dynamical systems and stochastic processes such as Markov chains. However, for short and noisy time series, Shannon entropy performs poorly. Complexity measures which are based on lossless compression algorithms are a good substitute in such scenarios. We evaluate the performance of two such Compression-Complexity Measures namely Lempel-Ziv complexity (LZ) and Effort-To-Compress (ETC) on short time series from chaotic dynamical systems in the presence of noise. Both LZ and ETC outperform Shannon entropy (H) in accurately characterizing the dynamical complexity of such systems. For very short binary sequences (which arise in neuroscience applications), ETC has higher number of distinct complexity values than LZ and H, thus enabling a finer resolution. For two-state ergodic Markov chains, we empirically show that ETC converges to a steady state value faster than LZ. Compression-Complexity measures are promising for applications which involve short and noisy time series.
Low-frequency songs lose their potency in noisy urban conditions
Halfwerk, Wouter; Bot, Sander; Buikx, Jasper; van der Velde, Marco; Komdeur, Jan; ten Cate, Carel; Slabbekoorn, Hans
2011-01-01
Many animal species communicate with their mates through acoustic signals, but this communication seems to become a struggle in urbanized areas because of increasing anthropogenic noise levels. Several bird species have been reported to increase song frequency by which they reduce the masking impact of spectrally overlapping noise. However, it remains unclear whether such behavioral flexibility provides a sufficient solution to noisy urban conditions or whether there are hidden costs. Species may rely on low frequencies to attract and impress females, and the use of high frequencies may, therefore, come at the cost of reduced attractiveness. We studied the potential tradeoff between signal strength and signal detection in a successful urban bird species, the great tit (Parus major). We show that the use of low-frequency songs by males is related to female fertility as well as sexual fidelity. We experimentally show that urban noise conditions impair male–female communication and that signal efficiency depends on song frequency in the presence of noise. Our data reveal a response advantage for high-frequency songs during sexual signaling in noisy conditions, whereas low-frequency songs are likely to be preferred. These data are critical for our understanding of the impact of anthropogenic noise on wild-ranging birds, because they provide evidence for low-frequency songs being linked to reproductive success and to be affected by noise-dependent signal efficiency. PMID:21876157
Gabbard, Ryan; Fendley, Mary; Dar, Irfaan A; Warren, Rik; Kashou, Nasser H
2017-10-01
Occupational noise frequently occurs in the work environment in military intelligence, surveillance, and reconnaissance operations. This impacts cognitive performance by acting as a stressor, potentially interfering with the analysts' decision-making process. We investigated the effects of different noise stimuli on analysts' performance and workload in anomaly detection by simulating a noisy work environment. We utilized functional near-infrared spectroscopy (fNIRS) to quantify oxy-hemoglobin (HbO) and deoxy-hemoglobin concentration changes in the prefrontal cortex (PFC), as well as behavioral measures, which include eye tracking, reaction time, and accuracy rate. We hypothesized that noisy environments would have a negative effect on the participant in terms of anomaly detection performance due to the increase in workload, which would be reflected by an increase in PFC activity. We found that HbO for some of the channels analyzed were significantly different across noise types ([Formula: see text]). Our results also indicated that HbO activation for short-intermittent noise stimuli was greater in the PFC compared to long-intermittent noises. These approaches using fNIRS in conjunction with an understanding of the impact on human analysts in anomaly detection could potentially lead to better performance by optimizing work environments.
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.
How Do Honeybees Attract Nestmates Using Waggle Dances in Dark and Noisy Hives?
Hasegawa, Yuji; Ikeno, Hidetoshi
2011-01-01
It is well known that honeybees share information related to food sources with nestmates using a dance language that is representative of symbolic communication among non-primates. Some honeybee species engage in visually apparent behavior, walking in a figure-eight pattern inside their dark hives. It has been suggested that sounds play an important role in this dance language, even though a variety of wing vibration sounds are produced by honeybee behaviors in hives. It has been shown that dances emit sounds primarily at about 250–300 Hz, which is in the same frequency range as honeybees' flight sounds. Thus the exact mechanism whereby honeybees attract nestmates using waggle dances in such a dark and noisy hive is as yet unclear. In this study, we used a flight simulator in which honeybees were attached to a torque meter in order to analyze the component of bees' orienting response caused only by sounds, and not by odor or by vibrations sensed by their legs. We showed using single sound localization that honeybees preferred sounds around 265 Hz. Furthermore, according to sound discrimination tests using sounds of the same frequency, honeybees preferred rhythmic sounds. Our results demonstrate that frequency and rhythmic components play a complementary role in localizing dance sounds. Dance sounds were presumably developed to share information in a dark and noisy environment. PMID:21603608
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.
Multi-objective optimization with estimation of distribution algorithm in a noisy environment.
Shim, Vui Ann; Tan, Kay Chen; Chia, Jun Yong; Al Mamun, Abdullah
2013-01-01
Many real-world optimization problems are subjected to uncertainties that may be characterized by the presence of noise in the objective functions. The estimation of distribution algorithm (EDA), which models the global distribution of the population for searching tasks, is one of the evolutionary computation techniques that deals with noisy information. This paper studies the potential of EDAs; particularly an EDA based on restricted Boltzmann machines that handles multi-objective optimization problems in a noisy environment. Noise is introduced to the objective functions in the form of a Gaussian distribution. In order to reduce the detrimental effect of noise, a likelihood correction feature is proposed to tune the marginal probability distribution of each decision variable. The EDA is subsequently hybridized with a particle swarm optimization algorithm in a discrete domain to improve its search ability. The effectiveness of the proposed algorithm is examined via eight benchmark instances with different characteristics and shapes of the Pareto optimal front. The scalability, hybridization, and computational time are rigorously studied. Comparative studies show that the proposed approach outperforms other state of the art algorithms.
Rubtsov, Denis V; Griffin, Julian L
2007-10-01
The problem of model detection and parameter estimation for noisy signals arises in different areas of science and engineering including audio processing, seismology, electrical engineering, and NMR spectroscopy. We have adopted the Bayesian modeling framework to jointly detect and estimate signal resonances. This considers a model of the time-domain complex free induction decay (FID) signal as a sum of exponentially damped sinusoidal components. The number of model components and component parameters are considered unknown random variables to be estimated. A Reversible Jump Markov Chain Monte Carlo technique is used to draw samples from the joint posterior distribution on the subspaces of different dimensions. The proposed algorithm has been tested on synthetic data, the (1)H NMR FID of a standard of L-glutamic acid and a blood plasma sample. The detection and estimation performance is compared with Akaike information criterion (AIC), minimum description length (MDL) and the matrix pencil method. The results show the Bayesian algorithm superior in performance especially in difficult cases of detecting low-amplitude and strongly overlapping resonances in noisy signals.
How do honeybees attract nestmates using waggle dances in dark and noisy hives?
Hasegawa, Yuji; Ikeno, Hidetoshi
2011-01-01
It is well known that honeybees share information related to food sources with nestmates using a dance language that is representative of symbolic communication among non-primates. Some honeybee species engage in visually apparent behavior, walking in a figure-eight pattern inside their dark hives. It has been suggested that sounds play an important role in this dance language, even though a variety of wing vibration sounds are produced by honeybee behaviors in hives. It has been shown that dances emit sounds primarily at about 250-300 Hz, which is in the same frequency range as honeybees' flight sounds. Thus the exact mechanism whereby honeybees attract nestmates using waggle dances in such a dark and noisy hive is as yet unclear. In this study, we used a flight simulator in which honeybees were attached to a torque meter in order to analyze the component of bees' orienting response caused only by sounds, and not by odor or by vibrations sensed by their legs. We showed using single sound localization that honeybees preferred sounds around 265 Hz. Furthermore, according to sound discrimination tests using sounds of the same frequency, honeybees preferred rhythmic sounds. Our results demonstrate that frequency and rhythmic components play a complementary role in localizing dance sounds. Dance sounds were presumably developed to share information in a dark and noisy environment.
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.
Effects of auditory and tactile warning on response to visual hazards under a noisy environment.
Murata, Atsuo; Kuroda, Takashi; Karwowski, Waldemar
2017-04-01
A warning signal presented via a visual or an auditory cue might interfere with auditory or visual information inside and outside a vehicle. On the other hand, such interference would be certainly reduced if a tactile cue is used. Therefore, it is expected that tactile cues would be promising as warning signals, especially in a noisy environment. In order to determine the most suitable modality of cue (warning) to a visual hazard in noisy environments, auditory and tactile cues were examined in this study. The condition of stimulus onset asynchrony (SOA) was set to 0ms, 500ms, and 1000ms. Two types of noises were used: white noise and noise outside a vehicle recorded in a real-world driving environment. The noise level LAeq (equivalent continuous A-weighted sound pressure level) inside the experimental chamber of each type of noise was adjusted to approximately 60 dB (A), 70 dB (A), and 80 dB (A). As a result, it was verified that tactile warning was more effective than auditory warning. When the noise outside a vehicle from a real-driving environment was used as the noise inside the experimental chamber, the reaction time to the auditory warning was not affected by the noise level.
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
Probability density of the empirical wavelet coefficients of a noisy chaos
NASA Astrophysics Data System (ADS)
Garcin, Matthieu; Guégan, Dominique
2014-05-01
We are interested in the random empirical wavelet coefficients of a noisy signal when this signal is a unidimensional or multidimensional chaos. More precisely we provide an expression of the conditional probability density of such coefficients, given a discrete observation grid. The noise is assumed to be described by a symmetric alpha-stable random variable. If the noise is a dynamic noise, then we present the exact expression of the probability density of each wavelet coefficient of the noisy signal. If we face a measurement noise, then the noise has a non-linear influence and we propose two approximations. The first one relies on a Taylor expansion whereas the second one, relying on an Edgeworth expansion, improves the first general Taylor approximation if the cumulants of the noise are defined. We give some illustrations of these theoretical results for the logistic map, the tent map and a multidimensional chaos, the Hénon map, disrupted by a Gaussian or a Cauchy noise.
Dynamical complexity of short and noisy time series. Compression-Complexity vs. Shannon entropy
NASA Astrophysics Data System (ADS)
Nagaraj, Nithin; Balasubramanian, Karthi
2017-07-01
Shannon entropy has been extensively used for characterizing complexity of time series arising from chaotic dynamical systems and stochastic processes such as Markov chains. However, for short and noisy time series, Shannon entropy performs poorly. Complexity measures which are based on lossless compression algorithms are a good substitute in such scenarios. We evaluate the performance of two such Compression-Complexity Measures namely Lempel-Ziv complexity (LZ) and Effort-To-Compress (ETC) on short time series from chaotic dynamical systems in the presence of noise. Both LZ and ETC outperform Shannon entropy (H) in accurately characterizing the dynamical complexity of such systems. For very short binary sequences (which arise in neuroscience applications), ETC has higher number of distinct complexity values than LZ and H, thus enabling a finer resolution. For two-state ergodic Markov chains, we empirically show that ETC converges to a steady state value faster than LZ. Compression-Complexity measures are promising for applications which involve short and noisy time series.
Storkel, Holly L.; Lee, Jaehoon; Cox, Casey
2016-01-01
Purpose Noisy conditions make auditory processing difficult. This study explores whether noisy conditions influence the effects of phonotactic probability (the likelihood of occurrence of a sound sequence) and neighborhood density (phonological similarity among words) on adults' word learning. Method Fifty-eight adults learned nonwords varying in phonotactic probability and neighborhood density in either an unfavorable (0-dB signal-to-noise ratio [SNR]) or a favorable (+8-dB SNR) listening condition. Word learning was assessed using a picture naming task by scoring the proportion of phonemes named correctly. Results The unfavorable 0-dB SNR condition showed a significant interaction between phonotactic probability and neighborhood density in the absence of main effects. In particular, adults learned more words when phonotactic probability and neighborhood density were both low or both high. The +8-dB SNR condition did not show this interaction. These results are inconsistent with those from a prior adult word learning study conducted under quiet listening conditions that showed main effects of word characteristics. Conclusions As the listening condition worsens, adult word learning benefits from a convergence of phonotactic probability and neighborhood density. Clinical implications are discussed for potential populations who experience difficulty with auditory perception or processing, making them more vulnerable to noise. PMID:27788276
Sun, Ming; Zhao, Lin; Cao, Wei; Xu, Yaoqun; Dai, Xuefeng; Wang, Xiaoxu
2010-09-01
Noisy chaotic neural network (NCNN), which can exhibit stochastic chaotic simulated annealing (SCSA), has been proven to be a powerful tool in solving combinatorial optimization problems. In order to retain the excellent optimization property of SCSA and improve the optimization performance of the NCNN using hysteretic dynamics without increasing network parameters, we first construct an equivalent model of the NCNN and then control noises in the equivalent model to propose a novel hysteretic noisy chaotic neural network (HNCNN). Compared with the NCNN, the proposed HNCNN can exhibit both SCSA and hysteretic dynamics without introducing extra system parameters, and can increase the effective convergence toward optimal or near-optimal solutions at higher noise levels. Broadcast scheduling problem (BSP) in packet radio networks (PRNs) is to design an optimal time-division multiple-access (TDMA) frame structure with minimal frame length, maximal channel utilization, and minimal average time delay. In this paper, the proposed HNCNN is applied to solve BSP in PRNs to demonstrate its performance. Simulation results show that the proposed HNCNN with higher noise amplitudes is more likely to find an optimal or near-optimal TDMA frame structure with a minimal average time delay than previous algorithms.
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.
Acoustic interaction in animal groups: signaling in noisy and social contexts.
Schwartz, Joshua J; Freeberg, Todd M
2008-08-01
It has long been known that individuals of many species vocally communicate with one another in noisy environments and in rich contexts of social interaction. It has recently become clear that researchers interested in understanding acoustic communication in animal groups must study vocal signaling in these noisy and socially complex settings. Furthermore, recent methodological advances have made it increasingly clear that the authors can tackle these more complex questions effectively. The articles in this Special Issue stem from a Symposium held at the June 2006 meeting of the Acoustical Society of America, and illustrate some of the taxonomic and methodological diversity in studies aimed at understanding how acoustic communication functions in social grouping. This introduction to the Special Issue provides a brief overview of the articles and key ideas in this field of inquiry, and suggests some future directions to take the field to help us understand how social pressures in animal groups may influence, and be influenced by, acoustic signals. (c) 2008 APA, all rights reserved
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.
Noisy decision thresholds can account for suboptimal detection of low coherence motion.
Price, Nicholas S C; VanCuylenberg, John B
2016-01-04
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.
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.
NASA Astrophysics Data System (ADS)
Rfifi, Saad
2016-10-01
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.
Decision forests for machine learning classification of large, noisy seafloor feature sets
NASA Astrophysics Data System (ADS)
Lawson, Ed; Smith, Denson; Sofge, Donald; Elmore, Paul; Petry, Frederick
2017-02-01
Extremely randomized trees (ET) classifiers, an extension of random forests (RF) are applied to classification of features such as seamounts derived from bathymetry data. This data is characterized by sparse training data from by large noisy features sets such as often found in other geospatial data. A variety of feature metrics may be useful for this task and we use a large number of metrics relevant to the task of finding seamounts. The major significant results to be described include: an outstanding seamount classification accuracy of 97%; an automated process to produce the most useful classification features that are relevant to geophysical scientists (as represented by the feature metrics); demonstration that topography provides the most important data representation for classification. As well as achieving good accuracy in classification, the human-understandable set of metrics generated by the classifier that are most relevant for the results are discussed.
Parameter estimation of the FitzHugh-Nagumo model using noisy measurements for membrane potential
NASA Astrophysics Data System (ADS)
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.
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.
Quantum Privacy Amplification and the Security of Quantum Cryptography over Noisy Channels
Deutsch, D.; Ekert, A.; Jozsa, R.; Macchiavello, C.; Popescu, S.; Sanpera, A. ||
1996-09-01
Existing quantum cryptographic schemes are not, as they stand, operable in the presence of noise on the quantum communication channel. Although they become operable if they are supplemented by classical privacy-amplification techniques, the resulting schemes are difficult to analyze and have not been proved secure. We introduce the concept of quantum privacy amplification and a cryptographic scheme incorporating it which is provably secure over a noisy channel. The scheme uses an {open_quote}{open_quote}entanglement purification{close_quote}{close_quote} procedure which, because it requires only a few quantum controlled-not and single-qubit operations, could be implemented using technology that is currently being developed. {copyright} {ital 1996 The American Physical Society.}
Garin, Pierre; Schmerber, Sébastien; Magnan, Jacques; Truy, Eric; Uziel, Alain; Triglia, Jean-Michel; Bebear, Jean-Pierre; Labassi, Samia; Lavieille, Jean-Pierre
2010-12-01
The results support bilateral sequential implantation for patients who are not completely satisfied after implantation of one side. To evaluate the benefit of bilateral Vibrant Soundbridge middle ear implantation as compared with unilateral implantation in quiet and noisy environments. This was a multicentric and retrospective study of 15 patients with symmetrical sensorineural hearing loss who were implanted sequentially in both ears. The performance of each subject was compared under three conditions: with the right implant activated, with the left implant activated, and with both implants activated. Audiometric tests were compared with self-assessment subjective evaluation by questionnaire. Both qualitative and quantitative assessments demonstrated improvement in speech intelligibility, especially in background noise, but also for low voice intensity in quiet.
Texture mapping 3D models of indoor environments with noisy camera poses
NASA Astrophysics Data System (ADS)
Cheng, Peter; Anderson, Michael; He, Stewart; Zakhor, Avideh
2013-03-01
Automated 3D modeling of building interiors is used in applications such as virtual reality and environment mapping. Texturing these models allows for photo-realistic visualizations of the data collected by such modeling systems. While data acquisition times for mobile mapping systems are considerably shorter than for static ones, their recovered camera poses often suffer from inaccuracies, resulting in visible discontinuities when successive images are projected onto a surface for texturing. We present a method for texture mapping models of indoor environments that starts by selecting images whose camera poses are well-aligned in two dimensions. We then align images to geometry as well as to each other, producing visually consistent textures even in the presence of inaccurate surface geometry and noisy camera poses. Images are then composited into a final texture mosaic and projected onto surface geometry for visualization. The effectiveness of the proposed method is demonstrated on a number of different indoor environments.
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.
Enhancement of noisy EDX HRSTEM spectrum-images by combination of filtering and PCA.
Potapov, Pavel; Longo, Paolo; Okunishi, Eiji
2017-05-01
STEM spectrum-imaging with collecting EDX signal is considered in view of the extraction of maximum information from very noisy data. It is emphasized that spectrum-images with weak EDX signal often suffer from information loss in the course of PCA treatment. The loss occurs when the level of random noise exceeds a certain threshold. Weighted PCA, though potentially helpful in isolation of meaningful variations from noise, might provoke the complete loss of information in the situation of weak EDX signal. Filtering datasets prior PCA can improve the situation and recover the lost information. In particular, Gaussian kernel filters are found to be efficient. A new filter useful in the case of sparse atomic-resolution EDX spectrum-images is suggested.
NASA Astrophysics Data System (ADS)
Lasota, Mikołaj; Filip, Radim; Usenko, Vladyslav C.
2017-07-01
Quantum key distribution can be enhanced and extended if nonclassical single-photon states of light are used. We study a connection between the security of quantum key distribution and quantum non-Gaussianity of light arriving at the receiver's detection system after the propagation through a noisy quantum channel, being under full control of an eavesdropper performing general collective attacks. We show that while quantum nonclassicality exhibited by the light arriving at the receiver's station is a necessary indication of the security of the discrete-variable protocols, quantum non-Gaussianity can be a sufficient indication of their security. Therefore, checking for non-Gaussianity of this light by performing standard autocorrelation function measurement can be used for prior verification of the usability of prepare-and-measure schemes. It can play a similar role to the prior verification of the quantum correlations sufficient to violate Bell inequalities for entanglement-based protocols.
Efficient selective repeat ARQ strategies for very noisy and fluctuating channels
NASA Astrophysics Data System (ADS)
Metzner, J. J.; Chang, D.
1985-05-01
Memory and selective repeat ARQ techniques, when channels in both directions are very noisy are investigated, demonstrating that a difficulty arises when memory ARQ is used in these situations, and proposing a remedy, the similarity test. The paper considers a combination of both memory ARQ techniques where an unacknowledged block is retransmitted exactly as before, and modified memory ARQ where alternate transmissions together form a rate 1/2 code. The following items are featured: (1) discussion and analysis of the similarity test, (2) a memory ARQ technique which employs double null zone reception and 3 bits of past-information storage per binary digit, and (3) for modified memory ARQ procedures, a discussion of how to resolve problems of confusing the identity of the two halves of the rate 1/2 code used.
JRSP of three-particle state via three tripartite GHZ class in quantum noisy channels
NASA Astrophysics Data System (ADS)
Falaye, Babatunde James; Sun, Guo-Hua; Camacho-Nieto, Oscar; Dong, Shi-Hai
2016-10-01
We present a scheme for joint remote state preparation (JRSP) of three-particle state via three tripartite Greenberger-Horne-Zeilinger (GHZ) entangled states as the quantum channel linking the parties. We use eight-qubit mutually orthogonal basis vector as measurement point of departure. The likelihood of success for this scheme has been found to be 1/8. However, by putting some special cases into consideration, the chances can be ameliorated to 1/4 and 1. The effects of amplitude-damping noise, phase-damping noise and depolarizing noise on this scheme have been scrutinized and the analytical derivations of fidelities for the quantum noisy channels have been presented. We found that for 0.55≤η≤1, the states conveyed through depolarizing channel lose more information than phase-damping channel while the information loss through amplitude damping channel is most minimal.
Emergent kinetic constraints, ergodicity breaking, and cooperative dynamics in noisy quantum systems
NASA Astrophysics Data System (ADS)
Everest, B.; Marcuzzi, M.; Garrahan, J. P.; Lesanovsky, I.
2016-11-01
Kinetically constrained spin systems play an important role in understanding key properties of the dynamics of slowly relaxing materials, such as glasses. Recent experimental studies have revealed that manifest kinetic constraints govern the evolution of strongly interacting gases of highly excited atoms in a noisy environment. Motivated by this development we explore which types of kinetically constrained dynamics can generally emerge in quantum spin systems subject to strong noise and show how, in this framework, constraints are accompanied by conservation laws. We discuss an experimentally realizable case of a lattice gas, where the interplay between those and the geometry of the lattice leads to collective behavior and time-scale separation even at infinite temperature. This is in contrast to models of glass-forming substances which typically rely on low temperatures and the consequent suppression of thermal activation.
Communication in a noisy environment: Perception of one's own voice and speech enhancement
NASA Astrophysics Data System (ADS)
Le Cocq, Cecile
Workers in noisy industrial environments are often confronted to communication problems. Lost of workers complain about not being able to communicate easily with their coworkers when they wear hearing protectors. In consequence, they tend to remove their protectors, which expose them to the risk of hearing loss. In fact this communication problem is a double one: first the hearing protectors modify one's own voice perception; second they interfere with understanding speech from others. This double problem is examined in this thesis. When wearing hearing protectors, the modification of one's own voice perception is partly due to the occlusion effect which is produced when an earplug is inserted in the car canal. This occlusion effect has two main consequences: first the physiological noises in low frequencies are better perceived, second the perception of one's own voice is modified. In order to have a better understanding of this phenomenon, the literature results are analyzed systematically, and a new method to quantify the occlusion effect is developed. Instead of stimulating the skull with a bone vibrator or asking the subject to speak as is usually done in the literature, it has been decided to excite the buccal cavity with an acoustic wave. The experiment has been designed in such a way that the acoustic wave which excites the buccal cavity does not excite the external car or the rest of the body directly. The measurement of the hearing threshold in open and occluded car has been used to quantify the subjective occlusion effect for an acoustic wave in the buccal cavity. These experimental results as well as those reported in the literature have lead to a better understanding of the occlusion effect and an evaluation of the role of each internal path from the acoustic source to the internal car. The speech intelligibility from others is altered by both the high sound levels of noisy industrial environments and the speech signal attenuation due to hearing
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
2012-01-01
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.
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.
Spurious Doppler maps from noisy spectra and zero-field inversions★
NASA Astrophysics Data System (ADS)
Stift, M. J.; Leone, F.
2017-03-01
Empirical abundance maps derived with the help of Zeeman Doppler mapping are found to be at variance with the predictions of numerical models of atomic diffusion in magnetic atmospheres of ApBp stars. Although theory has often been made responsible for this lack of agreement, direct spectral synthesis based on the published abundance maps reveals that all the chemical inhomogeneities claimed for HD 3980 are entirely spurious, and those of HD 50773 to a large extent. In the former case, this is shown to be due to the neglect of a strong magnetic field, and in the latter case, due to noisy spectra in combination with considerable rotational broadening and ensuing strong line blending. Doppler maps for other magnetic ApBp stars could be affected by similar problems. It is also pointed out that the patchy, extreme overabundances in HD 3980 cannot be reconciled with the theory of stellar atmospheres.
Collective dynamics in two populations of noisy oscillators with asymmetric interactions
NASA Astrophysics Data System (ADS)
Sonnenschein, Bernard; Peron, Thomas K. DM.; Rodrigues, Francisco A.; Kurths, Jürgen; Schimansky-Geier, Lutz
2015-06-01
We study two intertwined globally coupled networks of noisy Kuramoto phase oscillators that have the same natural frequency but differ in their perception of the mean field and their contribution to it. Such a give-and-take mechanism is given by asymmetric in- and out-coupling strengths which can be both positive and negative. We uncover in this minimal network of networks intriguing patterns of discordance, where the ensemble splits into two clusters separated by a constant phase lag. If it differs from π , then traveling wave solutions emerge. We observe a second route to traveling waves via traditional one-cluster states. Bistability is found between the various collective states. Analytical results and bifurcation diagrams are derived with a reduced system.
Stochastic resonant damping in a noisy monostable system: theory and experiment.
Volpe, Giovanni; Perrone, Sandro; Rubi, J Miguel; Petrov, Dmitri
2008-05-01
Usually in the presence of a background noise an increased effort put in controlling a system stabilizes its behavior. Rarely it is thought that an increased control of the system can lead to a looser response and, therefore, to a poorer performance. Strikingly there are many systems that show this weird behavior; examples can be drawn form physical, biological, and social systems. Until now no simple and general mechanism underlying such behaviors has been identified. Here we show that such a mechanism, named stochastic resonant damping, can be provided by the interplay between the background noise and the control exerted on the system. We experimentally verify our prediction on a physical model system based on a colloidal particle held in an oscillating optical potential. Our result adds a tool for the study of intrinsically noisy phenomena, joining the many constructive facets of noise identified in the past decades-for example, stochastic resonance, noise-induced activation, and Brownian ratchets.
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
SOM-based nonlinear least squares twin SVM via active contours for noisy image segmentation
NASA Astrophysics Data System (ADS)
Xie, Xiaomin; Wang, Tingting
2017-02-01
In this paper, a nonlinear least square twin support vector machine (NLSTSVM) with the integration of active contour model (ACM) is proposed for noisy image segmentation. Efforts have been made to seek the kernel-generated surfaces instead of hyper-planes for the pixels belonging to the foreground and background, respectively, using the kernel trick to enhance the performance. The concurrent self organizing maps (SOMs) are applied to approximate the intensity distributions in a supervised way, so as to establish the original training sets for the NLSTSVM. Further, the two sets are updated by adding the global region average intensities at each iteration. Moreover, a local variable regional term rather than edge stop function is adopted in the energy function to ameliorate the noise robustness. Experiment results demonstrate that our model holds the higher segmentation accuracy and more noise robustness.
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.
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.
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
A revisit to non-maximally entangled mixed states: teleportation witness, noisy channel and discord
NASA Astrophysics Data System (ADS)
Roy, Sovik; Ghosh, Biplab
2017-04-01
We constructed a class of non-maximally entangled mixed states (Adhikari et al. in Quantum Inf Comput 10:0398, 2010) and extensively studied their entanglement properties and also their usefulness as teleportation channels. In this article, we have revisited our constructed state and have studied it from three different perspectives. Since every entangled state is associated with a witness operator, we have found a suitable entanglement as well as teleportation witness operator for our non-maximally entangled mixed states. We considered the noisy channel's effects on our constructed states to see how much it affects the states' capacities as teleportation channels. For this purpose, we have mainly focussed on amplitude damping channel. A comparative study on concurrence and quantum discord of our constructed state of Adhikari et al. (2010) has also been carried out here.
Celik, Hasan; Shaka, A J
2010-11-01
The Filter Diagonalization Method (FDM) has been used to process NMR data in liquids and can be advantageous when the spectrum is sparse enough, the lines are sharp and Lorentzian, raw sensitivity is adequate, and the measured time-domain data is short, so that the Fourier Transform spectrum exhibits distorted line shapes. Noise can adversely impact resolution and/or frequency accuracy in FDM spectral estimates. Paradoxically, more complete data can lead to worse FDM spectra if there is appreciable noise. However, by modifying the numerical method, the FDM noise performance improves significantly, without apparently losing any of the existing advantages. The two key modifications are to adjust the FDM basis functions so that matrix elements computed from them have less noise contribution on average, and to regularize each dimension of a multidimensional spectrum independently. The modifications can be recommended for general-purpose use in the case of somewhat noisy, incomplete data. Copyright © 2010 Elsevier Inc. All rights reserved.
Nickerson, Naomi H; Li, Ying; Benjamin, Simon C
2013-01-01
A scalable quantum computer could be built by networking together many simple processor cells, thus avoiding the need to create a single complex structure. The difficulty is that realistic quantum links are very error prone. A solution is for cells to repeatedly communicate with each other and so purify any imperfections; however prior studies suggest that the cells themselves must then have prohibitively low internal error rates. Here we describe a method by which even error-prone cells can perform purification: groups of cells generate shared resource states, which then enable stabilization of topologically encoded data. Given a realistically noisy network (≥10% error rate) we find that our protocol can succeed provided that intra-cell error rates for initialisation, state manipulation and measurement are below 0.82%. This level of fidelity is already achievable in several laboratory systems.
Motion-adaptive weighted averaging for temporal filtering of noisy image sequences
NASA Astrophysics Data System (ADS)
Ozkan, Mehmet K.; Sezan, M. Ibrahim; Tekalp, A. Murat
1992-05-01
An algorithm for motion-adaptive, temporal filtering of noisy image sequences is proposed. The algorithm is applied in the temporal domain along motion trajectories that are determined using a robust motion estimation algorithm. Filtering is performed by computing weighted averages of image values over estimated motion trajectories. The weights are determined by optimizing a well-defined mathematical criterion so that they vary with respect to the accuracy of motion estimation, and hence the adaptivity of the algorithm. Our results suggest that the proposed algorithm is very effective in suppressing noise without over-smoothing the image detail. Further, the proposed algorithm is particularly well-suited for filtering sequences that contain segments with changing scene content due to a number of reasons such as rapid zooming, changes in the view of the camera, scene illumination, and in the place and time of image recording. Existing algorithms, in general, perform poorly in such cases.
An experimental implementation of oblivious transfer in the noisy storage model
NASA Astrophysics Data System (ADS)
Erven, C.; Ng, N.; Gigov, N.; Laflamme, R.; Wehner, S.; Weihs, G.
2014-03-01
Cryptography’s importance in our everyday lives continues to grow in our increasingly digital world. Oblivious transfer has long been a fundamental and important cryptographic primitive, as it is known that general two-party cryptographic tasks can be built from this basic building block. Here we show the experimental implementation of a 1-2 random oblivious transfer protocol by performing measurements on polarization-entangled photon pairs in a modified entangled quantum key distribution system, followed by all of the necessary classical postprocessing including one-way error correction. We successfully exchange a 1,366 bit random oblivious transfer string in ~3 min and include a full security analysis under the noisy storage model, accounting for all experimental error rates and finite size effects. This demonstrates the feasibility of using today’s quantum technologies to implement secure two-party protocols.
Nickerson, Naomi H.; Li, Ying; Benjamin, Simon C.
2013-01-01
A scalable quantum computer could be built by networking together many simple processor cells, thus avoiding the need to create a single complex structure. The difficulty is that realistic quantum links are very error prone. A solution is for cells to repeatedly communicate with each other and so purify any imperfections; however prior studies suggest that the cells themselves must then have prohibitively low internal error rates. Here we describe a method by which even error-prone cells can perform purification: groups of cells generate shared resource states, which then enable stabilization of topologically encoded data. Given a realistically noisy network (≥10% error rate) we find that our protocol can succeed provided that intra-cell error rates for initialisation, state manipulation and measurement are below 0.82%. This level of fidelity is already achievable in several laboratory systems. PMID:23612297
Unwrapping noisy phase maps by use of a minimum-cost-matching algorithm
NASA Astrophysics Data System (ADS)
Buckland, J. R.; Huntley, J. M.; Turner, S. R. E.
1995-08-01
An algorithm for unwrapping noisy phase maps by means of branch cuts has been proposed recently. These cuts join discontinuity sources that mark the beginning or end of a 2 pi phase discontinuity. After the placement of branch cuts, the unwrapped phase map is unique and independent of the unwrapping route. We show how a minimum-cost-matching graph-theory method can be used to find the set of cuts that has the global minimum of total cut length, in time approximately proportional to the square of the number of sources. The method enables one to unwrap unfiltered speckle-interferometry phase maps at higher source densities (0.1 sources pixel-1) than any previous branch-cut placement algorithm.
An improved teaching-learning based robust edge detection algorithm for noisy images.
Thirumavalavan, Sasirooba; Jayaraman, Sasikala
2016-11-01
This paper presents an improved Teaching Learning Based Optimization (TLO) and a methodology for obtaining the edge maps of the noisy real life digital images. TLO is a population based algorithm that simulates the teaching-learning mechanism in class rooms, comprising two phases of teaching and learning. The 'Teaching Phase' represents learning from the teacher and 'Learning Phase' indicates learning by the interaction between learners. This paper introduces a third phase denoted by "Avoiding Phase" that helps to keep the learners away from the worst students with a view of exploring the problem space more effectively and escaping from the sub-optimal solutions. The improved TLO (ITLO) explores the solution space and provides the global best solution. The edge detection problem is formulated as an optimization problem and solved using the ITLO. The results of real life and medical images illustrate the performance of the developed method.
Inferring solutions of differential equations using noisy multi-fidelity data
NASA Astrophysics Data System (ADS)
Raissi, Maziar; Perdikaris, Paris; Karniadakis, George Em
2017-04-01
For more than two centuries, solutions of differential equations have been obtained either analytically or numerically based on typically well-behaved forcing and boundary conditions for well-posed problems. We are changing this paradigm in a fundamental way by establishing an interface between probabilistic machine learning and differential equations. We develop data-driven algorithms for general linear equations using Gaussian process priors tailored to the corresponding integro-differential operators. The only observables are scarce noisy multi-fidelity data for the forcing and solution that are not required to reside on the domain boundary. The resulting predictive posterior distributions quantify uncertainty and naturally lead to adaptive solution refinement via active learning. This general framework circumvents the tyranny of numerical discretization as well as the consistency and stability issues of time-integration, and is scalable to high-dimensions.
NASA Astrophysics Data System (ADS)
Huber, Martin; Braun, Hans; Krieg, J.\\:Urgen-Christian
2004-03-01
Sensitization is discussed as an important phenomenon playing a role in normal physiology but also with respect to the initiation and progression of a variety of neuropsychiatric disorders such as epilepsia, substance-related disorders or recurrent affective disorders. The relevance to understand the dynamics of sensitization phenomena is emphasized by recent findings that even single stimulations can induce longlasting changes in biological systems. To address specific questions associated with the sensitization dynamics, we use a computational approach and develop simple but physiologically-plausible models. In the present study we examine the effect of noisy stimulation on sensitization development in the model. We consider sub- and suprathresold stimulations with varying noise intensities and determine as response measures the (i) absolute number of stimulus-induced sensitzations and (ii) the temporal relsation of stimulus-sensitization coupling. The findings indicate that stochastic effects including stochastic resonance might well contribute to the physiology of sensitization mechanisms under both nomal and pathological conditions.
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.
Collective dynamics in two populations of noisy oscillators with asymmetric interactions.
Sonnenschein, Bernard; Peron, Thomas K Dm; Rodrigues, Francisco A; Kurths, Jürgen; Schimansky-Geier, Lutz
2015-06-01
We study two intertwined globally coupled networks of noisy Kuramoto phase oscillators that have the same natural frequency but differ in their perception of the mean field and their contribution to it. Such a give-and-take mechanism is given by asymmetric in- and out-coupling strengths which can be both positive and negative. We uncover in this minimal network of networks intriguing patterns of discordance, where the ensemble splits into two clusters separated by a constant phase lag. If it differs from π, then traveling wave solutions emerge. We observe a second route to traveling waves via traditional one-cluster states. Bistability is found between the various collective states. Analytical results and bifurcation diagrams are derived with a reduced system.
Joint remote state preparation (JRSP) of two-qubit equatorial state in quantum noisy channels
NASA Astrophysics Data System (ADS)
Adepoju, Adenike Grace; Falaye, Babatunde James; Sun, Guo-Hua; Camacho-Nieto, Oscar; Dong, Shi-Hai
2017-02-01
This letter reports the influence of noisy channels on JRSP of two-qubit equatorial state. We present a protocol for JRSP of two-qubit equatorial state. Afterward, we investigate the effects of five quantum noises on the protocol. We find that the system loses some of its properties as consequence of unwanted interactions with environment. For instance, within the domain 0 < λ < 0.65, the information lost via transmission of qubits in amplitude channel is most minimal, while for 0.65 < λ ≤ 1, the information lost in phase flip channel becomes the most minimal. Also, for any given λ, the information transmitted through depolarizing channel has the least chance of success.
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. ©2013 Published by ISA. All rights reserved.
Everest, B; Marcuzzi, M; Garrahan, J P; Lesanovsky, I
2016-11-01
Kinetically constrained spin systems play an important role in understanding key properties of the dynamics of slowly relaxing materials, such as glasses. Recent experimental studies have revealed that manifest kinetic constraints govern the evolution of strongly interacting gases of highly excited atoms in a noisy environment. Motivated by this development we explore which types of kinetically constrained dynamics can generally emerge in quantum spin systems subject to strong noise and show how, in this framework, constraints are accompanied by conservation laws. We discuss an experimentally realizable case of a lattice gas, where the interplay between those and the geometry of the lattice leads to collective behavior and time-scale separation even at infinite temperature. This is in contrast to models of glass-forming substances which typically rely on low temperatures and the consequent suppression of thermal activation.
Multi-Robot, Multi-Target Particle Swarm Optimization Search in Noisy Wireless Environments
Kurt Derr; Milos Manic
2009-05-01
Multiple small robots (swarms) can work together using Particle Swarm Optimization (PSO) to perform tasks that are difficult or impossible for a single robot to accomplish. The problem considered in this paper is exploration of an unknown environment with the goal of finding a target(s) at an unknown location(s) using multiple small mobile robots. This work demonstrates the use of a distributed PSO algorithm with a novel adaptive RSS weighting factor to guide robots for locating target(s) in high risk environments. The approach was developed and analyzed on multiple robot single and multiple target search. The approach was further enhanced by the multi-robot-multi-target search in noisy environments. The experimental results demonstrated how the availability of radio frequency signal can significantly affect robot search time to reach a target.
NASA Astrophysics Data System (ADS)
Delpueyo, D.; Balandraud, X.; Grédiac, M.
2013-09-01
The aim of this paper is to present a post-processing technique based on a derivative Gaussian filter to reconstruct heat source fields from temperature fields measured by infrared thermography. Heat sources can be deduced from temperature variations thanks to the heat diffusion equation. Filtering and differentiating are key-issues which are closely related here because the temperature fields which are processed are unavoidably noisy. We focus here only on the diffusion term because it is the most difficult term to estimate in the procedure, the reason being that it involves spatial second derivatives (a Laplacian for isotropic materials). This quantity can be reasonably estimated using a convolution of the temperature variation fields with second derivatives of a Gaussian function. The study is first based on synthetic temperature variation fields corrupted by added noise. The filter is optimised in order to reconstruct at best the heat source fields. The influence of both the dimension and the level of a localised heat source is discussed. Obtained results are also compared with another type of processing based on an averaging filter. The second part of this study presents an application to experimental temperature fields measured with an infrared camera on a thin plate in aluminium alloy. Heat sources are generated with an electric heating patch glued on the specimen surface. Heat source fields reconstructed from measured temperature fields are compared with the imposed heat sources. Obtained results illustrate the relevancy of the derivative Gaussian filter to reliably extract heat sources from noisy temperature fields for the experimental thermomechanics of materials.
The efficient solution of the (quietly constrained) noisy, linear regulator problem
NASA Astrophysics Data System (ADS)
Gregory, John; Hughes, H. R.
2007-09-01
In a previous paper we gave a new, natural extension of the calculus of variations/optimal control theory to a (strong) stochastic setting. We now extend the theory of this most fundamental chapter of optimal control in several directions. Most importantly we present a new method of stochastic control, adding Brownian motion which makes the problem "noisy." Secondly, we show how to obtain efficient solutions: direct stochastic integration for simpler problems and/or efficient and accurate numerical methods with a global a priori error of O(h3/2) for more complex problems. Finally, we include "quiet" constraints, i.e. deterministic relationships between the state and control variables. Our theory and results can be immediately restricted to the non "noisy" (deterministic) case yielding efficient, numerical solution techniques and an a priori error of O(h2)E In this event we obtain the most efficient method of solving the (constrained) classical Linear Regulator Problem. Our methods are different from the standard theory of stochastic control. In some cases the solutions coincide or at least are closely related. However, our methods have many advantages including those mentioned above. In addition, our methods more directly follow the motivation and theory of classical (deterministic) optimization which is perhaps the most important area of physical and engineering science. Our results follow from related ideas in the deterministic theory. Thus, our approximation methods follow by guessing at an algorithm, but the proof of global convergence uses stochastic techniques because our trajectories are not differentiable. Along these lines, a general drift term in the trajectory equation is properly viewed as an added constraint and extends ideas given in the deterministic case by the first author.
MRS experiments in a noisy area of a detrital aquifer in the south of Spain
NASA Astrophysics Data System (ADS)
Plata, Juan; Rubio, Felix
2002-05-01
The signal measured in a Magnetic Resonance Sounding (MRS) is of very low amplitude, of the order of tens of nanovolts and is very easily disturbed by the presence of electromagnetic noise of industrial or natural origin. To expand the capabilities of this new geophysical method, it is of great importance to develop field and analytical techniques to reduce the influence of noise in the final results of the MRS. Some field techniques are analyzed in this paper, for several MRS taken in a noisy area at a detrital aquifer in the south of Spain. Two kinds of noise are present, both of amplitude higher than 1500 nV: continuous random noise and spiky noise, with bursts of very high amplitude and occurrence depending on the site and on the time of the day. Trial records made at these places are of little significance, and only complete records taken with the most suitable size, shape and orientation of the antenna, and with a large stacking number, allow to detect the decay pattern of the signal coming from the water-rich layers. The appropriate design of these recording parameters have proven capable of diminishing the effect of random noise, but the results are not as good for spikes, which demand the use of different techniques. The knowledge of the noise pattern obtained in the MRS measurement could be used to design digital filters to attenuate noise influence, together with the aid of surgical muting. The interpretation of the field data has been made without any prior knowledge of the geological information. Despite the high noise level observed on this site, the inversion result achieved present a remarkable correlation with geological data for the water content distribution and are worse for the decay time determination, which seems to be more affected by the existence of noise. Phase and frequency seem to be good quality control parameters before inverting the data, regardless the noisy aspect of the recorded values.
NASA Technical Reports Server (NTRS)
Brown, C. M., Jr.; Monopoli, R. V.
1974-01-01
A linear system identification technique developed by Lion is adapted for use on a third-order system with six unknown parameters and noisy input-output measurements. A digital computer is employed so that rapid identification takes place with only two state variable filters. Bias in the parameter estimates is partially eliminated by a signal-to-noise ratio testing procedure.
A method for subsample fetal heart rate estimation under noisy conditions.
Sahin, Ismet; Yilmazer, Nuri; Simaan, Marwan A
2010-04-01
difference function methods shows that our approach achieves very accurate period estimation results for both simulated and real fetal EGC waveforms that are taken at different stages of the gestation under noisy conditions.agnitude difference function methods shows that our approach achieves very accurate period estimation results for both simulated and real fetal EGC waveforms that are taken at different stages of the gestation under noisy conditions.
Fujimoto, Chisato; Yamamoto, Yoshiharu; Kamogashira, Teru; Kinoshita, Makoto; Egami, Naoya; Uemura, Yukari; Togo, Fumiharu; Yamasoba, Tatsuya; Iwasaki, Shinichi
2016-01-01
Vestibular dysfunction causes postural instability, which is prevalent in the elderly. We previously showed that an imperceptible level of noisy galvanic vestibular stimulation (nGVS) can improve postural stability in patients with bilateral vestibulopathy during the stimulus, presumably by enhancing vestibular information processing. In this study, we investigated the after-effects of an imperceptible long-duration nGVS on body balance in elderly adults. Thirty elderly participants underwent two nGVS sessions in a randomised order. In Session 1, participants received nGVS for 30 min twice with a 4-h interval. In Session 2, participants received nGVS for 3 h. Two-legged stance tasks were performed with eyes closed while participants stood on a foam rubber surface, with and without nGVS, and parameters related to postural stability were measured using posturography. In both sessions, the postural stability was markedly improved for more than 2 h after the cessation of the stimulus and tended to decrease thereafter. The second stimulation in Session 1 caused a moderate additional improvement in body balance and promoted the sustainability of the improvement. These results suggest that nGVS can lead to a postural stability improvement in elderly adults that lasts for several hours after the cessation of the stimulus, probably via vestibular neuroplasticity. PMID:27869225
Garcia-Ojalvo, Jordi; Süel, Gürol M.
2011-01-01
Cells must make reliable decisions under fluctuating extracellular conditions, but also be flexible enough to adapt to such changes. How cells reconcile these seemingly contradictory requirements through the dynamics of cellular decision-making is poorly understood. To study this issue we quantitatively measured gene expression and protein localization in single cells of the model organism Bacillus subtilis during the progression to spore formation. We found that sporulation proceeded through noisy and reversible steps towards an irreversible, all-or-none commitment point. Specifically, we observed cell-autonomous and spontaneous bursts of gene expression and transient protein localization events during sporulation. Based on these measurements we developed mathematical population models to investigate how the degree of reversibility affects cellular decision-making. In particular, we evaluated the effect of reversibility on the 1) reliability in the progression to sporulation, and 2) adaptability under changing extracellular stress conditions. Results show that reversible progression allows cells to remain responsive to long-term environmental fluctuations. In contrast, the irreversible commitment point supports reliable execution of cell fate choice that is robust against short-term reductions in stress. This combination of opposite dynamic behaviors (reversible and irreversible) thus maximizes both adaptable and reliable decision-making over a broad range of changes in environmental conditions. These results suggest that decision-making systems might employ a general hybrid strategy to cope with unpredictably fluctuating environmental conditions. PMID:22102806
Long-distance quantum communication over noisy networks without long-time quantum memory
NASA Astrophysics Data System (ADS)
Mazurek, Paweł; Grudka, Andrzej; Horodecki, Michał; Horodecki, Paweł; Łodyga, Justyna; Pankowski, Łukasz; PrzysieŻna, Anna
2014-12-01
The problem of sharing entanglement over large distances is crucial for implementations of quantum cryptography. A possible scheme for long-distance entanglement sharing and quantum communication exploits networks whose nodes share Einstein-Podolsky-Rosen (EPR) pairs. In Perseguers et al. [Phys. Rev. A 78, 062324 (2008), 10.1103/PhysRevA.78.062324] the authors put forward an important isomorphism between storing quantum information in a dimension D and transmission of quantum information in a D +1 -dimensional network. We show that it is possible to obtain long-distance entanglement in a noisy two-dimensional (2D) network, even when taking into account that encoding and decoding of a state is exposed to an error. For 3D networks we propose a simple encoding and decoding scheme based solely on syndrome measurements on 2D Kitaev topological quantum memory. Our procedure constitutes an alternative scheme of state injection that can be used for universal quantum computation on 2D Kitaev code. It is shown that the encoding scheme is equivalent to teleporting the state, from a specific node into a whole two-dimensional network, through some virtual EPR pair existing within the rest of network qubits. We present an analytic lower bound on fidelity of the encoding and decoding procedure, using as our main tool a modified metric on space-time lattice, deviating from a taxicab metric at the first and the last time slices.
NASA Astrophysics Data System (ADS)
Mutch, W. Alan C.
2005-05-01
Life support with a mechanical ventilator is used to manage patients with a variety of lung diseases including acute respiratory distress syndrome (ARDS). Recently, management of ARDS has concentrated on ventilating at lower airway pressure using lower tidal volume. A large international study demonstrated a 22% reduction in mortality with the low tidal volume approach. The potential advantages of adding physiologic noise with fractal characteristics to the respiratory rate and tidal volume as delivered by a mechanical ventilator are discussed. A so-called biologically variable ventilator (BVV), incorporating such noise, has been developed. Here we show that the benefits of noisy ventilation - at lower tidal volumes - can be deduced from a simple probabilistic result known as Jensen"s Inequality. Using the local convexity of the pressure-volume relationship in the lung we demonstrate that the addition of noise results in higher mean tidal volume or lower mean airway pressure. The consequence is enhanced gas exchange or less stress on the lungs, both clinically desirable. Jensen"s Inequality has important considerations in engineering, information theory and thermodynamics. Here is an example of the concept applied to medicine that may have important considerations for the clinical management of critically ill patients. Life support devices, such as mechanical ventilators, are of vital use in critical care units and operating rooms. These devices usually have monotonous output. Improving mechanical ventilators and other life support devices may be as simple as adding noise to their output signals.
Broadband Processing in a Noisy Shallow Ocean Environment: A Particle Filtering Approach
Candy, J. V.
2016-04-14
Here we report that when a broadband source propagates sound in a shallow ocean the received data can become quite complicated due to temperature-related sound-speed variations and therefore a highly dispersive environment. Noise and uncertainties disrupt this already chaotic environment even further because disturbances propagate through the same inherent acoustic channel. The broadband (signal) estimation/detection problem can be decomposed into a set of narrowband solutions that are processed separately and then combined to achieve more enhancement of signal levels than that available from a single frequency, thereby allowing more information to be extracted leading to a more reliable source detection. A Bayesian solution to the broadband modal function tracking, pressure-field enhancement, and source detection problem is developed that leads to nonparametric estimates of desired posterior distributions enabling the estimation of useful statistics and an improved processor/detector. In conclusion, to investigate the processor capabilities, we synthesize an ensemble of noisy, broadband, shallow-ocean measurements to evaluate its overall performance using an information theoretical metric for the preprocessor and the receiver operating characteristic curve for the detector.
Broadband Processing in a Noisy Shallow Ocean Environment: A Particle Filtering Approach
Candy, J. V.
2016-04-14
Here we report that when a broadband source propagates sound in a shallow ocean the received data can become quite complicated due to temperature-related sound-speed variations and therefore a highly dispersive environment. Noise and uncertainties disrupt this already chaotic environment even further because disturbances propagate through the same inherent acoustic channel. The broadband (signal) estimation/detection problem can be decomposed into a set of narrowband solutions that are processed separately and then combined to achieve more enhancement of signal levels than that available from a single frequency, thereby allowing more information to be extracted leading to a more reliable source detection.more » A Bayesian solution to the broadband modal function tracking, pressure-field enhancement, and source detection problem is developed that leads to nonparametric estimates of desired posterior distributions enabling the estimation of useful statistics and an improved processor/detector. In conclusion, to investigate the processor capabilities, we synthesize an ensemble of noisy, broadband, shallow-ocean measurements to evaluate its overall performance using an information theoretical metric for the preprocessor and the receiver operating characteristic curve for the detector.« less
The outbreak of cooperation among success-driven individuals under noisy conditions
Helbing, Dirk; Yu, Wenjian
2009-01-01
According to Thomas Hobbes' Leviathan [1651; 2008 (Touchstone, New York), English Ed], “the life of man [is] solitary, poor, nasty, brutish, and short,” and it would need powerful social institutions to establish social order. In reality, however, social cooperation can also arise spontaneously, based on local interactions rather than centralized control. The self-organization of cooperative behavior is particularly puzzling for social dilemmas related to sharing natural resources or creating common goods. Such situations are often described by the prisoner's dilemma. Here, we report the sudden outbreak of predominant cooperation in a noisy world dominated by selfishness and defection, when individuals imitate superior strategies and show success-driven migration. In our model, individuals are unrelated, and do not inherit behavioral traits. They defect or cooperate selfishly when the opportunity arises, and they do not know how often they will interact or have interacted with someone else. Moreover, our individuals have no reputation mechanism to form friendship networks, nor do they have the option of voluntary interaction or costly punishment. Therefore, the outbreak of prevailing cooperation, when directed motion is integrated in a game-theoretical model, is remarkable, particularly when random strategy mutations and random relocations challenge the formation and survival of cooperative clusters. Our results suggest that mobility is significant for the evolution of social order, and essential for its stabilization and maintenance. PMID:19237576
Shen, Hui-min; Lee, Kok-Meng; Hu, Liang; Foong, Shaohui; Fu, Xin
2016-01-01
Localization of active neural source (ANS) from measurements on head surface is vital in magnetoencephalography. As neuron-generated magnetic fields are extremely weak, significant uncertainties caused by stochastic measurement interference complicate its localization. This paper presents a novel computational method based on reconstructed magnetic field from sparse noisy measurements for enhanced ANS localization by suppressing effects of unrelated noise. In this approach, the magnetic flux density (MFD) in the nearby current-free space outside the head is reconstructed from measurements through formulating the infinite series solution of the Laplace's equation, where boundary condition (BC) integrals over the entire measurements provide "smooth" reconstructed MFD with the decrease in unrelated noise. Using a gradient-based method, reconstructed MFDs with good fidelity are selected for enhanced ANS localization. The reconstruction model, spatial interpolation of BC, parametric equivalent current dipole-based inverse estimation algorithm using reconstruction, and gradient-based selection are detailed and validated. The influences of various source depths and measurement signal-to-noise ratio levels on the estimated ANS location are analyzed numerically and compared with a traditional method (where measurements are directly used), and it was demonstrated that gradient-selected high-fidelity reconstructed data can effectively improve the accuracy of ANS localization.
Kernel estimation for robust motion deblurring of noisy and blurry images
NASA Astrophysics Data System (ADS)
Sun, Shijie; Zhao, Huaici; Li, Bo; Hao, Mingguo; Lv, Jinfeng
2016-05-01
Most state-of-the-art single image blind deblurring techniques are still sensitive to image noise, leading to serious performance degradation in their blur kernel estimation when the input image noise increases. We found that reliable kernel estimation could not be given by directly using denoising and existing deblurring algorithms in many cases. We focus on how to estimate a good blur kernel from a noisy blurred image via using the image structure. First, we applied denoising as a preprocess to remove the input image noise and then computed salient image structure of the denoised result based on the total variation model. We also applied a gradient selection method to remove those salient edges that have a possible adverse effect on blur kernel estimation. Next, we adopted a two-phase estimation strategy to obtain higher quality blur kernel estimation by jointly applying kernel estimation from salient image structure and iterative support detection (ISD) kernel refinement. Finally, we used the nonblind deconvolution method based on sparse prior knowledge to restore the latent image. Extensive experiments testify to the superiority of the proposed method over state-of-the-art algorithms, both qualitatively and quantitatively.
Crack detection in beams in noisy conditions using scale fractal dimension analysis of mode shapes
NASA Astrophysics Data System (ADS)
Bai, R. B.; Ostachowicz, W.; Cao, M. S.; Su, Z.
2014-06-01
Fractal dimension analysis of mode shapes has been actively studied in the area of structural damage detection. The most prominent features of fractal dimension analysis are high sensitivity to damage and instant determination of damage location. However, an intrinsic deficiency is its susceptibility to measurement noise, likely obscuring the features of damage. To address this deficiency, this study develops a novel damage detection method, scale fractal dimension (SFD) analysis of mode shapes, based on combining the complementary merits of a stationary wavelet transform (SWT) and Katz’s fractal dimension in damage characterization. With this method, the SWT is used to decompose a mode shape into a set of scale mode shapes at scale levels, with damage information and noise separated into distinct scale mode shapes because of their dissimilar scale characteristics; the Katz’s fractal dimension individually runs on every scale mode shape in the noise-adaptive condition provided by the SWT to canvass damage. Proof of concept for the SFD analysis is performed on cracked beams simulated by the spectral finite element method; the reliability of the method is assessed using Monte Carlo simulation to mimic the operational variability in realistic damage diagnosis. The proposed method is further experimentally validated on a cracked aluminum beam with mode shapes acquired by a scanning laser vibrometer. The results show that the SFD analysis of mode shapes provides a new strategy for damage identification in noisy conditions.
The outbreak of cooperation among success-driven individuals under noisy conditions.
Helbing, Dirk; Yu, Wenjian
2009-03-10
According to Thomas Hobbes' Leviathan [1651; 2008 (Touchstone, New York), English Ed], "the life of man [is] solitary, poor, nasty, brutish, and short," and it would need powerful social institutions to establish social order. In reality, however, social cooperation can also arise spontaneously, based on local interactions rather than centralized control. The self-organization of cooperative behavior is particularly puzzling for social dilemmas related to sharing natural resources or creating common goods. Such situations are often described by the prisoner's dilemma. Here, we report the sudden outbreak of predominant cooperation in a noisy world dominated by selfishness and defection, when individuals imitate superior strategies and show success-driven migration. In our model, individuals are unrelated, and do not inherit behavioral traits. They defect or cooperate selfishly when the opportunity arises, and they do not know how often they will interact or have interacted with someone else. Moreover, our individuals have no reputation mechanism to form friendship networks, nor do they have the option of voluntary interaction or costly punishment. Therefore, the outbreak of prevailing cooperation, when directed motion is integrated in a game-theoretical model, is remarkable, particularly when random strategy mutations and random relocations challenge the formation and survival of cooperative clusters. Our results suggest that mobility is significant for the evolution of social order, and essential for its stabilization and maintenance.
Information extraction from noisy televiewer logs of inclined holes in hard rock
Burns, K.L.
1985-01-01
A feature-extraction method was adapted from satellite image-processing to the problem of extracting information from extremely noisy and narrow-range televiewer imagery from GT-2 at Fenton Hill. From televiewer logs, 733 structures were recovered, compared with 42 from core. The average spacings were 3.13 and 0.55 feet, respectively, indicating that the televiewer yielded only 17.5% of the information available from core. Two televiewer runs overlapped between 4000 and 4275 feet depth, but no detectable structures were repeated on both runs. The lack of repetition was explained as due to random processes arising from thermally-induced electronic noise and manually-operated narrow-range recording. Two new coefficients of association were defined, termed ''coplanarity'' P, and ''collinearity'', L, respectively. The coplanarity of foliations demonstrated that, despite no repetition of individuals, the two runs could be correlated. The coplanarity averaged 60 degrees, falling to 43.5 degrees at match, at a lag of -4.5 feet. There was no systematic maximum in the coplanarity for fractures, indicating that these were not serially-correlated. A periodicity in the collinearity for foliations indicated a set of folds with wavelength of 80 feet. 8 refs., 10 figs.
Stochastic versus chaotic behaviour in the noisy generalized Kuramoto-Sivashinsky equation
NASA Astrophysics Data System (ADS)
Gotoda, Hiroshi; Pradas, Marc; Kalliadasis, Serafim
2016-11-01
Random fluctuations are well-known to have significant impact on the formation of complex spatiotemporal patterns in a wide spectrum of biological, engineering and physical environments, including fluid systems such Rayleigh-Bénard convection, contact line dynamics, or waves in free-surface thin film flows. Many of these systems can be modeled by stochastic partial differential equations in large or unbounded domains, a simple prototype of which is the generalised Kuramoto-Sivashinsky (gKS) equation. Its deterministic version has been used in a wide variety of fluid flow contexts, such as two-phase flows with surfactants, free falling films and films in the presence chemical reactions, heating effects and curved substrates, amongst others. Here we study the dynamical states of the noisy gKS equation by making use of time series techniques based on chaos theory, in particular permutation entropy and nonlinear forecasting. We focus on analyzing temporal signals of global measure in the spatiotemporal pattern as the dispersion parameter of the gKS equation and the strength of the noise are varied, observing a rich variety of different emerging regimes, from high-dimensional chaos to purely stochastic behaviour.
SparseTracer: the Reconstruction of Discontinuous Neuronal Morphology in Noisy Images.
Li, Shiwei; Zhou, Hang; Quan, Tingwei; Li, Jing; Li, Yuxin; Li, Anan; Luo, Qingming; Gong, Hui; Zeng, Shaoqun
2017-04-01
Digital reconstruction of a single neuron occupies an important position in computational neuroscience. Although many novel methods have been proposed, recent advances in molecular labeling and imaging systems allow for the production of large and complicated neuronal datasets, which pose many challenges for neuron reconstruction, especially when discontinuous neuronal morphology appears in a strong noise environment. Here, we develop a new pipeline to address this challenge. Our pipeline is based on two methods, one is the region-to-region connection (RRC) method for detecting the initial part of a neurite, which can effectively gather local cues, i.e., avoid the whole image analysis, and thus boosts the efficacy of computation; the other is constrained principal curves method for completing the neurite reconstruction, which uses the past reconstruction information of a neurite for current reconstruction and thus can be suitable for tracing discontinuous neurites. We investigate the reconstruction performances of our pipeline and some of the best state-of-the-art algorithms on the experimental datasets, indicating the superiority of our method in reconstructing sparsely distributed neurons with discontinuous neuronal morphologies in noisy environment. We show the strong ability of our pipeline in dealing with the large-scale image dataset. We validate the effectiveness in dealing with various kinds of image stacks including those from the DIADEM challenge and BigNeuron project.
Broadband Processing in a Noisy Shallow Ocean Environment: A Particle Filtering Approach
Candy, J. V.
2016-04-14
Here we report that when a broadband source propagates sound in a shallow ocean the received data can become quite complicated due to temperature-related sound-speed variations and therefore a highly dispersive environment. Noise and uncertainties disrupt this already chaotic environment even further because disturbances propagate through the same inherent acoustic channel. The broadband (signal) estimation/detection problem can be decomposed into a set of narrowband solutions that are processed separately and then combined to achieve more enhancement of signal levels than that available from a single frequency, thereby allowing more information to be extracted leading to a more reliable source detection. A Bayesian solution to the broadband modal function tracking, pressure-field enhancement, and source detection problem is developed that leads to nonparametric estimates of desired posterior distributions enabling the estimation of useful statistics and an improved processor/detector. In conclusion, to investigate the processor capabilities, we synthesize an ensemble of noisy, broadband, shallow-ocean measurements to evaluate its overall performance using an information theoretical metric for the preprocessor and the receiver operating characteristic curve for the detector.
EXTRACTING PERIODIC TRANSIT SIGNALS FROM NOISY LIGHT CURVES USING FOURIER SERIES
Samsing, Johan
2015-07-01
We present a simple and powerful method for extracting transit signals associated with a known transiting planet from noisy light curves. Assuming the orbital period of the planet is known and the signal is periodic, we illustrate that systematic noise can be removed in Fourier space at all frequencies by only using data within a fixed time frame with a width equal to an integer number of orbital periods. This results in a reconstruction of the full transit signal, which on average is unbiased despite no prior knowledge of either the noise or the transit signal itself being used in the analysis. The method therefore has clear advantages over standard phase folding, which normally requires external input such as nearby stars or noise models for removing systematic components. In addition, we can extract the full orbital transit signal (360°) simultaneously, and Kepler-like data can be analyzed in just a few seconds. We illustrate the performance of our method by applying it to a dataset composed of light curves from Kepler with a fake injected signal emulating a planet with rings. For extracting periodic transit signals, our presented method is in general the optimal and least biased estimator and could therefore lead the way toward the first detections of, e.g., planet rings and exo-trojan asteroids.
An analysis dictionary learning algorithm under a noisy data model with orthogonality constraint.
Zhang, Ye; Yu, Tenglong; Wang, Wenwu
2014-01-01
Two common problems are often encountered in analysis dictionary learning (ADL) algorithms. The first one is that the original clean signals for learning the dictionary are assumed to be known, which otherwise need to be estimated from noisy measurements. This, however, renders a computationally slow optimization process and potentially unreliable estimation (if the noise level is high), as represented by the Analysis K-SVD (AK-SVD) algorithm. The other problem is the trivial solution to the dictionary, for example, the null dictionary matrix that may be given by a dictionary learning algorithm, as discussed in the learning overcomplete sparsifying transform (LOST) algorithm. Here we propose a novel optimization model and an iterative algorithm to learn the analysis dictionary, where we directly employ the observed data to compute the approximate analysis sparse representation of the original signals (leading to a fast optimization procedure) and enforce an orthogonality constraint on the optimization criterion to avoid the trivial solutions. Experiments demonstrate the competitive performance of the proposed algorithm as compared with three baselines, namely, the AK-SVD, LOST, and NAAOLA algorithms.
A Robust Supervised Variable Selection for Noisy High-Dimensional Data
Kalina, Jan; Schlenker, Anna
2015-01-01
The Minimum Redundancy Maximum Relevance (MRMR) approach to supervised variable selection represents a successful methodology for dimensionality reduction, which is suitable for high-dimensional data observed in two or more different groups. Various available versions of the MRMR approach have been designed to search for variables with the largest relevance for a classification task while controlling for redundancy of the selected set of variables. However, usual relevance and redundancy criteria have the disadvantages of being too sensitive to the presence of outlying measurements and/or being inefficient. We propose a novel approach called Minimum Regularized Redundancy Maximum Robust Relevance (MRRMRR), suitable for noisy high-dimensional data observed in two groups. It combines principles of regularization and robust statistics. Particularly, redundancy is measured by a new regularized version of the coefficient of multiple correlation and relevance is measured by a highly robust correlation coefficient based on the least weighted squares regression with data-adaptive weights. We compare various dimensionality reduction methods on three real data sets. To investigate the influence of noise or outliers on the data, we perform the computations also for data artificially contaminated by severe noise of various forms. The experimental results confirm the robustness of the method with respect to outliers. PMID:26137474
Noisy Hegselmann-Krause Systems: Phase Transition and the 2 R-Conjecture
NASA Astrophysics Data System (ADS)
Wang, Chu; Li, Qianxiao; E, Weinan; Chazelle, Bernard
2017-03-01
The classic Hegselmann-Krause ( HK) model for opinion dynamics consists of a set of agents on the real line, each one instructed to move, at every time step, to the mass center of the agents within a fixed distance R. In this work, we investigate the effects of noise in the continuous-time version of the model as described by its mean-field Fokker-Planck equation. In the presence of a finite number of agents, the system exhibits a phase transition from order to disorder as the noise increases. We introduce an order parameter to track the phase transition and resolve the corresponding phase diagram. The system undergoes a phase transition for small R but none for larger R. Based on the stability analysis of the mean-field equation, we derive the existence of a forbidden zone for the disordered phase to emerge. We also provide a theoretical explanation for the well-known 2 R conjecture, which states that, for a random initial distribution in a fixed interval, the final configuration consists of clusters separated by a distance of roughly 2 R. Our theoretical analysis confirms previous simulations and predicts properties of the noisy HK model in higher dimension.
A knowledge-based, two-step procedure for extracting channel networks from noisy dem data
NASA Astrophysics Data System (ADS)
Smith, Terence R.; Zhan, Cixiang; Gao, Peng
We present a new procedure for extracting channel networks from noisy DEM data. The procedure is a knowledge-based, two-step procedure employing both local and nonlocal information. In particular, we employ a model of an ideal drainage network as a source of constraints that must be satisfied by the output of the procedure. We embed these constraints as part of the network extraction procedure. In a first step, the procedure employs the facet model of Haralick to extract valley information from digital images. The constraints employed at this stage relate to conditions indicating reliable valley pixels. In a second step, the procedure applies knowledge of drainage networks to integrate reliable valley points discovered into a network of single-pixel width lines. This network satisfies the constraints imposed by viewing a drainage network as a binary tree in which the channel segments have a one-pixel width. The procedure performs well on DEM data in the example investigated. The overall worst-case performance of the procedure is O( N) log N), but the most computationally intensive step in the procedure is parallelized easily. Hence the procedure is a good candidate for automation.
NASA Astrophysics Data System (ADS)
Sokolowski, Thomas; Tkačik, Gašper
Spatio-temporal protein signals play a crucial role in communicating information within and between cells. However, their ability to convey signals robustly is hampered by noise in gene regulation and biochemical transport, occuring at low copy numbers. While we increasingly understand distinct strategies of biochemical noise control, it remains unclear how nature orchestrates them to maximize information flow. Our recent work extends our information-theoretic framework for gene regulation to an explicitly spatial setting. We constructed a stochastic model enabling fast calculation of local means and variances in a spatially coupled gene regulatory system, which we use for rigorous quantification of information flow in an ensemble of units sensing a spatially distributed input and exchanging information via diffusion. By applying our framework to the paradigmatic Bcd-Hbk system in early fly development, we demonstrate that diffusive coupling can be of substantial benefit in encoding positional information, and uncover a novel optimal regulatory strategy relying on spatial coupling. Thanks to the generic methodology employed, our framework is universally applicable for realistic predictive modeling and data-driven inference of multicellular systems engaging in noisy communication. Institute of Science and Technology Austria, Am Campus 1, A-3400 Klosterneuburg, Austria.
Tsunami Lead Wave Reconstruction Based on Noisy Sea Surface Height Measurements
NASA Astrophysics Data System (ADS)
Yu, Kegen
2016-06-01
This paper presents a Tsunami lead wave reconstruction method using noisy sea surface height (SSH) measurements such as observed by a satellite-carried GNSS reflectometry (GNSS-R) sensor. It is proposed to utilize wavelet theory to mitigate the strong noise in the GNSS-R based SSH measurements. Through extracting the noise components by high-pass filters at decomposition stage and shrinking the noise by thresholding prior to reconstruction, the noise is greatly reduced. Real Tsunami data based simulation results demonstrate that in presence of SSH measurement error of standard deviation 50 cm the accuracy in terms of root mean square error (RMSE) of the lead wave height (true value 145.5 cm) and wavelength (true value 592.0 km) estimation is 21.5 cm and 56.2 km, respectively. The results also show that the proposed wavelet based method considerably outperforms the Kalman filter based method on average. The results demonstrate that the proposed wave reconstruction approach has the potential for Tsunami detection and parameter estimation to assist in achieving reliable Tsunami warning.
The evolution of alternative adaptive strategies for effective communication in noisy environments.
Ord, Terry J; Charles, Grace K; Hofer, Rebecca K
2011-01-01
Animals communicating socially are expected to produce signals that are conspicuous within the habitats in which they live. The particular way in which a species adapts to its environment will depend on its ancestral condition and evolutionary history. At this point, it is unclear how properties of the environment and historical factors interact to shape communication. Tropical Anolis lizards advertise territorial ownership using visual displays in habitats where visual motion or "noise" from windblown vegetation poses an acute problem for the detection of display movements. We studied eight Anolis species that live in similar noise environments but belong to separate island radiations with divergent evolutionary histories. We found that species on Puerto Rico displayed at times when their signals were more likely to be detected by neighboring males and females (during periods of low noise). In contrast, species on Jamaica displayed irrespective of the level of environmental motion, apparently because these species have a display that is effective in a range of viewing conditions. Our findings appear to reflect a case of species originating from different evolutionary starting points evolving different signal strategies for effective communication in noisy environments.
Errors, correlations and fidelity for noisy Hamilton flows. Theory and numerical examples
NASA Astrophysics Data System (ADS)
Turchetti, G.; Sinigardi, S.; Servizi, G.; Panichi, F.; Vaienti, S.
2017-02-01
We analyse the asymptotic growth of the error for Hamiltonian flows due to small random perturbations. We compare the forward error with the reversibility error, showing their equivalence for linear flows on a compact phase space. The forward error, given by the root mean square deviation σ (t) of the noisy flow, grows according to a power law if the system is integrable and according to an exponential law if it is chaotic. The autocorrelation and the fidelity, defined as the correlation of the perturbed flow with respect to the unperturbed one, exhibit an exponential decay as \\exp ≤ft(-2{π2}{σ2}(t)\\right) . Some numerical examples such as the anharmonic oscillator and the Hénon Heiles model confirm these results. We finally consider the effect of the observational noise on an integrable system, and show that the decay of correlations can only be observed after a sequence of measurements and that the multiplicative noise is more effective if the delay between two measurements is large.
Processing strategies for noisy land-based controlled-source electromagnetic data
NASA Astrophysics Data System (ADS)
Streich, R.; Becken, M.; Ritter, O.
2011-12-01
Controlled-source electromagnetic (CSEM) data acquired on land are commonly contaminated by high levels of cultural noise. To extract interpretable transfer functions from noisy land CSEM data, we combine a novel three-electrode current transmitter with processing concepts adopted from natural-source magnetotellurics. By using three grounded transmitter electrodes, we can generate multi-polarization data without physically moving the transmitter. In this way, we achieve more uniform source field distributions than is common with dipole transmitters that are typically deployed at two distinct orientations. From the multi-polarization data, transfer functions with respect to two independent source configurations can be determined using statistical methods. To this end, we first stack the data of each transmission sequence in the time domain after eliminating spikes and the noisiest time windows. We then compute transfer functions in the frequency domain using robust least-squares techniques, averaging over the known spectral peaks of the source signal within narrow frequency bands. This allows us to combine data from different source polarizations and waveforms. We present results of applying this procedure to land CSEM data collected in Germany across an area with abundant sources of noise, including pipelines, power lines, and wind power plants. The obtained transfer functions vary consistently in frequency and space to transmitter-receiver distances of more than 10 km.
Frakt, A B; Karl, W C; Willsky, A S
1998-01-01
In this paper, we investigate the problems of anomaly detection and localization from noisy tomographic data. These are characteristic of a class of problems that cannot be optimally solved because they involve hypothesis testing over hypothesis spaces with extremely large cardinality. Our multiscale hypothesis testing approach addresses the key issues associated with this class of problems. A multiscale hypothesis test is a hierarchical sequence of composite hypothesis tests that discards large portions of the hypothesis space with minimal computational burden and zooms in on the likely true hypothesis. For the anomaly detection and localization problems, hypothesis zooming corresponds to spatial zooming - anomalies are successively localized to finer and finer spatial scales. The key challenges we address include how to hierarchically divide a large hypothesis space and how to process the data at each stage of the hierarchy to decide which parts of the hypothesis space deserve more attention. For the latter, we pose and solve a nonlinear optimization problem for a decision statistic that maximally disambiguates composite hypotheses. With no more computational complexity, our optimized statistic shows substantial improvement over conventional approaches. We provide examples that demonstrate this and quantify how much performance is sacrificed by the use of a suboptimal method as compared to that achievable if the optimal approach were computationally feasible.
NASA Astrophysics Data System (ADS)
Sato, Hayato; Ota, Ryo; Morimoto, Masayuki; Sato, Hiroshi
2005-04-01
Assessing sound environment of classrooms for the aged is a very important issue, because classrooms can be used by the aged for their lifelong learning, especially in the aged society. Hence hearing loss due to aging is a considerable factor for classrooms. In this study, the optimal speech level in noisy fields for both young adults and aged persons was investigated. Listening difficulty ratings and word intelligibility scores for familiar words were used to evaluate speech transmission performance. The results of the tests demonstrated that the optimal speech level for moderate background noise (i.e., less than around 60 dBA) was fairly constant. Meanwhile, the optimal speech level depended on the speech-to-noise ratio when the background noise level exceeded around 60 dBA. The minimum required speech level to minimize difficulty ratings for the aged was higher than that for the young. However, the minimum difficulty ratings for both the young and the aged were given in the range of speech level of 70 to 80 dBA of speech level.
NASA Astrophysics Data System (ADS)
Chapeau-Blondeau, François
2017-04-01
Benefit from entanglement in quantum parameter estimation in the presence of noise or decoherence is investigated, with the quantum Fisher information to asses the performance. When an input probe experiences any (noisy) transformation introducing the parameter dependence, the performance is always maximized by a pure probe. As a generic estimation task, for estimating the phase of a unitary transformation on a qubit affected by depolarizing noise, the optimal separable probe and its performance are characterized as a function of the level of noise. By entangling qubits in pairs, enhancements of performance over that of the optimal separable probe are quantified, in various settings of the entangled pair. In particular, in the presence of the noise, enhancement over the performance of the one-qubit optimal probe can always be obtained with a second entangled qubit although never interacting with the process to be estimated. Also, enhancement over the performance of the two-qubit optimal separable probe can always be achieved by a two-qubit entangled probe, either partially or maximally entangled depending on the level of the depolarizing noise.
Impact source localization on an elastic plate in a noisy environment
NASA Astrophysics Data System (ADS)
Park, Jin-Ho; Kim, Yang-Hann
2006-10-01
Conventional source localization techniques when the source is located on a dispersive medium require both the time-of-arrival differences (TOADs) between the transducer signals and the group velocities. Furthermore, they are only practically applicable if we have a high signal-to-noise ratio (SNR). In practice, the material properties or the geometry of a medium are not fully known; therefore the group velocity is not available. The transducers' signals are usually very small or embedded in noise. In this paper, we propose a novel impact source localization method, in the case where we have the source on an elastic plate. The method is applicable even if we do not know the group velocity and we have a relatively small SNR. The group velocities are obtained by estimating a source location based on the measured TOADs. The estimated group velocities have a minimum variance at the impact source location. However, this estimation degrades as the SNR decreases. To reduce the noise effect, an exponential function is asymmetrically weighted in smoothed Wigner-Ville distributions (WVDs). Experiments and simulations are carried out to verify the validity of this technique. As a result, the proposed technique is found to be effective even in a relatively noisy environment.
A data mining approach to evolutionary optimisation of noisy multi-objective problems
NASA Astrophysics Data System (ADS)
Chia, J. Y.; Goh, C. K.; Shim, V. A.; Tan, K. C.
2012-07-01
Many real world optimisation problems have opposing objective functions which are subjected to the influence of noise. Noise in the objective functions can adversely affect the stability, performance and convergence of evolutionary optimisers. This article proposes a Bayesian frequent data mining (DM) approach to identify optimal regions to guide the population amidst the presence of noise. The aggregated information provided by all the solutions helped to average out the effects of noise. This article proposes a DM crossover operator to make use of the rules mined. After implementation of this operator, a better convergence to the true Pareto front is achieved at the expense of the diversity of the solution. Consequently, an ExtremalExploration operator will be proposed in the later part of this article to help curb the loss in diversity caused by the DM operator. The result is a more directive search with a faster convergence rate. The search is effective in decision space where the Pareto set is in a tight cluster. A further investigation of the performance of the proposed algorithm in noisy and noiseless environment will also be studied with respect to non-convexity, discontinuity, multi-modality and uniformity. The proposed algorithm is evaluated on ZDT and other benchmarks problems. The results of the simulations indicate that the proposed method is effective in handling noise and is competitive against the other noise tolerant algorithms.
Making sense of information in noisy networks: human communication, gossip, and distortion.
Laidre, Mark E; Lamb, Alex; Shultz, Susanne; Olsen, Megan
2013-01-21
Information from others can be unreliable. Humans nevertheless act on such information, including gossip, to make various social calculations, thus raising the question of whether individuals can sort through social information to identify what is, in fact, true. Inspired by empirical literature on people's decision-making when considering gossip, we built an agent-based simulation model to examine how well simple decision rules could make sense of information as it propagated through a network. Our simulations revealed that a minimalistic decision-rule 'Bit-wise mode' - which compared information from multiple sources and then sought a consensus majority for each component bit within the message - was consistently the most successful at converging upon the truth. This decision rule attained high relative fitness even in maximally noisy networks, composed entirely of nodes that distorted the message. The rule was also superior to other decision rules regardless of its frequency in the population. Simulations carried out with variable agent memory constraints, different numbers of observers who initiated information propagation, and a variety of network types suggested that the single most important factor in making sense of information was the number of independent sources that agents could consult. Broadly, our model suggests that despite the distortion information is subject to in the real world, it is nevertheless possible to make sense of it based on simple Darwinian computations that integrate multiple sources.
Tekin, Ramazan; Tagluk, Mehmet Emin
2017-03-01
Physiological rhythms play a critical role in the functional development of living beings. Many biological functions are executed with an interaction of rhythms produced by internal characteristics of scores of cells. While synchronized oscillations may be associated with normal brain functions, anomalies in these oscillations may cause or relate the emergence of some neurological or neuropsychological pathologies. This study was designed to investigate the effects of topological structure and synaptic conductivity noise on the spatial synchronization and temporal rhythmicity of the waves generated by cells in the network. Because of holding the ability of clustering and randomizing with change of parameters, small-world (SW) network topology was chosen. The oscillatory activity of network was tried out by manipulating an insulated SW, cortical network model whose morphology is very close to real world. According to the obtained results, it was observed that at the optimal probabilistic rates of conductivity noise and rewiring of SW, powerful synchronized oscillatory small waves are generated in relation to the internal dynamics of cells, which are in line with the network's input. These two parameters were observed to be quite effective on the excitation-inhibition balance of the network. Accordingly, it may be suggested that the topological dynamics of SW and noisy synaptic conductivity may be associated with the normal and abnormal development of neurobiological structure.
Wavelet shrinkage of a noisy dynamical system with non-linear noise impact
NASA Astrophysics Data System (ADS)
Garcin, Matthieu; Guégan, Dominique
2016-06-01
By filtering wavelet coefficients, it is possible to construct a good estimate of a pure signal from noisy data. Especially, for a simple linear noise influence, Donoho and Johnstone (1994) have already defined an optimal filter design in the sense of a minimization of the error made when estimating the pure signal. We set here a different framework where the influence of the noise is non-linear. In particular, we propose a method to filter the wavelet coefficients of a discrete dynamical system disrupted by a weak noise, in order to construct good estimates of the pure signal, including Bayes' estimate, minimax estimate, oracular estimate or thresholding estimate. We present the example of a logistic and a Lorenz chaotic dynamical system as well as an adaptation of our technique in order to show empirically the robustness of the thresholding method in presence of leptokurtic noise. Moreover, we test both the hard and the soft thresholding and also another kind of smoother thresholding which seems to have almost the same reconstruction power as the hard thresholding. Finally, besides the tests on an estimated dataset, the method is tested on financial data: oil prices and NOK/USD exchange rate.
Dual-microphone Sounds of Daily Life classification for telemonitoring in a noisy environment.
Maunder, David; Ambikairajah, Eliathamby; Epps, Julien; Celler, Branko
2008-01-01
Telemonitoring of elderly people in their homes using video cameras is complicated by privacy concerns, and hence sound has emerged as a promising alternative that is more acceptable to users. We investigate methods to address the accuracy degradation of sound classification that arises in the presence of background noise typical of a practical telemonitoring situation. A dual microphone configuration is used to record a database of Sounds of Daily Life (SDL) in a kitchen. We introduce a new algorithm employing the eigenvalues of the cross-spectral matrix of the recorded signals to detect the endpoints of a SDL in the presence of background noise. Independent component analysis is also used to improve the signal to noise ratio of the SDL. Results on a 7-class noisy SDL classification problem show that the error rate the proposed SDL classification system can be improved by up to 97% relative to a single-microphone system without noise reduction techniques, when evaluated on a large SDL database with SNRs in the range 0-28 dB.
NASA Astrophysics Data System (ADS)
Bovy Jo; Hogg, David W.; Roweis, Sam T.
2011-06-01
We generalize the well-known mixtures of Gaussians approach to density estimation and the accompanying Expectation-Maximization technique for finding the maximum likelihood parameters of the mixture to the case where each data point carries an individual d-dimensional uncertainty covariance and has unique missing data properties. This algorithm reconstructs the error-deconvolved or "underlying" distribution function common to all samples, even when the individual data points are samples from different distributions, obtained by convolving the underlying distribution with the heteroskedastic uncertainty distribution of the data point and projecting out the missing data directions. We show how this basic algorithm can be extended with conjugate priors on all of the model parameters and a "split-and-"erge- procedure designed to avoid local maxima of the likelihood. We demonstrate the full method by applying it to the problem of inferring the three-dimensional veloc! ity distribution of stars near the Sun from noisy two-dimensional, transverse velocity measurements from the Hipparcos satellite.
NASA Astrophysics Data System (ADS)
Carrillo, José Antonio; Perthame, Benoît; Salort, Delphine; Smets, Didier
2015-09-01
The Noisy Integrate-and-Fire equation is a standard non-linear Fokker-Planck equation used to describe the activity of a homogeneous neural network characterized by its connectivity b (each neuron connected to all others through synaptic weights); b > 0 describes excitatory networks and b < 0 inhibitory networks. In the excitatory case, it was proved that, once the proportion of neurons that are close to their action potential {{V}\\text{F}} is too high, solutions cannot exist for all times. In this paper, we show a priori uniform bounds in time on the firing rate to discard the scenario of blow-up, and, for small connectivity, we prove qualitative properties on the long time behavior of solutions. The methods are based on the one hand on relative entropy and Poincaré inequalities leading to L2 estimates and on the other hand, on the notion of ‘universal super-solution’ and parabolic regularizing effects to obtain {{L}∞} bounds.
An Analysis Dictionary Learning Algorithm under a Noisy Data Model with Orthogonality Constraint
Zhang, Ye; Yu, Tenglong
2014-01-01
Two common problems are often encountered in analysis dictionary learning (ADL) algorithms. The first one is that the original clean signals for learning the dictionary are assumed to be known, which otherwise need to be estimated from noisy measurements. This, however, renders a computationally slow optimization process and potentially unreliable estimation (if the noise level is high), as represented by the Analysis K-SVD (AK-SVD) algorithm. The other problem is the trivial solution to the dictionary, for example, the null dictionary matrix that may be given by a dictionary learning algorithm, as discussed in the learning overcomplete sparsifying transform (LOST) algorithm. Here we propose a novel optimization model and an iterative algorithm to learn the analysis dictionary, where we directly employ the observed data to compute the approximate analysis sparse representation of the original signals (leading to a fast optimization procedure) and enforce an orthogonality constraint on the optimization criterion to avoid the trivial solutions. Experiments demonstrate the competitive performance of the proposed algorithm as compared with three baselines, namely, the AK-SVD, LOST, and NAAOLA algorithms. PMID:25126605
Capacity and cutoff rate of (M+1)-ary decision rules for noisy M-ary optical PPM channel
NASA Technical Reports Server (NTRS)
Lee, P. J.
1983-01-01
The channel capacity C and the cutoff rate R sub o of two (M + 1)-ary decision rules for noisy M slots/symbol optical pulse position modulation (PPM) with ideal photon counting are computed and compared. Also the values of the optimum thresholds needed to minimize the signal requirements are given. With a minor increase in hardware complexity, the symbol by symbol threshold decision rule is shown to be superior to the slot by slot threshold detection and decision rule in two aspects: first, it saves more than 0.5 dB in signal energy for the very noisy cases of more than one noise photon per slot (for low noise cases it also saves signal energy, but a negligibly small amount). Second, it is more robust to variations in the noise level.
Lauer, Amanda M.
2017-01-01
Studies have suggested a role of weakened medial olivocochlear (OC) efferent feedback in accelerated hearing loss and increased susceptibility to noise. The present study investigated the progression of hearing loss with age and exposure to a noisy environment in medial OC-deficient mice. Alpha9 nicotinic acetylcholine receptor knockout (α9KO) and wild types were screened for hearing loss using auditory brainstem responses. α9KO mice housed in a quiet environment did not show increased hearing loss compared to wild types in young adulthood and middle age. Challenging the medial OC system by housing in a noisy environment did not increase hearing loss in α9KO mice compared to wild types. ABR wave 1 amplitudes also did not show differences between α9KO mice and wild types. These data suggest that deficient medial OC feedback does not result in early onset of hearing loss. PMID:28626386
Jeon, Gwanggil; Dubois, Eric
2013-01-01
This paper adapts the least-squares luma-chroma demultiplexing (LSLCD) demosaicking method to noisy Bayer color filter array (CFA) images. A model is presented for the noise in white-balanced gamma-corrected CFA images. A method to estimate the noise level in each of the red, green, and blue color channels is then developed. Based on the estimated noise parameters, one of a finite set of configurations adapted to a particular level of noise is selected to demosaic the noisy data. The noise-adaptive demosaicking scheme is called LSLCD with noise estimation (LSLCD-NE). Experimental results demonstrate state-of-the-art performance over a wide range of noise levels, with low computational complexity. Many results with several algorithms, noise levels, and images are presented on our companion web site along with software to allow reproduction of our results.
NASA Technical Reports Server (NTRS)
Sunahara, Y.; Kojima, F.
1987-01-01
The purpose of this paper is to establish a method for identifying unknown parameters involved in the boundary state of a class of diffusion systems under noisy observations. A mathematical model of the system dynamics is given by a two-dimensional diffusion equation. Noisy observations are made by sensors allocated on the system boundary. Starting with the mathematical model mentioned above, an online parameter estimation algorithm is proposed within the framework of the maximum likelihood estimation. Existence of the optimal solution and related necessary conditions are discussed. By solving a local variation of the cost functional with respect to the perturbation of parameters, the estimation mechanism is proposed in a form of recursive computations. Finally, the feasibility of the estimator proposed here is demonstrated through results of digital simulation experiments.
Jati, A; Singh, G; Koley, S; Konar, A; Ray, A K; Chakraborty, C
2015-03-01
Medical image segmentation demands higher segmentation accuracy especially when the images are affected by noise. This paper proposes a novel technique to segment medical images efficiently using an intuitionistic fuzzy divergence-based thresholding. A neighbourhood-based membership function is defined here. The intuitionistic fuzzy divergence-based image thresholding technique using the neighbourhood-based membership functions yield lesser degradation of segmentation performance in noisy environment. Its ability in handling noisy images has been validated. The algorithm is independent of any parameter selection. Moreover, it provides robustness to both additive and multiplicative noise. The proposed scheme has been applied on three types of medical image datasets in order to establish its novelty and generality. The performance of the proposed algorithm has been compared with other standard algorithms viz. Otsu's method, fuzzy C-means clustering, and fuzzy divergence-based thresholding with respect to (1) noise-free images and (2) ground truth images labelled by experts/clinicians. Experiments show that the proposed methodology is effective, more accurate and efficient for segmenting noisy images.
NASA Astrophysics Data System (ADS)
Cao, Mao-Sen; Xu, Wei; Ren, Wei-Xin; Ostachowicz, Wiesław; Sha, Gang-Gang; Pan, Li-Xia
2016-08-01
Detection of multiple damage using modal curvature in noisy environments has become a research focus of considerable challenge and great significance over the last few years. However, a noticeable deficiency of modal curvature is its susceptibility to noise, which usually results in a noisy modal curvature with obscured damage signature. To address this deficiency, this study formulates a new concept of complex-wavelet modal curvature. Complex-wavelet modal curvature features the ability to reveal and delineate damage under noisy conditions. The effectiveness of the concept is analytically verified using cracked beams with various types of boundary conditions. The applicability is further experimentally validated by an aluminum beam with a single crack and a carbon-fiber-reinforced polymer composite beam with three cracks in the laboratory with mode shapes measured by a scanning laser vibrometer. Both analytical and experimental results have demonstrated that the complex-wavelet modal curvature is capable of revealing slight damage by eliminating noise interference, with no need for prior knowledge of either material properties or boundary conditions of the beam under inspection.
NASA Astrophysics Data System (ADS)
Soares, Edward J.; Gifford, Howard C.; Glick, Stephen J.
2003-05-01
We investigated the estimation of the ensemble channelized Hotelling observer (CHO) signal-to-noise ratio (SNR) for ordered-subset (OS) image reconstruction using noisy projection data. Previously, we computed the ensemble CHO SNR using a method for approximating the channelized covariance of OS reconstruction, which requires knowledge of the noise-free projection data. Here, we use a "plug-in" approach, in which noisy data is used in place of the noise-free data in the aforementioned channelized covariance approximation. Additionally, we evaluated the use of smoothing of the noisy projections before use in the covariance approximation. Additionally, we evaluated the use of smoothing of the noisy projections before use in the covariance calculation. The task was detection of a 10% contrast Gaussian signal within a slice of the MCAT phantom. Simulated projections of the MCAT phantom were scaled and Poisson noise was added to create 100 noisy signal-absent data sets. Simulated projections of the scaled signal were then added to the noisy background projections to create 100 noisy signal-present data set. These noisy data sets were then used to generate 100 estimates of the ensemble CHO SNR for reconstructions at various iterates. For comparison purposes, the same calculation was repeated with the noise-free data. The results, reported as plots of the average CHO SNR generated in this fashion, along with 95% confidence intervals, demonstrate that this approach works very well, and would allow optimization of imaging systems and reconstruction methods using a more accurate object model (i.e., real patient data).
1992-05-22
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Neuroscience-inspired computational systems for speech recognition under noisy conditions
NASA Astrophysics Data System (ADS)
Schafer, Phillip B.
advantage of the neural representation's invariance in noise. The scheme centers on a speech similarity measure based on the longest common subsequence between spike sequences. The combined encoding and decoding scheme outperforms a benchmark system in extremely noisy acoustic conditions. Finally, I consider methods for decoding spike representations of continuous speech. To help guide the alignment of templates to words, I design a syllable detection scheme that robustly marks the locations of syllabic nuclei. The scheme combines SVM-based training with a peak selection algorithm designed to improve noise tolerance. By incorporating syllable information into the ASR system, I obtain strong recognition results in noisy conditions, although the performance in noiseless conditions is below the state of the art. The work presented here constitutes a novel approach to the problem of ASR that can be applied in the many challenging acoustic environments in which we use computer technologies today. The proposed spike-based processing methods can potentially be exploited in effcient hardware implementations and could significantly reduce the computational costs of ASR. The work also provides a framework for understanding the advantages of spike-based acoustic coding in the human brain.
Automatic Identification of Application I/O Signatures from Noisy Server-Side Traces
Liu, Yang; Gunasekaran, Raghul; Ma, Xiaosong; Vazhkudai, Sudharshan S
2014-01-01
Competing workloads on a shared storage system cause I/O resource contention and application performance vagaries. This problem is already evident in today s HPC storage systems and is likely to become acute at exascale. We need more interaction between application I/O requirements and system software tools to help alleviate the I/O bottleneck, moving towards I/O-aware job scheduling. However, this requires rich techniques to capture application I/O characteristics, which remain evasive in production systems. Traditionally, I/O characteristics have been obtained using client-side tracing tools, with drawbacks such as non-trivial instrumentation/development costs, large trace traffic, and inconsistent adoption. We present a novel approach, I/O Signature Identifier (IOSI), to characterize the I/O behavior of data-intensive applications. IOSI extracts signatures from noisy, zero-overhead server-side I/O throughput logs that are already collected on today s supercomputers, without interfering with the compiling/execution of applications. We evaluated IOSI using the Spider storage system at Oak Ridge National Laboratory, the S3D turbulence application (running on 18,000 Titan nodes), and benchmark-based pseudo-applications. Through our ex- periments we confirmed that IOSI effectively extracts an application s I/O signature despite significant server-side noise. Compared to client-side tracing tools, IOSI is transparent, interface-agnostic, and incurs no overhead. Compared to alternative data alignment techniques (e.g., dynamic time warping), it offers higher signature accuracy and shorter processing time.
Holt, Marla M; Noren, Dawn P; Dunkin, Robin C; Williams, Terrie M
2015-06-01
Many animals produce louder, longer or more repetitious vocalizations to compensate for increases in environmental noise. Biological costs of increased vocal effort in response to noise, including energetic costs, remain empirically undefined in many taxa, particularly in marine mammals that rely on sound for fundamental biological functions in increasingly noisy habitats. For this investigation, we tested the hypothesis that an increase in vocal effort would result in an energetic cost to the signaler by experimentally measuring oxygen consumption during rest and a 2 min vocal period in dolphins that were trained to vary vocal loudness across trials. Vocal effort was quantified as the total acoustic energy of sounds produced. Metabolic rates during the vocal period were, on average, 1.2 and 1.5 times resting metabolic rate (RMR) in dolphin A and B, respectively. As vocal effort increased, we found that there was a significant increase in metabolic rate over RMR during the 2 min following sound production in both dolphins, and in total oxygen consumption (metabolic cost of sound production plus recovery costs) in the dolphin that showed a wider range of vocal effort across trials. Increases in vocal effort, as a consequence of increases in vocal amplitude, repetition rate and/or duration, are consistent with behavioral responses to noise in free-ranging animals. Here, we empirically demonstrate for the first time in a marine mammal, that these vocal modifications can have an energetic impact at the individual level and, importantly, these data provide a mechanistic foundation for evaluating biological consequences of vocal modification in noise-polluted habitats.
Critical initial-slip scaling for the noisy complex Ginzburg-Landau equation
NASA Astrophysics Data System (ADS)
Liu, Weigang; Täuber, Uwe C.
2016-10-01
We employ the perturbative fieldtheoretic renormalization group method to investigate the universal critical behavior near the continuous non-equilibrium phase transition in the complex Ginzburg-Landau equation with additive white noise. This stochastic partial differential describes a remarkably wide range of physical systems: coupled nonlinear oscillators subject to external noise near a Hopf bifurcation instability; spontaneous structure formation in non-equilibrium systems, e.g., in cyclically competing populations; and driven-dissipative Bose-Einstein condensation, realized in open systems on the interface of quantum optics and many-body physics, such as cold atomic gases and exciton-polaritons in pumped semiconductor quantum wells in optical cavities. Our starting point is a noisy, dissipative Gross-Pitaevski or nonlinear Schrödinger equation, or equivalently purely relaxational kinetics originating from a complex-valued Landau-Ginzburg functional, which generalizes the standard equilibrium model A critical dynamics of a non-conserved complex order parameter field. We study the universal critical behavior of this system in the early stages of its relaxation from a Gaussian-weighted fully randomized initial state. In this critical aging regime, time translation invariance is broken, and the dynamics is characterized by the stationary static and dynamic critical exponents, as well as an independent ‘initial-slip’ exponent. We show that to first order in the dimensional expansion about the upper critical dimension, this initial-slip exponent in the complex Ginzburg-Landau equation is identical to its equilibrium model A counterpart. We furthermore employ the renormalization group flow equations as well as construct a suitable complex spherical model extension to argue that this conclusion likely remains true to all orders in the perturbation expansion.
Sequential quantum secret sharing in a noisy environment aided with weak measurements
NASA Astrophysics Data System (ADS)
Ray, Maharshi; Chatterjee, Sourav; Chakrabarty, Indranil
2016-05-01
In this work we give a (n,n)-threshold protocol for sequential secret sharing of quantum information for the first time. By sequential secret sharing we refer to a situation where the dealer is not having all the secrets at the same time, at the beginning of the protocol; however if the dealer wishes to share secrets at subsequent phases she/he can realize it with the help of our protocol. First of all we present our protocol for three parties and later we generalize it for the situation where we have more (n> 3) parties. Interestingly, we show that our protocol of sequential secret sharing requires less amount of quantum as well as classical resource as compared to the situation wherein existing protocols are repeatedly used. Further in a much more realistic situation, we consider the sharing of qubits through two kinds of noisy channels, namely the phase damping channel (PDC) and the amplitude damping channel (ADC). When we carry out the sequential secret sharing in the presence of noise we observe that the fidelity of secret sharing at the kth iteration is independent of the effect of noise at the (k - 1)th iteration. In case of ADC we have seen that the average fidelity of secret sharing drops down to ½ which is equivalent to a random guess of the quantum secret. Interestingly, we find that by applying weak measurements one can enhance the average fidelity. This increase of the average fidelity can be achieved with certain trade off with the success probability of the weak measurements.
Ajemian, Robert; D’Ausilio, Alessandro; Moorman, Helene; Bizzi, Emilio
2013-01-01
During the process of skill learning, synaptic connections in our brains are modified to form motor memories of learned sensorimotor acts. The more plastic the adult brain is, the easier it is to learn new skills or adapt to neurological injury. However, if the brain is too plastic and the pattern of synaptic connectivity is constantly changing, new memories will overwrite old memories, and learning becomes unstable. This trade-off is known as the stability–plasticity dilemma. Here a theory of sensorimotor learning and memory is developed whereby synaptic strengths are perpetually fluctuating without causing instability in motor memory recall, as long as the underlying neural networks are sufficiently noisy and massively redundant. The theory implies two distinct stages of learning—preasymptotic and postasymptotic—because once the error drops to a level comparable to that of the noise-induced error, further error reduction requires altered network dynamics. A key behavioral prediction derived from this analysis is tested in a visuomotor adaptation experiment, and the resultant learning curves are modeled with a nonstationary neural network. Next, the theory is used to model two-photon microscopy data that show, in animals, high rates of dendritic spine turnover, even in the absence of overt behavioral learning. Finally, the theory predicts enhanced task selectivity in the responses of individual motor cortical neurons as the level of task expertise increases. From these considerations, a unique interpretation of sensorimotor memory is proposed—memories are defined not by fixed patterns of synaptic weights but, rather, by nonstationary synaptic patterns that fluctuate coherently. PMID:24324147
NASA Astrophysics Data System (ADS)
Pandremmenou, K.; Tziortziotis, N.; Paluri, S.; Zhang, W.; Blekas, K.; Kondi, L. P.; Kumar, S.
2015-03-01
We propose the use of the Least Absolute Shrinkage and Selection Operator (LASSO) regression method in order to predict the Cumulative Mean Squared Error (CMSE), incurred by the loss of individual slices in video transmission. We extract a number of quality-relevant features from the H.264/AVC video sequences, which are given as input to the LASSO. This method has the benefit of not only keeping a subset of the features that have the strongest effects towards video quality, but also produces accurate CMSE predictions. Particularly, we study the LASSO regression through two different architectures; the Global LASSO (G.LASSO) and Local LASSO (L.LASSO). In G.LASSO, a single regression model is trained for all slice types together, while in L.LASSO, motivated by the fact that the values for some features are closely dependent on the considered slice type, each slice type has its own regression model, in an e ort to improve LASSO's prediction capability. Based on the predicted CMSE values, we group the video slices into four priority classes. Additionally, we consider a video transmission scenario over a noisy channel, where Unequal Error Protection (UEP) is applied to all prioritized slices. The provided results demonstrate the efficiency of LASSO in estimating CMSE with high accuracy, using only a few features. les that typically contain high-entropy data, producing a footprint that is far less conspicuous than existing methods. The system uses a local web server to provide a le system, user interface and applications through an web architecture.
An efficient system for reliably transmitting image and video data over low bit rate noisy channels
NASA Technical Reports Server (NTRS)
Costello, Daniel J., Jr.; Huang, Y. F.; Stevenson, Robert L.
1994-01-01
This research project is intended to develop an efficient system for reliably transmitting image and video data over low bit rate noisy channels. The basic ideas behind the proposed approach are the following: employ statistical-based image modeling to facilitate pre- and post-processing and error detection, use spare redundancy that the source compression did not remove to add robustness, and implement coded modulation to improve bandwidth efficiency and noise rejection. Over the last six months, progress has been made on various aspects of the project. Through our studies of the integrated system, a list-based iterative Trellis decoder has been developed. The decoder accepts feedback from a post-processor which can detect channel errors in the reconstructed image. The error detection is based on the Huber Markov random field image model for the compressed image. The compression scheme used here is that of JPEG (Joint Photographic Experts Group). Experiments were performed and the results are quite encouraging. The principal ideas here are extendable to other compression techniques. In addition, research was also performed on unequal error protection channel coding, subband vector quantization as a means of source coding, and post processing for reducing coding artifacts. Our studies on unequal error protection (UEP) coding for image transmission focused on examining the properties of the UEP capabilities of convolutional codes. The investigation of subband vector quantization employed a wavelet transform with special emphasis on exploiting interband redundancy. The outcome of this investigation included the development of three algorithms for subband vector quantization. The reduction of transform coding artifacts was studied with the aid of a non-Gaussian Markov random field model. This results in improved image decompression. These studies are summarized and the technical papers included in the appendices.
Detection of bifurcations in noisy coupled systems from multiple time series
Williamson, Mark S. Lenton, Timothy M.
2015-03-15
We generalize a method of detecting an approaching bifurcation in a time series of a noisy system from the special case of one dynamical variable to multiple dynamical variables. For a system described by a stochastic differential equation consisting of an autonomous deterministic part with one dynamical variable and an additive white noise term, small perturbations away from the system's fixed point will decay slower the closer the system is to a bifurcation. This phenomenon is known as critical slowing down and all such systems exhibit this decay-type behaviour. However, when the deterministic part has multiple coupled dynamical variables, the possible dynamics can be much richer, exhibiting oscillatory and chaotic behaviour. In our generalization to the multi-variable case, we find additional indicators to decay rate, such as frequency of oscillation. In the case of approaching a homoclinic bifurcation, there is no change in decay rate but there is a decrease in frequency of oscillations. The expanded method therefore adds extra tools to help detect and classify approaching bifurcations given multiple time series, where the underlying dynamics are not fully known. Our generalisation also allows bifurcation detection to be applied spatially if one treats each spatial location as a new dynamical variable. One may then determine the unstable spatial mode(s). This is also something that has not been possible with the single variable method. The method is applicable to any set of time series regardless of its origin, but may be particularly useful when anticipating abrupt changes in the multi-dimensional climate system.
Universal critical behavior of noisy coupled oscillators: a renormalization group study.
Risler, Thomas; Prost, Jacques; Jülicher, Frank
2005-07-01
We show that the synchronization transition of a large number of noisy coupled oscillators is an example for a dynamic critical point far from thermodynamic equilibrium. The universal behaviors of such critical oscillators, arranged on a lattice in a d -dimensional space and coupled by nearest-neighbors interactions, can be studied using field-theoretical methods. The field theory associated with the critical point of a homogeneous oscillatory instability (or Hopf bifurcation of coupled oscillators) is the complex Ginzburg-Landau equation with additive noise. We perform a perturbative renormalization group (RG) study in a (4-epsilon)-dimensional space. We develop an RG scheme that eliminates the phase and frequency of the oscillations using a scale-dependent oscillating reference frame. Within Callan-Symanzik's RG scheme to two-loop order in perturbation theory, we find that the RG fixed point is formally related to the one of the model A dynamics of the real Ginzburg-Landau theory with an O2 symmetry of the order parameter. Therefore, the dominant critical exponents for coupled oscillators are the same as for this equilibrium field theory. This formal connection with an equilibrium critical point imposes a relation between the correlation and response functions of coupled oscillators in the critical regime. Since the system operates far from thermodynamic equilibrium, a strong violation of the fluctuation-dissipation relation occurs and is characterized by a universal divergence of an effective temperature. The formal relation between critical oscillators and equilibrium critical points suggests that long-range phase order exists in critical oscillators above two dimensions.
Loescher, D.H.; Noren, K.
1996-09-01
The current that flows between the electrical test equipment and the nuclear explosive must be limited to safe levels during electrical tests conducted on nuclear explosives at the DOE Pantex facility. The safest way to limit the current is to use batteries that can provide only acceptably low current into a short circuit; unfortunately this is not always possible. When it is not possible, current limiters, along with other design features, are used to limit the current. Three types of current limiters, the fuse blower, the resistor limiter, and the MOSFET-pass-transistor limiters, are used extensively in Pantex test equipment. Detailed failure mode and effects analyses were conducted on these limiters. Two other types of limiters were also analyzed. It was found that there is no best type of limiter that should be used in all applications. The fuse blower has advantages when many circuits must be monitored, a low insertion voltage drop is important, and size and weight must be kept low. However, this limiter has many failure modes that can lead to the loss of over current protection. The resistor limiter is simple and inexpensive, but is normally usable only on circuits for which the nominal current is less than a few tens of milliamperes. The MOSFET limiter can be used on high current circuits, but it has a number of single point failure modes that can lead to a loss of protective action. Because bad component placement or poor wire routing can defeat any limiter, placement and routing must be designed carefully and documented thoroughly.
A Methodology for the Parametric Reconstruction of Non-Steady and Noisy Meteorological Time Series
NASA Astrophysics Data System (ADS)
Rovira, F.; Palau, J. L.; Millán, M.
2009-09-01
Climatic and meteorological time series often show some persistence (in time) in the variability of certain features. One could regard annual, seasonal and diurnal time variability as trivial persistence in the variability of some meteorological magnitudes (as, e.g., global radiation, air temperature above surface, etc.). In these cases, the traditional Fourier transform into frequency space will show the principal harmonics as the components with the largest amplitude. Nevertheless, meteorological measurements often show other non-steady (in time) variability. Some fluctuations in measurements (at different time scales) are driven by processes that prevail on some days (or months) of the year but disappear on others. By decomposing a time series into time-frequency space through the continuous wavelet transformation, one is able to determine both the dominant modes of variability and how those modes vary in time. This study is based on a numerical methodology to analyse non-steady principal harmonics in noisy meteorological time series. This methodology combines both the continuous wavelet transform and the development of a parametric model that includes the time evolution of the principal and the most statistically significant harmonics of the original time series. The parameterisation scheme proposed in this study consists of reproducing the original time series by means of a statistically significant finite sum of sinusoidal signals (waves), each defined by using the three usual parameters: amplitude, frequency and phase. To ensure the statistical significance of the parametric reconstruction of the original signal, we propose a standard statistical t-student analysis of the confidence level of the amplitude in the parametric spectrum for the different wave components. Once we have assured the level of significance of the different waves composing the parametric model, we can obtain the statistically significant principal harmonics (in time) of the original
Learning grammar rules of building parts from precise models and noisy observations
NASA Astrophysics Data System (ADS)
Dehbi, Y.; Plümer, L.
The automatic interpretation of dense three-dimensional (3D) point clouds is still an open research problem. The quality and usability of the derived models depend to a large degree on the availability of highly structured models which represent semantics explicitly and provide a priori knowledge to the interpretation process. The usage of formal grammars for modelling man-made objects has gained increasing interest in the last few years. In order to cope with the variety and complexity of buildings, a large number of fairly sophisticated grammar rules are needed. As yet, such rules mostly have to be designed by human experts. This article describes a novel approach to machine learning of attribute grammar rules based on the Inductive Logic Programming paradigm. Apart from syntactic differences, logic programs and attribute grammars are basically the same language. Attribute grammars extend context-free grammars by attributes and semantic rules and provide a much larger expressive power. Our approach to derive attribute grammars is able to deal with two kinds of input data. On the one hand, we show how attribute grammars can be derived from precise descriptions in the form of examples provided by a human user as the teacher. On the other hand, we present the acquisition of models from noisy observations such as 3D point clouds. This includes the learning of geometric and topological constraints by taking measurement errors into account. The feasibility of our approach is proven exemplarily by stairs, and a generic framework for learning other building parts is discussed. Stairs aggregate an arbitrary number of steps in a manner which is specified by topological and geometric constraints and can be modelled in a recursive way. Due to this recursion, they pose a special challenge to machine learning. In order to learn the concept of stairs, only a small number of examples were required. Our approach represents and addresses the quality of the given observations and
Neo, Yik Yaw; Parie, Lisa; Bakker, Frederique; Snelderwaard, Peter; Tudorache, Christian; Schaaf, Marcel; Slabbekoorn, Hans
2015-01-01
Auditory sensitivity in fish serves various important functions, but also makes fish susceptible to noise pollution. Human-generated sounds may affect behavioral patterns of fish, both in natural conditions and in captivity. Fish are often kept for consumption in aquaculture, on display in zoos and hobby aquaria, and for medical sciences in research facilities, but little is known about the impact of ambient sounds in fish tanks. In this study, we conducted two indoor exposure experiments with zebrafish (Danio rerio). The first experiment demonstrated that exposure to moderate sound levels (112 dB re 1 μPa) can affect the swimming behavior of fish by changing group cohesion, swimming speed and swimming height. Effects were brief for both continuous and intermittent noise treatments. In the second experiment, fish could influence exposure to higher sound levels by swimming freely between an artificially noisy fish tank (120-140 dB re 1 μPa) and another with ambient noise levels (89 dB re 1 μPa). Despite initial startle responses, and a brief period in which many individuals in the noisy tank dived down to the bottom, there was no spatial avoidance or noise-dependent tank preference at all. The frequent exchange rate of about 60 fish passages per hour between tanks was not affected by continuous or intermittent exposures. In conclusion, small groups of captive zebrafish were able to detect sounds already at relatively low sound levels and adjust their behavior to it. Relatively high sound levels were at least at the on-set disturbing, but did not lead to spatial avoidance. Further research is needed to show whether zebrafish are not able to avoid noisy areas or just not bothered. Quantitatively, these data are not directly applicable to other fish species or other fish tanks, but they do indicate that sound exposure may affect fish behavior in any captive condition.
Neo, Yik Yaw; Parie, Lisa; Bakker, Frederique; Snelderwaard, Peter; Tudorache, Christian; Schaaf, Marcel; Slabbekoorn, Hans
2015-01-01
Auditory sensitivity in fish serves various important functions, but also makes fish susceptible to noise pollution. Human-generated sounds may affect behavioral patterns of fish, both in natural conditions and in captivity. Fish are often kept for consumption in aquaculture, on display in zoos and hobby aquaria, and for medical sciences in research facilities, but little is known about the impact of ambient sounds in fish tanks. In this study, we conducted two indoor exposure experiments with zebrafish (Danio rerio). The first experiment demonstrated that exposure to moderate sound levels (112 dB re 1 μPa) can affect the swimming behavior of fish by changing group cohesion, swimming speed and swimming height. Effects were brief for both continuous and intermittent noise treatments. In the second experiment, fish could influence exposure to higher sound levels by swimming freely between an artificially noisy fish tank (120–140 dB re 1 μPa) and another with ambient noise levels (89 dB re 1 μPa). Despite initial startle responses, and a brief period in which many individuals in the noisy tank dived down to the bottom, there was no spatial avoidance or noise-dependent tank preference at all. The frequent exchange rate of about 60 fish passages per hour between tanks was not affected by continuous or intermittent exposures. In conclusion, small groups of captive zebrafish were able to detect sounds already at relatively low sound levels and adjust their behavior to it. Relatively high sound levels were at least at the on-set disturbing, but did not lead to spatial avoidance. Further research is needed to show whether zebrafish are not able to avoid noisy areas or just not bothered. Quantitatively, these data are not directly applicable to other fish species or other fish tanks, but they do indicate that sound exposure may affect fish behavior in any captive condition. PMID:25741256
Oprisan, Sorinel A.; Buhusi, Catalin V.
2011-01-01
In most species, the capability of perceiving and using the passage of time in the seconds-to-minutes range (interval timing) is not only accurate but also scalar: errors in time estimation are linearly related to the estimated duration. The ubiquity of scalar timing extends over behavioral, lesion, and pharmacological manipulations. For example, in mammals, dopaminergic drugs induce an immediate, scalar change in the perceived time (clock pattern), whereas cholinergic drugs induce a gradual, scalar change in perceived time (memory pattern). How do these properties emerge from unreliable, noisy neurons firing in the milliseconds range? Neurobiological information relative to the brain circuits involved in interval timing provide support for an striatal beat frequency (SBF) model, in which time is coded by the coincidental activation of striatal spiny neurons by cortical neural oscillators. While biologically plausible, the impracticality of perfect oscillators, or their lack thereof, questions this mechanism in a brain with noisy neurons. We explored the computational mechanisms required for the clock and memory patterns in an SBF model with biophysically realistic and noisy Morris–Lecar neurons (SBF–ML). Under the assumption that dopaminergic drugs modulate the firing frequency of cortical oscillators, and that cholinergic drugs modulate the memory representation of the criterion time, we show that our SBF–ML model can reproduce the pharmacological clock and memory patterns observed in the literature. Numerical results also indicate that parameter variability (noise) – which is ubiquitous in the form of small fluctuations in the intrinsic frequencies of neural oscillators within and between trials, and in the errors in recording/retrieving stored information related to criterion time – seems to be critical for the time-scale invariance of the clock and memory patterns. PMID:21977014
Schmidt, Sein; Scholz, Michael; Obermayer, Klaus; Brandt, Stephan A.
2013-01-01
Brain stimulation is having remarkable impact on clinical neurology. Brain stimulation can modulate neuronal activity in functionally segregated circumscribed regions of the human brain. Polarity, frequency, and noise specific stimulation can induce specific manipulations on neural activity. In contrast to neocortical stimulation, deep-brain stimulation has become a tool that can dramatically improve the impact clinicians can possibly have on movement disorders. In contrast, neocortical brain stimulation is proving to be remarkably susceptible to intrinsic brain-states. Although evidence is accumulating that brain stimulation can facilitate recovery processes in patients with cerebral stroke, the high variability of results impedes successful clinical implementation. Interestingly, recent data in healthy subjects suggests that brain-state dependent patterned stimulation might help resolve some of the intrinsic variability found in previous studies. In parallel, other studies suggest that noisy “stochastic resonance” (SR)-like processes are a non-negligible component in non-invasive brain stimulation studies. The hypothesis developed in this manuscript is that stimulation patterning with noisy and oscillatory components will help patients recover from stroke related deficits more reliably. To address this hypothesis we focus on two factors common to both neural computation (intrinsic variables) as well as brain stimulation (extrinsic variables): noise and oscillation. We review diverse theoretical and experimental evidence that demonstrates that subject-function specific brain-states are associated with specific oscillatory activity patterns. These states are transient and can be maintained by noisy processes. The resulting control procedures can resemble homeostatic or SR processes. In this context we try to extend awareness for inter-individual differences and the use of individualized stimulation in the recovery maximization of stroke patients. PMID:23825456
Adel Ghahraman, Mansoureh; Zahmatkesh, Maryam; Pourbakht, Akram; Seifi, Behjat; Jalaie, Shohreh; Adeli, Soheila; Niknami, Zohreh
2016-04-01
There are several anatomical connections between vestibular system and brain areas construct spatial memory. Since subliminal noisy galvanic vestibular stimulation (GVS) has been demonstrated to enhance some types of memory, we speculated that application of noisy GVS may improve spatial memory in a rat model of intracerebroventricular streptozotocin (ICV-STZ)-induced cognitive impairment. Moreover, we attempted to determine the effect of repeated exposure to GVS on spatial memory performance. The spatial memory was assessed using Morris water maze test. The groups received 1 (ICV-STZ/GVS-I) or 5 (ICV-STZ/GVS-II) sessions, each lasting 30 min, of low amplitude noisy GVS, or no GVS at all (Control, ICV-saline, ICV-STZ/noGVS). Hippocampal morphological changes investigated with cresyl violet staining and the immediate early gene product c-Fos, as a neuronal activity marker, was measured. Hippocampal c-Fos positive cells increased in both GVS stimulated groups. We observed significantly improved spatial performance only in ICV-STZ/GVS-II group. Histological evaluation showed normal density in ICV-STZ/GVS-II group whereas degeneration observed in ICV-STZ/GVS-I group similar to ICV-STZ/noGVS. The results showed the improvement of memory impairment after repeated exposure to GVS. This effect may be due in part to frequent activation of the vestibular neurons and the hippocampal regions connected to them. Our current study suggests the potential role of GVS as a practical method to combat cognitive decline induced by sporadic Alzheimer disease. Copyright © 2016 Elsevier Inc. All rights reserved.
Oprisan, Sorinel A; Buhusi, Catalin V
2011-01-01
In most species, the capability of perceiving and using the passage of time in the seconds-to-minutes range (interval timing) is not only accurate but also scalar: errors in time estimation are linearly related to the estimated duration. The ubiquity of scalar timing extends over behavioral, lesion, and pharmacological manipulations. For example, in mammals, dopaminergic drugs induce an immediate, scalar change in the perceived time (clock pattern), whereas cholinergic drugs induce a gradual, scalar change in perceived time (memory pattern). How do these properties emerge from unreliable, noisy neurons firing in the milliseconds range? Neurobiological information relative to the brain circuits involved in interval timing provide support for an striatal beat frequency (SBF) model, in which time is coded by the coincidental activation of striatal spiny neurons by cortical neural oscillators. While biologically plausible, the impracticality of perfect oscillators, or their lack thereof, questions this mechanism in a brain with noisy neurons. We explored the computational mechanisms required for the clock and memory patterns in an SBF model with biophysically realistic and noisy Morris-Lecar neurons (SBF-ML). Under the assumption that dopaminergic drugs modulate the firing frequency of cortical oscillators, and that cholinergic drugs modulate the memory representation of the criterion time, we show that our SBF-ML model can reproduce the pharmacological clock and memory patterns observed in the literature. Numerical results also indicate that parameter variability (noise) - which is ubiquitous in the form of small fluctuations in the intrinsic frequencies of neural oscillators within and between trials, and in the errors in recording/retrieving stored information related to criterion time - seems to be critical for the time-scale invariance of the clock and memory patterns.
Albocher, U; Barbone, P E; Richards, M S; Oberai, A A; Harari, I
2014-01-01
We apply the adjoint weighted equation method (AWE) to the direct solution of inverse problems of incompressible plane strain elasticity. We show that based on untreated noisy displacements, the reconstruction of the shear modulus can be very poor. We link this poor performance to loss of coercivity of the weak form when treating problems with discontinuous coefficients. We demonstrate that by smoothing the displacements and appending a regularization term to the AWE formulation, a dramatic improvement in the reconstruction can be achieved. With these improvements, the advantages of the AWE method as a direct solution approach can be extended to a wider range of problems.
Albocher, U.; Barbone, P.E.; Richards, M.S.; Oberai, A.A.; Harari, I.
2014-01-01
We apply the adjoint weighted equation method (AWE) to the direct solution of inverse problems of incompressible plane strain elasticity. We show that based on untreated noisy displacements, the reconstruction of the shear modulus can be very poor. We link this poor performance to loss of coercivity of the weak form when treating problems with discontinuous coefficients. We demonstrate that by smoothing the displacements and appending a regularization term to the AWE formulation, a dramatic improvement in the reconstruction can be achieved. With these improvements, the advantages of the AWE method as a direct solution approach can be extended to a wider range of problems. PMID:25383085
Fogedby, Hans C
2003-08-01
Using the previously developed canonical phase space approach applied to the noisy Burgers equation in one dimension, we discuss in detail the growth morphology in terms of nonlinear soliton modes and superimposed linear modes. We moreover analyze the non-Hermitian character of the linear mode spectrum and the associated dynamical pinning, and mode transmutation from diffusive to propagating behavior induced by the solitons. We discuss the anomalous diffusion of growth modes, switching and pathways, correlations in the multisoliton sector, and in detail the correlations and scaling properties in the two-soliton sector.
The effects of wall surface defects on boundary-layer transition in quiet and noisy supersonic flow
NASA Technical Reports Server (NTRS)
Morrisette, E. Leon; Creel, Theodore R., Jr.
1987-01-01
The design of supersonic vehicles with laminar flow control and vehicles such as the Space Shuttle requires information on allowable transition tolerances to fabrication defects such as discrete surface roughness and waviness. A relatively large data base on the effects of discrete roughness on transition exists for subsonic and supersonic speeds. The existing supersonic wind tunnel transition data are contaminated by wind tunnel noise emanating from the turbulent boundary layers on the nozzle walls. Roughness and waviness transition data obtained in a quiet Mach 3.5 supersonic wind tunnel are compared with those obtained in conventional noisy flows.
Fundamental Limits to Cellular Sensing
NASA Astrophysics Data System (ADS)
ten Wolde, Pieter Rein; Becker, Nils B.; Ouldridge, Thomas E.; Mugler, Andrew
2016-03-01
In recent years experiments have demonstrated that living cells can measure low chemical concentrations with high precision, and much progress has been made in understanding what sets the fundamental limit to the precision of chemical sensing. Chemical concentration measurements start with the binding of ligand molecules to receptor proteins, which is an inherently noisy process, especially at low concentrations. The signaling networks that transmit the information on the ligand concentration from the receptors into the cell have to filter this receptor input noise as much as possible. These networks, however, are also intrinsically stochastic in nature, which means that they will also add noise to the transmitted signal. In this review, we will first discuss how the diffusive transport and binding of ligand to the receptor sets the receptor correlation time, which is the timescale over which fluctuations in the state of the receptor, arising from the stochastic receptor-ligand binding, decay. We then describe how downstream signaling pathways integrate these receptor-state fluctuations, and how the number of receptors, the receptor correlation time, and the effective integration time set by the downstream network, together impose a fundamental limit on the precision of sensing. We then discuss how cells can remove the receptor input noise while simultaneously suppressing the intrinsic noise in the signaling network. We describe why this mechanism of time integration requires three classes (groups) of resources—receptors and their integration time, readout molecules, energy—and how each resource class sets a fundamental sensing limit. We also briefly discuss the scheme of maximum-likelihood estimation, the role of receptor cooperativity, and how cellular copy protocols differ from canonical copy protocols typically considered in the computational literature, explaining why cellular sensing systems can never reach the Landauer limit on the optimal trade
A Bayesian approach to solve proton stopping powers from noisy multi-energy CT data.
Lalonde, Arthur; Bär, Esther; Bouchard, Hugo
2017-10-01
using up to five energy bins. In terms of range prediction, Bayesian ETD with four energy bins in realistic conditions reduces proton beam range uncertainties by a factor of up to 1.5 compared to ρe - Z. The Bayesian ETD is shown to be more robust against noise than similar methods and a promising approach to extract SPR from noisy DECT data. In the advent of commercially available multi-energy CT or photon-counting CT scanners, the Bayesian ETD is expected to allow extracting more information and improve the precision of proton therapy beyond DECT. © 2017 American Association of Physicists in Medicine.
Hiley, Michael J; Yeadon, Maurice R
2014-08-01
The upstart is a fundamental skill in gymnastics, requiring whole body coordination to transfer the gymnast from a swing beneath the bar to a support position above the bar. The aim of this study was to determine the solution space within which a gymnast could successfully perform an upstart. A previous study had shown that the underlying control strategy for the upstart could be accounted for by maximizing the likelihood of success while operating in a noisy environment. In the current study, data were collected on a senior gymnast and a computer simulation model of a gymnast and bar was used to determine the solution space for maximizing success while operating in a noisy environment. The effects of timing important actions, gymnast strength, and movement execution noise on the success of the upstart were then systematically determined. The solution space for the senior gymnast was relatively large. Decreasing strength and increasing movement execution noise reduced the size of the solution space. A weaker gymnast would have to use a different technique than that used by the senior gymnast to produce an acceptable success rate.
Qazi, Sanjive; Beltukov, Aleksei; Trimmer, Barry A
2004-01-01
The first event in signal transduction at a synapse is the binding of transmitters to receptors. Because of rapidly changing transmitter levels this binding is unlikely to occur at equilibrium. We describe a mathematical approach that models complex receptor interactions in which the timing and amplitude of transmitter release are noisy. We show that exact solutions for simple bimolecular interactions and receptor transitions can be used to model complex reaction schemes by expressing them in sets of difference equations. Results from the difference equation method to describe binding and channel opening at extended time points compare well with standard solutions using ordinary differential equations. Because it is applicable to noisy systems we used the difference method to investigate the information processing capabilities of GABA receptors and predict how pharmacological agents may modify these properties. As previously demonstrated, the response to a single pulse of GABA is prolonged through entry into a desensitized state. During trains of stimuli the signal to noise ratio can change, and even increase progressively, but the overall transmitted fidelity of the signal decreases with increased driving frequency. The GABA modulator chlorpromazine (primarily affects agonist on and off rates) is predicated to increase receptor signal to noise ratio at all frequencies whereas pregnenolone sulfate (affects receptor desensitization) completely inhibits information transfer.
Moosavi, S Amin; Montakhab, Afshin
2014-05-01
Motivated by recent experiments in neuroscience which indicate that neuronal avalanches exhibit scale invariant behavior similar to self-organized critical systems, we study the role of noisy (nonconservative) local dynamics on the critical behavior of a sandpile model which can be taken to mimic the dynamics of neuronal avalanches. We find that despite the fact that noise breaks the strict local conservation required to attain criticality, our system exhibits true criticality for a wide range of noise in various dimensions, given that conservation is respected on the average. Although the system remains critical, exhibiting finite-size scaling, the value of critical exponents change depending on the intensity of local noise. Interestingly, for a sufficiently strong noise level, the critical exponents approach and saturate at their mean-field values, consistent with empirical measurements of neuronal avalanches. This is confirmed for both two and three dimensional models. However, the addition of noise does not affect the exponents at the upper critical dimension (D = 4). In addition to an extensive finite-size scaling analysis of our systems, we also employ a useful time-series analysis method to establish true criticality of noisy systems. Finally, we discuss the implications of our work in neuroscience as well as some implications for the general phenomena of criticality in nonequilibrium systems.
Meese, Tim S; Summers, Robert J
2012-10-17
Contrast sensitivity improves with the area of a sine-wave grating, but why? Here we assess this phenomenon against contemporary models involving spatial summation, probability summation, uncertainty, and stochastic noise. Using a two-interval forced-choice procedure we measured contrast sensitivity for circular patches of sine-wave gratings with various diameters that were blocked or interleaved across trials to produce low and high extrinsic uncertainty, respectively. Summation curves were steep initially, becoming shallower thereafter. For the smaller stimuli, sensitivity was slightly worse for the interleaved design than for the blocked design. Neither area nor blocking affected the slope of the psychometric function. We derived model predictions for noisy mechanisms and extrinsic uncertainty that was either low or high. The contrast transducer was either linear (c(1.0)) or nonlinear (c(2.0)), and pooling was either linear or a MAX operation. There was either no intrinsic uncertainty, or it was fixed or proportional to stimulus size. Of these 10 canonical models, only the nonlinear transducer with linear pooling (the noisy energy model) described the main forms of the data for both experimental designs. We also show how a cross-correlator can be modified to fit our results and provide a contemporary presentation of the relation between summation and the slope of the psychometric function.
NASA Astrophysics Data System (ADS)
Xiang, Shang; Jiang, Weikang; Pan, Siwei
2015-12-01
A modified inverse patch transfer function (iPTF) method is used to reconstruct the normal velocities of the target source in a noisy environment. The iPTF method simplifies the Helmholtz integral equation to one term by constructing a Green's function satisfying Neumann boundary conditions for an enclosure, which is generally constructed by slowly convergent modal expansions. The main objective of the present work is to provide an evanescent Green's function to improve the convergence of calculations. A brief description of the iPTF method and two sets of Green's functions for a rectangular cavity are presented firstly. In simulations, both the Green's functions are used to calculate the condition numbers of impedance matrices describing the relation between source and measurement patches, and the time cost of calculation based on the two sets of Green's functions at 450 Hz is compared. Double pressure measurements are then employed as the input data instead of pressure and velocity measurements. The normal velocities of two baffled loudspeakers are reconstructed by the combination of a measurement method and a Green's function in the presence of a disturbing source in the frequency range of 50-1000 Hz. In addition, the double pressure measurements are examined by an experiment. The precise identification of the sources indicates that the double pressure measurements are capable of localizing sources in a noisy environment. It is also found that the reconstruction with the evanescent Green's functions is slightly better than that with the modal expansions.
Choi, Yong-Sun; Lee, Soo-Young
2013-09-01
A nonlinear speech feature extraction algorithm was developed by modeling human cochlear functions, and demonstrated as a noise-robust front-end for speech recognition systems. The algorithm was based on a model of the Organ of Corti in the human cochlea with such features as such as basilar membrane (BM), outer hair cells (OHCs), and inner hair cells (IHCs). Frequency-dependent nonlinear compression and amplification of OHCs were modeled by lateral inhibition to enhance spectral contrasts. In particular, the compression coefficients had frequency dependency based on the psychoacoustic evidence. Spectral subtraction and temporal adaptation were applied in the time-frame domain. With long-term and short-term adaptation characteristics, these factors remove stationary or slowly varying components and amplify the temporal changes such as onset or offset. The proposed features were evaluated with a noisy speech database and showed better performance than the baseline methods such as mel-frequency cepstral coefficients (MFCCs) and RASTA-PLP in unknown noisy conditions.
NASA Astrophysics Data System (ADS)
Moosavi, S. Amin; Montakhab, Afshin
2014-05-01
Motivated by recent experiments in neuroscience which indicate that neuronal avalanches exhibit scale invariant behavior similar to self-organized critical systems, we study the role of noisy (nonconservative) local dynamics on the critical behavior of a sandpile model which can be taken to mimic the dynamics of neuronal avalanches. We find that despite the fact that noise breaks the strict local conservation required to attain criticality, our system exhibits true criticality for a wide range of noise in various dimensions, given that conservation is respected on the average. Although the system remains critical, exhibiting finite-size scaling, the value of critical exponents change depending on the intensity of local noise. Interestingly, for a sufficiently strong noise level, the critical exponents approach and saturate at their mean-field values, consistent with empirical measurements of neuronal avalanches. This is confirmed for both two and three dimensional models. However, the addition of noise does not affect the exponents at the upper critical dimension (D =4). In addition to an extensive finite-size scaling analysis of our systems, we also employ a useful time-series analysis method to establish true criticality of noisy systems. Finally, we discuss the implications of our work in neuroscience as well as some implications for the general phenomena of criticality in nonequilibrium systems.
NASA Technical Reports Server (NTRS)
Holzmann, Gerard J.
2008-01-01
In the last 3 decades or so, the size of systems we have been able to verify formally with automated tools has increased dramatically. At each point in this development, we encountered a different set of limits -- many of which we were eventually able to overcome. Today, we may have reached some limits that may be much harder to conquer. The problem I will discuss is the following: given a hypothetical machine with infinite memory that is seamlessly shared among infinitely many CPUs (or CPU cores), what is the largest problem size that we could solve?
Quantum cryptography approaching the classical limit.
Weedbrook, Christian; Pirandola, Stefano; Lloyd, Seth; Ralph, Timothy C
2010-09-10
We consider the security of continuous-variable quantum cryptography as we approach the classical limit, i.e., when the unknown preparation noise at the sender's station becomes significantly noisy or thermal (even by as much as 10(4) times greater than the variance of the vacuum mode). We show that, provided the channel transmission losses do not exceed 50%, the security of quantum cryptography is not dependent on the channel transmission, and is therefore incredibly robust against significant amounts of excess preparation noise. We extend these results to consider for the first time quantum cryptography at wavelengths considerably longer than optical and find that regions of security still exist all the way down to the microwave.
Porter, P.S.; Ward, R.C.; Bell, H.F.
1988-08-01
Water quality monitoring data are plagued with levels of chemicals that are too low to be measured precisely. This discussion will focus on the information needs of water quality management and how these needs are best met for monitoring systems that require many trace-level measurements. We propose that the limit of detection (LOD) or the limit of quantitation (LOQ) not be used to censor data. Although LOD and LOQ aid in the interpretation of individual measurements, they hinder statistical analysis of water quality data. More information is gained when a numerical result and an estimate of measurement precision are reported for every measurement, as opposed to reporting not detected or less than. This article is not intended to be a review of the issues pertaining to the LOD and related concepts.
NASA Astrophysics Data System (ADS)
Webb, S. J.; Van Buren, R.
2013-12-01
Airborne geophysical methods play an important role in the exploration for kimberlites. As regions become more intensively explored, smaller kimberlites, which can be extremely difficult to find, are being targeted. These smaller kimberlites, as evidenced by the M-1 Maarsfontein pipe in the Klipspringer cluster in South Africa, can be highly profitable. The Goedgevonden and Syferfontein pipes are small kimberlites (~0.2 ha) ~25 km NNE of Klerksdorp in South Africa. The Goedgevonden pipe has been known since the 1930s and is diamondiferous, but not commercially viable due to small stone size and low quality of stones. In the early 1990s, Gold Fields used this pipe as a typical kimberlite to collect example geophysical data. The nearby (~1 km to the east) Syferfontein pipe is not diamondiferous but was discovered in 1994 as part of a speculative airborne EM survey conducted by Gold Fields and Geodass (now CGG) as part of their case study investigations. Both kimberlites have had extensive ground geophysical survey data collected and have prominent magnetic, gravity and EM responses that aided in the delineation of the pipes. These pipes represent a realistic and challenging case study target due to their small size and the magnetically noisy environment into which they have been emplaced. The discovery of the Syferfontein pipe in 1994 stimulated further testing of airborne methods, especially as the surface was undisturbed. These pipes are located in a region that hosts highly variably magnetized Hospital Hill shales, dolerite dykes and Ventersdorp lavas, a 2-3 m thick resistive ferricrete cap and significant cultural features such as an electric railroad and high tension power line. Although the kimberlites both show prominent magnetic anomalies on ground surveys, the airborne data are significantly noisy and the pipes do not show up as well determined targets. However, the clay-rich weathered zone of the pipes provides an ideal target for the EM method, and both
Geophysical Prospection of Archaeological Structures in a Noisy Area in Shayzar, Syria
NASA Astrophysics Data System (ADS)
Seren, S.; Hinterleitner, A.; Löcker, K.; Bayirli, E.
2009-04-01
Site The roman town "Caesarea", which was named "Sezer" and used as a citadel in middle ages, is located within the modern town "Shayzar" in the north-west of Syria. The modern buildings, power lines and the streets with a lot of cars cause a very noisy environment for geophysical prospection. A football ground of about 50x90 m was chosen for testing both methods, magnetic and ground penetrating radar (GPR), to detect archaeological structures. Instruments and survey area The magnetic survey was carried out using a fluxgate magnetic acquisition system with 4 sensors in gradient array from the manufacturer FÖRSTER® mounted on a one wheel cart. The cart was developed in our institute and allows to record high quality data in areas with difficult field conditions. An optical distance measurement system on the wheel ensures an exact positioning of the magnetic data. The measurement grid was 50x10 cm. GPR survey was carried out using a NOGGIN system with 250 MHz antenna from the manufacturer Sensors & Software. A new base plate was mounted on the antenna for the easy moving at rough surface conditions. The measurement grid was 50x5 cm. Data processing The magnetic data are processed using the self developed software ApMag. The main steps of the processing are filtering, removing of the line pattern, interpolation to a grid of 10x10 cm, geo-referencing and producing of a grey scale magnetogramm for visualizing in a geographical information system (GIS). The GPR data are automatically processed using the self developed software package ApRadar. Several pre-processing steps were carried out including removing of constant shifts, automatic detection of the starting point (time zero), frequency dependent high-pass filtering and a background removal filter to get the best results for each measurement. There is no gain control algorithm applied to the traces of a section but a statistical correction of each depth-slice for each section. This is equal to an automatic gain
Keil, Matthias S.
2015-01-01
Power laws describe brain functions at many levels (from biophysics to psychophysics). It is therefore possible that they are generated by similar underlying mechanisms. Previously, the response properties of a collision-sensitive neuron were reproduced by a model which used a power law for scaling its inhibitory input. A common characteristic of such neurons is that they integrate information across a large part of the visual field. Here we present a biophysically plausible model of collision-sensitive neurons with η-like response properties, in which we assume that each information channel is noisy and has a response threshold. Then, an approximative power law is obtained as a result of pooling these channels. We show that with this mechanism one can successfully predict many response characteristics of the Lobula Giant Movement Detector Neuron (LGMD). Moreover, the results depend critically on noise in the inhibitory pathway, but they are fairly robust against noise in the excitatory pathway. PMID:26513150
Katkovnik, Vladimir; Shevkunov, Igor; Petrov, Nikolay V; Egiazarian, Karen
2016-10-31
A variational algorithm to object wavefront reconstruction from noisy intensity observations is developed for the off-axis holography scenario with imaging in the acquisition plane. The algorithm is based on the local least square technique proposed in paper [J. Opt. Soc. Am. A21, 367 (2004)]. First, multiple reconstructions of the wavefront are produced for various size and various directional windows applied for localization of estimation. At the second stage, a special statistical rule is applied in order to select the best window size estimate for each pixel of the image and for each of the directional windows. At the third final stage the estimates of the different directions obtained for each pixel are aggregated in the final one. Simulation experiments and real data processing prove that the developed algorithm demonstrate the performance of the extraordinary quality and accuracy for both the phase and amplitude of the object wavefront.
ERIC Educational Resources Information Center
Nguyen, Huong Thi Thien
2011-01-01
The two objectives of this single-subject study were to assess how an FM system use impacts parent-child interaction in a noisy listening environment, and how a parent/caregiver training affect the interaction between parent/caregiver and child. Two 5-year-old children with hearing loss and their parent/caregiver participated. Experiment 1 was…
Whole Sentence Spelling and Grammar Correction Using a Noisy Channel Model
ERIC Educational Resources Information Center
Park, Yonghahk Albert
2013-01-01
Automated grammar correction techniques have seen improvement over the years, but there is still much room for increased performance. Current correction techniques mainly focus on identifying and correcting a specific type of error, such as verb form misuse or preposition misuse, which restricts the corrections to a limited scope. We introduce a…
Whole Sentence Spelling and Grammar Correction Using a Noisy Channel Model
ERIC Educational Resources Information Center
Park, Yonghahk Albert
2013-01-01
Automated grammar correction techniques have seen improvement over the years, but there is still much room for increased performance. Current correction techniques mainly focus on identifying and correcting a specific type of error, such as verb form misuse or preposition misuse, which restricts the corrections to a limited scope. We introduce a…
Antfolk, Jan
2017-03-01
Whereas women of all ages prefer slightly older sexual partners, men-regardless of their age-have a preference for women in their 20s. Earlier research has suggested that this difference between the sexes' age preferences is resolved according to women's preferences. This research has not, however, sufficiently considered that the age range of considered partners might change over the life span. Here we investigated the age limits (youngest and oldest) of considered and actual sex partners in a population-based sample of 2,655 adults (aged 18-50 years). Over the investigated age span, women reported a narrower age range than men and women tended to prefer slightly older men. We also show that men's age range widens as they get older: While they continue to consider sex with young women, men also consider sex with women their own age or older. Contrary to earlier suggestions, men's sexual activity thus reflects also their own age range, although their potential interest in younger women is not likely converted into sexual activity. Compared to homosexual men, bisexual and heterosexual men were more unlikely to convert young preferences into actual behavior, supporting female-choice theory.
Multiscale Analysis of Photon-Limited Astronomical Images
NASA Astrophysics Data System (ADS)
Willett, R.
2007-11-01
Many astronomical studies rely upon the accurate reconstruction of spatially distributed phenomena from photon-limited data. These measurements are inherently ``noisy'' due to low photon counts. In addition, the behavior of the underlying photon intensity functions can be very rich and complex, and consequently difficult to model a priori. Nonparametric multiscale reconstruction methods overcome these challenges and facilitate characterization of fundamental performance limits. In this paper, we review several multiscale approaches to photon-limited image reconstruction, including wavelets combined with variance stabilizing transforms, corrected Haar wavelet transforms, multiplicative multiscale innovations, platelets, and the à trous wavelet transform. We discuss the performance of these methods in simulation studies, and describe statistical analyses of their performances.
How input noise limits biochemical sensing in ultrasensitive systems
NASA Astrophysics Data System (ADS)
Hu, Bo; Rappel, Wouter-Jan; Levine, Herbert
2014-09-01
Many biological processes are regulated by molecular devices that respond in an ultrasensitive fashion to upstream signals. An important question is whether such ultrasensitivity improves or limits its ability to read out the (noisy) input stimuli. Here, we develop a simple model to study the statistical properties of ultrasensitive signaling systems. We demonstrate that the output sensory noise is always bounded, in contrast to earlier theories using the small noise approximation, which tends to overestimate the impact of noise in ultrasensitive pathways. Our analysis also shows that the apparent sensitivity of the system is ultimately constrained by the input signal-to-noise ratio. Thus, ultrasensitivity can improve the precision of biochemical sensing only to a finite extent. This corresponds to a new limit for ultrasensitive signaling systems, which is strictly tighter than the Berg-Purcell limit.
Etchepareborda, Pablo; Vadnjal, Ana Laura; Federico, Alejandro; Kaufmann, Guillermo H
2012-09-15
We evaluate the extension of the exact nonlinear reconstruction technique developed for digital holography to the phase-recovery problems presented by other optical interferometric methods, which use carrier modulation. It is shown that the introduction of an analytic wavelet analysis in the ridge of the cepstrum transformation corresponding to the analyzed interferogram can be closely related to the well-known wavelet analysis of the interferometric intensity. Subsequently, the phase-recovery process is improved. The advantages and limitations of this framework are analyzed and discussed using numerical simulations in singular scalar light fields and in temporal speckle pattern interferometry.
NASA Astrophysics Data System (ADS)
Trofimov, Vyacheslav A.; Varentsova, Svetlana A.; Trofimov, Vladislav V.; Tikhomirov, Vasily V.
2015-08-01
Principal limitations of the standard THz-TDS method for the detection and identification are demonstrated under real conditions (at long distance of about 3.5 m and at a high relative humidity more than 50%) using neutral substances thick paper bag, paper napkins and chocolate. We show also that the THz-TDS method detects spectral features of dangerous substances even if the THz signals were measured in laboratory conditions (at distance 30-40 cm from the receiver and at a low relative humidity less than 2%); silicon-based semiconductors were used as the samples. However, the integral correlation criteria, based on SDA method, allows us to detect the absence of dangerous substances in the neutral substances. The discussed algorithm shows high probability of the substance identification and a reliability of realization in practice, especially for security applications and non-destructive testing.
Renewal Approach to the Analysis of the Asynchronous State for Coupled Noisy Oscillators
NASA Astrophysics Data System (ADS)
Farkhooi, Farzad; van Vreeswijk, Carl
2015-07-01
We develop a framework in which the activity of nonlinear pulse-coupled oscillators is posed within the renewal theory. In this approach, the evolution of the interevent density allows for a self-consistent calculation that determines the asynchronous state and its stability. This framework can readily be extended to the analysis of systems with more state variables and provides a population density treatment to evolve them in their thermodynamical limits. To demonstrate this we study a nonlinear pulse-coupled system, where couplings are dynamic and activity dependent. We investigate its stability and numerically study the nonequilibrium behavior of the system after the bifurcation. We show that this system undergoes a supercritical Hopf bifurcation to collective synchronization.
Zhang, Zhongqiang; Yang, Xiu; Lin, Guang
2016-04-14
Sensor placement at the extrema of Proper Orthogonal Decomposition (POD) is efficient and leads to accurate reconstruction of the wind field from a limited number of measure- ments. In this paper we extend this approach of sensor placement and take into account measurement errors and detect possible malfunctioning sensors. We use the 48 hourly spa- tial wind field simulation data sets simulated using the Weather Research an Forecasting (WRF) model applied to the Maine Bay to evaluate the performances of our methods. Specifically, we use an exclusion disk strategy to distribute sensors when the extrema of POD modes are close. It turns out that this strategy can also reduce the error of recon- struction from noise measurements. Also, by a cross-validation technique, we successfully locate the malfunctioning sensors.
Power Spectrum of a Noisy System Close to a Heteroclinic Orbit
NASA Astrophysics Data System (ADS)
Giner-Baldó, Jordi; Thomas, Peter J.; Lindner, Benjamin
2017-07-01
We consider a two-dimensional dynamical system that possesses a heteroclinic orbit connecting four saddle points. This system is not able to show self-sustained oscillations on its own. If endowed with white Gaussian noise it displays stochastic oscillations, the frequency and quality factor of which are controlled by the noise intensity. This stochastic oscillation of a nonlinear system with noise is conveniently characterized by the power spectrum of suitable observables. In this paper we explore different analytical and semianalytical ways to compute such power spectra. Besides a number of explicit expressions for the power spectrum, we find scaling relations for the frequency, spectral width, and quality factor of the stochastic heteroclinic oscillator in the limit of weak noise. In particular, the quality factor shows a slow logarithmic increase with decreasing noise of the form Q˜ [ln (1/D)]^2. Our results are compared to numerical simulations of the respective Langevin equations.
Zhang, Zhongqiang; Yang, Xiu; Lin, Guang
2016-04-14
Sensor placement at the extrema of Proper Orthogonal Decomposition (POD) is efficient and leads to accurate reconstruction of the wind field from a limited number of measure- ments. In this paper we extend this approach of sensor placement and take into account measurement errors and detect possible malfunctioning sensors. We use the 48 hourly spa- tial wind field simulation data sets simulated using the Weather Research an Forecasting (WRF) model applied to the Maine Bay to evaluate the performances of our methods. Specifically, we use an exclusion disk strategy to distribute sensors when the extrema of POD modes are close.more » It turns out that this strategy can also reduce the error of recon- struction from noise measurements. Also, by a cross-validation technique, we successfully locate the malfunctioning sensors.« less
Kercel, Stephen W.
1998-10-11
For several reasons, Bayesian parameter estimation is superior to other methods for extracting features of a weak signal from noise. Since it exploits prior knowledge, the analysis begins from a more advantageous starting point than other methods. Also, since ''nuisance parameters'' can be dropped out of the Bayesian analysis, the description of the model need not be as complete as is necessary for such methods as matched filtering. In the limit for perfectly random noise and a perfect description of the model, the signal-to-noise ratio improves as the square root of the number of samples in the data. Even with the imperfections of real-world data, Bayesian approaches this ideal limit of performance more closely than other methods. A major unsolved problem in landmine detection is the fusion of data from multiple sensor types. Bayesian data fusion is only beginning to be explored as a solution to the problem. In single sensor processes Bayesian analysis can sense multiple parameters from the data stream of the one sensor. It does so by computing a joint probability density function of a set of parameter values from the sensor output. However, there is no inherent requirement that the information must come from a single sensor. If multiple sensors are applied to a single process, where several different parameters are implicit in each sensor output data stream, the joint probability density function of all the parameters of interest can be computed in exactly the same manner as the single sensor case. Thus, it is just as practical to base decisions on multiple sensor outputs as it is for single sensors. This should provide a practical way to combine the outputs of dissimilar sensors, such as ground penetrating radar and electromagnetic induction devices, producing a better detection decision than could be provided by either sensor alone.
Detecting and estimating signals in noisy cable structures, II: information theoretical analysis.
Manwani, A; Koch, C
1999-11-15
This is the second in a series of articles that seek to recast classical single-neuron biophysics in information-theoretical terms. Classical cable theory focuses on analyzing the voltage or current attenuation of a synaptic signal as it propagates from its dendritic input location to the spike initiation zone. On the other hand, we are interested in analyzing the amount of information lost about the signal in this process due to the presence of various noise sources distributed throughout the neuronal membrane. We use a stochastic version of the linear one-dimensional cable equation to derive closed-form expressions for the second-order moments of the fluctuations of the membrane potential associated with different membrane current noise sources: thermal noise, noise due to the random opening and closing of sodium and potassium channels, and noise due to the presence of "spontaneous" synaptic input. We consider two different scenarios. In the signal estimation paradigm, the time course of the membrane potential at a location on the cable is used to reconstruct the detailed time course of a random, band-limited current injected some distance away. Estimation performance is characterized in terms of the coding fraction and the mutual information. In the signal detection paradigm, the membrane potential is used to determine whether a distant synaptic event occurred within a given observation interval. In the light of our analytical results, we speculate that the length of weakly active apical dendrites might be limited by the information loss due to the accumulated noise between distal synaptic input sites and the soma and that the presence of dendritic nonlinearities probably serves to increase dendritic information transfer.
Lymperopoulos, Ilias N; Ioannou, George D
2016-10-01
We develop and validate a model of the micro-level dynamics underlying the formation of macro-level information propagation patterns in online social networks. In particular, we address the dynamics at the level of the mechanism regulating a user's participation in an online information propagation process. We demonstrate that this mechanism can be realistically described by the dynamics of noisy spiking neurons driven by endogenous and exogenous, deterministic and stochastic stimuli representing the influence modulating one's intention to be an information spreader. Depending on the dynamically changing influence characteristics, time-varying propagation patterns emerge reflecting the temporal structure, strength, and signal-to-noise ratio characteristics of the stimulation driving the online users' information sharing activity. The proposed model constitutes an overarching, novel, and flexible approach to the modeling of the micro-level mechanisms whereby information propagates in online social networks. As such, it can be used for a comprehensive understanding of the online transmission of information, a process integral to the sociocultural evolution of modern societies. The proposed model is highly adaptable and suitable for the study of the propagation patterns of behavior, opinions, and innovations among others.
NASA Astrophysics Data System (ADS)
Trofimov, Vyacheslav A.; Varentsova, Svetlana A.; Trofimov, Vladislav V.
2015-05-01
We show possibility of the detection and identification of substance at long distance (several metres, for example) using the THz pulse reflected from the object under the real conditions: at room temperature and humidity of about 70%. The main feature of this report consists in a demonstration of the detection and identification of substance using the computer processing of the noisy THz pulse. Amplitude of the useful signal is less than the amplitude of a noise. Nevertheless, it is possible to detect "fingerprint" frequencies of substance if these frequencies are known and the SDA method is used together with new assessments for probability estimation for presence of detected frequencies. Essential restrictions of the commonly used THz TDS method for the detection and identification under real conditions (at long distance about 3.5 m and at a high relative humidity more than 50%) are demonstrated using the physical experiment with chocolate bar and thick paper bag. We show also that the THz TDS method detects spectral features of dangerous substances even in the THz signals measured in laboratory conditions (at distance 30-40 cm from the receiver and at a low relative humidity less than 2%); the n-Si and p-Si semiconductors were used as neutral substances. However, the integral correlation and likeness criteria, based on SDA method, allow us to detect the absence of dangerous substances in the samples. Current results show feasibility of using the discussed method of the THz pulsed spectroscopy for the counter-terrorism problem.
NASA Astrophysics Data System (ADS)
Wang, Xuemei; Ni, Wenbo
2016-09-01
For loosely coupled INS/GPS integrated navigation systems with low-cost and low-accuracy microelectromechanical device inertial sensors, in order to obtain enough accuracy, a full-state nonlinear dynamic model rather than a linearized error model is much more preferable. Particle filters are particularly for nonlinear and non-Gaussian situations, but typical bootstrap particle filters (BPFs) and some improved particle filters (IPFs) such as auxiliary particle filters (APFs) and Gaussian particle filters (GPFs) cannot solve the mismatch between the importance function and the likelihood function very well. The predicted particles propagated through inertial navigation equations cannot be scattered with certainty within the effective range of current observation when there are large drift errors of the inertial sensors. Therefore, the current observation cannot play the correction role well and these particle filters are invalid to some extent. The proposed IPF firstly estimates the corresponding state bias errors according to the current observation and then corrects the bias errors of the predicted particles before determining the weights and resampling the particles. Simulations and practical experiments both show that the proposed IPF can effectively solve the mismatch between the importance function and the likelihood function of a BPF and compensate the accumulated errors of INSs very well. It has great robustness in a serious noisy scenario.
Moore, Steven T; Dilda, Valentina; Morris, Tiffany R; Yungher, Don A; MacDougall, Hamish G
2015-01-01
Performance on a visuomotor task in the presence of novel vestibular stimulation was assessed in nine healthy subjects. Four subjects had previously been adapted to 120 min exposure to noisy Galvanic vestibular stimulation (GVS) over 12 weekly sessions of 10 min; the remaining five subjects had never experienced GVS. Subjects were seated in a flight simulator and asked to null the roll motion of a visual bar presented on a screen using a joystick. Both the visual bar and the simulator cabin were moving in roll with a pseudorandom (sum of sines) waveform that were uncorrelated. The cross correlation coefficient, which ranges from 1 (identical waveforms) to 0 (unrelated waveforms), was calculated for the ideal (perfect nulling of bar motion) and actual joystick input waveform for each subject. The cross correlation coefficient for the GVS-adapted group (0.90 [SD 0.04]) was significantly higher (t[8] = 3.162; p = 0.013) than the control group (0.82 [SD 0.04]), suggesting that prior adaptation to GVS was associated with an enhanced ability to perform the visuomotor task in the presence of novel vestibular noise.