Jeuring, J.T.
1995-01-01
The pattern matching problem can be informally specified as follows: given a pattern and a text, find all occurrences of the pattern in the text. The pattern and the text may both be lists, or they may both be trees, or they may both be multi-dimensional arrays, etc. This paper describes a general
Pattern recognition and string matching
Cheng, Xiuzhen
2002-01-01
The research and development of pattern recognition have proven to be of importance in science, technology, and human activity. Many useful concepts and tools from different disciplines have been employed in pattern recognition. Among them is string matching, which receives much theoretical and practical attention. String matching is also an important topic in combinatorial optimization. This book is devoted to recent advances in pattern recognition and string matching. It consists of twenty eight chapters written by different authors, addressing a broad range of topics such as those from classifica tion, matching, mining, feature selection, and applications. Each chapter is self-contained, and presents either novel methodological approaches or applications of existing theories and techniques. The aim, intent, and motivation for publishing this book is to pro vide a reference tool for the increasing number of readers who depend upon pattern recognition or string matching in some way. This includes student...
Feature Matching for SAR and Optical Images Based on Gaussian-Gamma-shaped Edge Strength Map
Directory of Open Access Journals (Sweden)
CHEN Min
2016-03-01
Full Text Available A matching method for SAR and optical images, robust to pixel noise and nonlinear grayscale differences, is presented. Firstly, a rough correction to eliminate rotation and scale change between images is performed. Secondly, features robust to speckle noise of SAR image are detected by improving the original phase congruency based method. Then, feature descriptors are constructed on the Gaussian-Gamma-shaped edge strength map according to the histogram of oriented gradient pattern. Finally, descriptor similarity and geometrical relationship are combined to constrain the matching processing.The experimental results demonstrate that the proposed method provides significant improvement in correct matches number and image registration accuracy compared with other traditional methods.
Fuzzy automata and pattern matching
Setzer, C. B.; Warsi, N. A.
1986-01-01
A wide-ranging search for articles and books concerned with fuzzy automata and syntactic pattern recognition is presented. A number of survey articles on image processing and feature detection were included. Hough's algorithm is presented to illustrate the way in which knowledge about an image can be used to interpret the details of the image. It was found that in hand generated pictures, the algorithm worked well on following the straight lines, but had great difficulty turning corners. An algorithm was developed which produces a minimal finite automaton recognizing a given finite set of strings. One difficulty of the construction is that, in some cases, this minimal automaton is not unique for a given set of strings and a given maximum length. This algorithm compares favorably with other inference algorithms. More importantly, the algorithm produces an automaton with a rigorously described relationship to the original set of strings that does not depend on the algorithm itself.
A review on compressed pattern matching
Directory of Open Access Journals (Sweden)
Surya Prakash Mishra
2016-09-01
Full Text Available Compressed pattern matching (CPM refers to the task of locating all the occurrences of a pattern (or set of patterns inside the body of compressed text. In this type of matching, pattern may or may not be compressed. CPM is very useful in handling large volume of data especially over the network. It has many applications in computational biology, where it is useful in finding similar trends in DNA sequences; intrusion detection over the networks, big data analytics etc. Various solutions have been provided by researchers where pattern is matched directly over the uncompressed text. Such solution requires lot of space and consumes lot of time when handling the big data. Various researchers have proposed the efficient solutions for compression but very few exist for pattern matching over the compressed text. Considering the future trend where data size is increasing exponentially day-by-day, CPM has become a desirable task. This paper presents a critical review on the recent techniques on the compressed pattern matching. The covered techniques includes: Word based Huffman codes, Word Based Tagged Codes; Wavelet Tree Based Indexing. We have presented a comparative analysis of all the techniques mentioned above and highlighted their advantages and disadvantages.
Xiao, Di; Vignarajan, Janardhan; An, Dong; Tay-Kearney, Mei-Ling; Kanagasingam, Yogi
2016-03-01
Retinal photography is a non-invasive and well-accepted clinical diagnosis of ocular diseases. Qualitative and quantitative assessment of retinal images is crucial in ocular diseases related clinical application. In this paper, we proposed approaches for improving the quality of blood vessel detection based on our initial blood vessel detection methods. A blood vessel spur pruning method has been developed for removing the blood vessel spurs both on vessel medial lines and binary vessel masks, which are caused by artifacts and side-effect of Gaussian matched vessel enhancement. A Gaussian matched filtering compensation method has been developed for removing incorrect vessel branches in the areas of low illumination. The proposed approaches were applied and tested on the color fundus images from one publicly available database and our diabetic retinopathy screening dataset. A preliminary result has demonstrated the robustness and good performance of the proposed approaches and their potential application for improving retinal blood vessel detection.
Dwivedi, Prashant Povel; Kumar, Challa Sesha Sai Pavan; Choi, Hee Joo; Cha, Myoungsik
2016-02-01
Random duty-cycle error (RDE) is inherent in the fabrication of ferroelectric quasi-phase-matching (QPM) gratings. Although a small RDE may not affect the nonlinearity of QPM devices, it enhances non-phase-matched parasitic harmonic generations, limiting the device performance in some applications. Recently, we demonstrated a simple method for measuring the RDE in QPM gratings by analyzing the far-field diffraction pattern obtained by uniform illumination (Dwivedi et al. in Opt Express 21:30221-30226, 2013). In the present study, we used a Gaussian beam illumination for the diffraction experiment to measure noise spectra that are less affected by the pedestals of the strong diffraction orders. Our results were compared with our calculations based on a random grating model, demonstrating improved resolution in the RDE estimation.
Directory of Open Access Journals (Sweden)
Abdenaceur Boudlal
2010-01-01
Full Text Available This article investigates a new method of motion estimation based on block matching criterion through the modeling of image blocks by a mixture of two and three Gaussian distributions. Mixture parameters (weights, means vectors, and covariance matrices are estimated by the Expectation Maximization algorithm (EM which maximizes the log-likelihood criterion. The similarity between a block in the current image and the more resembling one in a search window on the reference image is measured by the minimization of Extended Mahalanobis distance between the clusters of mixture. Performed experiments on sequences of real images have given good results, and PSNR reached 3 dB.
On Tree Pattern Matching by Pushdown Automata
Directory of Open Access Journals (Sweden)
T. Flouri
2009-01-01
Full Text Available Tree pattern matching is an important operation in Computer Science on which a number of tasks such as mechanical theorem proving, term-rewriting, symbolic computation and non-procedural programming languages are based on. Work has begun on a systematic approach to the construction of tree pattern matchers by deterministic pushdown automata which read subject trees in prefix notation. The method is analogous to the construction of string pattern matchers: for given patterns, a non-deterministic pushdown automaton is created and then it is determinised. In this first paper, we present the proposed non-deterministic pushdown automaton which will serve as a basis for the determinisation process, and prove its correctness.
Enhancement of force patterns classification based on Gaussian distributions.
Ertelt, Thomas; Solomonovs, Ilja; Gronwald, Thomas
2018-01-23
Description of the patterns of ground reaction force is a standard method in areas such as medicine, biomechanics and robotics. The fundamental parameter is the time course of the force, which is classified visually in particular in the field of clinical diagnostics. Here, the knowledge and experience of the diagnostician is relevant for its assessment. For an objective and valid discrimination of the ground reaction force pattern, a generic method, especially in the medical field, is absolutely necessary to describe the qualities of the time-course. The aim of the presented method was to combine the approaches of two existing procedures from the fields of machine learning and the Gauss approximation in order to take advantages of both methods for the classification of ground reaction force patterns. The current limitations of both methods could be eliminated by an overarching method. Twenty-nine male athletes from different sports were examined. Each participant was given the task of performing a one-legged stopping maneuver on a force plate from the maximum possible starting speed. The individual time course of the ground reaction force of each subject was registered and approximated on the basis of eight Gaussian distributions. The descriptive coefficients were then classified using Bayesian regulated neural networks. The different sports served as the distinguishing feature. Although the athletes were all given the same task, all sports referred to a different quality in the time course of ground reaction force. Meanwhile within each sport, the athletes were homogeneous. With an overall prediction (R = 0.938) all subjects/sports were classified correctly with 94.29% accuracy. The combination of the two methods: the mathematical description of the time course of ground reaction forces on the basis of Gaussian distributions and their classification by means of Bayesian regulated neural networks, seems an adequate and promising method to discriminate the
Linking network usage patterns to traffic Gaussianity fit
de Oliveira Schmidt, R.; Sadre, R.; Melnikov, Nikolay; Schönwälder, Jürgen; Pras, Aiko
Gaussian traffic models are widely used in the domain of network traffic modeling. The central assumption is that traffic aggregates are Gaussian distributed. Due to its importance, the Gaussian character of network traffic has been extensively assessed by researchers in the past years. In 2001,
Spatial pattern formation induced by Gaussian white noise.
Scarsoglio, Stefania; Laio, Francesco; D'Odorico, Paolo; Ridolfi, Luca
2011-02-01
The ability of Gaussian noise to induce ordered states in dynamical systems is here presented in an overview of the main stochastic mechanisms able to generate spatial patterns. These mechanisms involve: (i) a deterministic local dynamics term, accounting for the local rate of variation of the field variable, (ii) a noise component (additive or multiplicative) accounting for the unavoidable environmental disturbances, and (iii) a linear spatial coupling component, which provides spatial coherence and takes into account diffusion mechanisms. We investigate these dynamics using analytical tools, such as mean-field theory, linear stability analysis and structure function analysis, and use numerical simulations to confirm these analytical results. Copyright © 2010 Elsevier Inc. All rights reserved.
Rewrite Systems, Pattern Matching, and Code Generation
1988-06-09
fmd a local set L’ which includes L and define the transformation on L’ instead of on L. 11 The straightforward way to define tree transformations...Proposition 2.19 Both B-ftt and T-ftt include: REL relabelings FTA (t ,t) such that t e RECOG HOM homomorphisms LHOM linear homomorphisms The capabilities...fsa for the set of the structures of the original pattern set. The LB-fsa IS used to fmd the structural subpatterns matching a: each node of the
Gaussian mixed model in support of semiglobal matching leveraged by ground control points
Ma, Hao; Zheng, Shunyi; Li, Chang; Li, Yingsong; Gui, Li
2017-04-01
Semiglobal matching (SGM) has been widely applied in large aerial images because of its good tradeoff between complexity and robustness. The concept of ground control points (GCPs) is adopted to make SGM more robust. We model the effect of GCPs as two data terms for stereo matching between high-resolution aerial epipolar images in an iterative scheme. One term based on GCPs is formulated by Gaussian mixture model, which strengths the relation between GCPs and the pixels to be estimated and encodes some degree of consistency between them with respect to disparity values. Another term depends on pixel-wise confidence, and we further design a confidence updating equation based on three rules. With this confidence-based term, the assignment of disparity can be heuristically selected among disparity search ranges during the iteration process. Several iterations are sufficient to bring out satisfactory results according to our experiments. Experimental results validate that the proposed method outperforms surface reconstruction, which is a representative variant of SGM and behaves excellently on aerial images.
Performance of peaky template matching under additive white Gaussian noise and uniform quantization
Horvath, Matthew S.; Rigling, Brian D.
2015-05-01
Peaky template matching (PTM) is a special case of a general algorithm known as multinomial pattern matching originally developed for automatic target recognition of synthetic aperture radar data. The algorithm is a model- based approach that first quantizes pixel values into Nq = 2 discrete values yielding generative Beta-Bernoulli models as class-conditional templates. Here, we consider the case of classification of target chips in AWGN and develop approximations to image-to-template classification performance as a function of the noise power. We focus specifically on the case of a uniform quantization" scheme, where a fixed number of the largest pixels are quantized high as opposed to using a fixed threshold. This quantization method reduces sensitivity to the scaling of pixel intensities and quantization in general reduces sensitivity to various nuisance parameters difficult to account for a priori. Our performance expressions are verified using forward-looking infrared imagery from the Army Research Laboratory Comanche dataset.
Computationally Secure Pattern Matching in the Presence of Malicious Adversaries
DEFF Research Database (Denmark)
Hazay, Carmit; Toft, Tomas
2014-01-01
for important variations of the secure pattern matching problem that are significantly more efficient than the current state of art solutions: First, we deal with secure pattern matching with wildcards. In this variant the pattern may contain wildcards that match both 0 and 1. Our protocol requires O......We propose a protocol for the problem of secure two-party pattern matching, where Alice holds a text t∈{0,1}∗ of length n, while Bob has a pattern p∈{0,1}∗ of length m. The goal is for Bob to (only) learn where his pattern occurs in Alice’s text, while Alice learns nothing. Private pattern matching...... is an important problem that has many applications in the area of DNA search, computational biology and more. Our construction guarantees full simulation in the presence of malicious, polynomial-time adversaries (assuming the hardness of DDH assumption) and exhibits computation and communication costs of O...
High Performance Embedded System for Real-Time Pattern Matching
Sotiropoulou, Calliope Louisa; The ATLAS collaboration; Gkaitatzis, Stamatios; Citraro, Saverio; Giannetti, Paola; Dell'Orso, Mauro
2016-01-01
In this paper we present an innovative and high performance embedded system for real-time pattern matching. This system is based on the evolution of hardware and algorithms developed for the field of High Energy Physics (HEP) and more specifically for the execution of extremely fast pattern matching for tracking of particles produced by proton-proton collisions in hadron collider experiments. A miniaturised version of this complex system is being developed for pattern matching in generic image processing applications. The system works as a contour identifier able to extract the salient features of an image. It is based on the principles of cognitive image processing, which means that it executes fast pattern matching and data reduction mimicking the operation of the human brain. The pattern matching can be executed by a custom designed Associative Memory (AM) chip. The reference patterns are chosen by a complex training algorithm implemented on an FPGA device. Post processing algorithms (e.g. pixel clustering...
Structural pattern matching of nonribosomal peptides
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Leclère Valérie
2009-03-01
Full Text Available Abstract Background Nonribosomal peptides (NRPs, bioactive secondary metabolites produced by many microorganisms, show a broad range of important biological activities (e.g. antibiotics, immunosuppressants, antitumor agents. NRPs are mainly composed of amino acids but their primary structure is not always linear and can contain cycles or branchings. Furthermore, there are several hundred different monomers that can be incorporated into NRPs. The NORINE database, the first resource entirely dedicated to NRPs, currently stores more than 700 NRPs annotated with their monomeric peptide structure encoded by undirected labeled graphs. This opens a way to a systematic analysis of structural patterns occurring in NRPs. Such studies can investigate the functional role of some monomeric chains, or analyse NRPs that have been computationally predicted from the synthetase protein sequence. A basic operation in such analyses is the search for a given structural pattern in the database. Results We developed an efficient method that allows for a quick search for a structural pattern in the NORINE database. The method identifies all peptides containing a pattern substructure of a given size. This amounts to solving a variant of the maximum common subgraph problem on pattern and peptide graphs, which is done by computing cliques in an appropriate compatibility graph. Conclusion The method has been incorporated into the NORINE database, available at http://bioinfo.lifl.fr/norine. Less than one second is needed to search for a pattern in the entire database.
Deterministic matrices matching the compressed sensing phase transitions of Gaussian random matrices
Monajemi, Hatef; Jafarpour, Sina; Gavish, Matan; Donoho, David L.; Ambikasaran, Sivaram; Bacallado, Sergio; Bharadia, Dinesh; Chen, Yuxin; Choi, Young; Chowdhury, Mainak; Chowdhury, Soham; Damle, Anil; Fithian, Will; Goetz, Georges; Grosenick, Logan; Gross, Sam; Hills, Gage; Hornstein, Michael; Lakkam, Milinda; Lee, Jason; Li, Jian; Liu, Linxi; Sing-Long, Carlos; Marx, Mike; Mittal, Akshay; Monajemi, Hatef; No, Albert; Omrani, Reza; Pekelis, Leonid; Qin, Junjie; Raines, Kevin; Ryu, Ernest; Saxe, Andrew; Shi, Dai; Siilats, Keith; Strauss, David; Tang, Gary; Wang, Chaojun; Zhou, Zoey; Zhu, Zhen
2013-01-01
In compressed sensing, one takes samples of an N-dimensional vector using an matrix A, obtaining undersampled measurements . For random matrices with independent standard Gaussian entries, it is known that, when is k-sparse, there is a precisely determined phase transition: for a certain region in the (,)-phase diagram, convex optimization typically finds the sparsest solution, whereas outside that region, it typically fails. It has been shown empirically that the same property—with the same phase transition location—holds for a wide range of non-Gaussian random matrix ensembles. We report extensive experiments showing that the Gaussian phase transition also describes numerous deterministic matrices, including Spikes and Sines, Spikes and Noiselets, Paley Frames, Delsarte-Goethals Frames, Chirp Sensing Matrices, and Grassmannian Frames. Namely, for each of these deterministic matrices in turn, for a typical k-sparse object, we observe that convex optimization is successful over a region of the phase diagram that coincides with the region known for Gaussian random matrices. Our experiments considered coefficients constrained to for four different sets , and the results establish our finding for each of the four associated phase transitions. PMID:23277588
Statistical density modification using local pattern matching
International Nuclear Information System (INIS)
Terwilliger, Thomas C.
2003-01-01
Statistical density modification can make use of local patterns of density found in protein structures to improve crystallographic phases. A method for improving crystallographic phases is presented that is based on the preferential occurrence of certain local patterns of electron density in macromolecular electron-density maps. The method focuses on the relationship between the value of electron density at a point in the map and the pattern of density surrounding this point. Patterns of density that can be superimposed by rotation about the central point are considered equivalent. Standard templates are created from experimental or model electron-density maps by clustering and averaging local patterns of electron density. The clustering is based on correlation coefficients after rotation to maximize the correlation. Experimental or model maps are also used to create histograms relating the value of electron density at the central point to the correlation coefficient of the density surrounding this point with each member of the set of standard patterns. These histograms are then used to estimate the electron density at each point in a new experimental electron-density map using the pattern of electron density at points surrounding that point and the correlation coefficient of this density to each of the set of standard templates, again after rotation to maximize the correlation. The method is strengthened by excluding any information from the point in question from both the templates and the local pattern of density in the calculation. A function based on the origin of the Patterson function is used to remove information about the electron density at the point in question from nearby electron density. This allows an estimation of the electron density at each point in a map, using only information from other points in the process. The resulting estimates of electron density are shown to have errors that are nearly independent of the errors in the original map using
Deterministic matrices matching the compressed sensing phase transitions of Gaussian random matrices
Monajemi, Hatef; Jafarpour, Sina; Gavish, Matan; Donoho, David L.; Ambikasaran, Sivaram; Bacallado, Sergio; Bharadia, Dinesh; Chen, Yuxin; Choi, Young; Chowdhury, Mainak; Chowdhury, Soham; Damle, Anil; Fithian, Will; Goetz, Georges; Grosenick, Logan
2012-01-01
In compressed sensing, one takes samples of an N-dimensional vector using an matrix A, obtaining undersampled measurements . For random matrices with independent standard Gaussian entries, it is known that, when is k-sparse, there is a precisely determined phase transition: for a certain region in the (,)-phase diagram, convex optimization typically finds the sparsest solution, whereas outside that region, it typically fails. It has been shown empirically that the same property—with the ...
High performance embedded system for real-time pattern matching
International Nuclear Information System (INIS)
Sotiropoulou, C.-L.; Luciano, P.; Gkaitatzis, S.; Citraro, S.; Giannetti, P.; Dell'Orso, M.
2017-01-01
In this paper we present an innovative and high performance embedded system for real-time pattern matching. This system is based on the evolution of hardware and algorithms developed for the field of High Energy Physics and more specifically for the execution of extremely fast pattern matching for tracking of particles produced by proton–proton collisions in hadron collider experiments. A miniaturized version of this complex system is being developed for pattern matching in generic image processing applications. The system works as a contour identifier able to extract the salient features of an image. It is based on the principles of cognitive image processing, which means that it executes fast pattern matching and data reduction mimicking the operation of the human brain. The pattern matching can be executed by a custom designed Associative Memory chip. The reference patterns are chosen by a complex training algorithm implemented on an FPGA device. Post processing algorithms (e.g. pixel clustering) are also implemented on the FPGA. The pattern matching can be executed on a 2D or 3D space, on black and white or grayscale images, depending on the application and thus increasing exponentially the processing requirements of the system. We present the firmware implementation of the training and pattern matching algorithm, performance and results on a latest generation Xilinx Kintex Ultrascale FPGA device. - Highlights: • A high performance embedded system for real-time pattern matching is proposed. • It is based on a system developed for High Energy Physics experiment triggers. • It mimics the operation of the human brain (cognitive image processing). • The process can be executed on 2D and 3D, black and white or grayscale images. • The implementation uses FPGAs and custom designed associative memory (AM) chips.
High performance embedded system for real-time pattern matching
Energy Technology Data Exchange (ETDEWEB)
Sotiropoulou, C.-L., E-mail: c.sotiropoulou@cern.ch [University of Pisa, Largo B. Pontecorvo 3, 56127 Pisa (Italy); INFN-Pisa Section, Largo B. Pontecorvo 3, 56127 Pisa (Italy); Luciano, P. [University of Cassino and Southern Lazio, Gaetano di Biasio 43, Cassino 03043 (Italy); INFN-Pisa Section, Largo B. Pontecorvo 3, 56127 Pisa (Italy); Gkaitatzis, S. [Aristotle University of Thessaloniki, 54124 Thessaloniki (Greece); Citraro, S. [University of Pisa, Largo B. Pontecorvo 3, 56127 Pisa (Italy); INFN-Pisa Section, Largo B. Pontecorvo 3, 56127 Pisa (Italy); Giannetti, P. [INFN-Pisa Section, Largo B. Pontecorvo 3, 56127 Pisa (Italy); Dell' Orso, M. [University of Pisa, Largo B. Pontecorvo 3, 56127 Pisa (Italy); INFN-Pisa Section, Largo B. Pontecorvo 3, 56127 Pisa (Italy)
2017-02-11
In this paper we present an innovative and high performance embedded system for real-time pattern matching. This system is based on the evolution of hardware and algorithms developed for the field of High Energy Physics and more specifically for the execution of extremely fast pattern matching for tracking of particles produced by proton–proton collisions in hadron collider experiments. A miniaturized version of this complex system is being developed for pattern matching in generic image processing applications. The system works as a contour identifier able to extract the salient features of an image. It is based on the principles of cognitive image processing, which means that it executes fast pattern matching and data reduction mimicking the operation of the human brain. The pattern matching can be executed by a custom designed Associative Memory chip. The reference patterns are chosen by a complex training algorithm implemented on an FPGA device. Post processing algorithms (e.g. pixel clustering) are also implemented on the FPGA. The pattern matching can be executed on a 2D or 3D space, on black and white or grayscale images, depending on the application and thus increasing exponentially the processing requirements of the system. We present the firmware implementation of the training and pattern matching algorithm, performance and results on a latest generation Xilinx Kintex Ultrascale FPGA device. - Highlights: • A high performance embedded system for real-time pattern matching is proposed. • It is based on a system developed for High Energy Physics experiment triggers. • It mimics the operation of the human brain (cognitive image processing). • The process can be executed on 2D and 3D, black and white or grayscale images. • The implementation uses FPGAs and custom designed associative memory (AM) chips.
High Performance Embedded System for Real-Time Pattern Matching
Sotiropoulou, Calliope Louisa; The ATLAS collaboration; Gkaitatzis, Stamatios; Citraro, Saverio; Giannetti, Paola; Dell'Orso, Mauro
2016-01-01
We present an innovative and high performance embedded system for real-time pattern matching. This system is based on the evolution of hardware and algorithms developed for the field of High Energy Physics (HEP) and more specifically for the execution of extremely fast pattern matching for tracking of particles produced by proton-proton collisions in hadron collider experiments. A miniaturized version of this complex system is being developed for pattern matching in generic image processing applications. The design uses the flexibility of Field Programmable Gate Arrays (FPGAs) and the powerful Associative Memory Chip (ASIC) to achieve real-time performance. The system works as a contour identifier able to extract the salient features of an image. It is based on the principles of cognitive image processing, which means that it executes fast pattern matching and data reduction mimicking the operation of the human brain.
Sleep patterns and match performance in elite Australian basketball athletes.
Staunton, Craig; Gordon, Brett; Custovic, Edhem; Stanger, Jonathan; Kingsley, Michael
2017-08-01
To assess sleep patterns and associations between sleep and match performance in elite Australian female basketball players. Prospective cohort study. Seventeen elite female basketball players were monitored across two consecutive in-season competitions (30 weeks). Total sleep time and sleep efficiency were determined using triaxial accelerometers for Baseline, Pre-match, Match-day and Post-match timings. Match performance was determined using the basketball efficiency statistic (EFF). The effects of match schedule (Regular versus Double-Header; Home versus Away) and sleep on EFF were assessed. The Double-Header condition changed the pattern of sleep when compared with the Regular condition (F (3,48) =3.763, P=0.017), where total sleep time Post-match was 11% less for Double-Header (mean±SD; 7.2±1.4h) compared with Regular (8.0±1.3h; P=0.007). Total sleep time for Double-Header was greater Pre-match (8.2±1.7h) compared with Baseline (7.1±1.6h; P=0.022) and Match-day (7.3±1.5h; P=0.007). Small correlations existed between sleep metrics at Pre-match and EFF for pooled data (r=-0.39 to -0.22; P≥0.238). Relationships between total sleep time and EFF ranged from moderate negative to large positive correlations for individual players (r=-0.37 to 0.62) and reached significance for one player (r=0.60; P=0.025). Match schedule can affect the sleep patterns of elite female basketball players. A large degree of inter-individual variability existed in the relationship between sleep and match performance; nevertheless, sleep monitoring might assist in the optimisation of performance for some athletes. Copyright © 2017 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.
Betting on Illusory Patterns: Probability Matching in Habitual Gamblers.
Gaissmaier, Wolfgang; Wilke, Andreas; Scheibehenne, Benjamin; McCanney, Paige; Barrett, H Clark
2016-03-01
Why do people gamble? A large body of research suggests that cognitive distortions play an important role in pathological gambling. Many of these distortions are specific cases of a more general misperception of randomness, specifically of an illusory perception of patterns in random sequences. In this article, we provide further evidence for the assumption that gamblers are particularly prone to perceiving illusory patterns. In particular, we compared habitual gamblers to a matched sample of community members with regard to how much they exhibit the choice anomaly 'probability matching'. Probability matching describes the tendency to match response proportions to outcome probabilities when predicting binary outcomes. It leads to a lower expected accuracy than the maximizing strategy of predicting the most likely event on each trial. Previous research has shown that an illusory perception of patterns in random sequences fuels probability matching. So does impulsivity, which is also reported to be higher in gamblers. We therefore hypothesized that gamblers will exhibit more probability matching than non-gamblers, which was confirmed in a controlled laboratory experiment. Additionally, gamblers scored much lower than community members on the cognitive reflection task, which indicates higher impulsivity. This difference could account for the difference in probability matching between the samples. These results suggest that gamblers are more willing to bet impulsively on perceived illusory patterns.
Kangaroo – A pattern-matching program for biological sequences
Directory of Open Access Journals (Sweden)
Betel Doron
2002-07-01
Full Text Available Abstract Background Biologists are often interested in performing a simple database search to identify proteins or genes that contain a well-defined sequence pattern. Many databases do not provide straightforward or readily available query tools to perform simple searches, such as identifying transcription binding sites, protein motifs, or repetitive DNA sequences. However, in many cases simple pattern-matching searches can reveal a wealth of information. We present in this paper a regular expression pattern-matching tool that was used to identify short repetitive DNA sequences in human coding regions for the purpose of identifying potential mutation sites in mismatch repair deficient cells. Results Kangaroo is a web-based regular expression pattern-matching program that can search for patterns in DNA, protein, or coding region sequences in ten different organisms. The program is implemented to facilitate a wide range of queries with no restriction on the length or complexity of the query expression. The program is accessible on the web at http://bioinfo.mshri.on.ca/kangaroo/ and the source code is freely distributed at http://sourceforge.net/projects/slritools/. Conclusion A low-level simple pattern-matching application can prove to be a useful tool in many research settings. For example, Kangaroo was used to identify potential genetic targets in a human colorectal cancer variant that is characterized by a high frequency of mutations in coding regions containing mononucleotide repeats.
Analysis of multi-species point patterns using multivariate log Gaussian Cox processes
DEFF Research Database (Denmark)
Waagepetersen, Rasmus; Guan, Yongtao; Jalilian, Abdollah
Multivariate log Gaussian Cox processes are flexible models for multivariate point patterns. However, they have so far only been applied in bivariate cases. In this paper we move beyond the bivariate case in order to model multi-species point patterns of tree locations. In particular we address t...... of the data. The selected number of common latent fields provides an index of complexity of the multivariate covariance structure. Hierarchical clustering is used to identify groups of species with similar patterns of dependence on the common latent fields.......Multivariate log Gaussian Cox processes are flexible models for multivariate point patterns. However, they have so far only been applied in bivariate cases. In this paper we move beyond the bivariate case in order to model multi-species point patterns of tree locations. In particular we address...... the problems of identifying parsimonious models and of extracting biologically relevant information from the fitted models. The latent multivariate Gaussian field is decomposed into components given in terms of random fields common to all species and components which are species specific. This allows...
Directory of Open Access Journals (Sweden)
Taehwan Kim
2017-05-01
Full Text Available By incorporating a growing number of sensors and adopting machine learning technologies, wearable devices have recently become a prominent health care application domain. Among the related research topics in this field, one of the most important issues is detecting falls while walking. Since such falls may lead to serious injuries, automatically and promptly detecting them during daily use of smartphones and/or smart watches is a particular need. In this paper, we investigate the use of Gaussian process (GP methods for characterizing dynamic walking patterns and detecting falls while walking with built-in wearable sensors in smartphones and/or smartwatches. For the task of characterizing dynamic walking patterns in a low-dimensional latent feature space, we propose a novel approach called auto-encoded Gaussian process dynamical model, in which we combine a GP-based state space modeling method with a nonlinear dimensionality reduction method in a unique manner. The Gaussian process methods are fit for this task because one of the most import strengths of the Gaussian process methods is its capability of handling uncertainty in the model parameters. Also for detecting falls while walking, we propose to recycle the latent samples generated in training the auto-encoded Gaussian process dynamical model for GP-based novelty detection, which can lead to an efficient and seamless solution to the detection task. Experimental results show that the combined use of these GP-based methods can yield promising results for characterizing dynamic walking patterns and detecting falls while walking with the wearable sensors.
PATTERN CLASSIFICATION APPROACHES TO MATCHING BUILDING POLYGONS AT MULTIPLE SCALES
Directory of Open Access Journals (Sweden)
X. Zhang
2012-07-01
Full Text Available Matching of building polygons with different levels of detail is crucial in the maintenance and quality assessment of multi-representation databases. Two general problems need to be addressed in the matching process: (1 Which criteria are suitable? (2 How to effectively combine different criteria to make decisions? This paper mainly focuses on the second issue and views data matching as a supervised pattern classification. Several classifiers (i.e. decision trees, Naive Bayes and support vector machines are evaluated for the matching task. Four criteria (i.e. position, size, shape and orientation are used to extract information for these classifiers. Evidence shows that these classifiers outperformed the weighted average approach.
A new taxonomy of sublinear keyword pattern matching algorithms
Cleophas, L.G.W.A.; Watson, B.W.; Zwaan, G.
2004-01-01
Abstract This paper presents a new taxonomy of sublinear (multiple) keyword pattern matching algorithms. Based on an earlier taxonomy by Watson and Zwaan [WZ96, WZ95], this new taxonomy includes not only suffix-based algorithms related to the Boyer-Moore, Commentz-Walter and Fan-Su algorithms, but
International Nuclear Information System (INIS)
Borisenko, Konstantin B; Kirkland, Angus I
2014-01-01
We describe an algorithm to reconstruct the electron exit wave of a weak-phase object from single diffraction pattern. The algorithm uses analytic formulations describing the diffraction intensities through a representation of the object exit wave in a Gaussian basis. The reconstruction is achieved by solving an overdetermined system of non-linear equations using an easily parallelisable global multi-start search with Levenberg-Marquard optimisation and analytic derivatives
Attention Modulates Visual-Tactile Interaction in Spatial Pattern Matching
Göschl, Florian; Engel, Andreas K.; Friese, Uwe
2014-01-01
Factors influencing crossmodal interactions are manifold and operate in a stimulus-driven, bottom-up fashion, as well as via top-down control. Here, we evaluate the interplay of stimulus congruence and attention in a visual-tactile task. To this end, we used a matching paradigm requiring the identification of spatial patterns that were concurrently presented visually on a computer screen and haptically to the fingertips by means of a Braille stimulator. Stimulation in our paradigm was always bimodal with only the allocation of attention being manipulated between conditions. In separate blocks of the experiment, participants were instructed to (a) focus on a single modality to detect a specific target pattern, (b) pay attention to both modalities to detect a specific target pattern, or (c) to explicitly evaluate if the patterns in both modalities were congruent or not. For visual as well as tactile targets, congruent stimulus pairs led to quicker and more accurate detection compared to incongruent stimulation. This congruence facilitation effect was more prominent under divided attention. Incongruent stimulation led to behavioral decrements under divided attention as compared to selectively attending a single sensory channel. Additionally, when participants were asked to evaluate congruence explicitly, congruent stimulation was associated with better performance than incongruent stimulation. Our results extend previous findings from audiovisual studies, showing that stimulus congruence also resulted in behavioral improvements in visuotactile pattern matching. The interplay of stimulus processing and attentional control seems to be organized in a highly flexible fashion, with the integration of signals depending on both bottom-up and top-down factors, rather than occurring in an ‘all-or-nothing’ manner. PMID:25203102
Attention modulates visual-tactile interaction in spatial pattern matching.
Directory of Open Access Journals (Sweden)
Florian Göschl
Full Text Available Factors influencing crossmodal interactions are manifold and operate in a stimulus-driven, bottom-up fashion, as well as via top-down control. Here, we evaluate the interplay of stimulus congruence and attention in a visual-tactile task. To this end, we used a matching paradigm requiring the identification of spatial patterns that were concurrently presented visually on a computer screen and haptically to the fingertips by means of a Braille stimulator. Stimulation in our paradigm was always bimodal with only the allocation of attention being manipulated between conditions. In separate blocks of the experiment, participants were instructed to (a focus on a single modality to detect a specific target pattern, (b pay attention to both modalities to detect a specific target pattern, or (c to explicitly evaluate if the patterns in both modalities were congruent or not. For visual as well as tactile targets, congruent stimulus pairs led to quicker and more accurate detection compared to incongruent stimulation. This congruence facilitation effect was more prominent under divided attention. Incongruent stimulation led to behavioral decrements under divided attention as compared to selectively attending a single sensory channel. Additionally, when participants were asked to evaluate congruence explicitly, congruent stimulation was associated with better performance than incongruent stimulation. Our results extend previous findings from audiovisual studies, showing that stimulus congruence also resulted in behavioral improvements in visuotactile pattern matching. The interplay of stimulus processing and attentional control seems to be organized in a highly flexible fashion, with the integration of signals depending on both bottom-up and top-down factors, rather than occurring in an 'all-or-nothing' manner.
Highly Parallelized Pattern Matching Execution for the ATLAS Experiment
Citraro, Saverio; The ATLAS collaboration
2015-01-01
The trigger system of the ATLAS experiment at LHC will extend its rejection capabilities during operations in 2015-2018 by introducing the Fast TracKer system (FTK). FTK is a hardware based system capable of finding charged particle tracks by analyzing hits in silicon detectors at the rate of 105 events per second. The core of track reconstruction is performed into two pipelined steps. At first step the candidate tracks are found by matching combination of low resolution hits to predefined patterns; then they are used in the second step to seed a more precise track fitting algorithm. The key FTK component is an Associative Memory (AM) system that is used to perform pattern matching with high degree of parallelism. The AM system implementation, the AM Serial Link Processor, is based on an extremely powerful network of 2 Gb/s serial links to sustain a huge traffic of data. We report on the design of the Serial Link Processor consisting of two types of boards, the Little Associative Memory Board (LAMB), a mezzan...
Highly Parallelized Pattern Matching Execution for the ATLAS Experiment
Citraro, Saverio; The ATLAS collaboration
2015-01-01
Abstract– The Associative Memory (AM) system of the Fast Tracker (FTK) processor has been designed to perform pattern matching using as input the data from the silicon tracker in the ATLAS experiment. The AM is the primary component of the FTK system and is designed using ASIC technology (the AM chip) to execute pattern matching with a high degree of parallelism. The FTK system finds track candidates at low resolution that are seeds for a full resolution track fitting. The AM system implementation is named “Serial Link Processor” and is based on an extremely powerful network of 2 Gb/s serial links to sustain a huge traffic of data. This paper reports on the design of the Serial Link Processor consisting of two types of boards, the Little Associative Memory Board (LAMB), a mezzanine where the AM chips are mounted, and the Associative Memory Board (AMB), a 9U VME motherboard which hosts four LAMB daughterboards. We also report on the performance of the prototypes (both hardware and firmware) produced and ...
Directory of Open Access Journals (Sweden)
VIMALA C.
2015-05-01
Full Text Available In recent years, speech technology has become a vital part of our daily lives. Various techniques have been proposed for developing Automatic Speech Recognition (ASR system and have achieved great success in many applications. Among them, Template Matching techniques like Dynamic Time Warping (DTW, Statistical Pattern Matching techniques such as Hidden Markov Model (HMM and Gaussian Mixture Models (GMM, Machine Learning techniques such as Neural Networks (NN, Support Vector Machine (SVM, and Decision Trees (DT are most popular. The main objective of this paper is to design and develop a speaker-independent isolated speech recognition system for Tamil language using the above speech recognition techniques. The background of ASR system, the steps involved in ASR, merits and demerits of the conventional and machine learning algorithms and the observations made based on the experiments are presented in this paper. For the above developed system, highest word recognition accuracy is achieved with HMM technique. It offered 100% accuracy during training process and 97.92% for testing process.
Optimizing Fukushima Emissions Through Pattern Matching and Genetic Algorithms
Lucas, D. D.; Simpson, M. D.; Philip, C. S.; Baskett, R.
2017-12-01
Hazardous conditions during the Fukushima Daiichi nuclear power plant (NPP) accident hindered direct observations of the emissions of radioactive materials into the atmosphere. A wide range of emissions are estimated from bottom-up studies using reactor inventories and top-down approaches based on inverse modeling. We present a new inverse modeling estimate of cesium-137 emitted from the Fukushima NPP. Our estimate considers weather uncertainty through a large ensemble of Weather Research and Forecasting model simulations and uses the FLEXPART atmospheric dispersion model to transport and deposit cesium. The simulations are constrained by observations of the spatial distribution of cumulative cesium deposited on the surface of Japan through April 2, 2012. Multiple spatial metrics are used to quantify differences between observed and simulated deposition patterns. In order to match the observed pattern, we use a multi-objective genetic algorithm to optimize the time-varying emissions. We find that large differences with published bottom-up estimates are required to explain the observations. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.
Clemens, Joshua William
Game theory has application across multiple fields, spanning from economic strategy to optimal control of an aircraft and missile on an intercept trajectory. The idea of game theory is fascinating in that we can actually mathematically model real-world scenarios and determine optimal decision making. It may not always be easy to mathematically model certain real-world scenarios, nonetheless, game theory gives us an appreciation for the complexity involved in decision making. This complexity is especially apparent when the players involved have access to different information upon which to base their decision making (a nonclassical information pattern). Here we will focus on the class of adversarial two-player games (sometimes referred to as pursuit-evasion games) with nonclassical information pattern. We present a two-sided (simultaneous) optimization solution method for the two-player linear quadratic Gaussian (LQG) multistage game. This direct solution method allows for further interpretation of each player's decision making (strategy) as compared to previously used formal solution methods. In addition to the optimal control strategies, we present a saddle point proof and we derive an expression for the optimal performance index value. We provide some numerical results in order to further interpret the optimal control strategies and to highlight real-world application of this game-theoretic optimal solution.
The effect of football matches on crime patterns in Barcelona
Struse, Simon Planells; Montolio, Daniel
2014-01-01
Given the actual debate, in many European countries, about the need for public administrations to raise their revenues through taxing the crime externalities generated by some private leisure activities, this article analyzes the effect of football matches on crime focusing both on property crimes and interpersonal violent crimes. Our aim is to determine up to what extent a private leisure activity, such as football matches, induces negative crime externalities to the whole society. Using dat...
Drory Retwitzer, Matan; Polishchuk, Maya; Churkin, Elena; Kifer, Ilona; Yakhini, Zohar; Barash, Danny
2015-01-01
Searching for RNA sequence-structure patterns is becoming an essential tool for RNA practitioners. Novel discoveries of regulatory non-coding RNAs in targeted organisms and the motivation to find them across a wide range of organisms have prompted the use of computational RNA pattern matching as an enhancement to sequence similarity. State-of-the-art programs differ by the flexibility of patterns allowed as queries and by their simplicity of use. In particular—no existing method is available as a user-friendly web server. A general program that searches for RNA sequence-structure patterns is RNA Structator. However, it is not available as a web server and does not provide the option to allow flexible gap pattern representation with an upper bound of the gap length being specified at any position in the sequence. Here, we introduce RNAPattMatch, a web-based application that is user friendly and makes sequence/structure RNA queries accessible to practitioners of various background and proficiency. It also extends RNA Structator and allows a more flexible variable gaps representation, in addition to analysis of results using energy minimization methods. RNAPattMatch service is available at http://www.cs.bgu.ac.il/rnapattmatch. A standalone version of the search tool is also available to download at the site. PMID:25940619
Rotation and scale change invariant point pattern relaxation matching by the Hopfield neural network
Sang, Nong; Zhang, Tianxu
1997-12-01
Relaxation matching is one of the most relevant methods for image matching. The original relaxation matching technique using point patterns is sensitive to rotations and scale changes. We improve the original point pattern relaxation matching technique to be invariant to rotations and scale changes. A method that makes the Hopfield neural network perform this matching process is discussed. An advantage of this is that the relaxation matching process can be performed in real time with the neural network's massively parallel capability to process information. Experimental results with large simulated images demonstrate the effectiveness and feasibility of the method to perform point patten relaxation matching invariant to rotations and scale changes and the method to perform this matching by the Hopfield neural network. In addition, we show that the method presented can be tolerant to small random error.
What makes a pattern? Matching decoding methods to data in multivariate pattern analysis
Directory of Open Access Journals (Sweden)
Philip A Kragel
2012-11-01
Full Text Available Research in neuroscience faces the challenge of integrating information across different spatial scales of brain function. A promising technique for harnessing information at a range of spatial scales is multivariate pattern analysis (MVPA of functional magnetic resonance imaging (fMRI data. While the prevalence of MVPA has increased dramatically in recent years, its typical implementations for classification of mental states utilize only a subset of the information encoded in local fMRI signals. We review published studies employing multivariate pattern classification since the technique’s introduction, which reveal an extensive focus on the improved detection power that linear classifiers provide over traditional analysis techniques. We demonstrate using simulations and a searchlight approach, however, that nonlinear classifiers are capable of extracting distinct information about interactions within a local region. We conclude that for spatially localized analyses, such as searchlight and region of interest, multiple classification approaches should be compared in order to match fMRI analyses to the properties of local circuits.
Rating Algorithm for Pronunciation of English Based on Audio Feature Pattern Matching
Directory of Open Access Journals (Sweden)
Li Kun
2015-01-01
Full Text Available With the increasing internationalization of China, language communication has become an important channel for us to adapt to the political and economic environment. How to improve English learners’ language learning efficiency in limited conditions has turned into a problem demanding prompt solution at present. This paper applies two pronunciation patterns according to the actual needs of English pronunciation rating: to-be-evaluated pronunciation pattern and standard pronunciation pattern. It will translate the patterns into English pronunciation rating results through European distance. Besides, this paper will introduce the design philosophy of the whole algorithm in combination with CHMM matching pattern. Each link of the CHMM pattern will be given selective analysis while a contrast experiment between the CHMM matching pattern and the other two patterns will be conducted. From the experiment results, it can be concluded that CHMM pattern is the best option.
A Vision Chip for Color Segmentation and Pattern Matching
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Ralph Etienne-Cummings
2003-06-01
Full Text Available A 128(H ÃƒÂ— 64(V ÃƒÂ— RGB CMOS imager is integrated with region-of-interest selection, RGB-to-HSI transformation, HSI-based pixel segmentation, (36bins ÃƒÂ— 12bits-HSI histogramming, and sum-of-absolute-difference (SAD template matching. Thirty-two learned color templates are stored and compared to each image. The chip captures the R, G, and B images using in-pixel storage before passing the pixel content to a multiplying digital-to-analog converter (DAC for white balancing. The DAC can also be used to pipe in images for a PC. The color processing uses a biologically inspired color opponent representation and an analog lookup table to determine the Hue (H of each pixel. Saturation (S is computed using a loser-take-all circuit. Intensity (I is given by the sum of the color components. A histogram of the segments of the image, constructed by counting the number of pixels falling into 36 Hue intervals of 10 degrees, is stored on a chip and compared against the histograms of new segments using SAD comparisons. We demonstrate color-based image segmentation and object recognition with this chip. Running at 30 fps, it uses 1 mW. To our knowledge, this is the first chip that integrates imaging, color segmentation, and color-based object recognition at the focal plane.
Directory of Open Access Journals (Sweden)
Chang-Ku Kang
Full Text Available Many moths have wing patterns that resemble bark of trees on which they rest. The wing patterns help moths to become camouflaged and to avoid predation because the moths are able to assume specific body orientations that produce a very good match between the pattern on the bark and the pattern on the wings. Furthermore, after landing on a bark moths are able to perceive stimuli that correlate with their crypticity and are able to re-position their bodies to new more cryptic locations and body orientations. However, the proximate mechanisms, i.e. how a moth finds an appropriate resting position and orientation, are poorly studied. Here, we used a geometrid moth Jankowskia fuscaria to examine i whether a choice of resting orientation by moths depends on the properties of natural background, and ii what sensory cues moths use. We studied moths' behavior on natural (a tree log and artificial backgrounds, each of which was designed to mimic one of the hypothetical cues that moths may perceive on a tree trunk (visual pattern, directional furrow structure, and curvature. We found that moths mainly used structural cues from the background when choosing their resting position and orientation. Our findings highlight the possibility that moths use information from one type of sensory modality (structure of furrows is probably detected through tactile channel to achieve crypticity in another sensory modality (visual. This study extends our knowledge of how behavior, sensory systems and morphology of animals interact to produce crypsis.
Kang, Chang-Ku; Moon, Jong-Yeol; Lee, Sang-Im; Jablonski, Piotr G
2013-01-01
Many moths have wing patterns that resemble bark of trees on which they rest. The wing patterns help moths to become camouflaged and to avoid predation because the moths are able to assume specific body orientations that produce a very good match between the pattern on the bark and the pattern on the wings. Furthermore, after landing on a bark moths are able to perceive stimuli that correlate with their crypticity and are able to re-position their bodies to new more cryptic locations and body orientations. However, the proximate mechanisms, i.e. how a moth finds an appropriate resting position and orientation, are poorly studied. Here, we used a geometrid moth Jankowskia fuscaria to examine i) whether a choice of resting orientation by moths depends on the properties of natural background, and ii) what sensory cues moths use. We studied moths' behavior on natural (a tree log) and artificial backgrounds, each of which was designed to mimic one of the hypothetical cues that moths may perceive on a tree trunk (visual pattern, directional furrow structure, and curvature). We found that moths mainly used structural cues from the background when choosing their resting position and orientation. Our findings highlight the possibility that moths use information from one type of sensory modality (structure of furrows is probably detected through tactile channel) to achieve crypticity in another sensory modality (visual). This study extends our knowledge of how behavior, sensory systems and morphology of animals interact to produce crypsis.
Fast Partial Evaluation of Pattern Matching in Strings
DEFF Research Database (Denmark)
Ager, Mads Sig; Danvy, Olivier; Rohde, Henning Korsholm
2006-01-01
We show how to obtain all of Knuth, Morris, and Pratt's linear-time string matcher by specializing a quadratic-time string matcher with respect to a pattern string. Although it has been known for 15 years how to obtain this linear matcher by partial evaluation of a quadratic one, how to obtain...... it in linear time has remained an open problem. Obtaining a linear matcher by partial evaluation of a quadratic one is achieved by performing its backtracking at specialization time and memoizing its results. We show (1) how to rewrite the source matcher such that its static intermediate computations can...... be shared at specialization time and (2) how to extend the memoization capabilities of a partial evaluator to static functions. Such an extended partial evaluator, if its memoization is implemented efficiently, specializes the rewritten source matcher in linear time. Finally, we show that the method also...
Fast Partial Evaluation of Pattern Matching in Strings
DEFF Research Database (Denmark)
Ager, Mads Sig; Danvy, Olivier; Rohde, Henning Korsholm
2003-01-01
We show how to obtain all of Knuth, Morris, and Pratt's linear-time string matcher by specializing a quadratic-time string matcher with respect to a pattern string. Although it has been known for 15 years how to obtain this linear matcher by partial evaluation of a quadratic one, how to obtain...... it in linear time has remained an open problem. Obtaining a linear matcher by partial evaluation of a quadratic one is achieved by performing its backtracking at specialization time and memoizing its results. We show (1) how to rewrite the source matcher such that its static intermediate computations can...... be shared at specialization time and (2) how to extend the memoization capabilities of a partial evaluator to static functions. Such an extended partial evaluator, if its memoization is implemented efficiently, specializes the rewritten source matcher in linear time. Finally, we show that the method also...
Fast Partial Evaluation of Pattern Matching in Strings
DEFF Research Database (Denmark)
Ager, Mads Sig; Danvy, Olivier; Rohde, Henning Korsholm
2003-01-01
We show how to obtain all of Knuth, Morris, and Pratt's linear-time string matcher by partial evaluation of a quadratic-time string matcher with respect to a pattern string. Although it has been known for 15 years how to obtain this linear matcher by partial evaluation of a quadratic one, how...... to obtain it in linear time has remained an open problem.Obtaining a linear matcher by partial evaluation of a quadratic one is achieved by performing its backtracking at specialization time and memoizing its results. We show (1) how to rewrite the source matcher such that its static intermediate...... computations can be shared at specialization time and (2) how to extend the memoization capabilities of a partial evaluator to static functions. Such an extended partial evaluator, if its memoization is implemented efficiently, specializes the rewritten source matcher in linear time....
Fan fault diagnosis based on symmetrized dot pattern analysis and image matching
Xu, Xiaogang; Liu, Haixiao; Zhu, Hao; Wang, Songling
2016-07-01
To detect the mechanical failure of fans, a new diagnostic method based on the symmetrized dot pattern (SDP) analysis and image matching is proposed. Vibration signals of 13 kinds of running states are acquired on a centrifugal fan test bed and reconstructed by the SDP technique. The SDP pattern templates of each running state are established. An image matching method is performed to diagnose the fault. In order to improve the diagnostic accuracy, the single template, multiple templates and clustering fault templates are used to perform the image matching.
A multi-pattern hash-binary hybrid algorithm for URL matching in the HTTP protocol.
Directory of Open Access Journals (Sweden)
Ping Zeng
Full Text Available In this paper, based on our previous multi-pattern uniform resource locator (URL binary-matching algorithm called HEM, we propose an improved multi-pattern matching algorithm called MH that is based on hash tables and binary tables. The MH algorithm can be applied to the fields of network security, data analysis, load balancing, cloud robotic communications, and so on-all of which require string matching from a fixed starting position. Our approach effectively solves the performance problems of the classical multi-pattern matching algorithms. This paper explores ways to improve string matching performance under the HTTP protocol by using a hash method combined with a binary method that transforms the symbol-space matching problem into a digital-space numerical-size comparison and hashing problem. The MH approach has a fast matching speed, requires little memory, performs better than both the classical algorithms and HEM for matching fields in an HTTP stream, and it has great promise for use in real-world applications.
DEFF Research Database (Denmark)
Dimitrov, Nikolay Krasimirov; Natarajan, Anand
2017-01-01
We demonstrate a method for incorporating wind velocity measurements from multiple-point scanning lidars into threedimensional wind turbulence time series serving as input to wind turbine load simulations. Simulated lidar scanning patterns are implemented by imposing constraints on randomly gener...
A Boyer-Moore (or Watson-Watson) type algorithm for regular tree pattern matching
Watson, B.W.; Aarts, E.H.L.; Eikelder, ten H.M.M.; Hemerik, C.; Rem, M.
1995-01-01
In this chapter, I outline a new algorithm for regular tree pattern matching. The existence of this algorithm was first mentioned in the statements accompanying my dissertation, [2]. In order to avoid repeating the material in my dissertation, it is assumed that the reader is familiar with Chapters
Length-Bounded Hybrid CPU/GPU Pattern Matching Algorithm for Deep Packet Inspection
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Yi-Shan Lin
2017-01-01
Full Text Available Since frequent communication between applications takes place in high speed networks, deep packet inspection (DPI plays an important role in the network application awareness. The signature-based network intrusion detection system (NIDS contains a DPI technique that examines the incoming packet payloads by employing a pattern matching algorithm that dominates the overall inspection performance. Existing studies focused on implementing efficient pattern matching algorithms by parallel programming on software platforms because of the advantages of lower cost and higher scalability. Either the central processing unit (CPU or the graphic processing unit (GPU were involved. Our studies focused on designing a pattern matching algorithm based on the cooperation between both CPU and GPU. In this paper, we present an enhanced design for our previous work, a length-bounded hybrid CPU/GPU pattern matching algorithm (LHPMA. In the preliminary experiment, the performance and comparison with the previous work are displayed, and the experimental results show that the LHPMA can achieve not only effective CPU/GPU cooperation but also higher throughput than the previous method.
Two related algorithms for root-to-frontier tree pattern matching
Cleophas, L.G.W.A.; Hemerik, C.; Zwaan, G.
2006-01-01
Tree pattern matching (TPM) algorithms on ordered, ranked trees play an important role in applications such as compilers and term rewriting systems. Many TPM algorithms appearing in the literature are based on tree automata. For efficiency, these automata should be deterministic, yet deterministic
Wang, Lynn T.-N.; Madhavan, Sriram
2018-03-01
A pattern matching and rule-based polygon clustering methodology with DFM scoring is proposed to detect decomposition-induced manufacturability detractors and fix the layout designs prior to manufacturing. A pattern matcher scans the layout for pre-characterized patterns from a library. If a pattern were detected, rule-based clustering identifies the neighboring polygons that interact with those captured by the pattern. Then, DFM scores are computed for the possible layout fixes: the fix with the best score is applied. The proposed methodology was applied to two 20nm products with a chip area of 11 mm2 on the metal 2 layer. All the hotspots were resolved. The number of DFM spacing violations decreased by 7-15%.
Uniform Local Binary Pattern for Fingerprint Liveness Detection in the Gaussian Pyramid
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Yujia Jiang
2018-01-01
Full Text Available Fingerprint recognition schemas are widely used in our daily life, such as Door Security, Identification, and Phone Verification. However, the existing problem is that fingerprint recognition systems are easily tricked by fake fingerprints for collaboration. Therefore, designing a fingerprint liveness detection module in fingerprint recognition systems is necessary. To solve the above problem and discriminate true fingerprint from fake ones, a novel software-based liveness detection approach using uniform local binary pattern (ULBP in spatial pyramid is applied to recognize fingerprint liveness in this paper. Firstly, preprocessing operation for each fingerprint is necessary. Then, to solve image rotation and scale invariance, three-layer spatial pyramids of fingerprints are introduced in this paper. Next, texture information for three layers spatial pyramids is described by using uniform local binary pattern to extract features of given fingerprints. The accuracy of our proposed method has been compared with several state-of-the-art methods in fingerprint liveness detection. Experiments based on standard databases, taken from Liveness Detection Competition 2013 composed of four different fingerprint sensors, have been carried out. Finally, classifier model based on extracted features is trained using SVM classifier. Experimental results present that our proposed method can achieve high recognition accuracy compared with other methods.
Papa, Frank; And Others
1990-01-01
In this study an artificial intelligence assessment tool used disease-by-feature frequency estimates to create disease prototypes for nine common causes of acute chest pain. The tool then used each subject's prototypes and a pattern-recognition-based decision-making mechanism to diagnose 18 myocardial infarction cases. (MLW)
Receptive fields of locust brain neurons are matched to polarization patterns of the sky.
Bech, Miklós; Homberg, Uwe; Pfeiffer, Keram
2014-09-22
Many animals, including insects, are able to use celestial cues as a reference for spatial orientation and long-distance navigation [1]. In addition to direct sunlight, the chromatic gradient of the sky and its polarization pattern are suited to serve as orientation cues [2-5]. Atmospheric scattering of sunlight causes a regular pattern of E vectors in the sky, which are arranged along concentric circles around the sun [5, 6]. Although certain insects rely predominantly on sky polarization for spatial orientation [7], it has been argued that detection of celestial E vector orientation may not suffice to differentiate between solar and antisolar directions [8, 9]. We show here that polarization-sensitive (POL) neurons in the brain of the desert locust Schistocerca gregaria can overcome this ambiguity. Extracellular recordings from POL units in the central complex and lateral accessory lobes revealed E vector tunings arranged in concentric circles within large receptive fields, matching the sky polarization pattern at certain solar positions. Modeling of neuronal responses under an idealized sky polarization pattern (Rayleigh sky) suggests that these "matched filter" properties allow locusts to unambiguously determine the solar azimuth by relying solely on the sky polarization pattern for compass navigation. Copyright © 2014 Elsevier Ltd. All rights reserved.
Data-Driven Engineering of Social Dynamics: Pattern Matching and Profit Maximization.
Peng, Huan-Kai; Lee, Hao-Chih; Pan, Jia-Yu; Marculescu, Radu
2016-01-01
In this paper, we define a new problem related to social media, namely, the data-driven engineering of social dynamics. More precisely, given a set of observations from the past, we aim at finding the best short-term intervention that can lead to predefined long-term outcomes. Toward this end, we propose a general formulation that covers two useful engineering tasks as special cases, namely, pattern matching and profit maximization. By incorporating a deep learning model, we derive a solution using convex relaxation and quadratic-programming transformation. Moreover, we propose a data-driven evaluation method in place of the expensive field experiments. Using a Twitter dataset, we demonstrate the effectiveness of our dynamics engineering approach for both pattern matching and profit maximization, and study the multifaceted interplay among several important factors of dynamics engineering, such as solution validity, pattern-matching accuracy, and intervention cost. Finally, the method we propose is general enough to work with multi-dimensional time series, so it can potentially be used in many other applications.
Inoue, Kentaro; Shimozono, Shinichi; Yoshida, Hideaki; Kurata, Hiroyuki
2012-01-01
For visualizing large-scale biochemical network maps, it is important to calculate the coordinates of molecular nodes quickly and to enhance the understanding or traceability of them. The grid layout is effective in drawing compact, orderly, balanced network maps with node label spaces, but existing grid layout algorithms often require a high computational cost because they have to consider complicated positional constraints through the entire optimization process. We propose a hybrid grid layout algorithm that consists of a non-grid, fast layout (preprocessor) algorithm and an approximate pattern matching algorithm that distributes the resultant preprocessed nodes on square grid points. To demonstrate the feasibility of the hybrid layout algorithm, it is characterized in terms of the calculation time, numbers of edge-edge and node-edge crossings, relative edge lengths, and F-measures. The proposed algorithm achieves outstanding performances compared with other existing grid layouts. Use of an approximate pattern matching algorithm quickly redistributes the laid-out nodes by fast, non-grid algorithms on the square grid points, while preserving the topological relationships among the nodes. The proposed algorithm is a novel use of the pattern matching, thereby providing a breakthrough for grid layout. This application program can be freely downloaded from http://www.cadlive.jp/hybridlayout/hybridlayout.html.
Directory of Open Access Journals (Sweden)
Kentaro Inoue
Full Text Available BACKGROUND: For visualizing large-scale biochemical network maps, it is important to calculate the coordinates of molecular nodes quickly and to enhance the understanding or traceability of them. The grid layout is effective in drawing compact, orderly, balanced network maps with node label spaces, but existing grid layout algorithms often require a high computational cost because they have to consider complicated positional constraints through the entire optimization process. RESULTS: We propose a hybrid grid layout algorithm that consists of a non-grid, fast layout (preprocessor algorithm and an approximate pattern matching algorithm that distributes the resultant preprocessed nodes on square grid points. To demonstrate the feasibility of the hybrid layout algorithm, it is characterized in terms of the calculation time, numbers of edge-edge and node-edge crossings, relative edge lengths, and F-measures. The proposed algorithm achieves outstanding performances compared with other existing grid layouts. CONCLUSIONS: Use of an approximate pattern matching algorithm quickly redistributes the laid-out nodes by fast, non-grid algorithms on the square grid points, while preserving the topological relationships among the nodes. The proposed algorithm is a novel use of the pattern matching, thereby providing a breakthrough for grid layout. This application program can be freely downloaded from http://www.cadlive.jp/hybridlayout/hybridlayout.html.
Data-Driven Engineering of Social Dynamics: Pattern Matching and Profit Maximization.
Directory of Open Access Journals (Sweden)
Huan-Kai Peng
Full Text Available In this paper, we define a new problem related to social media, namely, the data-driven engineering of social dynamics. More precisely, given a set of observations from the past, we aim at finding the best short-term intervention that can lead to predefined long-term outcomes. Toward this end, we propose a general formulation that covers two useful engineering tasks as special cases, namely, pattern matching and profit maximization. By incorporating a deep learning model, we derive a solution using convex relaxation and quadratic-programming transformation. Moreover, we propose a data-driven evaluation method in place of the expensive field experiments. Using a Twitter dataset, we demonstrate the effectiveness of our dynamics engineering approach for both pattern matching and profit maximization, and study the multifaceted interplay among several important factors of dynamics engineering, such as solution validity, pattern-matching accuracy, and intervention cost. Finally, the method we propose is general enough to work with multi-dimensional time series, so it can potentially be used in many other applications.
Data-Driven Engineering of Social Dynamics: Pattern Matching and Profit Maximization
Peng, Huan-Kai; Lee, Hao-Chih; Pan, Jia-Yu; Marculescu, Radu
2016-01-01
In this paper, we define a new problem related to social media, namely, the data-driven engineering of social dynamics. More precisely, given a set of observations from the past, we aim at finding the best short-term intervention that can lead to predefined long-term outcomes. Toward this end, we propose a general formulation that covers two useful engineering tasks as special cases, namely, pattern matching and profit maximization. By incorporating a deep learning model, we derive a solution using convex relaxation and quadratic-programming transformation. Moreover, we propose a data-driven evaluation method in place of the expensive field experiments. Using a Twitter dataset, we demonstrate the effectiveness of our dynamics engineering approach for both pattern matching and profit maximization, and study the multifaceted interplay among several important factors of dynamics engineering, such as solution validity, pattern-matching accuracy, and intervention cost. Finally, the method we propose is general enough to work with multi-dimensional time series, so it can potentially be used in many other applications. PMID:26771830
Robust real-time pattern matching using bayesian sequential hypothesis testing.
Pele, Ofir; Werman, Michael
2008-08-01
This paper describes a method for robust real time pattern matching. We first introduce a family of image distance measures, the "Image Hamming Distance Family". Members of this family are robust to occlusion, small geometrical transforms, light changes and non-rigid deformations. We then present a novel Bayesian framework for sequential hypothesis testing on finite populations. Based on this framework, we design an optimal rejection/acceptance sampling algorithm. This algorithm quickly determines whether two images are similar with respect to a member of the Image Hamming Distance Family. We also present a fast framework that designs a near-optimal sampling algorithm. Extensive experimental results show that the sequential sampling algorithm performance is excellent. Implemented on a Pentium 4 3 GHz processor, detection of a pattern with 2197 pixels, in 640 x 480 pixel frames, where in each frame the pattern rotated and was highly occluded, proceeds at only 0.022 seconds per frame.
A novel iris patterns matching algorithm of weighted polar frequency correlation
Zhao, Weijie; Jiang, Linhua
2014-11-01
Iris recognition is recognized as one of the most accurate techniques for biometric authentication. In this paper, we present a novel correlation method - Weighted Polar Frequency Correlation(WPFC) - to match and evaluate two iris images, actually it can also be used for evaluating the similarity of any two images. The WPFC method is a novel matching and evaluating method for iris image matching, which is complete different from the conventional methods. For instance, the classical John Daugman's method of iris recognition uses 2D Gabor wavelets to extract features of iris image into a compact bit stream, and then matching two bit streams with hamming distance. Our new method is based on the correlation in the polar coordinate system in frequency domain with regulated weights. The new method is motivated by the observation that the pattern of iris that contains far more information for recognition is fine structure at high frequency other than the gross shapes of iris images. Therefore, we transform iris images into frequency domain and set different weights to frequencies. Then calculate the correlation of two iris images in frequency domain. We evaluate the iris images by summing the discrete correlation values with regulated weights, comparing the value with preset threshold to tell whether these two iris images are captured from the same person or not. Experiments are carried out on both CASIA database and self-obtained images. The results show that our method is functional and reliable. Our method provides a new prospect for iris recognition system.
Dietary pattern analysis: a comparison between matched vegetarian and omnivorous subjects.
Clarys, Peter; Deriemaeker, Peter; Huybrechts, Inge; Hebbelinck, Marcel; Mullie, Patrick
2013-06-13
Dietary pattern analysis, based on the concept that foods eaten together are as important as a reductive methodology characterized by a single food or nutrient analysis, has emerged as an alternative approach to study the relation between nutrition and disease. The aim of the present study was to compare nutritional intake and the results of dietary pattern analysis in properly matched vegetarian and omnivorous subjects. Vegetarians (n = 69) were recruited via purposeful sampling and matched non-vegetarians (n = 69) with same age, gender, health and lifestyle characteristics were searched for via convenience sampling. Two dietary pattern analysis methods, the Healthy Eating Index-2010 (HEI-2010) and the Mediterranean Diet Score (MDS) were calculated and analysed in function of the nutrient intake. Mean total energy intake was comparable between vegetarians and omnivorous subjects (p > 0.05). Macronutrient analysis revealed significant differences between the mean values for vegetarians and omnivorous subjects (absolute and relative protein and total fat intake were significantly lower in vegetarians, while carbohydrate and fibre intakes were significantly higher in vegetarians than in omnivorous subjects). The HEI and MDS were significantly higher for the vegetarians (HEI = 53.8.1 ± 11.2; MDS = 4.3 ± 1.3) compared to the omnivorous subjects (HEI = 46.4 ± 15.3; MDS = 3.8 ± 1.4). Our results indicate a more nutrient dense pattern, closer to the current dietary recommendations for the vegetarians compared to the omnivorous subjects. Both indexing systems were able to discriminate between the vegetarians and the non-vegetarians with higher scores for the vegetarian subjects.
Chan, H. M.; Yen, K. S.; Ratnam, M. M.
2008-09-01
The moire method has been extensively studied in the past and applied in various engineering applications. Several techniques are available for generating the moire fringes in these applications, which include moire interferometry, projection moire, shadow moire, moire deflectometry etc. Most of these methods use the superposition of linear gratings to generate the moire patterns. The use of non-linear gratings, such as circular, radial and elongated gratings has received less attention from the research community. The potential of non-linear gratings in engineering measurement has been realized in a limited number of applications, such as rotation measurement, measurement of linear displacement, measurement of expansion coefficients of materials and measurement of strain distribution. In this work, circular gratings of different pitch were applied to the sensing and measurement of crack displacement in concrete structures. Gratings of pitch 0.50 mm and 0.55 mm were generated using computer software and attached to two overlapping acrylic plates that were bonded to either side of the crack. The resulting moire patterns were captured using a standard digital camera and compared with a set of reference patterns generated using a precision positioning stage. Using several image pre-processing stages, such as filtering and morphological operations, and pattern matching the magnitude displacements along two orthogonal axes can be detected with a resolution of 0.05 mm.
Bettonviel A, E O; Brinkmans N, Y J; Russcher, Kris; Wardenaar, Floris C; Witard, Oliver C
2016-06-01
The nutritional status of elite soccer players across match, postmatch, training and rest days has not been defined. Recent evidence suggests the pattern of dietary protein intake impacts the daytime turnover of muscle proteins and, as such, influences muscle recovery. We assessed the nutritional status and daytime pattern of protein intake in senior professional and elite youth soccer players and compared findings against published recommendations. Fourteen senior professional (SP) and 15 youth elite (YP) soccer players from the Dutch premier division completed nutritional assessments using a 24-hr web-based recall method. Recall days consisted of a match, postmatch, rest, and training day. Daily energy intake over the 4-day period was similar between SP (2988 ± 583 kcal/day) and YP (2938 ± 465 kcal/day; p = .800). Carbohydrate intake over the combined 4-day period was lower in SP (4.7 ± 0.7 g·kg-1 BM·day-1) vs. YP (6.0 ± 1.5 g·kg-1 BM·day-1, p = .006) and SP failed to meet recommended carbohydrate intakes on match and training days. Conversely, recommended protein intakes were met for SP (1.9 ± 0.3 g·kg-1 BM·day-1) and YP (1.7 ± 0.4 g·kg-1 BM·day-1), with no differences between groups (p = .286). Accordingly, both groups met or exceeded recommended daily protein intakes on individual match, postmatch, rest and training days. A similar "balanced" daytime pattern of protein intake was observed in SP and YP. To conclude, SP increased protein intake on match and training days to a greater extent than YP, however at the expense of carbohydrate intake. The daytime distribution of protein intake for YP and SP aligned with current recommendations of a balanced protein meal pattern.
Pattern Matching Framework to Estimate the Urgency of Off-Normal Situations in NPPs
Energy Technology Data Exchange (ETDEWEB)
Shin, Jin Soo; Park, Sang Jun; Heo, Gyun Young [Kyung Hee University, Yongin (Korea, Republic of); Park, Jin Kyun [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of); Kim, Hyo Jin; Park, Soon Yeol [Korea Hydro and Nuclear Power, Yeonggwang (Korea, Republic of)
2010-10-15
According to power plant operators, it was said that they could quite well recognize off-normal situations from an incipient stage and also anticipate the possibility of upcoming trips in case of skilled operators, even though it is difficult to clarify the cause of the off-normal situation. From the interview, we could assure the feasibility of two assumptions for the diagnosis of off-normal conditions: One is that we can predict whether an accidental shutdown happens or not if we observe the early stage when an off-normal starts to grow. The other is the observation at the early stage can provide the remaining time to a trip as well as the cause of such an off-normal situation. For this purpose, the development of on-line monitoring systems using various data processing techniques in nuclear power plants (NPPs) has been the subject of increasing attention and becomes important contributor to improve performance and economics. Many of studies have suggested the diagnostic methodologies. One of representative methods was to use the distance discrimination as a similarity measure, for example, such as the Euclidean distance. A variety of artificial intelligence techniques such as a neural network have been developed as well. In addition, some of these methodologies were to reduce the data dimensions for more effectively work. While sharing the same motivation with the previous achievements, this study proposed non-parametric pattern matching techniques to reduce the uncertainty in pursuance of selection of models and modeling processes. This could be characterized by the following two aspects: First, for overcoming considering only a few typical scenarios in the most of the studies, this study is getting the entire sets of off-normal situations which are anticipated in NPPs, which are created by a full-scope simulator. Second, many of the existing researches adopted the process of forming a diagnosis model which is so-called a training technique or a parametric
Pattern Matching Framework to Estimate the Urgency of Off-Normal Situations in NPPs
International Nuclear Information System (INIS)
Shin, Jin Soo; Park, Sang Jun; Heo, Gyun Young; Park, Jin Kyun; Kim, Hyo Jin; Park, Soon Yeol
2010-01-01
According to power plant operators, it was said that they could quite well recognize off-normal situations from an incipient stage and also anticipate the possibility of upcoming trips in case of skilled operators, even though it is difficult to clarify the cause of the off-normal situation. From the interview, we could assure the feasibility of two assumptions for the diagnosis of off-normal conditions: One is that we can predict whether an accidental shutdown happens or not if we observe the early stage when an off-normal starts to grow. The other is the observation at the early stage can provide the remaining time to a trip as well as the cause of such an off-normal situation. For this purpose, the development of on-line monitoring systems using various data processing techniques in nuclear power plants (NPPs) has been the subject of increasing attention and becomes important contributor to improve performance and economics. Many of studies have suggested the diagnostic methodologies. One of representative methods was to use the distance discrimination as a similarity measure, for example, such as the Euclidean distance. A variety of artificial intelligence techniques such as a neural network have been developed as well. In addition, some of these methodologies were to reduce the data dimensions for more effectively work. While sharing the same motivation with the previous achievements, this study proposed non-parametric pattern matching techniques to reduce the uncertainty in pursuance of selection of models and modeling processes. This could be characterized by the following two aspects: First, for overcoming considering only a few typical scenarios in the most of the studies, this study is getting the entire sets of off-normal situations which are anticipated in NPPs, which are created by a full-scope simulator. Second, many of the existing researches adopted the process of forming a diagnosis model which is so-called a training technique or a parametric
GPUs for fast triggering and pattern matching at the CERN experiment NA62
International Nuclear Information System (INIS)
Lamanna, Gianluca; Collazuol, Gianmaria; Sozzi, Marco
2011-01-01
In rare decays experiments an effective trigger is crucial to reduce both the quantity of data written on tape and the bandwidth requirements for the DAQ (Data Acquisition) system. A multilevel architecture is commonly used to achieve a higher reduction factor, exploiting dedicated custom hardware and flexible software in standard computers. In this paper we discuss the possibility to use commercial video card processors (GPU) to build a fast and effective trigger system, both at hardware and software level. The case of fast pattern matching in the RICH detector of the NA62 experiment at CERN aiming at measuring the Branching Ratio of the ultra rare decay K + →π + νν-bar is considered as use case although the versatility and the customizability of this approach easily allow exporting the concept to different contexts.
A Hybrid CPU/GPU Pattern-Matching Algorithm for Deep Packet Inspection.
Directory of Open Access Journals (Sweden)
Chun-Liang Lee
Full Text Available The large quantities of data now being transferred via high-speed networks have made deep packet inspection indispensable for security purposes. Scalable and low-cost signature-based network intrusion detection systems have been developed for deep packet inspection for various software platforms. Traditional approaches that only involve central processing units (CPUs are now considered inadequate in terms of inspection speed. Graphic processing units (GPUs have superior parallel processing power, but transmission bottlenecks can reduce optimal GPU efficiency. In this paper we describe our proposal for a hybrid CPU/GPU pattern-matching algorithm (HPMA that divides and distributes the packet-inspecting workload between a CPU and GPU. All packets are initially inspected by the CPU and filtered using a simple pre-filtering algorithm, and packets that might contain malicious content are sent to the GPU for further inspection. Test results indicate that in terms of random payload traffic, the matching speed of our proposed algorithm was 3.4 times and 2.7 times faster than those of the AC-CPU and AC-GPU algorithms, respectively. Further, HPMA achieved higher energy efficiency than the other tested algorithms.
Du, Pan; Kibbe, Warren A; Lin, Simon M
2006-09-01
A major problem for current peak detection algorithms is that noise in mass spectrometry (MS) spectra gives rise to a high rate of false positives. The false positive rate is especially problematic in detecting peaks with low amplitudes. Usually, various baseline correction algorithms and smoothing methods are applied before attempting peak detection. This approach is very sensitive to the amount of smoothing and aggressiveness of the baseline correction, which contribute to making peak detection results inconsistent between runs, instrumentation and analysis methods. Most peak detection algorithms simply identify peaks based on amplitude, ignoring the additional information present in the shape of the peaks in a spectrum. In our experience, 'true' peaks have characteristic shapes, and providing a shape-matching function that provides a 'goodness of fit' coefficient should provide a more robust peak identification method. Based on these observations, a continuous wavelet transform (CWT)-based peak detection algorithm has been devised that identifies peaks with different scales and amplitudes. By transforming the spectrum into wavelet space, the pattern-matching problem is simplified and in addition provides a powerful technique for identifying and separating the signal from the spike noise and colored noise. This transformation, with the additional information provided by the 2D CWT coefficients can greatly enhance the effective signal-to-noise ratio. Furthermore, with this technique no baseline removal or peak smoothing preprocessing steps are required before peak detection, and this improves the robustness of peak detection under a variety of conditions. The algorithm was evaluated with SELDI-TOF spectra with known polypeptide positions. Comparisons with two other popular algorithms were performed. The results show the CWT-based algorithm can identify both strong and weak peaks while keeping false positive rate low. The algorithm is implemented in R and will be
Directory of Open Access Journals (Sweden)
Hao Yu
2018-01-01
Full Text Available This study introduces a data-driven modeling strategy for smart grid power quality (PQ coupling assessment based on time series pattern matching to quantify the influence of single and integrated disturbance among nodes in different pollution patterns. Periodic and random PQ patterns are constructed by using multidimensional frequency-domain decomposition for all disturbances. A multidimensional piecewise linear representation based on local extreme points is proposed to extract the patterns features of single and integrated disturbance in consideration of disturbance variation trend and severity. A feature distance of pattern (FDP is developed to implement pattern matching on univariate PQ time series (UPQTS and multivariate PQ time series (MPQTS to quantify the influence of single and integrated disturbance among nodes in the pollution patterns. Case studies on a 14-bus distribution system are performed and analyzed; the accuracy and applicability of the FDP in the smart grid PQ coupling assessment are verified by comparing with other time series pattern matching methods.
Göschl, Florian; Friese, Uwe; Daume, Jonathan; König, Peter; Engel, Andreas K
2015-08-01
Coherent percepts emerge from the accurate combination of inputs from the different sensory systems. There is an ongoing debate about the neurophysiological mechanisms of crossmodal interactions in the brain, and it has been proposed that transient synchronization of neurons might be of central importance. Oscillatory activity in lower frequency ranges (congruence. Analysis of the behavioral data showed benefits for congruent visuotactile stimulus combinations. Differences in oscillatory dynamics related to crossmodal congruence within the two tasks were observed in the beta-band for crossmodal target detection, as well as in the theta-band for congruence evaluation. Contrasting ongoing activity preceding visuotactile stimulation between the two tasks revealed differences in the alpha- and beta-bands. Source reconstruction of between-task differences showed prominent involvement of premotor cortex, supplementary motor area, somatosensory association cortex and the supramarginal gyrus. These areas not only exhibited more involvement in the pre-stimulus interval for target detection compared to congruence evaluation, but were also crucially involved in post-stimulus differences related to crossmodal stimulus congruence within the detection task. These results add to the increasing evidence that low frequency oscillations are functionally relevant for integration in distributed brain networks, as demonstrated for crossmodal interactions in visuotactile pattern matching in the current study. Copyright © 2015 Elsevier Inc. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
Andrulis, Mindaugas [Institute of Pathology, University of Heidelberg, Heidelberg (Germany); Bäuerle, Tobias [Department of Diagnostic and Interventional Radiology, University of Hamburg, Hamburg (Germany); Goldschmidt, Hartmut [Department of Hematology and Oncology, University of Heidelberg, Heidelberg (Germany); Delorme, Stefan [Department of Radiology, German Cancer Research Center (DKFZ), Heidelberg (Germany); Landgren, Ola [Multiple Myeloma Section, Metabolism Branch, National Cancer Institute, Bethesda (United States); Schirmacher, Peter [Institute of Pathology, University of Heidelberg, Heidelberg (Germany); Hillengass, Jens, E-mail: jens.hillengass@med.uni-heidelberg.de [Department of Hematology and Oncology, University of Heidelberg, Heidelberg (Germany); Department of Radiology, German Cancer Research Center (DKFZ), Heidelberg (Germany)
2014-06-15
Objectives: To investigate how plasma cell infiltration patterns detected by MRI match the plasma cell distribution in bone marrow biopsy. Methods: We assessed 50 patients with monoclonal plasma cell disorders of all clinical stages. MRI infiltration pattern was compared with matched BM histology from the same anatomic region. Results: MRI revealed a minimal (n = 11, 22%), focal (n = 5, 10%), diffuse (n = 14, 28%) and mixed (n = 20, 40%) infiltration pattern. Diffuse MRI pattern was predominant in smoldering myeloma patients whereas the MRI patterns with “focal component” (i.e. focal and mixed) were most common in symptomatic myeloma (p < 0.01). In histology an interstitial (n = 13, 26%), nodular (n = 23, 46%) and packed marrow (n = 14, 28%) was found respectively. All three histological types of infiltration were observed in patients with diffuse and mixed MRI patterns. Minimal MRI pattern was found in all MGUS patients and was associated with an interstitial BM infiltration. In two patients with minimal MRI pattern an extensive micro-nodular BM infiltration was found in histology. Conclusions: Infiltration patterns in MRI represent different histological growth patterns of plasma cells, but the MRI resolution is not sufficient to visualize micro-nodular aggregates of plasma cells.
International Nuclear Information System (INIS)
Andrulis, Mindaugas; Bäuerle, Tobias; Goldschmidt, Hartmut; Delorme, Stefan; Landgren, Ola; Schirmacher, Peter; Hillengass, Jens
2014-01-01
Objectives: To investigate how plasma cell infiltration patterns detected by MRI match the plasma cell distribution in bone marrow biopsy. Methods: We assessed 50 patients with monoclonal plasma cell disorders of all clinical stages. MRI infiltration pattern was compared with matched BM histology from the same anatomic region. Results: MRI revealed a minimal (n = 11, 22%), focal (n = 5, 10%), diffuse (n = 14, 28%) and mixed (n = 20, 40%) infiltration pattern. Diffuse MRI pattern was predominant in smoldering myeloma patients whereas the MRI patterns with “focal component” (i.e. focal and mixed) were most common in symptomatic myeloma (p < 0.01). In histology an interstitial (n = 13, 26%), nodular (n = 23, 46%) and packed marrow (n = 14, 28%) was found respectively. All three histological types of infiltration were observed in patients with diffuse and mixed MRI patterns. Minimal MRI pattern was found in all MGUS patients and was associated with an interstitial BM infiltration. In two patients with minimal MRI pattern an extensive micro-nodular BM infiltration was found in histology. Conclusions: Infiltration patterns in MRI represent different histological growth patterns of plasma cells, but the MRI resolution is not sufficient to visualize micro-nodular aggregates of plasma cells
CERN. Geneva
2006-01-01
The flexible and modular design of the engine allows a broad spectrum of applications, ranging from high-end enterprise level network devices that need to match hundreds of thousands of patterns at speeds of tens of gigabits per second, to low-end dev...
Schomaker, Lambertus; Mangalagiu, D.; Vuurpijl, Louis; Weinfeld, M.; Schomaker, Lambert; Vuurpijl, Louis
2000-01-01
This paper describes treebased classification of character images, comparing two methods of tree formation and two methods of matching: nearest neighbor and nearest centroid. The first method, Preprocess Using Relative Distances (PURD) is a treebased reorganization of a flat list of patterns,
GPUs for fast pattern matching in the RICH of the NA62 experiment
International Nuclear Information System (INIS)
Lamanna, Gianluca; Collazuol, Gianmaria; Sozzi, Marco
2011-01-01
In rare decays experiments an effective online selection is a fundamental part of the data acquisition system (DAQ) in order to reduce both the quantity of data written on tape and the bandwidth requirements for the DAQ system. A multilevel architecture is commonly used to achieve a higher reduction factor, exploiting dedicated custom hardware and flexible software in standard computers. In this paper we discuss the possibility to use commercial video card processors (GPU) to build a fast and effective trigger system, both at hardware and software level. The computing power of the GPUs allows to design a real-time system in which trigger decisions are taken directly in the video processor with a defined maximum latency. This allows building lowest trigger levels based on standard off-the-shelf PCs with CPU and GPU (instead of the commonly adopted solutions based on custom electronics with FPGA or ASICs) with enhanced and high performance computation capabilities, resulting in high rejection power, high efficiency and simpler low level triggers. The ongoing work presented here shows the results achieved in the case of fast pattern matching in the RICH detector of the NA62 at CERN, aiming at measuring the Branching Ratio of the ultra rare decay K + →π + νν-bar, is considered as use case, although the versatility and the customizability of this approach easily allow exporting the concept to different contexts. In particular the application is related to particle identification in the RICH detector of the NA62 experiment, where the rate of events to be analyzed will be around 10 MHz. The results obtained in lab tests are very encouraging to go towards a working prototype. Due to the use of off-the-shelf technology, in continuous development for other purposes (Video Games, image editing,...), the architecture described would be easily exported into other experiments, for building powerful, flexible and fully customizable trigger systems.
GPUs for fast pattern matching in the RICH of the NA62 experiment
Energy Technology Data Exchange (ETDEWEB)
Lamanna, Gianluca, E-mail: gianluca.lamanna@cern.c [CERN, 1211 Geneve 23 (Switzerland); Collazuol, Gianmaria, E-mail: gianmaria.collazuol@cern.c [INFN Pisa, Largo Pontecorvo 3, 56127 Pisa (Italy); Sozzi, Marco, E-mail: marco.sozzi@cern.c [University and INFN Pisa, Largo Pontecorvo 3, 56127 Pisa (Italy)
2011-05-21
In rare decays experiments an effective online selection is a fundamental part of the data acquisition system (DAQ) in order to reduce both the quantity of data written on tape and the bandwidth requirements for the DAQ system. A multilevel architecture is commonly used to achieve a higher reduction factor, exploiting dedicated custom hardware and flexible software in standard computers. In this paper we discuss the possibility to use commercial video card processors (GPU) to build a fast and effective trigger system, both at hardware and software level. The computing power of the GPUs allows to design a real-time system in which trigger decisions are taken directly in the video processor with a defined maximum latency. This allows building lowest trigger levels based on standard off-the-shelf PCs with CPU and GPU (instead of the commonly adopted solutions based on custom electronics with FPGA or ASICs) with enhanced and high performance computation capabilities, resulting in high rejection power, high efficiency and simpler low level triggers. The ongoing work presented here shows the results achieved in the case of fast pattern matching in the RICH detector of the NA62 at CERN, aiming at measuring the Branching Ratio of the ultra rare decay K{sup +}{yields}{pi}{sup +}{nu}{nu}-bar, is considered as use case, although the versatility and the customizability of this approach easily allow exporting the concept to different contexts. In particular the application is related to particle identification in the RICH detector of the NA62 experiment, where the rate of events to be analyzed will be around 10 MHz. The results obtained in lab tests are very encouraging to go towards a working prototype. Due to the use of off-the-shelf technology, in continuous development for other purposes (Video Games, image editing,...), the architecture described would be easily exported into other experiments, for building powerful, flexible and fully customizable trigger systems.
Millán, María S.
2012-10-01
On the verge of the 50th anniversary of Vander Lugt’s formulation for pattern matching based on matched filtering and optical correlation, we acknowledge the very intense research activity developed in the field of correlation-based pattern recognition during this period of time. The paper reviews some domains that appeared as emerging fields in the last years of the 20th century and have been developed later on in the 21st century. Such is the case of three-dimensional (3D) object recognition, biometric pattern matching, optical security and hybrid optical-digital processors. 3D object recognition is a challenging case of multidimensional image recognition because of its implications in the recognition of real-world objects independent of their perspective. Biometric recognition is essentially pattern recognition for which the personal identification is based on the authentication of a specific physiological characteristic possessed by the subject (e.g. fingerprint, face, iris, retina, and multifactor combinations). Biometric recognition often appears combined with encryption-decryption processes to secure information. The optical implementations of correlation-based pattern recognition processes still rely on the 4f-correlator, the joint transform correlator, or some of their variants. But the many applications developed in the field have been pushing the systems for a continuous improvement of their architectures and algorithms, thus leading towards merged optical-digital solutions.
International Nuclear Information System (INIS)
Millán, María S
2012-01-01
On the verge of the 50th anniversary of Vander Lugt’s formulation for pattern matching based on matched filtering and optical correlation, we acknowledge the very intense research activity developed in the field of correlation-based pattern recognition during this period of time. The paper reviews some domains that appeared as emerging fields in the last years of the 20th century and have been developed later on in the 21st century. Such is the case of three-dimensional (3D) object recognition, biometric pattern matching, optical security and hybrid optical–digital processors. 3D object recognition is a challenging case of multidimensional image recognition because of its implications in the recognition of real-world objects independent of their perspective. Biometric recognition is essentially pattern recognition for which the personal identification is based on the authentication of a specific physiological characteristic possessed by the subject (e.g. fingerprint, face, iris, retina, and multifactor combinations). Biometric recognition often appears combined with encryption–decryption processes to secure information. The optical implementations of correlation-based pattern recognition processes still rely on the 4f-correlator, the joint transform correlator, or some of their variants. But the many applications developed in the field have been pushing the systems for a continuous improvement of their architectures and algorithms, thus leading towards merged optical–digital solutions. (review article)
Network-level accident-mapping: Distance based pattern matching using artificial neural network.
Deka, Lipika; Quddus, Mohammed
2014-04-01
The objective of an accident-mapping algorithm is to snap traffic accidents onto the correct road segments. Assigning accidents onto the correct segments facilitate to robustly carry out some key analyses in accident research including the identification of accident hot-spots, network-level risk mapping and segment-level accident risk modelling. Existing risk mapping algorithms have some severe limitations: (i) they are not easily 'transferable' as the algorithms are specific to given accident datasets; (ii) they do not perform well in all road-network environments such as in areas of dense road network; and (iii) the methods used do not perform well in addressing inaccuracies inherent in and type of road environment. The purpose of this paper is to develop a new accident mapping algorithm based on the common variables observed in most accident databases (e.g. road name and type, direction of vehicle movement before the accident and recorded accident location). The challenges here are to: (i) develop a method that takes into account uncertainties inherent to the recorded traffic accident data and the underlying digital road network data, (ii) accurately determine the type and proportion of inaccuracies, and (iii) develop a robust algorithm that can be adapted for any accident set and road network of varying complexity. In order to overcome these challenges, a distance based pattern-matching approach is used to identify the correct road segment. This is based on vectors containing feature values that are common in the accident data and the network data. Since each feature does not contribute equally towards the identification of the correct road segments, an ANN approach using the single-layer perceptron is used to assist in "learning" the relative importance of each feature in the distance calculation and hence the correct link identification. The performance of the developed algorithm was evaluated based on a reference accident dataset from the UK confirming that
A pattern-matched Twitter analysis of US cancer-patient sentiments.
Crannell, W Christian; Clark, Eric; Jones, Chris; James, Ted A; Moore, Jesse
2016-12-01
Twitter has been recognized as an important source of organic sentiment and opinion. This study aimed to (1) characterize the content of tweets authored by the United States cancer patients; and (2) use patient tweets to compute the average happiness of cancer patients for each cancer diagnosis. A large sample of English tweets from March 2014 through December 2014 was obtained from Twitter. Using regular expression software pattern matching, the tweets were filtered by cancer diagnosis. For each cancer-specific tweetset, individual patients were extracted, and the content of the tweet was categorized. The patients' Twitter identification numbers were used to gather all tweets for each patient, and happiness values for patient tweets were calculated using a quantitative hedonometric analysis. The most frequently tweeted cancers were breast (n = 15,421, 11% of total cancer tweets), lung (n = 2928, 2.0%), prostate (n = 1036, 0.7%), and colorectal (n = 773, 0.5%). Patient tweets pertained to the treatment course (n = 73, 26%), diagnosis (n = 65, 23%), and then surgery and/or biopsy (n = 42, 15%). Computed happiness values for each cancer diagnosis revealed higher average happiness values for thyroid (h_avg = 6.1625), breast (h_avg = 6.1485), and lymphoma (h_avg = 6.0977) cancers and lower average happiness values for pancreatic (h_avg = 5.8766), lung (h_avg = 5.8733), and kidney (h_avg = 5.8464) cancers. The study confirms that patients are expressing themselves openly on social media about their illness and that unique cancer diagnoses are correlated with varying degrees of happiness. Twitter can be employed as a tool to identify patient needs and as a means to gauge the cancer patient experience. Copyright Â© 2016 Elsevier Inc. All rights reserved.
Movement patterns and muscle damage during simulated rugby sevens matches in National team players.
Pereira, Lucas A; Nakamura, Fábio Y; Moraes, José E; Kitamura, Katia; Ramos, Solange P; Loturco, Irineu
2017-02-23
The aim of this study was to analyze the match performance (i.e., distance covered in different intensities), signs of muscle damage (assessed by means of creatine kinase [CK] activity and rate of force development [RFD]), and neuromuscular fatigue (using linear sprint and vertical jump performances) following three single-day simulated matches performed by rugby sevens players from the Brazilian National Team. Ten male rugby sevens players (25.2 ± 3.6 years; 88.7 ± 7.1 kg; 182.2 ± 6.3 cm) participated in this study. On the day prior to the matches, the athletes performed a 40-m sprint, a vertical jump assessment and a maximal isometric force test. In the morning of the match day, blood samples were collected to analyze the CK activity. Afterwards, three simulated rugby sevens' matches were performed with 2-h intermission periods. The match performance (encompassing total distance and distance covered in different velocity ranges and body loads [BL]) were obtained from global positioning system units. The statistical analysis was performed by using a mixed model approach and the effect sizes (ES) of the differences. The statistical significance level was set at P0.8) and significant (P< 0.05) reductions were demonstrated in the total distance and BL when comparing the 2 with the 1 halves. Decrements in the explosive force capacity (assessed by means of RFD) and the squat jump were noticed (ES varying from 0.55 to 1.14; P< 0.05). The CK activity increased after the matches (ES = 1.29; P< 0.05). The rugby sevens players were able to maintain the physical performance across three successive matches simulating the first day of a tournament. The augmented CK activity and the decreases in the squat jump and RFD suggest that increased levels of muscle damage were experienced on the day after the matches. Therefore, the technical staff are encouraged to implement recovery strategies and planned substitutions during multi-day tournaments in order to reduce the impact of
Directory of Open Access Journals (Sweden)
Barbara Diana
2017-08-01
Full Text Available The influence of game location on performance has been widely examined in sport contexts. Concerning soccer, game-location affects positively the secondary and tertiary level of performance; however, there are fewer evidences about its effect on game structure (primary level of performance. This study aimed to detect the effect of game location on a primary level of performance in soccer. In particular, the objective was to reveal the hidden structures underlying the attack actions, in both home and away matches played by a top club (Serie A 2012/2013—First Leg. The methodological approach was based on systematic observation, supported by digital recordings and T-pattern analysis. Data were analyzed with THEME 6.0 software. A quantitative analysis, with nonparametric Mann–Whitney test and descriptive statistics, was carried out to test the hypotheses. A qualitative analysis on complex patterns was performed to get in-depth information on the game structure. This study showed that game tactics were significantly different, with home matches characterized by a more structured and varied game than away matches. In particular, a higher number of different patterns, with a higher level of complexity and including more unique behaviors was detected in home matches than in the away ones. No significant differences were found in the number of events coded per game between the two conditions. THEME software, and the corresponding T-pattern detection algorithm, enhance research opportunities by going further than frequency-based analyses, making this method an effective tool in supporting sport performance analysis and training.
Diana, Barbara; Zurloni, Valentino; Elia, Massimiliano; Cavalera, Cesare M; Jonsson, Gudberg K; Anguera, M Teresa
2017-01-01
The influence of game location on performance has been widely examined in sport contexts. Concerning soccer, game-location affects positively the secondary and tertiary level of performance; however, there are fewer evidences about its effect on game structure (primary level of performance). This study aimed to detect the effect of game location on a primary level of performance in soccer. In particular, the objective was to reveal the hidden structures underlying the attack actions, in both home and away matches played by a top club (Serie A 2012/2013-First Leg). The methodological approach was based on systematic observation, supported by digital recordings and T-pattern analysis. Data were analyzed with THEME 6.0 software. A quantitative analysis, with nonparametric Mann-Whitney test and descriptive statistics, was carried out to test the hypotheses. A qualitative analysis on complex patterns was performed to get in-depth information on the game structure. This study showed that game tactics were significantly different, with home matches characterized by a more structured and varied game than away matches. In particular, a higher number of different patterns, with a higher level of complexity and including more unique behaviors was detected in home matches than in the away ones. No significant differences were found in the number of events coded per game between the two conditions. THEME software, and the corresponding T-pattern detection algorithm, enhance research opportunities by going further than frequency-based analyses, making this method an effective tool in supporting sport performance analysis and training.
Directory of Open Access Journals (Sweden)
Yonghui Zhang
Full Text Available BACKGROUND: Influenza A virus displays strong reassortment characteristics, which enable it to achieve adaptation in human infection. Surveying the reassortment and virulence of novel viruses is important in the prevention and control of an influenza pandemic. Meanwhile, studying the mechanism of reassortment may accelerate the development of anti-influenza strategies. METHODOLOGY/PRINCIPAL FINDINGS: The hemagglutinin (HA and neuraminidase (NA matching patterns of two pandemic H1N1 viruses (the 1918 and current 2009 strains and a highly pathogenic avian influenza A virus (H5N1 were studied using a pseudotyped particle (pp system. Our data showed that four of the six chimeric HA/NA combinations could produce infectious pps, and that some of the chimeric pps had greater infectivity than did their ancestors, raising the possibility of reassortment among these viruses. The NA of H5N1 (A/Anhui/1/2005 could hardly reassort with the HAs of the two H1N1 viruses. Many biological characteristics of HA and NA, including infectivity, hemagglutinating ability, and NA activity, are dependent on their matching pattern. CONCLUSIONS/SIGNIFICANCE: Our data suggest the existence of an interaction between HA and NA, and the HA NA matching pattern is critical for valid viral reassortment.
Generalized Phase contrast and matched filtering for speckle‐free patterned illumination
DEFF Research Database (Denmark)
Palima, Darwin; Bañas, Andrew Rafael; Villangca, Mark Jayson
2013-01-01
Generalized Phase Contrast (GPC) and matched‐filtering GPC use tandem diffractive phase elements on Fourier‐conjugate planes of a 4f optical processor to efficiently reshape incident light into a pattern that resembles the input phase modulation pattern. The synthesized patterns are inherently...... to optically trap and mechanically manipulate microparticles, GPC has also been applied for laser beamshaping, optical phase cryptography, and greyscale image projection. Recent reports from our collaborators highlight that GPC‐based spatial lightshaping, when combined with temporal focusing and multiphoton...... excitation, exhibits some robustness against light scattering and, hence, makes a promising tool for spatially precise targeting of deeper subsurface neurons using minimally speckled patterned illumination for multiphoton excitation....
Tassin, Philippe; Van der Sande, Guy; Veretennicoff, Irina; Kockaert, Pascal; Tlidi, Mustapha
2009-05-25
We consider a degenerate optical parametric oscillator containing a left-handed material. We show that the inclusion of a left-handed material layer allows for controlling the strength and sign of the diffraction coefficient at either the pump or the signal frequency. Subsequently, we demonstrate the existence of stable dissipative structures without diffraction matching, i.e., without the usual relationship between the diffraction coefficients of the signal and pump fields. Finally, we investigate the size scaling of these light structures with decreasing diffraction strength.
Spatio-temporal dynamics of global H5N1 outbreaks match bird migration patterns
Directory of Open Access Journals (Sweden)
Yali Si
2009-11-01
Full Text Available The global spread of highly pathogenic avian influenza H5N1 in poultry, wild birds and humans, poses a significant pandemic threat and a serious public health risk. An efficient surveillance and disease control system relies on the understanding of the dispersion patterns and spreading mechanisms of the virus. A space-time cluster analysis of H5N1 outbreaks was used to identify spatio-temporal patterns at a global scale and over an extended period of time. Potential mechanisms explaining the spread of the H5N1 virus, and the role of wild birds, were analyzed. Between December 2003 and December 2006, three global epidemic phases of H5N1 influenza were identified. These H5N1 outbreaks showed a clear seasonal pattern, with a high density of outbreaks in winter and early spring (i.e., October to March. In phase I and II only the East Asia Australian flyway was affected. During phase III, the H5N1 viruses started to appear in four other flyways: the Central Asian flyway, the Black Sea Mediterranean flyway, the East Atlantic flyway and the East Africa West Asian flyway. Six disease cluster patterns along these flyways were found to be associated with the seasonal migration of wild birds. The spread of the H5N1 virus, as demonstrated by the space-time clusters, was associated with the patterns of migration of wild birds. Wild birds may therefore play an important role in the spread of H5N1 over long distances. Disease clusters were also detected at sites where wild birds are known to overwinter and at times when migratory birds were present. This leads to the suggestion that wild birds may also be involved in spreading the H5N1 virus over short distances.
Fletcher, Martyn; Liang, Bojian; Smith, Leslie; Knowles, Alastair; Jackson, Tom; Jessop, Mark; Austin, Jim
2008-10-01
In the study of information flow in the nervous system, component processes can be investigated using a range of electrophysiological and imaging techniques. Although data is difficult and expensive to produce, it is rarely shared and collaboratively exploited. The Code Analysis, Repository and Modelling for e-Neuroscience (CARMEN) project addresses this challenge through the provision of a virtual neuroscience laboratory: an infrastructure for sharing data, tools and services. Central to the CARMEN concept are federated CARMEN nodes, which provide: data and metadata storage, new, thirdparty and legacy services, and tools. In this paper, we describe the CARMEN project as well as the node infrastructure and an associated thick client tool for pattern visualisation and searching, the Signal Data Explorer (SDE). We also discuss new spike detection methods, which are central to the services provided by CARMEN. The SDE is a client application which can be used to explore data in the CARMEN repository, providing data visualization, signal processing and a pattern matching capability. It performs extremely fast pattern matching and can be used to search for complex conditions composed of many different patterns across the large datasets that are typical in neuroinformatics. Searches can also be constrained by specifying text based metadata filters. Spike detection services which use wavelet and morphology techniques are discussed, and have been shown to outperform traditional thresholding and template based systems. A number of different spike detection and sorting techniques will be deployed as services within the CARMEN infrastructure, to allow users to benchmark their performance against a wide range of reference datasets.
Xie, Tao; Cho, Yong Beom; Wang, Kai; Huang, Donghui; Hong, Hye Kyung; Choi, Yoon-La; Ko, Young Hyeh; Nam, Do-Hyun; Jin, Juyoun; Yang, Heekyoung; Fernandez, Julio; Deng, Shibing; Rejto, Paul A; Lee, Woo Yong; Mao, Mao
2014-10-01
Colorectal cancer (CRC) patients have poor prognosis after formation of distant metastasis. Understanding the molecular mechanisms by which genetic changes facilitate metastasis is critical for the development of targeted therapeutic strategies aimed at controlling disease progression while minimizing toxic side effects. A comprehensive portrait of somatic alterations in CRC and the changes between primary and metastatic tumors has yet to be developed. We performed whole genome sequencing of two primary CRC tumors and their matched liver metastases. By comparing to matched germline DNA, we catalogued somatic alterations at multiple scales, including single nucleotide variations, small insertions and deletions, copy number aberrations and structural variations in both the primary and matched metastasis. We found that the majority of these somatic alterations are present in both sites. Despite the overall similarity, several de novo alterations in the metastases were predicted to be deleterious, in genes including FBXW7, DCLK1 and FAT2, which might contribute to the initiation and progression of distant metastasis. Through careful examination of the mutation prevalence among tumor cells at each site, we also proposed distinct clonal evolution patterns between primary and metastatic tumors in the two cases. These results suggest that somatic alterations may play an important role in driving the development of colorectal cancer metastasis and present challenges and opportunities when considering the choice of treatment. Copyright © 2014 Elsevier Inc. All rights reserved.
Cannavo, F.; Cannata, A.; Cassisi, C.
2017-12-01
The importance of assessing the ongoing status of active volcanoes is crucial not only for exposures to the local population but due to possible presence of tephra also for airline traffic. Adequately monitoring of active volcanoes, hence, plays a key role for civil protection purposes. In last decades, in order to properly monitor possible threats, continuous measuring networks have been designed and deployed on most of potentially hazardous volcanos. Nevertheless, at the present, volcano real-time surveillance is basically delegated to one or more human experts in volcanology, who interpret data coming from different kind of monitoring networks using their experience and non-measurable information (e.g. information from the field) to infer the volcano status. In some cases, raw data are used in some models to obtain more clues on the ongoing activity. In the last decades, with the development of volcano monitoring networks, huge amount of data of different geophysical, geochemical and volcanological types have been collected and stored in large databases. Having such big data sets with many examples of volcanic activity allows us to study volcano monitoring from a machine learning perspective. Thus, exploiting opportunities offered by the abundance of volcano monitoring time-series data we can try to address the following questions: Are the monitored parameters sufficient to discriminate the volcano status? Is it possible to infer/distinguish the volcano status only from the multivariate patterns of measurements? Are all the kind of measurements in the pattern equally useful for status assessment? How accurate would be an automatic system of status inference based only on pattern recognition of data? Here we present preliminary results of the data analysis we performed on a set of data and activity covering the period 2011-2017 at Mount Etna (Italy). In the considered period, we had 52 events of lava fountaining and long periods of Strombolian activity. We
International Nuclear Information System (INIS)
Ishitani, Kazuki; Yamane, Yoshihiro
1999-01-01
In nuclear fuel reprocessing plants, monitoring the spatial profile of neutron flux to infer subcriticality and distribution of fuel concentration using detectors such as PSPC, is very beneficial in sight of criticality safety. In this paper a method of subcriticality and fuel concentration estimation which is supposed to use under non-uniformed system is proposed. Its basic concept is the pattern matching between measured neutron flux distribution and beforehand calculated one. In any kind of subcriticality estimation, we can regard that measured neutron counts put any kind of black box, and then this black box outputs subcriticality. We proposed the use of artificial neural network or 'pattern matching' as black box which have no theoretical clear base. These method are wholly based on the calculated value as recently advancement of computer code accuracy for criticality safety. The most difference between indirect bias estimation method and our method is that our new approach target are the unknown non-uniform system. (J.P.N.)
Foland-Ross, Lara C.; Thompson, Paul M.; Sugar, Catherine A.; Madsen, Sarah K.; Shen, Jim K.; Penfold, Conor; Ahlf, Kyle; Rasser, Paul E.; Fischer, Jeffrey; Yang, Yilan; Townsend, Jennifer; Bookheimer, Susan Y.; Altshuler, Lori L.
2013-01-01
Objective Several lines of evidence implicate gray matter abnormalities in the prefrontal cortex and anterior cingulate cortex in patients with bipolar disorder. Findings however, have been largely inconsistent across studies. Differences in patients’ medication status or mood state, or the application of traditional volumetric methods that are insensitive to subtle neuroanatomic differences may have contributed to these inconsistent findings. Given this, we used magnetic resonance imaging (MRI) in conjunction with cortical pattern matching methods to assess cortical thickness abnormalities in euthymic bipolar subjects who were not treated with lithium. Method Sixty-five subjects, including 34 lithium-free euthymic subjects with bipolar (type I) disorder and 31 healthy subjects were scanned using magnetic resonance imaging (MRI). Data were processed to measure cortical gray matter thickness. Cortical pattern matching methods associated homologous brain regions across subjects. Spatially normalized thickness maps were analyzed to assess illness effects and associations with clinical variables. Results Relative to healthy subjects, euthymic bipolar I subjects had significantly thinner gray matter in bilateral prefrontal cortex (Brodmann Areas 11, 10, 8 and 44) and left anterior cingulate cortex (Brodmann Areas 24/32). Additionally, thinning in these regions was more pronounced in patients with a history of psychosis. No areas of thicker cortex were detected in bipolar subjects versus healthy subjects. Conclusions Using a technique that is highly sensitive to subtle neuroanatomic differences, significant regional cortical thinning was found in euthymic subjects with bipolar disorder. Clinical implications are discussed. PMID:21285139
Energy Technology Data Exchange (ETDEWEB)
Hoejstrup, J [NEG Micon Project Development A/S, Randers (Denmark); Hansen, K S [Denmarks Technical Univ., Dept. of Energy Engineering, Lyngby (Denmark); Pedersen, B J [VESTAS Wind Systems A/S, Lem (Denmark); Nielsen, M [Risoe National Lab., Wind Energy and Atmospheric Physics, Roskilde (Denmark)
1999-03-01
The pdf`s of atmospheric turbulence have somewhat wider tails than a Gaussian, especially regarding accelerations, whereas velocities are close to Gaussian. This behaviour is being investigated using data from a large WEB-database in order to quantify the amount of non-Gaussianity. Models for non-Gaussian turbulence have been developed, by which artificial turbulence can be generated with specified distributions, spectra and cross-correlations. The artificial time series will then be used in load models and the resulting loads in the Gaussian and the non-Gaussian cases will be compared. (au)
Improving the Pattern Reproducibility of Multiple-Point-Based Prior Models Using Frequency Matching
DEFF Research Database (Denmark)
Cordua, Knud Skou; Hansen, Thomas Mejer; Mosegaard, Klaus
2014-01-01
Some multiple-point-based sampling algorithms, such as the snesim algorithm, rely on sequential simulation. The conditional probability distributions that are used for the simulation are based on statistics of multiple-point data events obtained from a training image. During the simulation, data...... events with zero probability in the training image statistics may occur. This is handled by pruning the set of conditioning data until an event with non-zero probability is found. The resulting probability distribution sampled by such algorithms is a pruned mixture model. The pruning strategy leads...... to a probability distribution that lacks some of the information provided by the multiple-point statistics from the training image, which reduces the reproducibility of the training image patterns in the outcome realizations. When pruned mixture models are used as prior models for inverse problems, local re...
Bruder, Markus; Won, Sae-Yeon; Wagner, Marlies; Brawanski, Nina; Dinc, Nazife; Kashefiolasl, Sepide; Seifert, Volker; Konczalla, Juergen
2018-05-01
Demographic changes are leading to an aging society with a growing number of patients with cardiovascular diseases, relying on antiplatelet drugs like acetylsalicylic acid (ASA). Although antiplatelet agents are suspected to be protective not only in the cardiologic but in the neurovascular field, the alteration of the coagulating process could have a major impact on the course and outcome after rupture of intracranial aneurysms. Between June 1999 and December 2014, 1422 patients were treated for aneurysmal SAH in our institution, 144 (10.1%) with continuous ASA at the time of aneurysm rupture. A matched-pair analysis was performed. The rate of patients with continuous ASA treatment while rupture of the aneurysm is rising significantly (P bleeding pattern. Outcome was not different in the matched-pair analysis. There was no statistical difference in treatment related-complication rates of microsurgical and endovascular procedures. Therefore, ASA use should not influence treatment decision of the ruptured aneurysm. Copyright © 2018 Elsevier Inc. All rights reserved.
Fixed-pattern noise correction method based on improved moment matching for a TDI CMOS image sensor.
Xu, Jiangtao; Nie, Huafeng; Nie, Kaiming; Jin, Weimin
2017-09-01
In this paper, an improved moment matching method based on a spatial correlation filter (SCF) and bilateral filter (BF) is proposed to correct the fixed-pattern noise (FPN) of a time-delay-integration CMOS image sensor (TDI-CIS). First, the values of row FPN (RFPN) and column FPN (CFPN) are estimated and added to the original image through SCF and BF, respectively. Then the filtered image will be processed by an improved moment matching method with a moving window. Experimental results based on a 128-stage TDI-CIS show that, after correcting the FPN in the image captured under uniform illumination, the standard deviation of row mean vector (SDRMV) decreases from 5.6761 LSB to 0.1948 LSB, while the standard deviation of the column mean vector (SDCMV) decreases from 15.2005 LSB to 13.1949LSB. In addition, for different images captured by different TDI-CISs, the average decrease of SDRMV and SDCMV is 5.4922/2.0357 LSB, respectively. Comparative experimental results indicate that the proposed method can effectively correct the FPNs of different TDI-CISs while maintaining image details without any auxiliary equipment.
MCEM algorithm for the log-Gaussian Cox process
Delmas, Celine; Dubois-Peyrard, Nathalie; Sabbadin, Regis
2014-01-01
Log-Gaussian Cox processes are an important class of models for aggregated point patterns. They have been largely used in spatial epidemiology (Diggle et al., 2005), in agronomy (Bourgeois et al., 2012), in forestry (Moller et al.), in ecology (sightings of wild animals) or in environmental sciences (radioactivity counts). A log-Gaussian Cox process is a Poisson process with a stochastic intensity depending on a Gaussian random eld. We consider the case where this Gaussian random eld is ...
Jekova, Irena; Krasteva, Vessela; Schmid, Ramun
2018-01-27
Human identification (ID) is a biometric task, comparing single input sample to many stored templates to identify an individual in a reference database. This paper aims to present the perspectives of personalized heartbeat pattern for reliable ECG-based identification. The investigations are using a database with 460 pairs of 12-lead resting electrocardiograms (ECG) with 10-s durations recorded at time-instants T1 and T2 > T1 + 1 year. Intra-subject long-term ECG stability and inter-subject variability of personalized PQRST (500 ms) and QRS (100 ms) patterns is quantified via cross-correlation, amplitude ratio and pattern matching between T1 and T2 using 7 features × 12-leads. Single and multi-lead ID models are trained on the first 230 ECG pairs. Their validation on 10, 20, ... 230 reference subjects (RS) from the remaining 230 ECG pairs shows: (i) two best single-lead ID models using lead II for a small population RS = (10-140) with identification accuracy AccID = (89.4-67.2)% and aVF for a large population RS = (140-230) with AccID = (67.2-63.9)%; (ii) better performance of the 6-lead limb vs. the 6-lead chest ID model-(91.4-76.1)% vs. (90.9-70)% for RS = (10-230); (iii) best performance of the 12-lead ID model-(98.4-87.4)% for RS = (10-230). The tolerable reference database size, keeping AccID > 80%, is RS = 30 in the single-lead ID scenario (II); RS = 50 (6 chest leads); RS = 100 (6 limb leads), RS > 230-maximal population in this study (12-lead ECG).
DEFF Research Database (Denmark)
Faust, Sebastian; Hazay, Carmit; Venturi, Daniele
2013-01-01
In secure delegatable computation, computationally weak devices (or clients) wish to outsource their computation and data to an untrusted server in the cloud. While most earlier work considers the general question of how to securely outsource any computation to the cloud server, we focus...... that contain confidential data (e.g., health related data about patient history). Our constructions offer simulation-based security in the presence of semi-honest and malicious adversaries (in the random oracle model) and limit the communication in the query phase to O(m) bits plus the number of occurrences...
Boxed Permutation Pattern Matching
DEFF Research Database (Denmark)
Amit, Mika; Bille, Philip; Cording, Patrick Hagge
2016-01-01
the goal is to only find the boxed subsequences of T that are order-isomorphic to P. This problem was introduced by Bruner and Lackner who showed that it can be solved in O(n3) time. Cho et al. [CPM 2015] gave an O(n2m) time algorithm and improved it to O(n2 logm). In this paper we present a solution...
Gaussian entanglement revisited
Lami, Ludovico; Serafini, Alessio; Adesso, Gerardo
2018-02-01
We present a novel approach to the separability problem for Gaussian quantum states of bosonic continuous variable systems. We derive a simplified necessary and sufficient separability criterion for arbitrary Gaussian states of m versus n modes, which relies on convex optimisation over marginal covariance matrices on one subsystem only. We further revisit the currently known results stating the equivalence between separability and positive partial transposition (PPT) for specific classes of Gaussian states. Using techniques based on matrix analysis, such as Schur complements and matrix means, we then provide a unified treatment and compact proofs of all these results. In particular, we recover the PPT-separability equivalence for: (i) Gaussian states of 1 versus n modes; and (ii) isotropic Gaussian states. In passing, we also retrieve (iii) the recently established equivalence between separability of a Gaussian state and and its complete Gaussian extendability. Our techniques are then applied to progress beyond the state of the art. We prove that: (iv) Gaussian states that are invariant under partial transposition are necessarily separable; (v) the PPT criterion is necessary and sufficient for separability for Gaussian states of m versus n modes that are symmetric under the exchange of any two modes belonging to one of the parties; and (vi) Gaussian states which remain PPT under passive optical operations can not be entangled by them either. This is not a foregone conclusion per se (since Gaussian bound entangled states do exist) and settles a question that had been left unanswered in the existing literature on the subject. This paper, enjoyable by both the quantum optics and the matrix analysis communities, overall delivers technical and conceptual advances which are likely to be useful for further applications in continuous variable quantum information theory, beyond the separability problem.
Golan, Ofer; Gordon, Ilanit; Fichman, Keren; Keinan, Giora
2018-01-01
Children with ASD show emotion recognition difficulties, as part of their social communication deficits. We examined facial emotion recognition (FER) in intellectually disabled children with ASD and in younger typically developing (TD) controls, matched on mental age. Our emotion-matching paradigm employed three different modalities: facial, vocal…
CSIR Research Space (South Africa)
Roux, FS
2009-01-01
Full Text Available , t0)} = P(du, dv) {FR{g(u, v, t0)}} Replacement: u→ du = t− t0 i2 ∂ ∂u′ v → dv = t− t0 i2 ∂ ∂v′ CSIR National Laser Centre – p.13/30 Differentiation i.s.o integration Evaluate the integral over the Gaussian beam (once and for all). Then, instead... . Gaussian beams with vortex dipoles CSIR National Laser Centre – p.2/30 Gaussian beam notation Gaussian beam in normalised coordinates: g(u, v, t) = exp ( −u 2 + v2 1− it ) u = xω0 v = yω0 t = zρ ρ = piω20 λ ω0 — 1/e2 beam waist radius; ρ— Rayleigh range ω ω...
Gaussian operations and privacy
International Nuclear Information System (INIS)
Navascues, Miguel; Acin, Antonio
2005-01-01
We consider the possibilities offered by Gaussian states and operations for two honest parties, Alice and Bob, to obtain privacy against a third eavesdropping party, Eve. We first extend the security analysis of the protocol proposed in [Navascues et al. Phys. Rev. Lett. 94, 010502 (2005)]. Then, we prove that a generalized version of this protocol does not allow one to distill a secret key out of bound entangled Gaussian states
Nonclassicality by Local Gaussian Unitary Operations for Gaussian States
Directory of Open Access Journals (Sweden)
Yangyang Wang
2018-04-01
Full Text Available A measure of nonclassicality N in terms of local Gaussian unitary operations for bipartite Gaussian states is introduced. N is a faithful quantum correlation measure for Gaussian states as product states have no such correlation and every non product Gaussian state contains it. For any bipartite Gaussian state ρ A B , we always have 0 ≤ N ( ρ A B < 1 , where the upper bound 1 is sharp. An explicit formula of N for ( 1 + 1 -mode Gaussian states and an estimate of N for ( n + m -mode Gaussian states are presented. A criterion of entanglement is established in terms of this correlation. The quantum correlation N is also compared with entanglement, Gaussian discord and Gaussian geometric discord.
Generalized Gaussian Error Calculus
Grabe, Michael
2010-01-01
For the first time in 200 years Generalized Gaussian Error Calculus addresses a rigorous, complete and self-consistent revision of the Gaussian error calculus. Since experimentalists realized that measurements in general are burdened by unknown systematic errors, the classical, widespread used evaluation procedures scrutinizing the consequences of random errors alone turned out to be obsolete. As a matter of course, the error calculus to-be, treating random and unknown systematic errors side by side, should ensure the consistency and traceability of physical units, physical constants and physical quantities at large. The generalized Gaussian error calculus considers unknown systematic errors to spawn biased estimators. Beyond, random errors are asked to conform to the idea of what the author calls well-defined measuring conditions. The approach features the properties of a building kit: any overall uncertainty turns out to be the sum of a contribution due to random errors, to be taken from a confidence inter...
Learning conditional Gaussian networks
DEFF Research Database (Denmark)
Bøttcher, Susanne Gammelgaard
This paper considers conditional Gaussian networks. The parameters in the network are learned by using conjugate Bayesian analysis. As conjugate local priors, we apply the Dirichlet distribution for discrete variables and the Gaussian-inverse gamma distribution for continuous variables, given...... a configuration of the discrete parents. We assume parameter independence and complete data. Further, to learn the structure of the network, the network score is deduced. We then develop a local master prior procedure, for deriving parameter priors in these networks. This procedure satisfies parameter...... independence, parameter modularity and likelihood equivalence. Bayes factors to be used in model search are introduced. Finally the methods derived are illustrated by a simple example....
Plummer, MD
1986-01-01
This study of matching theory deals with bipartite matching, network flows, and presents fundamental results for the non-bipartite case. It goes on to study elementary bipartite graphs and elementary graphs in general. Further discussed are 2-matchings, general matching problems as linear programs, the Edmonds Matching Algorithm (and other algorithmic approaches), f-factors and vertex packing.
AUTONOMOUS GAUSSIAN DECOMPOSITION
Energy Technology Data Exchange (ETDEWEB)
Lindner, Robert R.; Vera-Ciro, Carlos; Murray, Claire E.; Stanimirović, Snežana; Babler, Brian [Department of Astronomy, University of Wisconsin, 475 North Charter Street, Madison, WI 53706 (United States); Heiles, Carl [Radio Astronomy Lab, UC Berkeley, 601 Campbell Hall, Berkeley, CA 94720 (United States); Hennebelle, Patrick [Laboratoire AIM, Paris-Saclay, CEA/IRFU/SAp-CNRS-Université Paris Diderot, F-91191 Gif-sur Yvette Cedex (France); Goss, W. M. [National Radio Astronomy Observatory, P.O. Box O, 1003 Lopezville, Socorro, NM 87801 (United States); Dickey, John, E-mail: rlindner@astro.wisc.edu [University of Tasmania, School of Maths and Physics, Private Bag 37, Hobart, TAS 7001 (Australia)
2015-04-15
We present a new algorithm, named Autonomous Gaussian Decomposition (AGD), for automatically decomposing spectra into Gaussian components. AGD uses derivative spectroscopy and machine learning to provide optimized guesses for the number of Gaussian components in the data, and also their locations, widths, and amplitudes. We test AGD and find that it produces results comparable to human-derived solutions on 21 cm absorption spectra from the 21 cm SPectral line Observations of Neutral Gas with the EVLA (21-SPONGE) survey. We use AGD with Monte Carlo methods to derive the H i line completeness as a function of peak optical depth and velocity width for the 21-SPONGE data, and also show that the results of AGD are stable against varying observational noise intensity. The autonomy and computational efficiency of the method over traditional manual Gaussian fits allow for truly unbiased comparisons between observations and simulations, and for the ability to scale up and interpret the very large data volumes from the upcoming Square Kilometer Array and pathfinder telescopes.
Bounded Gaussian process regression
DEFF Research Database (Denmark)
Jensen, Bjørn Sand; Nielsen, Jens Brehm; Larsen, Jan
2013-01-01
We extend the Gaussian process (GP) framework for bounded regression by introducing two bounded likelihood functions that model the noise on the dependent variable explicitly. This is fundamentally different from the implicit noise assumption in the previously suggested warped GP framework. We...... with the proposed explicit noise-model extension....
AUTONOMOUS GAUSSIAN DECOMPOSITION
International Nuclear Information System (INIS)
Lindner, Robert R.; Vera-Ciro, Carlos; Murray, Claire E.; Stanimirović, Snežana; Babler, Brian; Heiles, Carl; Hennebelle, Patrick; Goss, W. M.; Dickey, John
2015-01-01
We present a new algorithm, named Autonomous Gaussian Decomposition (AGD), for automatically decomposing spectra into Gaussian components. AGD uses derivative spectroscopy and machine learning to provide optimized guesses for the number of Gaussian components in the data, and also their locations, widths, and amplitudes. We test AGD and find that it produces results comparable to human-derived solutions on 21 cm absorption spectra from the 21 cm SPectral line Observations of Neutral Gas with the EVLA (21-SPONGE) survey. We use AGD with Monte Carlo methods to derive the H i line completeness as a function of peak optical depth and velocity width for the 21-SPONGE data, and also show that the results of AGD are stable against varying observational noise intensity. The autonomy and computational efficiency of the method over traditional manual Gaussian fits allow for truly unbiased comparisons between observations and simulations, and for the ability to scale up and interpret the very large data volumes from the upcoming Square Kilometer Array and pathfinder telescopes
Dave, Jayna M; Cullen, Karen W
2018-02-20
To assess the agreement of posted menus with foods served to 3- to 5-year-old children attending federal Child and Adult Care Food Program (CACFP)-enrolled facilities, and the degree to which the facilities met the new meal patterns and best practices. On-site observations and menu coding. Nine early care and education centers. Agreement of posted menus with foods served, and comparison of foods served and consumed with the new CACFP meal guidelines and best practices. Data were compiled for each meal (breakfast, lunch, and snacks). Frequencies and percentages of agreement with the posted menu (coded matches, substitutions, additions, and omissions) were calculated for each food component in the CACFP menu guidelines. Menu total match was created by summing the menu match plus acceptable substitutions. Menus were compared with the new CACFP meal guidelines and best practices. The match between the posted menus and foods actually served to children at breakfast, lunch, and snack was high when the acceptable menu substitutions were considered (approximately 94% to 100% total match). Comparing the menus with the new meal guidelines and best practices, the 1 guideline that was fully implemented was serving only unflavored, low-fat, or 1% milk; fruit and vegetable guidelines were partially met; fruit juice was not served often, nor were legumes; the guideline for 1 whole grain-rich serving/d was not met; and regular beef and full-fat cheese products were commonly served. Early care and education centers enrolled in CACFP provided meals that met the current CACFP guidelines. Some menu improvements are needed for the centers to meet the new guidelines and best practices. Copyright © 2018 Society for Nutrition Education and Behavior. Published by Elsevier Inc. All rights reserved.
DEFF Research Database (Denmark)
Bañas, Andrew Rafael; Aabo, Thomas; Palima, Darwin
2013-01-01
as a combination of Generalized Phase Contrast and phase-only correlation. Such an analysis makes it convenient to optimize an mGPC system for different setup conditions. Results showing binary-only phase generation of dynamic spot arrays and line patterns are presented. © 201 Optical Society of America...
Quantum information with Gaussian states
International Nuclear Information System (INIS)
Wang Xiangbin; Hiroshima, Tohya; Tomita, Akihisa; Hayashi, Masahito
2007-01-01
Quantum optical Gaussian states are a type of important robust quantum states which are manipulatable by the existing technologies. So far, most of the important quantum information experiments are done with such states, including bright Gaussian light and weak Gaussian light. Extending the existing results of quantum information with discrete quantum states to the case of continuous variable quantum states is an interesting theoretical job. The quantum Gaussian states play a central role in such a case. We review the properties and applications of Gaussian states in quantum information with emphasis on the fundamental concepts, the calculation techniques and the effects of imperfections of the real-life experimental setups. Topics here include the elementary properties of Gaussian states and relevant quantum information device, entanglement-based quantum tasks such as quantum teleportation, quantum cryptography with weak and strong Gaussian states and the quantum channel capacity, mathematical theory of quantum entanglement and state estimation for Gaussian states
Toward the detection of gravitational waves under non-Gaussian noises I. Locally optimal statistic.
Yokoyama, Jun'ichi
2014-01-01
After reviewing the standard hypothesis test and the matched filter technique to identify gravitational waves under Gaussian noises, we introduce two methods to deal with non-Gaussian stationary noises. We formulate the likelihood ratio function under weakly non-Gaussian noises through the Edgeworth expansion and strongly non-Gaussian noises in terms of a new method we call Gaussian mapping where the observed marginal distribution and the two-body correlation function are fully taken into account. We then apply these two approaches to Student's t-distribution which has a larger tails than Gaussian. It is shown that while both methods work well in the case the non-Gaussianity is small, only the latter method works well for highly non-Gaussian case.
Gaussian discriminating strength
Rigovacca, L.; Farace, A.; De Pasquale, A.; Giovannetti, V.
2015-10-01
We present a quantifier of nonclassical correlations for bipartite, multimode Gaussian states. It is derived from the Discriminating Strength measure, introduced for finite dimensional systems in Farace et al., [New J. Phys. 16, 073010 (2014), 10.1088/1367-2630/16/7/073010]. As the latter the new measure exploits the quantum Chernoff bound to gauge the susceptibility of the composite system with respect to local perturbations induced by unitary gates extracted from a suitable set of allowed transformations (the latter being identified by posing some general requirements). Closed expressions are provided for the case of two-mode Gaussian states obtained by squeezing or by linearly mixing via a beam splitter a factorized two-mode thermal state. For these density matrices, we study how nonclassical correlations are related with the entanglement present in the system and with its total photon number.
Chen, Cunjian; Ross, Arun
2013-05-01
Researchers in face recognition have been using Gabor filters for image representation due to their robustness to complex variations in expression and illumination. Numerous methods have been proposed to model the output of filter responses by employing either local or global descriptors. In this work, we propose a novel but simple approach for encoding Gradient information on Gabor-transformed images to represent the face, which can be used for identity, gender and ethnicity assessment. Extensive experiments on the standard face benchmark FERET (Visible versus Visible), as well as the heterogeneous face dataset HFB (Near-infrared versus Visible), suggest that the matching performance due to the proposed descriptor is comparable against state-of-the-art descriptor-based approaches in face recognition applications. Furthermore, the same feature set is used in the framework of a Collaborative Representation Classification (CRC) scheme for deducing soft biometric traits such as gender and ethnicity from face images in the AR, Morph and CAS-PEAL databases.
Grötzinger, Stefan W.; Alam, Intikhab; Ba Alawi, Wail; Bajic, Vladimir B.; Stingl, Ulrich; Eppinger, Jörg
2014-01-01
Reliable functional annotation of genomic data is the key-step in the discovery of novel enzymes. Intrinsic sequencing data quality problems of single amplified genomes (SAGs) and poor homology of novel extremophile's genomes pose significant challenges for the attribution of functions to the coding sequences identified. The anoxic deep-sea brine pools of the Red Sea are a promising source of novel enzymes with unique evolutionary adaptation. Sequencing data from Red Sea brine pool cultures and SAGs are annotated and stored in the Integrated Data Warehouse of Microbial Genomes (INDIGO) data warehouse. Low sequence homology of annotated genes (no similarity for 35% of these genes) may translate into false positives when searching for specific functions. The Profile and Pattern Matching (PPM) strategy described here was developed to eliminate false positive annotations of enzyme function before progressing to labor-intensive hyper-saline gene expression and characterization. It utilizes InterPro-derived Gene Ontology (GO)-terms (which represent enzyme function profiles) and annotated relevant PROSITE IDs (which are linked to an amino acid consensus pattern). The PPM algorithm was tested on 15 protein families, which were selected based on scientific and commercial potential. An initial list of 2577 enzyme commission (E.C.) numbers was translated into 171 GO-terms and 49 consensus patterns. A subset of INDIGO-sequences consisting of 58 SAGs from six different taxons of bacteria and archaea were selected from six different brine pool environments. Those SAGs code for 74,516 genes, which were independently scanned for the GO-terms (profile filter) and PROSITE IDs (pattern filter). Following stringent reliability filtering, the non-redundant hits (106 profile hits and 147 pattern hits) are classified as reliable, if at least two relevant descriptors (GO-terms and/or consensus patterns) are present. Scripts for annotation, as well as for the PPM algorithm, are available
Directory of Open Access Journals (Sweden)
Stefan Wolfgang Grötzinger
2014-04-01
Full Text Available Reliable functional annotation of genomic data is the key-step in the discovery of novel enzymes. Intrinsic sequencing data quality problems of single amplified genomes (SAGs and poor homology of novel extremophile’s genomes pose significant challenges for the attribution of functions to the coding sequences identified. The anoxic deep-sea brine pools of the Red Sea are a promising source of novel enzymes with unique evolutionary adaptation. Sequencing data from Red Sea brine pool cultures and SAGs are annotated and stored in the INDIGO data warehouse. Low sequence homology of annotated genes (no similarity for 35% of these genes may translate into false positives when searching for specific functions. The Profile & Pattern Matching (PPM strategy described here was developed to eliminate false positive annotations of enzyme function before progressing to labor-intensive hyper-saline gene expression and characterization. It utilizes InterPro-derived Gene Ontology (GO-terms (which represent enzyme function profiles and annotated relevant PROSITE IDs (which are linked to an amino acid consensus pattern. The PPM algorithm was tested on 15 protein families, which were selected based on scientific and commercial potential. An initial list of 2,577 E.C. numbers was translated into 171 GO-terms and 49 consensus patterns. A subset of INDIGO-sequences consisting of 58 SAGs from six different taxons of bacteria and archaea were selected from 6 different brine pool environments. Those SAGs code for 74,516 genes, which were independently scanned for the GO-terms (profile filter and PROSITE IDs (pattern filter. Following stringent reliability filtering, the non-redundant hits (106 profile hits and 147 pattern hits are classified as reliable, if at least two relevant descriptors (GO-terms and/or consensus patterns are present. Scripts for annotation, as well as for the PPM algorithm, are available through the INDIGO website.
Grötzinger, Stefan W.
2014-04-07
Reliable functional annotation of genomic data is the key-step in the discovery of novel enzymes. Intrinsic sequencing data quality problems of single amplified genomes (SAGs) and poor homology of novel extremophile\\'s genomes pose significant challenges for the attribution of functions to the coding sequences identified. The anoxic deep-sea brine pools of the Red Sea are a promising source of novel enzymes with unique evolutionary adaptation. Sequencing data from Red Sea brine pool cultures and SAGs are annotated and stored in the Integrated Data Warehouse of Microbial Genomes (INDIGO) data warehouse. Low sequence homology of annotated genes (no similarity for 35% of these genes) may translate into false positives when searching for specific functions. The Profile and Pattern Matching (PPM) strategy described here was developed to eliminate false positive annotations of enzyme function before progressing to labor-intensive hyper-saline gene expression and characterization. It utilizes InterPro-derived Gene Ontology (GO)-terms (which represent enzyme function profiles) and annotated relevant PROSITE IDs (which are linked to an amino acid consensus pattern). The PPM algorithm was tested on 15 protein families, which were selected based on scientific and commercial potential. An initial list of 2577 enzyme commission (E.C.) numbers was translated into 171 GO-terms and 49 consensus patterns. A subset of INDIGO-sequences consisting of 58 SAGs from six different taxons of bacteria and archaea were selected from six different brine pool environments. Those SAGs code for 74,516 genes, which were independently scanned for the GO-terms (profile filter) and PROSITE IDs (pattern filter). Following stringent reliability filtering, the non-redundant hits (106 profile hits and 147 pattern hits) are classified as reliable, if at least two relevant descriptors (GO-terms and/or consensus patterns) are present. Scripts for annotation, as well as for the PPM algorithm, are available
Imaoka, Hiroshi; Shimizu, Yasuhiro; Mizuno, Nobumasa; Hara, Kazuo; Hijioka, Susumu; Tajika, Masahiro; Tanaka, Tsutomu; Ishihara, Makoto; Ogura, Takeshi; Obayashi, Tomohiko; Shinagawa, Akihide; Sakaguchi, Masafumi; Yamaura, Hidekazu; Kato, Mina; Niwa, Yasumasa; Yamao, Kenji
2014-01-01
Adenosquamous carcinoma of the pancreas (ASC) is a rare malignant neoplasm of the pancreas, exhibiting both glandular and squamous differentiation. However, little is known about its imaging features. This study examined the imaging features of pancreatic ASC. We evaluated images of contrast-enhanced computed tomography (CT) and endoscopic ultrasonography (EUS). As controls, solid pancreatic neoplasms matched in a 2:1 ratio to ASC cases for age, sex and tumor location were also evaluated. Twenty-three ASC cases were examined, and 46 solid pancreatic neoplasms (43 pancreatic ductal adenocarcinomas, two pancreatic neuroendocrine tumors and one acinar cell carcinoma) were matched as controls. Univariate analysis demonstrated significant differences in the outline and vascularity of tumors on contrast-enhanced CT in the ASC and control groups (P outline, cystic changes, and the ring-enhancement pattern on contrast-enhanced CT were seen to have significant predictive powers by stepwise forward logistic regression analysis (P = 0.044, P = 0.010, and P = 0.001, respectively). Of the three, the ring-enhancement pattern was the most useful, and its predictive diagnostic sensitivity, specificity, positive predictive value and negative predictive value for diagnosis of ASC were 65.2%, 89.6%, 75.0% and 84.3%, respectively. These results demonstrate that presence of the ring-enhancement pattern on contrast-enhanced CT is the most useful predictive factor for ASC. Copyright © 2014 IAP and EPC. Published by Elsevier B.V. All rights reserved.
Interconversion of pure Gaussian states requiring non-Gaussian operations
Jabbour, Michael G.; García-Patrón, Raúl; Cerf, Nicolas J.
2015-01-01
We analyze the conditions under which local operations and classical communication enable entanglement transformations between bipartite pure Gaussian states. A set of necessary and sufficient conditions had been found [G. Giedke et al., Quant. Inf. Comput. 3, 211 (2003)] for the interconversion between such states that is restricted to Gaussian local operations and classical communication. Here, we exploit majorization theory in order to derive more general (sufficient) conditions for the interconversion between bipartite pure Gaussian states that goes beyond Gaussian local operations. While our technique is applicable to an arbitrary number of modes for each party, it allows us to exhibit surprisingly simple examples of 2 ×2 Gaussian states that necessarily require non-Gaussian local operations to be transformed into each other.
Yurinsky, Vadim Vladimirovich
1995-01-01
Surveys the methods currently applied to study sums of infinite-dimensional independent random vectors in situations where their distributions resemble Gaussian laws. Covers probabilities of large deviations, Chebyshev-type inequalities for seminorms of sums, a method of constructing Edgeworth-type expansions, estimates of characteristic functions for random vectors obtained by smooth mappings of infinite-dimensional sums to Euclidean spaces. A self-contained exposition of the modern research apparatus around CLT, the book is accessible to new graduate students, and can be a useful reference for researchers and teachers of the subject.
Log Gaussian Cox processes on the sphere
DEFF Research Database (Denmark)
Pacheco, Francisco Andrés Cuevas; Møller, Jesper
We define and study the existence of log Gaussian Cox processes (LGCPs) for the description of inhomogeneous and aggregated/clustered point patterns on the d-dimensional sphere, with d = 2 of primary interest. Useful theoretical properties of LGCPs are studied and applied for the description of sky...... positions of galaxies, in comparison with previous analysis using a Thomas process. We focus on simple estimation procedures and model checking based on functional summary statistics and the global envelope test....
Rotating quantum Gaussian packets
International Nuclear Information System (INIS)
Dodonov, V V
2015-01-01
We study two-dimensional quantum Gaussian packets with a fixed value of mean angular momentum. This value is the sum of two independent parts: the ‘external’ momentum related to the motion of the packet center and the ‘internal’ momentum due to quantum fluctuations. The packets minimizing the mean energy of an isotropic oscillator with the fixed mean angular momentum are found. They exist for ‘co-rotating’ external and internal motions, and they have nonzero correlation coefficients between coordinates and momenta, together with some (moderate) amount of quadrature squeezing. Variances of angular momentum and energy are calculated, too. Differences in the behavior of ‘co-rotating’ and ‘anti-rotating’ packets are shown. The time evolution of rotating Gaussian packets is analyzed, including the cases of a charge in a homogeneous magnetic field and a free particle. In the latter case, the effect of initial shrinking of packets with big enough coordinate-momentum correlation coefficients (followed by the well known expansion) is discovered. This happens due to a competition of ‘focusing’ and ‘de-focusing’ in the orthogonal directions. (paper)
International Nuclear Information System (INIS)
McFadden, Paul; Skenderis, Kostas
2011-01-01
We investigate the non-Gaussianity of primordial cosmological perturbations within our recently proposed holographic description of inflationary universes. We derive a holographic formula that determines the bispectrum of cosmological curvature perturbations in terms of correlation functions of a holographically dual three-dimensional non-gravitational quantum field theory (QFT). This allows us to compute the primordial bispectrum for a universe which started in a non-geometric holographic phase, using perturbative QFT calculations. Strikingly, for a class of models specified by a three-dimensional super-renormalisable QFT, the primordial bispectrum is of exactly the factorisable equilateral form with f NL equil. = 5/36, irrespective of the details of the dual QFT. A by-product of this investigation is a holographic formula for the three-point function of the trace of the stress-energy tensor along general holographic RG flows, which should have applications outside the remit of this work
Palm distributions for log Gaussian Cox processes
DEFF Research Database (Denmark)
Coeurjolly, Jean-Francois; Møller, Jesper; Waagepetersen, Rasmus Plenge
2017-01-01
This paper establishes a remarkable result regarding Palm distributions for a log Gaussian Cox process: the reduced Palm distribution for a log Gaussian Cox process is itself a log Gaussian Cox process that only differs from the original log Gaussian Cox process in the intensity function. This new...... result is used to study functional summaries for log Gaussian Cox processes....
Topics in combinatorial pattern matching
DEFF Research Database (Denmark)
Vildhøj, Hjalte Wedel
Problem. Given m documents of total length n, we consider the problem of finding a longest string common to at least d ≥ 2 of the documents. This problem is known as the longest common substring (LCS) problem and has a classic O(n) space and O(n) time solution (Weiner [FOCS’73], Hui [CPM’92]). However...
Geometry of Gaussian quantum states
International Nuclear Information System (INIS)
Link, Valentin; Strunz, Walter T
2015-01-01
We study the Hilbert–Schmidt measure on the manifold of mixed Gaussian states in multi-mode continuous variable quantum systems. An analytical expression for the Hilbert–Schmidt volume element is derived. Its corresponding probability measure can be used to study typical properties of Gaussian states. It turns out that although the manifold of Gaussian states is unbounded, an ensemble of Gaussian states distributed according to this measure still has a normalizable distribution of symplectic eigenvalues, from which unitarily invariant properties can be obtained. By contrast, we find that for an ensemble of one-mode Gaussian states based on the Bures measure the corresponding distribution cannot be normalized. As important applications, we determine the distribution and the mean value of von Neumann entropy and purity for the Hilbert–Schmidt measure. (paper)
On the Shaker Simulation of Wind-Induced Non-Gaussian Random Vibration
Directory of Open Access Journals (Sweden)
Fei Xu
2016-01-01
Full Text Available Gaussian signal is produced by ordinary random vibration controllers to test the products in the laboratory, while the field data is usually non-Gaussian. Two methodologies are presented in this paper for shaker simulation of wind-induced non-Gaussian vibration. The first methodology synthesizes the non-Gaussian signal offline and replicates it on the shaker in the Time Waveform Replication (TWR mode. A new synthesis method is used to model the non-Gaussian signal as a Gaussian signal multiplied by an amplitude modulation function (AMF. A case study is presented to show that the synthesized non-Gaussian signal has the same power spectral density (PSD, probability density function (PDF, and loading cycle distribution (LCD as the field data. The second methodology derives a damage equivalent Gaussian signal from the non-Gaussian signal based on the fatigue damage spectrum (FDS and the extreme response spectrum (ERS and reproduces it on the shaker in the closed-loop frequency domain control mode. The PSD level and the duration time of the derived Gaussian signal can be manipulated for accelerated testing purpose. A case study is presented to show that the derived PSD matches the damage potential of the non-Gaussian environment for both fatigue and peak response.
Resource theory of non-Gaussian operations
Zhuang, Quntao; Shor, Peter W.; Shapiro, Jeffrey H.
2018-05-01
Non-Gaussian states and operations are crucial for various continuous-variable quantum information processing tasks. To quantitatively understand non-Gaussianity beyond states, we establish a resource theory for non-Gaussian operations. In our framework, we consider Gaussian operations as free operations, and non-Gaussian operations as resources. We define entanglement-assisted non-Gaussianity generating power and show that it is a monotone that is nonincreasing under the set of free superoperations, i.e., concatenation and tensoring with Gaussian channels. For conditional unitary maps, this monotone can be analytically calculated. As examples, we show that the non-Gaussianity of ideal photon-number subtraction and photon-number addition equal the non-Gaussianity of the single-photon Fock state. Based on our non-Gaussianity monotone, we divide non-Gaussian operations into two classes: (i) the finite non-Gaussianity class, e.g., photon-number subtraction, photon-number addition, and all Gaussian-dilatable non-Gaussian channels; and (ii) the diverging non-Gaussianity class, e.g., the binary phase-shift channel and the Kerr nonlinearity. This classification also implies that not all non-Gaussian channels are exactly Gaussian dilatable. Our resource theory enables a quantitative characterization and a first classification of non-Gaussian operations, paving the way towards the full understanding of non-Gaussianity.
Sparse reconstruction using distribution agnostic bayesian matching pursuit
Masood, Mudassir; Al-Naffouri, Tareq Y.
2013-01-01
A fast matching pursuit method using a Bayesian approach is introduced for sparse signal recovery. This method performs Bayesian estimates of sparse signals even when the signal prior is non-Gaussian or unknown. It is agnostic on signal statistics
Handbook of Gaussian basis sets
International Nuclear Information System (INIS)
Poirier, R.; Kari, R.; Csizmadia, I.G.
1985-01-01
A collection of a large body of information is presented useful for chemists involved in molecular Gaussian computations. Every effort has been made by the authors to collect all available data for cartesian Gaussian as found in the literature up to July of 1984. The data in this text includes a large collection of polarization function exponents but in this case the collection is not complete. Exponents for Slater type orbitals (STO) were included for completeness. This text offers a collection of Gaussian exponents primarily without criticism. (Auth.)
Lueck, Jennifer A
2017-07-01
Although disproportionally affected by depression, most depressed college students do not seek the help they need. Research has recently uncovered the potential negative effects of depression help-seeking messages if depressed cognition is not considered in the health message design process. It is unclear if depression determines whether and how individuals pay attention to gain- and loss-framed depression help-seeking messages-a mechanism that has significant implications for the strategic planning of health communication interventions. In order to enable the effective matching of message design and audience features, this study investigated attention patterns for gain (n = 75)- and loss (n = 78)-framed depression help-seeking messages using eye-tracking technology and self-report measures. The results confirmed that depression is a characteristic of risk avoidance and negative cognition. Depressed participants tended to pay more attention to disease information that was placed in a loss-framed rather than a gain-framed depression help-seeking message. Using negative message framing strategies for health messages seeking to educate about depression symptoms might therefore be a useful persuasive strategy-particularly when disseminated to vulnerable populations affected by depression. Furthermore, the present study emphasizes the effective use of eye-tracking technology in communication research.
... to know FAQ Living donation What is living donation? Organs Types Being a living donor First steps Being ... brochures What Every Patient Needs to Know Living Donation Multiple Listing Visit UNOS Store Learn more How organs are matched How to become a living donor ...
International Nuclear Information System (INIS)
Lian-Huang, Li; Fu-Yuan, Guo
2009-01-01
This paper analyzes the characteristic of matching efficiency between the fundamental mode of two kinds of optical waveguides and its Gaussian approximate field. Then, it presents a new method where the mode-field half-width of Gaussian approximation for the fundamental mode should be defined according to the maximal matching efficiency method. The relationship between the mode-field half-width of the Gaussian approximate field obtained from the maximal matching efficiency and normalized frequency is studied; furthermore, two formulas of mode-field half-widths as a function of normalized frequency are proposed
Overlay Spectrum Sharing using Improper Gaussian Signaling
Amin, Osama
2016-11-30
Improper Gaussian signaling (IGS) scheme has been recently shown to provide performance improvements in interference limited networks as opposed to the conventional proper Gaussian signaling (PGS) scheme. In this paper, we implement the IGS scheme in overlay cognitive radio system, where the secondary transmitter broadcasts a mixture of two different signals. The first signal is selected from the PGS scheme to match the primary message transmission. On the other hand, the second signal is chosen to be from the IGS scheme in order to reduce the interference effect on the primary receiver. We then optimally design the overlay cognitive radio to maximize the secondary link achievable rate while satisfying the primary network quality of service requirements. In particular, we consider full and partial channel knowledge scenarios and derive the feasibility conditions of operating the overlay cognitive radio systems. Moreover, we derive the superiority conditions of the IGS schemes over the PGS schemes supported with closed form expressions for the corresponding power distribution and the circularity coefficient and parameters. Simulation results are provided to support our theoretical derivations.
Information geometry of Gaussian channels
International Nuclear Information System (INIS)
Monras, Alex; Illuminati, Fabrizio
2010-01-01
We define a local Riemannian metric tensor in the manifold of Gaussian channels and the distance that it induces. We adopt an information-geometric approach and define a metric derived from the Bures-Fisher metric for quantum states. The resulting metric inherits several desirable properties from the Bures-Fisher metric and is operationally motivated by distinguishability considerations: It serves as an upper bound to the attainable quantum Fisher information for the channel parameters using Gaussian states, under generic constraints on the physically available resources. Our approach naturally includes the use of entangled Gaussian probe states. We prove that the metric enjoys some desirable properties like stability and covariance. As a by-product, we also obtain some general results in Gaussian channel estimation that are the continuous-variable analogs of previously known results in finite dimensions. We prove that optimal probe states are always pure and bounded in the number of ancillary modes, even in the presence of constraints on the reduced state input in the channel. This has experimental and computational implications. It limits the complexity of optimal experimental setups for channel estimation and reduces the computational requirements for the evaluation of the metric: Indeed, we construct a converging algorithm for its computation. We provide explicit formulas for computing the multiparametric quantum Fisher information for dissipative channels probed with arbitrary Gaussian states and provide the optimal observables for the estimation of the channel parameters (e.g., bath couplings, squeezing, and temperature).
Gaussian entanglement distribution via satellite
Hosseinidehaj, Nedasadat; Malaney, Robert
2015-02-01
In this work we analyze three quantum communication schemes for the generation of Gaussian entanglement between two ground stations. Communication occurs via a satellite over two independent atmospheric fading channels dominated by turbulence-induced beam wander. In our first scheme, the engineering complexity remains largely on the ground transceivers, with the satellite acting simply as a reflector. Although the channel state information of the two atmospheric channels remains unknown in this scheme, the Gaussian entanglement generation between the ground stations can still be determined. On the ground, distillation and Gaussification procedures can be applied, leading to a refined Gaussian entanglement generation rate between the ground stations. We compare the rates produced by this first scheme with two competing schemes in which quantum complexity is added to the satellite, thereby illustrating the tradeoff between space-based engineering complexity and the rate of ground-station entanglement generation.
Tachyon mediated non-Gaussianity
International Nuclear Information System (INIS)
Dutta, Bhaskar; Leblond, Louis; Kumar, Jason
2008-01-01
We describe a general scenario where primordial non-Gaussian curvature perturbations are generated in models with extra scalar fields. The extra scalars communicate to the inflaton sector mainly through the tachyonic (waterfall) field condensing at the end of hybrid inflation. These models can yield significant non-Gaussianity of the local shape, and both signs of the bispectrum can be obtained. These models have cosmic strings and a nearly flat power spectrum, which together have been recently shown to be a good fit to WMAP data. We illustrate with a model of inflation inspired from intersecting brane models.
Chabdarov, Shamil M.; Nadeev, Adel F.; Chickrin, Dmitry E.; Faizullin, Rashid R.
2011-04-01
In this paper we discuss unconventional detection technique also known as «full resolution receiver». This receiver uses Gaussian probability mixtures for interference structure adaptation. Full resolution receiver is alternative to conventional matched filter receivers in the case of non-Gaussian interferences. For the DS-CDMA forward channel with presence of complex interferences sufficient performance increasing was shown.
The Multivariate Gaussian Probability Distribution
DEFF Research Database (Denmark)
Ahrendt, Peter
2005-01-01
This technical report intends to gather information about the multivariate gaussian distribution, that was previously not (at least to my knowledge) to be found in one place and written as a reference manual. Additionally, some useful tips and tricks are collected that may be useful in practical ...
On Gaussian conditional independence structures
Czech Academy of Sciences Publication Activity Database
Lněnička, Radim; Matúš, František
2007-01-01
Roč. 43, č. 3 (2007), s. 327-342 ISSN 0023-5954 R&D Projects: GA AV ČR IAA100750603 Institutional research plan: CEZ:AV0Z10750506 Keywords : multivariate Gaussian distribution * positive definite matrices * determinants * gaussoids * covariance selection models * Markov perfectness Subject RIV: BA - General Mathematics Impact factor: 0.552, year: 2007
Gaussian processes for machine learning.
Seeger, Matthias
2004-04-01
Gaussian processes (GPs) are natural generalisations of multivariate Gaussian random variables to infinite (countably or continuous) index sets. GPs have been applied in a large number of fields to a diverse range of ends, and very many deep theoretical analyses of various properties are available. This paper gives an introduction to Gaussian processes on a fairly elementary level with special emphasis on characteristics relevant in machine learning. It draws explicit connections to branches such as spline smoothing models and support vector machines in which similar ideas have been investigated. Gaussian process models are routinely used to solve hard machine learning problems. They are attractive because of their flexible non-parametric nature and computational simplicity. Treated within a Bayesian framework, very powerful statistical methods can be implemented which offer valid estimates of uncertainties in our predictions and generic model selection procedures cast as nonlinear optimization problems. Their main drawback of heavy computational scaling has recently been alleviated by the introduction of generic sparse approximations.13,78,31 The mathematical literature on GPs is large and often uses deep concepts which are not required to fully understand most machine learning applications. In this tutorial paper, we aim to present characteristics of GPs relevant to machine learning and to show up precise connections to other "kernel machines" popular in the community. Our focus is on a simple presentation, but references to more detailed sources are provided.
Wen, Xian-Huan; Gómez-Hernández, J. Jaime
1998-03-01
The macrodispersion of an inert solute in a 2-D heterogeneous porous media is estimated numerically in a series of fields of varying heterogeneity. Four different random function (RF) models are used to model log-transmissivity (ln T) spatial variability, and for each of these models, ln T variance is varied from 0.1 to 2.0. The four RF models share the same univariate Gaussian histogram and the same isotropic covariance, but differ from one another in terms of the spatial connectivity patterns at extreme transmissivity values. More specifically, model A is a multivariate Gaussian model for which, by definition, extreme values (both high and low) are spatially uncorrelated. The other three models are non-multi-Gaussian: model B with high connectivity of high extreme values, model C with high connectivity of low extreme values, and model D with high connectivities of both high and low extreme values. Residence time distributions (RTDs) and macrodispersivities (longitudinal and transverse) are computed on ln T fields corresponding to the different RF models, for two different flow directions and at several scales. They are compared with each other, as well as with predicted values based on first-order analytical results. Numerically derived RTDs and macrodispersivities for the multi-Gaussian model are in good agreement with analytically derived values using first-order theories for log-transmissivity variance up to 2.0. The results from the non-multi-Gaussian models differ from each other and deviate largely from the multi-Gaussian results even when ln T variance is small. RTDs in non-multi-Gaussian realizations with high connectivity at high extreme values display earlier breakthrough than in multi-Gaussian realizations, whereas later breakthrough and longer tails are observed for RTDs from non-multi-Gaussian realizations with high connectivity at low extreme values. Longitudinal macrodispersivities in the non-multi-Gaussian realizations are, in general, larger than
Laguerre Gaussian beam multiplexing through turbulence
CSIR Research Space (South Africa)
Trichili, A
2014-08-17
Full Text Available We analyze the effect of atmospheric turbulence on the propagation of multiplexed Laguerre Gaussian modes. We present a method to multiplex Laguerre Gaussian modes using digital holograms and decompose the resulting field after encountering a...
Analytic matrix elements with shifted correlated Gaussians
DEFF Research Database (Denmark)
Fedorov, D. V.
2017-01-01
Matrix elements between shifted correlated Gaussians of various potentials with several form-factors are calculated analytically. Analytic matrix elements are of importance for the correlated Gaussian method in quantum few-body physics.......Matrix elements between shifted correlated Gaussians of various potentials with several form-factors are calculated analytically. Analytic matrix elements are of importance for the correlated Gaussian method in quantum few-body physics....
Gaussian process regression analysis for functional data
Shi, Jian Qing
2011-01-01
Gaussian Process Regression Analysis for Functional Data presents nonparametric statistical methods for functional regression analysis, specifically the methods based on a Gaussian process prior in a functional space. The authors focus on problems involving functional response variables and mixed covariates of functional and scalar variables.Covering the basics of Gaussian process regression, the first several chapters discuss functional data analysis, theoretical aspects based on the asymptotic properties of Gaussian process regression models, and new methodological developments for high dime
Gaussian statistics for palaeomagnetic vectors
Love, J.J.; Constable, C.G.
2003-01-01
With the aim of treating the statistics of palaeomagnetic directions and intensities jointly and consistently, we represent the mean and the variance of palaeomagnetic vectors, at a particular site and of a particular polarity, by a probability density function in a Cartesian three-space of orthogonal magnetic-field components consisting of a single (unimoda) non-zero mean, spherically-symmetrical (isotropic) Gaussian function. For palaeomagnetic data of mixed polarities, we consider a bimodal distribution consisting of a pair of such symmetrical Gaussian functions, with equal, but opposite, means and equal variances. For both the Gaussian and bi-Gaussian distributions, and in the spherical three-space of intensity, inclination, and declination, we obtain analytical expressions for the marginal density functions, the cumulative distributions, and the expected values and variances for each spherical coordinate (including the angle with respect to the axis of symmetry of the distributions). The mathematical expressions for the intensity and off-axis angle are closed-form and especially manageable, with the intensity distribution being Rayleigh-Rician. In the limit of small relative vectorial dispersion, the Gaussian (bi-Gaussian) directional distribution approaches a Fisher (Bingham) distribution and the intensity distribution approaches a normal distribution. In the opposite limit of large relative vectorial dispersion, the directional distributions approach a spherically-uniform distribution and the intensity distribution approaches a Maxwell distribution. We quantify biases in estimating the properties of the vector field resulting from the use of simple arithmetic averages, such as estimates of the intensity or the inclination of the mean vector, or the variances of these quantities. With the statistical framework developed here and using the maximum-likelihood method, which gives unbiased estimates in the limit of large data numbers, we demonstrate how to
Gaussian statistics for palaeomagnetic vectors
Love, J. J.; Constable, C. G.
2003-03-01
With the aim of treating the statistics of palaeomagnetic directions and intensities jointly and consistently, we represent the mean and the variance of palaeomagnetic vectors, at a particular site and of a particular polarity, by a probability density function in a Cartesian three-space of orthogonal magnetic-field components consisting of a single (unimodal) non-zero mean, spherically-symmetrical (isotropic) Gaussian function. For palaeomagnetic data of mixed polarities, we consider a bimodal distribution consisting of a pair of such symmetrical Gaussian functions, with equal, but opposite, means and equal variances. For both the Gaussian and bi-Gaussian distributions, and in the spherical three-space of intensity, inclination, and declination, we obtain analytical expressions for the marginal density functions, the cumulative distributions, and the expected values and variances for each spherical coordinate (including the angle with respect to the axis of symmetry of the distributions). The mathematical expressions for the intensity and off-axis angle are closed-form and especially manageable, with the intensity distribution being Rayleigh-Rician. In the limit of small relative vectorial dispersion, the Gaussian (bi-Gaussian) directional distribution approaches a Fisher (Bingham) distribution and the intensity distribution approaches a normal distribution. In the opposite limit of large relative vectorial dispersion, the directional distributions approach a spherically-uniform distribution and the intensity distribution approaches a Maxwell distribution. We quantify biases in estimating the properties of the vector field resulting from the use of simple arithmetic averages, such as estimates of the intensity or the inclination of the mean vector, or the variances of these quantities. With the statistical framework developed here and using the maximum-likelihood method, which gives unbiased estimates in the limit of large data numbers, we demonstrate how to
Reproducing kernel Hilbert spaces of Gaussian priors
Vaart, van der A.W.; Zanten, van J.H.; Clarke, B.; Ghosal, S.
2008-01-01
We review definitions and properties of reproducing kernel Hilbert spaces attached to Gaussian variables and processes, with a view to applications in nonparametric Bayesian statistics using Gaussian priors. The rate of contraction of posterior distributions based on Gaussian priors can be described
Nicolas, F; Coëtmellec, S; Brunel, M; Allano, D; Lebrun, D; Janssen, A J E M
2005-11-01
The authors have studied the diffraction pattern produced by a particle field illuminated by an elliptic and astigmatic Gaussian beam. They demonstrate that the bidimensional fractional Fourier transformation is a mathematically suitable tool to analyse the diffraction pattern generated not only by a collimated plane wave [J. Opt. Soc. Am A 19, 1537 (2002)], but also by an elliptic and astigmatic Gaussian beam when two different fractional orders are considered. Simulations and experimental results are presented.
Inflation in random Gaussian landscapes
Energy Technology Data Exchange (ETDEWEB)
Masoumi, Ali; Vilenkin, Alexander; Yamada, Masaki, E-mail: ali@cosmos.phy.tufts.edu, E-mail: vilenkin@cosmos.phy.tufts.edu, E-mail: Masaki.Yamada@tufts.edu [Institute of Cosmology, Department of Physics and Astronomy, Tufts University, Medford, MA 02155 (United States)
2017-05-01
We develop analytic and numerical techniques for studying the statistics of slow-roll inflation in random Gaussian landscapes. As an illustration of these techniques, we analyze small-field inflation in a one-dimensional landscape. We calculate the probability distributions for the maximal number of e-folds and for the spectral index of density fluctuations n {sub s} and its running α {sub s} . These distributions have a universal form, insensitive to the correlation function of the Gaussian ensemble. We outline possible extensions of our methods to a large number of fields and to models of large-field inflation. These methods do not suffer from potential inconsistencies inherent in the Brownian motion technique, which has been used in most of the earlier treatments.
General Galilei Covariant Gaussian Maps
Gasbarri, Giulio; Toroš, Marko; Bassi, Angelo
2017-09-01
We characterize general non-Markovian Gaussian maps which are covariant under Galilean transformations. In particular, we consider translational and Galilean covariant maps and show that they reduce to the known Holevo result in the Markovian limit. We apply the results to discuss measures of macroscopicity based on classicalization maps, specifically addressing dissipation, Galilean covariance and non-Markovianity. We further suggest a possible generalization of the macroscopicity measure defined by Nimmrichter and Hornberger [Phys. Rev. Lett. 110, 16 (2013)].
Gaussian Embeddings for Collaborative Filtering
Dos Santos , Ludovic; Piwowarski , Benjamin; Gallinari , Patrick
2017-01-01
International audience; Most collaborative ltering systems, such as matrix factorization, use vector representations for items and users. Those representations are deterministic, and do not allow modeling the uncertainty of the learned representation, which can be useful when a user has a small number of rated items (cold start), or when there is connict-ing information about the behavior of a user or the ratings of an item. In this paper, we leverage recent works in learning Gaussian embeddi...
Nonlinear and non-Gaussian Bayesian based handwriting beautification
Shi, Cao; Xiao, Jianguo; Xu, Canhui; Jia, Wenhua
2013-03-01
A framework is proposed in this paper to effectively and efficiently beautify handwriting by means of a novel nonlinear and non-Gaussian Bayesian algorithm. In the proposed framework, format and size of handwriting image are firstly normalized, and then typeface in computer system is applied to optimize vision effect of handwriting. The Bayesian statistics is exploited to characterize the handwriting beautification process as a Bayesian dynamic model. The model parameters to translate, rotate and scale typeface in computer system are controlled by state equation, and the matching optimization between handwriting and transformed typeface is employed by measurement equation. Finally, the new typeface, which is transformed from the original one and gains the best nonlinear and non-Gaussian optimization, is the beautification result of handwriting. Experimental results demonstrate the proposed framework provides a creative handwriting beautification methodology to improve visual acceptance.
Searching for primordial non-Gaussianity in Planck CMB maps using a combined estimator
Energy Technology Data Exchange (ETDEWEB)
Novaes, C.P.; Wuensche, C.A. [Divisão de Astrofísica, Instituto Nacional de Pesquisas Espaciais, Av. dos Astronautas 1758, São José dos Campos 12227-010, SP (Brazil); Bernui, A. [Observatório Nacional, Rua General José Cristino 77, São Cristóvão, 20921-400, Rio de Janeiro, RJ (Brazil); Ferreira, I.S., E-mail: camilapnovaes@gmail.com, E-mail: bernui@on.br, E-mail: ivan@fis.unb.br, E-mail: ca.wuensche@inpe.br [Instituto de Física, Universidade de Brasília, Campus Universitário Darcy Ribeiro, Asa Norte, 70919-970, Brasília, DF (Brazil)
2014-01-01
The extensive search for deviations from Gaussianity in cosmic microwave background radiation (CMB) data is very important due to the information about the very early moments of the universe encoded there. Recent analyses from Planck CMB data do not exclude the presence of non-Gaussianity of small amplitude, although they are consistent with the Gaussian hypothesis. The use of different techniques is essential to provide information about types and amplitudes of non-Gaussianities in the CMB data. In particular, we find interesting to construct an estimator based upon the combination of two powerful statistical tools that appears to be sensitive enough to detect tiny deviations from Gaussianity in CMB maps. This estimator combines the Minkowski functionals with a Neural Network, maximizing a tool widely used to study non-Gaussian signals with a reinforcement of another tool designed to identify patterns in a data set. We test our estimator by analyzing simulated CMB maps contaminated with different amounts of local primordial non-Gaussianity quantified by the dimensionless parameter f{sub NL}. We apply it to these sets of CMB maps and find ∼> 98% of chance of positive detection, even for small intensity local non-Gaussianity like f{sub NL} = 38±18, the current limit from Planck data for large angular scales. Additionally, we test the suitability to distinguish between primary and secondary non-Gaussianities: first we train the Neural Network with two sets, one of nearly Gaussian CMB maps (|f{sub NL}| ≤ 10) but contaminated with realistic inhomogeneous Planck noise (i.e., secondary non-Gaussianity) and the other of non-Gaussian CMB maps, that is, maps endowed with weak primordial non-Gaussianity (28 ≤ f{sub NL} ≤ 48); after that we test an ensemble composed of CMB maps either with one of these non-Gaussian contaminations, and find out that our method successfully classifies ∼ 95% of the tested maps as being CMB maps containing primordial or
Energy Technology Data Exchange (ETDEWEB)
Lao, Louis [Department of Radiation Oncology, Princess Margaret Cancer Centre, University of Toronto, Toronto, Ontario (Canada); Department of Radiation Oncology, Auckland City Hospital, Auckland (New Zealand); Hope, Andrew J. [Department of Radiation Oncology, Princess Margaret Cancer Centre, University of Toronto, Toronto, Ontario (Canada); Maganti, Manjula [Department of Biostatistics, Princess Margaret Cancer Centre, University of Toronto, Toronto, Ontario (Canada); Brade, Anthony; Bezjak, Andrea; Saibishkumar, Elantholi P.; Giuliani, Meredith; Sun, Alexander [Department of Radiation Oncology, Princess Margaret Cancer Centre, University of Toronto, Toronto, Ontario (Canada); Cho, B. C. John, E-mail: john.cho@rmp.uhn.on.ca [Department of Radiation Oncology, Princess Margaret Cancer Centre, University of Toronto, Toronto, Ontario (Canada)
2014-09-01
Purpose: Reported rates of non-small cell lung cancer (NSCLC) nodal failure following stereotactic body radiation therapy (SBRT) are lower than those reported in the surgical series when matched for stage. We hypothesized that this effect was due to incidental prophylactic nodal irradiation. Methods and Materials: A prospectively collected group of medically inoperable early stage NSCLC patients from 2004 to 2010 was used to identify cases with nodal relapses. Controls were matched to cases, 2:1, controlling for tumor volume (ie, same or greater) and tumor location (ie, same lobe). Reference (normalized to equivalent dose for 2-Gy fractions [EQD2]) point doses at the ipsilateral hilum and carina, demographic data, and clinical outcomes were extracted from the medical records. Univariate conditional logistical regression analyses were performed with variables of interest. Results: Cases and controls were well matched except for size. The controls, as expected, had larger gross tumor volumes (P=.02). The mean ipsilateral hilar doses were 9.6 Gy and 22.4 Gy for cases and controls, respectively (P=.014). The mean carinal doses were 7.0 Gy and 9.2 Gy, respectively (P=.13). Mediastinal nodal relapses, with and without ipsilateral hilar relapse, were associated with mean ipsilateral hilar doses of 3.6 Gy and 19.8 Gy, respectively (P=.01). The conditional density plot appears to demonstrate an inverse dose-effect relationship between ipsilateral hilar normalized total dose and risk of ipsilateral hilar relapse. Conclusions: Incidental hilar dose greater than 20 Gy is significantly associated with fewer ipsilateral hilar relapses in inoperable early stage NSCLC patients treated with SBRT.
International Nuclear Information System (INIS)
Lao, Louis; Hope, Andrew J.; Maganti, Manjula; Brade, Anthony; Bezjak, Andrea; Saibishkumar, Elantholi P.; Giuliani, Meredith; Sun, Alexander; Cho, B. C. John
2014-01-01
Purpose: Reported rates of non-small cell lung cancer (NSCLC) nodal failure following stereotactic body radiation therapy (SBRT) are lower than those reported in the surgical series when matched for stage. We hypothesized that this effect was due to incidental prophylactic nodal irradiation. Methods and Materials: A prospectively collected group of medically inoperable early stage NSCLC patients from 2004 to 2010 was used to identify cases with nodal relapses. Controls were matched to cases, 2:1, controlling for tumor volume (ie, same or greater) and tumor location (ie, same lobe). Reference (normalized to equivalent dose for 2-Gy fractions [EQD2]) point doses at the ipsilateral hilum and carina, demographic data, and clinical outcomes were extracted from the medical records. Univariate conditional logistical regression analyses were performed with variables of interest. Results: Cases and controls were well matched except for size. The controls, as expected, had larger gross tumor volumes (P=.02). The mean ipsilateral hilar doses were 9.6 Gy and 22.4 Gy for cases and controls, respectively (P=.014). The mean carinal doses were 7.0 Gy and 9.2 Gy, respectively (P=.13). Mediastinal nodal relapses, with and without ipsilateral hilar relapse, were associated with mean ipsilateral hilar doses of 3.6 Gy and 19.8 Gy, respectively (P=.01). The conditional density plot appears to demonstrate an inverse dose-effect relationship between ipsilateral hilar normalized total dose and risk of ipsilateral hilar relapse. Conclusions: Incidental hilar dose greater than 20 Gy is significantly associated with fewer ipsilateral hilar relapses in inoperable early stage NSCLC patients treated with SBRT
Our objective was to assess the agreement of posted menus with foods served to 3- to 5-year-old children attending federal Child and Adult Care Food Program (CACFP)-enrolled facilities, and the degree to which the facilities met the new meal patterns and best practices. On-site observations and menu...
Standard forms and entanglement engineering of multimode Gaussian states under local operations
International Nuclear Information System (INIS)
Serafini, Alessio; Adesso, Gerardo
2007-01-01
We investigate the action of local unitary operations on multimode (pure or mixed) Gaussian states and single out the minimal number of locally invariant parameters which completely characterize the covariance matrix of such states. For pure Gaussian states, central resources for continuous-variable quantum information, we investigate separately the parameter reduction due to the additional constraint of global purity, and the one following by the local-unitary freedom. Counting arguments and insights from the phase-space Schmidt decomposition and in general from the framework of symplectic analysis, accompany our description of the standard form of pure n-mode Gaussian states. In particular, we clarify why only in pure states with n ≤ 3 modes all the direct correlations between position and momentum operators can be set to zero by local unitary operations. For any n, the emerging minimal set of parameters contains complete information about all forms of entanglement in the corresponding states. An efficient state engineering scheme (able to encode direct correlations between position and momentum operators as well) is proposed to produce entangled multimode Gaussian resources, its number of optical elements matching the minimal number of locally invariant degrees of freedom of general pure n-mode Gaussian states. Finally, we demonstrate that so-called 'block-diagonal' Gaussian states, without direct correlations between position and momentum, are systematically less entangled, on average, than arbitrary pure Gaussian states
Bootstrapping realized volatility and realized beta under a local Gaussianity assumption
DEFF Research Database (Denmark)
Hounyo, Ulrich
The main contribution of this paper is to propose a new bootstrap method for statistics based on high frequency returns. The new method exploits the local Gaussianity and the local constancy of volatility of high frequency returns, two assumptions that can simplify inference in the high frequency...... context, as recently explained by Mykland and Zhang (2009). Our main contributions are as follows. First, we show that the local Gaussian bootstrap is firstorder consistent when used to estimate the distributions of realized volatility and ealized betas. Second, we show that the local Gaussian bootstrap...... matches accurately the first four cumulants of realized volatility, implying that this method provides third-order refinements. This is in contrast with the wild bootstrap of Gonçalves and Meddahi (2009), which is only second-order correct. Third, we show that the local Gaussian bootstrap is able...
Detecting periodicities with Gaussian processes
Directory of Open Access Journals (Sweden)
Nicolas Durrande
2016-04-01
Full Text Available We consider the problem of detecting and quantifying the periodic component of a function given noise-corrupted observations of a limited number of input/output tuples. Our approach is based on Gaussian process regression, which provides a flexible non-parametric framework for modelling periodic data. We introduce a novel decomposition of the covariance function as the sum of periodic and aperiodic kernels. This decomposition allows for the creation of sub-models which capture the periodic nature of the signal and its complement. To quantify the periodicity of the signal, we derive a periodicity ratio which reflects the uncertainty in the fitted sub-models. Although the method can be applied to many kernels, we give a special emphasis to the Matérn family, from the expression of the reproducing kernel Hilbert space inner product to the implementation of the associated periodic kernels in a Gaussian process toolkit. The proposed method is illustrated by considering the detection of periodically expressed genes in the arabidopsis genome.
Monogamy inequality for distributed gaussian entanglement.
Hiroshima, Tohya; Adesso, Gerardo; Illuminati, Fabrizio
2007-02-02
We show that for all n-mode Gaussian states of continuous variable systems, the entanglement shared among n parties exhibits the fundamental monogamy property. The monogamy inequality is proven by introducing the Gaussian tangle, an entanglement monotone under Gaussian local operations and classical communication, which is defined in terms of the squared negativity in complete analogy with the case of n-qubit systems. Our results elucidate the structure of quantum correlations in many-body harmonic lattice systems.
Breaking Gaussian incompatibility on continuous variable quantum systems
Energy Technology Data Exchange (ETDEWEB)
Heinosaari, Teiko, E-mail: teiko.heinosaari@utu.fi [Turku Centre for Quantum Physics, Department of Physics and Astronomy, University of Turku, FI-20014 Turku (Finland); Kiukas, Jukka, E-mail: jukka.kiukas@aber.ac.uk [Department of Mathematics, Aberystwyth University, Penglais, Aberystwyth, SY23 3BZ (United Kingdom); Schultz, Jussi, E-mail: jussi.schultz@gmail.com [Turku Centre for Quantum Physics, Department of Physics and Astronomy, University of Turku, FI-20014 Turku (Finland); Dipartimento di Matematica, Politecnico di Milano, Piazza Leonardo da Vinci 32, I-20133 Milano (Italy)
2015-08-15
We characterise Gaussian quantum channels that are Gaussian incompatibility breaking, that is, transform every set of Gaussian measurements into a set obtainable from a joint Gaussian observable via Gaussian postprocessing. Such channels represent local noise which renders measurements useless for Gaussian EPR-steering, providing the appropriate generalisation of entanglement breaking channels for this scenario. Understanding the structure of Gaussian incompatibility breaking channels contributes to the resource theory of noisy continuous variable quantum information protocols.
Harmonic emission due to the nonlinear coupling of a Gaussian laser and a plasma wave
Energy Technology Data Exchange (ETDEWEB)
Pathak, R; Jain, R K [Department of Mathematics, SSL Jain College, Vidisha, MP, 464001 (India); Parashar, J [Department of Physics, Samrat Ashok Technological Institute, Vidisha, MP, 464001 (India)
2010-04-15
A high-power Gaussian laser propagating through a plasma couples with a large-amplitude plasma wave and undergoes scattering to produce harmonics. The process is sensitive to the phase matching angle between the laser and plasma wave numbers and the plasma wave frequency. For larger harmonics, the phase matching angle is high. The efficiency of the process is comparatively high at higher plasma wave frequencies.
Operation of a quasi-optical gyrotron with a gaussian output coupler
Energy Technology Data Exchange (ETDEWEB)
Hogge, J.P.; Tran, T.M.; Paris, P.J.; Tran, M.Q. [Ecole Polytechnique Federale, Lausanne (Switzerland). Centre de Recherche en Physique des Plasma (CRPP)
1996-03-01
The operation of a 92 GHz quasi-optical gyrotron (QOG) having a resonator formed by a spherical mirror and a diffraction grating placed in -1 order Littrow mount is presented. A power of 150 kW with a gaussian output pattern was measured. The gaussian content in the output was 98% with less than 1% of depolarization. By optimizing the magnetic field at fixed frequency, a maximum efficiency of 15% was reached. (author) 12 figs., 2 tabs., 22 refs.
Directory of Open Access Journals (Sweden)
Amy Hillier
2013-01-01
Full Text Available Increasing research has focused on the built food environment and nutrition-related outcomes, yet what constitutes a food environment and how this environment influences individual behavior still remain unclear. This study assesses whether travel mode and distance to food shopping venues differ among individuals in varying food environments and whether individual- and household-level factors are associated with food shopping patterns. Fifty neighbors who share a traditionally defined food environment (25 in an unfavorable environment and 25 in a favorable environment were surveyed using a mix of close- and open-ended survey questions. Food shopping patterns were mapped using Geographic Information Systems (GIS. Stores visited were beyond the 0.5-mile (805 meters radius traditionally used to represent the extent of an individual’s food environment in an urban area. We found no significant difference in shopping frequency or motivating factor behind store choice between the groups. No differences existed between the two groups for big food shopping trips. For small trips, individuals in the favorable food environment traveled shorter distances and were more likely to walk than drive. Socioeconomic status, including car ownership, education, and income influenced distance traveled. These findings highlight the complexities involved in the study and measurement of food environments.
Hirsch, Jana A; Hillier, Amy
2013-01-14
Increasing research has focused on the built food environment and nutrition-related outcomes, yet what constitutes a food environment and how this environment influences individual behavior still remain unclear. This study assesses whether travel mode and distance to food shopping venues differ among individuals in varying food environments and whether individual- and household-level factors are associated with food shopping patterns. Fifty neighbors who share a traditionally defined food environment (25 in an unfavorable environment and 25 in a favorable environment) were surveyed using a mix of close- and open-ended survey questions. Food shopping patterns were mapped using Geographic Information Systems (GIS). Stores visited were beyond the 0.5-mile (805 meters) radius traditionally used to represent the extent of an individual's food environment in an urban area. We found no significant difference in shopping frequency or motivating factor behind store choice between the groups. No differences existed between the two groups for big food shopping trips. For small trips, individuals in the favorable food environment traveled shorter distances and were more likely to walk than drive. Socioeconomic status, including car ownership, education, and income influenced distance traveled. These findings highlight the complexities involved in the study and measurement of food environments.
An approximate fractional Gaussian noise model with computational cost
Sørbye, Sigrunn H.
2017-09-18
Fractional Gaussian noise (fGn) is a stationary time series model with long memory properties applied in various fields like econometrics, hydrology and climatology. The computational cost in fitting an fGn model of length $n$ using a likelihood-based approach is ${\\\\mathcal O}(n^{2})$, exploiting the Toeplitz structure of the covariance matrix. In most realistic cases, we do not observe the fGn process directly but only through indirect Gaussian observations, so the Toeplitz structure is easily lost and the computational cost increases to ${\\\\mathcal O}(n^{3})$. This paper presents an approximate fGn model of ${\\\\mathcal O}(n)$ computational cost, both with direct or indirect Gaussian observations, with or without conditioning. This is achieved by approximating fGn with a weighted sum of independent first-order autoregressive processes, fitting the parameters of the approximation to match the autocorrelation function of the fGn model. The resulting approximation is stationary despite being Markov and gives a remarkably accurate fit using only four components. The performance of the approximate fGn model is demonstrated in simulations and two real data examples.
Optimal background matching camouflage.
Michalis, Constantine; Scott-Samuel, Nicholas E; Gibson, David P; Cuthill, Innes C
2017-07-12
Background matching is the most familiar and widespread camouflage strategy: avoiding detection by having a similar colour and pattern to the background. Optimizing background matching is straightforward in a homogeneous environment, or when the habitat has very distinct sub-types and there is divergent selection leading to polymorphism. However, most backgrounds have continuous variation in colour and texture, so what is the best solution? Not all samples of the background are likely to be equally inconspicuous, and laboratory experiments on birds and humans support this view. Theory suggests that the most probable background sample (in the statistical sense), at the size of the prey, would, on average, be the most cryptic. We present an analysis, based on realistic assumptions about low-level vision, that estimates the distribution of background colours and visual textures, and predicts the best camouflage. We present data from a field experiment that tests and supports our predictions, using artificial moth-like targets under bird predation. Additionally, we present analogous data for humans, under tightly controlled viewing conditions, searching for targets on a computer screen. These data show that, in the absence of predator learning, the best single camouflage pattern for heterogeneous backgrounds is the most probable sample. © 2017 The Authors.
International Nuclear Information System (INIS)
McHugh, Derek; Buzek, Vladimir; Ziman, Mario
2006-01-01
We present a class of non-Gaussian two-mode continuous-variable states for which the separability criterion for Gaussian states can be employed to detect whether they are separable or not. These states reduce to the two-mode Gaussian states as a special case
Quantum beamstrahlung from gaussian bunches
International Nuclear Information System (INIS)
Chen, P.
1987-08-01
The method of Baier and Katkov is applied to calculate the correction terms to the Sokolov-Ternov radiation formula due to the variation of the magnetic field strength along the trajectory of a radiating particle. We carry the calculation up to the second order in the power expansion of B tau/B, where tau is the formation time of radiation. The expression is then used to estimate the quantum beamstrahlung average energy loss from e + e - bunches with gaussian distribution in bunch currents. We show that the effect of the field variation is to reduce the average energy loss from previous calculations based on the Sokolov-Ternov formula or its equivalent. Due to the limitation of our method, only an upper bound of the reduction is obtained. 18 refs
Techniques Used in String Matching for Network Security
Jamuna Bhandari
2014-01-01
String matching also known as pattern matching is one of primary concept for network security. In this area the effectiveness and efficiency of string matching algorithms is important for applications in network security such as network intrusion detection, virus detection, signature matching and web content filtering system. This paper presents brief review on some of string matching techniques used for network security.
Lin, Yi-Hsuan; Brady, Jacob P.; Forman-Kay, Julie D.; Chan, Hue Sun
2017-11-01
Biologically functional liquid-liquid phase separation of intrinsically disordered proteins (IDPs) is driven by interactions encoded by their amino acid sequences. Little is currently known about the molecular recognition mechanisms for distributing different IDP sequences into various cellular membraneless compartments. Pertinent physics was addressed recently by applying random-phase-approximation (RPA) polymer theory to electrostatics, which is a major energetic component governing IDP phase properties. RPA accounts for charge patterns and thus has advantages over Flory-Huggins (FH) and Overbeek-Voorn mean-field theories. To make progress toward deciphering the phase behaviors of multiple IDP sequences, the RPA formulation for one IDP species plus solvent is hereby extended to treat polyampholyte solutions containing two IDP species plus solvent. The new formulation generally allows for binary coexistence of two phases, each containing a different set of volume fractions ({φ }1,{φ }2) for the two different IDP sequences. The asymmetry between the two predicted coexisting phases with regard to their {φ }1/{φ }2 ratios for the two sequences increases with increasing mismatch between their charge patterns. This finding points to a multivalent, stochastic, ‘fuzzy’ mode of molecular recognition that helps populate various IDP sequences differentially into separate phase compartments. An intuitive illustration of this trend is provided by FH models, whereby a hypothetical case of ternary coexistence is also explored. Augmentations of the present RPA theory with a relative permittivity {ɛ }{{r}}(φ ) that depends on IDP volume fraction φ ={φ }1+{φ }2 lead to higher propensities to phase separate, in line with the case with one IDP species we studied previously. Notably, the cooperative, phase-separation-enhancing effects predicted by the prescriptions for {ɛ }{{r}}(φ ) we deem physically plausible are much more prominent than that entailed by common
Limit theorems for functionals of Gaussian vectors
Institute of Scientific and Technical Information of China (English)
Hongshuai DAI; Guangjun SHEN; Lingtao KONG
2017-01-01
Operator self-similar processes,as an extension of self-similar processes,have been studied extensively.In this work,we study limit theorems for functionals of Gaussian vectors.Under some conditions,we determine that the limit of partial sums of functionals of a stationary Gaussian sequence of random vectors is an operator self-similar process.
Palm distributions for log Gaussian Cox processes
DEFF Research Database (Denmark)
Coeurjolly, Jean-Francois; Møller, Jesper; Waagepetersen, Rasmus
This paper reviews useful results related to Palm distributions of spatial point processes and provides a new result regarding the characterization of Palm distributions for the class of log Gaussian Cox processes. This result is used to study functional summary statistics for a log Gaussian Cox...
Gaussian limit of compact spin systems
International Nuclear Information System (INIS)
Bellissard, J.; Angelis, G.F. de
1981-01-01
It is shown that the Wilson and Wilson-Villain U(1) models reproduce, in the low coupling limit, the gaussian lattice approximation of the Euclidean electromagnetic field. By the same methods it is also possible to prove that the plane rotator and the Villain model share a common gaussian behaviour in the low temperature limit. (Auth.)
On the dependence structure of Gaussian queues
Es-Saghouani, A.; Mandjes, M.R.H.
2009-01-01
In this article we study Gaussian queues (that is, queues fed by Gaussian processes, such as fractional Brownian motion (fBm) and the integrated Ornstein-Uhlenbeck (iOU) process), with a focus on the dependence structure of the workload process. The main question is to what extent does the workload
Shedding new light on Gaussian harmonic analysis
Teuwen, J.J.B.
2016-01-01
This dissertation consists out of two rather disjoint parts. One part concerns some results on Gaussian harmonic analysis and the other on an optimization problem in optics. In the first part we study the Ornstein–Uhlenbeck process with respect to the Gaussian measure. We focus on two areas. One is
Energy Technology Data Exchange (ETDEWEB)
Chance, William W. [Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Rice, David C. [Department of Thoracic and Cardiovascular Surgery, The University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Allen, Pamela K. [Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Tsao, Anne S. [Department of Thoracic/Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Fontanilla, Hiral P. [Princeton Radiation Oncology, Monroe Township, New Jersey (United States); Liao, Zhongxing; Chang, Joe Y.; Tang, Chad; Pan, Hubert Y.; Welsh, James W. [Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Mehran, Reza J. [Department of Thoracic and Cardiovascular Surgery, The University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Gomez, Daniel R., E-mail: dgomez@mdanderson.org [Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas (United States)
2015-01-01
Purpose: To investigate safety, efficacy, and recurrence after hemithoracic intensity modulated radiation therapy after pleurectomy/decortication (PD-IMRT) and after extrapleural pneumonectomy (EPP-IMRT). Methods and Materials: In 2009-2013, 24 patients with mesothelioma underwent PD-IMRT to the involved hemithorax to a dose of 45 Gy, with an optional integrated boost; 22 also received chemotherapy. Toxicity was scored with the Common Terminology Criteria for Adverse Events v4.0. Pulmonary function was compared at baseline, after surgery, and after IMRT. Kaplan-Meier analysis was used to calculate overall survival (OS), progression-free survival (PFS), time to locoregional failure, and time to distant metastasis. Failures were in-field, marginal, or out of field. Outcomes were compared with those of 24 patients, matched for age, nodal status, performance status, and chemotherapy, who had received EPP-IMRT. Results: Median follow-up time was 12.2 months. Grade 3 toxicity rates were 8% skin and 8% pulmonary. Pulmonary function declined from baseline to after surgery (by 21% for forced vital capacity, 16% for forced expiratory volume in 1 second, and 19% for lung diffusion of carbon monoxide [P for all = .01]) and declined still further after IMRT (by 31% for forced vital capacity [P=.02], 25% for forced expiratory volume in 1 second [P=.01], and 30% for lung diffusion of carbon monoxide [P=.01]). The OS and PFS rates were 76% and 67%, respectively, at 1 year and 56% and 34% at 2 years. Median OS (28.4 vs 14.2 months, P=.04) and median PFS (16.4 vs 8.2 months, P=.01) favored PD-IMRT versus EPP-IMRT. No differences were found in grade 4-5 toxicity (0 of 24 vs 3 of 24, P=.23), median time to locoregional failure (18.7 months vs not reached, P not calculable), or median time to distant metastasis (18.8 vs 11.8 months, P=.12). Conclusions: Hemithoracic intensity modulated radiation therapy after pleurectomy/decortication produced little high-grade toxicity but
Color Texture Segmentation by Decomposition of Gaussian Mixture Model
Czech Academy of Sciences Publication Activity Database
Grim, Jiří; Somol, Petr; Haindl, Michal; Pudil, Pavel
2006-01-01
Roč. 19, č. 4225 (2006), s. 287-296 ISSN 0302-9743. [Iberoamerican Congress on Pattern Recognition. CIARP 2006 /11./. Cancun, 14.11.2006-17.11.2006] R&D Projects: GA AV ČR 1ET400750407; GA MŠk 1M0572; GA MŠk 2C06019 EU Projects: European Commission(XE) 507752 - MUSCLE Institutional research plan: CEZ:AV0Z10750506 Keywords : texture segmentation * gaussian mixture model * EM algorithm Subject RIV: IN - Informatics, Computer Science Impact factor: 0.402, year: 2005 http://library.utia.cas.cz/separaty/historie/grim-color texture segmentation by decomposition of gaussian mixture model.pdf
Entanglement in Gaussian matrix-product states
International Nuclear Information System (INIS)
Adesso, Gerardo; Ericsson, Marie
2006-01-01
Gaussian matrix-product states are obtained as the outputs of projection operations from an ancillary space of M infinitely entangled bonds connecting neighboring sites, applied at each of N sites of a harmonic chain. Replacing the projections by associated Gaussian states, the building blocks, we show that the entanglement range in translationally invariant Gaussian matrix-product states depends on how entangled the building blocks are. In particular, infinite entanglement in the building blocks produces fully symmetric Gaussian states with maximum entanglement range. From their peculiar properties of entanglement sharing, a basic difference with spin chains is revealed: Gaussian matrix-product states can possess unlimited, long-range entanglement even with minimum number of ancillary bonds (M=1). Finally we discuss how these states can be experimentally engineered from N copies of a three-mode building block and N two-mode finitely squeezed states
Gaussian vs non-Gaussian turbulence: impact on wind turbine loads
DEFF Research Database (Denmark)
Berg, Jacob; Natarajan, Anand; Mann, Jakob
2016-01-01
taking into account the safety factor for extreme moments. Other extreme load moments as well as the fatigue loads are not affected because of the use of non-Gaussian turbulent inflow. It is suggested that the turbine thus acts like a low-pass filter that averages out the non-Gaussian behaviour, which......From large-eddy simulations of atmospheric turbulence, a representation of Gaussian turbulence is constructed by randomizing the phases of the individual modes of variability. Time series of Gaussian turbulence are constructed and compared with its non-Gaussian counterpart. Time series from the two...
Nicolas, F.; Coëtmellec, S.; Brunel, M.; Allano, D.; Lebrun, D.; Janssen, A.J.E.M.
2005-01-01
The authors have studied the diffraction pattern produced by a particle field illuminated by an elliptic and astigmatic Gaussian beam. They demonstrate that the bidimensional fractional Fourier transformation is a mathematically suitable tool to analyse the diffraction pattern generated not only by
Sankaranarayanan, Preethi; Schomay, Theodore E.; Aiello, Katherine A.; Alter, Orly
2015-01-01
The number of large-scale high-dimensional datasets recording different aspects of a single disease is growing, accompanied by a need for frameworks that can create one coherent model from multiple tensors of matched columns, e.g., patients and platforms, but independent rows, e.g., probes. We define and prove the mathematical properties of a novel tensor generalized singular value decomposition (GSVD), which can simultaneously find the similarities and dissimilarities, i.e., patterns of varying relative significance, between any two such tensors. We demonstrate the tensor GSVD in comparative modeling of patient- and platform-matched but probe-independent ovarian serous cystadenocarcinoma (OV) tumor, mostly high-grade, and normal DNA copy-number profiles, across each chromosome arm, and combination of two arms, separately. The modeling uncovers previously unrecognized patterns of tumor-exclusive platform-consistent co-occurring copy-number alterations (CNAs). We find, first, and validate that each of the patterns across only 7p and Xq, and the combination of 6p+12p, is correlated with a patient’s prognosis, is independent of the tumor’s stage, the best predictor of OV survival to date, and together with stage makes a better predictor than stage alone. Second, these patterns include most known OV-associated CNAs that map to these chromosome arms, as well as several previously unreported, yet frequent focal CNAs. Third, differential mRNA, microRNA, and protein expression consistently map to the DNA CNAs. A coherent picture emerges for each pattern, suggesting roles for the CNAs in OV pathogenesis and personalized therapy. In 6p+12p, deletion of the p21-encoding CDKN1A and p38-encoding MAPK14 and amplification of RAD51AP1 and KRAS encode for human cell transformation, and are correlated with a cell’s immortality, and a patient’s shorter survival time. In 7p, RPA3 deletion and POLD2 amplification are correlated with DNA stability, and a longer survival. In Xq
Directory of Open Access Journals (Sweden)
Preethi Sankaranarayanan
Full Text Available The number of large-scale high-dimensional datasets recording different aspects of a single disease is growing, accompanied by a need for frameworks that can create one coherent model from multiple tensors of matched columns, e.g., patients and platforms, but independent rows, e.g., probes. We define and prove the mathematical properties of a novel tensor generalized singular value decomposition (GSVD, which can simultaneously find the similarities and dissimilarities, i.e., patterns of varying relative significance, between any two such tensors. We demonstrate the tensor GSVD in comparative modeling of patient- and platform-matched but probe-independent ovarian serous cystadenocarcinoma (OV tumor, mostly high-grade, and normal DNA copy-number profiles, across each chromosome arm, and combination of two arms, separately. The modeling uncovers previously unrecognized patterns of tumor-exclusive platform-consistent co-occurring copy-number alterations (CNAs. We find, first, and validate that each of the patterns across only 7p and Xq, and the combination of 6p+12p, is correlated with a patient's prognosis, is independent of the tumor's stage, the best predictor of OV survival to date, and together with stage makes a better predictor than stage alone. Second, these patterns include most known OV-associated CNAs that map to these chromosome arms, as well as several previously unreported, yet frequent focal CNAs. Third, differential mRNA, microRNA, and protein expression consistently map to the DNA CNAs. A coherent picture emerges for each pattern, suggesting roles for the CNAs in OV pathogenesis and personalized therapy. In 6p+12p, deletion of the p21-encoding CDKN1A and p38-encoding MAPK14 and amplification of RAD51AP1 and KRAS encode for human cell transformation, and are correlated with a cell's immortality, and a patient's shorter survival time. In 7p, RPA3 deletion and POLD2 amplification are correlated with DNA stability, and a longer survival
Towards optimal packed string matching
DEFF Research Database (Denmark)
Ben-Kiki, Oren; Bille, Philip; Breslauer, Dany
2014-01-01
-size string-matching instruction wssm is available in contemporary commodity processors. The other word-size maximum-suffix instruction wslm is only required during the pattern pre-processing. Benchmarks show that our solution can be efficiently implemented, unlike some prior theoretical packed string...
Increasing Entanglement between Gaussian States by Coherent Photon Subtraction
DEFF Research Database (Denmark)
Ourjoumtsev, Alexei; Dantan, Aurelien Romain; Tualle Brouri, Rosa
2007-01-01
We experimentally demonstrate that the entanglement between Gaussian entangled states can be increased by non-Gaussian operations. Coherent subtraction of single photons from Gaussian quadrature-entangled light pulses, created by a nondegenerate parametric amplifier, produces delocalized states...
Representation of Gaussian semimartingales with applications to the covariance function
DEFF Research Database (Denmark)
Basse-O'Connor, Andreas
2010-01-01
stationary Gaussian semimartingales and their canonical decomposition. Thirdly, we give a new characterization of the covariance function of Gaussian semimartingales, which enable us to characterize the class of martingales and the processes of bounded variation among the Gaussian semimartingales. We...
Mu, Hongqian; Wang, Muguang; Tang, Yu; Zhang, Jing; Jian, Shuisheng
2018-03-01
A novel scheme for the generation of FCC-compliant UWB pulse is proposed based on modified Gaussian quadruplet and incoherent wavelength-to-time conversion. The modified Gaussian quadruplet is synthesized based on linear sum of a broad Gaussian pulse and two narrow Gaussian pulses with the same pulse-width and amplitude peak. Within specific parameter range, FCC-compliant UWB with spectral power efficiency of higher than 39.9% can be achieved. In order to realize the designed waveform, a UWB generator based on spectral shaping and incoherent wavelength-to-time mapping is proposed. The spectral shaper is composed of a Gaussian filter and a programmable filter. Single-mode fiber functions as both dispersion device and transmission medium. Balanced photodetection is employed to combine linearly the broad Gaussian pulse and two narrow Gaussian pulses, and at same time to suppress pulse pedestals that result in low-frequency components. The proposed UWB generator can be reconfigured for UWB doublet by operating the programmable filter as a single-band Gaussian filter. The feasibility of proposed UWB generator is demonstrated experimentally. Measured UWB pulses match well with simulation results. FCC-compliant quadruplet with 10-dB bandwidth of 6.88-GHz, fractional bandwidth of 106.8% and power efficiency of 51% is achieved.
Some continual integrals from gaussian forms
International Nuclear Information System (INIS)
Mazmanishvili, A.S.
1985-01-01
The result summary of continual integration of gaussian functional type is given. The summary contains 124 continual integrals which are the mathematical expectation of the corresponding gaussian form by the continuum of random trajectories of four types: real-valued Ornstein-Uhlenbeck process, Wiener process, complex-valued Ornstein-Uhlenbeck process and the stochastic harmonic one. The summary includes both the known continual integrals and the unpublished before integrals. Mathematical results of the continual integration carried in the work may be applied in the problem of the theory of stochastic process, approaching to the finding of mean from gaussian forms by measures generated by the pointed stochastic processes
Loop corrections to primordial non-Gaussianity
Boran, Sibel; Kahya, E. O.
2018-02-01
We discuss quantum gravitational loop effects to observable quantities such as curvature power spectrum and primordial non-Gaussianity of cosmic microwave background (CMB) radiation. We first review the previously shown case where one gets a time dependence for zeta-zeta correlator due to loop corrections. Then we investigate the effect of loop corrections to primordial non-Gaussianity of CMB. We conclude that, even with a single scalar inflaton, one might get a huge value for non-Gaussianity which would exceed the observed value by at least 30 orders of magnitude. Finally we discuss the consequences of this result for scalar driven inflationary models.
Gaussian Mixture Model of Heart Rate Variability
Costa, Tommaso; Boccignone, Giuseppe; Ferraro, Mario
2012-01-01
Heart rate variability (HRV) is an important measure of sympathetic and parasympathetic functions of the autonomic nervous system and a key indicator of cardiovascular condition. This paper proposes a novel method to investigate HRV, namely by modelling it as a linear combination of Gaussians. Results show that three Gaussians are enough to describe the stationary statistics of heart variability and to provide a straightforward interpretation of the HRV power spectrum. Comparisons have been made also with synthetic data generated from different physiologically based models showing the plausibility of the Gaussian mixture parameters. PMID:22666386
Non-Gaussianity from isocurvature perturbations
Energy Technology Data Exchange (ETDEWEB)
Kawasaki, Masahiro; Nakayama, Kazunori; Sekiguchi, Toyokazu; Suyama, Teruaki [Institute for Cosmic Ray Research, University of Tokyo, Kashiwa 277-8582 (Japan); Takahashi, Fuminobu, E-mail: kawasaki@icrr.u-tokyo.ac.jp, E-mail: nakayama@icrr.u-tokyo.ac.jp, E-mail: sekiguti@icrr.u-tokyo.ac.jp, E-mail: suyama@icrr.u-tokyo.ac.jp, E-mail: fuminobu.takahashi@ipmu.jp [Institute for the Physics and Mathematics of the Universe, University of Tokyo, Kashiwa 277-8568 (Japan)
2008-11-15
We develop a formalism for studying non-Gaussianity in both curvature and isocurvature perturbations. It is shown that non-Gaussianity in the isocurvature perturbation between dark matter and photons leaves distinct signatures in the cosmic microwave background temperature fluctuations, which may be confirmed in future experiments, or possibly even in the currently available observational data. As an explicit example, we consider the quantum chromodynamics axion and show that it can actually induce sizable non-Gaussianity for the inflationary scale, H{sub inf} = O(10{sup 9}-10{sup 11}) GeV.
Gaussian measures of entanglement versus negativities: Ordering of two-mode Gaussian states
International Nuclear Information System (INIS)
Adesso, Gerardo; Illuminati, Fabrizio
2005-01-01
We study the entanglement of general (pure or mixed) two-mode Gaussian states of continuous-variable systems by comparing the two available classes of computable measures of entanglement: entropy-inspired Gaussian convex-roof measures and positive partial transposition-inspired measures (negativity and logarithmic negativity). We first review the formalism of Gaussian measures of entanglement, adopting the framework introduced in M. M. Wolf et al., Phys. Rev. A 69, 052320 (2004), where the Gaussian entanglement of formation was defined. We compute explicitly Gaussian measures of entanglement for two important families of nonsymmetric two-mode Gaussian state: namely, the states of extremal (maximal and minimal) negativities at fixed global and local purities, introduced in G. Adesso et al., Phys. Rev. Lett. 92, 087901 (2004). This analysis allows us to compare the different orderings induced on the set of entangled two-mode Gaussian states by the negativities and by the Gaussian measures of entanglement. We find that in a certain range of values of the global and local purities (characterizing the covariance matrix of the corresponding extremal states), states of minimum negativity can have more Gaussian entanglement of formation than states of maximum negativity. Consequently, Gaussian measures and negativities are definitely inequivalent measures of entanglement on nonsymmetric two-mode Gaussian states, even when restricted to a class of extremal states. On the other hand, the two families of entanglement measures are completely equivalent on symmetric states, for which the Gaussian entanglement of formation coincides with the true entanglement of formation. Finally, we show that the inequivalence between the two families of continuous-variable entanglement measures is somehow limited. Namely, we rigorously prove that, at fixed negativities, the Gaussian measures of entanglement are bounded from below. Moreover, we provide some strong evidence suggesting that they
Evaluation of Gaussian approximations for data assimilation in reservoir models
Iglesias, Marco A.
2013-07-14
The Bayesian framework is the standard approach for data assimilation in reservoir modeling. This framework involves characterizing the posterior distribution of geological parameters in terms of a given prior distribution and data from the reservoir dynamics, together with a forward model connecting the space of geological parameters to the data space. Since the posterior distribution quantifies the uncertainty in the geologic parameters of the reservoir, the characterization of the posterior is fundamental for the optimal management of reservoirs. Unfortunately, due to the large-scale highly nonlinear properties of standard reservoir models, characterizing the posterior is computationally prohibitive. Instead, more affordable ad hoc techniques, based on Gaussian approximations, are often used for characterizing the posterior distribution. Evaluating the performance of those Gaussian approximations is typically conducted by assessing their ability at reproducing the truth within the confidence interval provided by the ad hoc technique under consideration. This has the disadvantage of mixing up the approximation properties of the history matching algorithm employed with the information content of the particular observations used, making it hard to evaluate the effect of the ad hoc approximations alone. In this paper, we avoid this disadvantage by comparing the ad hoc techniques with a fully resolved state-of-the-art probing of the Bayesian posterior distribution. The ad hoc techniques whose performance we assess are based on (1) linearization around the maximum a posteriori estimate, (2) randomized maximum likelihood, and (3) ensemble Kalman filter-type methods. In order to fully resolve the posterior distribution, we implement a state-of-the art Markov chain Monte Carlo (MCMC) method that scales well with respect to the dimension of the parameter space, enabling us to study realistic forward models, in two space dimensions, at a high level of grid refinement. Our
Optimal unitary dilation for bosonic Gaussian channels
International Nuclear Information System (INIS)
Caruso, Filippo; Eisert, Jens; Giovannetti, Vittorio; Holevo, Alexander S.
2011-01-01
A general quantum channel can be represented in terms of a unitary interaction between the information-carrying system and a noisy environment. In this paper the minimal number of quantum Gaussian environmental modes required to provide a unitary dilation of a multimode bosonic Gaussian channel is analyzed for both pure and mixed environments. We compute this quantity in the case of pure environment corresponding to the Stinespring representation and give an improved estimate in the case of mixed environment. The computations rely, on one hand, on the properties of the generalized Choi-Jamiolkowski state and, on the other hand, on an explicit construction of the minimal dilation for arbitrary bosonic Gaussian channel. These results introduce a new quantity reflecting ''noisiness'' of bosonic Gaussian channels and can be applied to address some issues concerning transmission of information in continuous variables systems.
Phase statistics in non-Gaussian scattering
International Nuclear Information System (INIS)
Watson, Stephen M; Jakeman, Eric; Ridley, Kevin D
2006-01-01
Amplitude weighting can improve the accuracy of frequency measurements in signals corrupted by multiplicative speckle noise. When the speckle field constitutes a circular complex Gaussian process, the optimal function of amplitude weighting is provided by the field intensity, corresponding to the intensity-weighted phase derivative statistic. In this paper, we investigate the phase derivative and intensity-weighted phase derivative returned from a two-dimensional random walk, which constitutes a generic scattering model capable of producing both Gaussian and non-Gaussian fluctuations. Analytical results are developed for the correlation properties of the intensity-weighted phase derivative, as well as limiting probability densities of the scattered field. Numerical simulation is used to generate further probability densities and determine optimal weighting criteria from non-Gaussian fields. The results are relevant to frequency retrieval in radiation scattered from random media
Galaxy bias and primordial non-Gaussianity
Energy Technology Data Exchange (ETDEWEB)
Assassi, Valentin; Baumann, Daniel [DAMTP, Cambridge University, Wilberforce Road, Cambridge CB3 0WA (United Kingdom); Schmidt, Fabian, E-mail: assassi@ias.edu, E-mail: D.D.Baumann@uva.nl, E-mail: fabians@MPA-Garching.MPG.DE [Max-Planck-Institut für Astrophysik, Karl-Schwarzschild-Str. 1, 85748 Garching (Germany)
2015-12-01
We present a systematic study of galaxy biasing in the presence of primordial non-Gaussianity. For a large class of non-Gaussian initial conditions, we define a general bias expansion and prove that it is closed under renormalization, thereby showing that the basis of operators in the expansion is complete. We then study the effects of primordial non-Gaussianity on the statistics of galaxies. We show that the equivalence principle enforces a relation between the scale-dependent bias in the galaxy power spectrum and that in the dipolar part of the bispectrum. This provides a powerful consistency check to confirm the primordial origin of any observed scale-dependent bias. Finally, we also discuss the imprints of anisotropic non-Gaussianity as motivated by recent studies of higher-spin fields during inflation.
Optimal cloning of mixed Gaussian states
International Nuclear Information System (INIS)
Guta, Madalin; Matsumoto, Keiji
2006-01-01
We construct the optimal one to two cloning transformation for the family of displaced thermal equilibrium states of a harmonic oscillator, with a fixed and known temperature. The transformation is Gaussian and it is optimal with respect to the figure of merit based on the joint output state and norm distance. The proof of the result is based on the equivalence between the optimal cloning problem and that of optimal amplification of Gaussian states which is then reduced to an optimization problem for diagonal states of a quantum oscillator. A key concept in finding the optimum is that of stochastic ordering which plays a similar role in the purely classical problem of Gaussian cloning. The result is then extended to the case of n to m cloning of mixed Gaussian states
Encoding information using laguerre gaussian modes
CSIR Research Space (South Africa)
Trichili, A
2015-08-01
Full Text Available The authors experimentally demonstrate an information encoding protocol using the two degrees of freedom of Laguerre Gaussian modes having different radial and azimuthal components. A novel method, based on digital holography, for information...
Interweave Cognitive Radio with Improper Gaussian Signaling
Hedhly, Wafa; Amin, Osama; Alouini, Mohamed-Slim
2018-01-01
Improper Gaussian signaling (IGS) has proven its ability in improving the performance of underlay and overlay cognitive radio paradigms. In this paper, the interweave cognitive radio paradigm is studied when the cognitive user employs IGS
Galaxy bias and primordial non-Gaussianity
International Nuclear Information System (INIS)
Assassi, Valentin; Baumann, Daniel; Schmidt, Fabian
2015-01-01
We present a systematic study of galaxy biasing in the presence of primordial non-Gaussianity. For a large class of non-Gaussian initial conditions, we define a general bias expansion and prove that it is closed under renormalization, thereby showing that the basis of operators in the expansion is complete. We then study the effects of primordial non-Gaussianity on the statistics of galaxies. We show that the equivalence principle enforces a relation between the scale-dependent bias in the galaxy power spectrum and that in the dipolar part of the bispectrum. This provides a powerful consistency check to confirm the primordial origin of any observed scale-dependent bias. Finally, we also discuss the imprints of anisotropic non-Gaussianity as motivated by recent studies of higher-spin fields during inflation
Statistically tuned Gaussian background subtraction technique for ...
Indian Academy of Sciences (India)
temporal median method and mixture of Gaussian model and performance evaluation ... to process the videos captured by unmanned aerial vehicle (UAV). ..... The output is obtained by simulation using MATLAB 2010 in a standalone PC with ...
A non-Gaussian multivariate distribution with all lower-dimensional Gaussians and related families
Dutta, Subhajit
2014-07-28
Several fascinating examples of non-Gaussian bivariate distributions which have marginal distribution functions to be Gaussian have been proposed in the literature. These examples often clarify several properties associated with the normal distribution. In this paper, we generalize this result in the sense that we construct a pp-dimensional distribution for which any proper subset of its components has the Gaussian distribution. However, the jointpp-dimensional distribution is inconsistent with the distribution of these subsets because it is not Gaussian. We study the probabilistic properties of this non-Gaussian multivariate distribution in detail. Interestingly, several popular tests of multivariate normality fail to identify this pp-dimensional distribution as non-Gaussian. We further extend our construction to a class of elliptically contoured distributions as well as skewed distributions arising from selections, for instance the multivariate skew-normal distribution.
A non-Gaussian multivariate distribution with all lower-dimensional Gaussians and related families
Dutta, Subhajit; Genton, Marc G.
2014-01-01
Several fascinating examples of non-Gaussian bivariate distributions which have marginal distribution functions to be Gaussian have been proposed in the literature. These examples often clarify several properties associated with the normal distribution. In this paper, we generalize this result in the sense that we construct a pp-dimensional distribution for which any proper subset of its components has the Gaussian distribution. However, the jointpp-dimensional distribution is inconsistent with the distribution of these subsets because it is not Gaussian. We study the probabilistic properties of this non-Gaussian multivariate distribution in detail. Interestingly, several popular tests of multivariate normality fail to identify this pp-dimensional distribution as non-Gaussian. We further extend our construction to a class of elliptically contoured distributions as well as skewed distributions arising from selections, for instance the multivariate skew-normal distribution.
Gaussian sum rules for optical functions
International Nuclear Information System (INIS)
Kimel, I.
1981-12-01
A new (Gaussian) type of sum rules (GSR) for several optical functions, is presented. The functions considered are: dielectric permeability, refractive index, energy loss function, rotatory power and ellipticity (circular dichroism). While reducing to the usual type of sum rules in a certain limit, the GSR contain in general, a Gaussian factor that serves to improve convergence. GSR might be useful in analysing experimental data. (Author) [pt
Gaussian maximally multipartite-entangled states
Facchi, Paolo; Florio, Giuseppe; Lupo, Cosmo; Mancini, Stefano; Pascazio, Saverio
2009-12-01
We study maximally multipartite-entangled states in the context of Gaussian continuous variable quantum systems. By considering multimode Gaussian states with constrained energy, we show that perfect maximally multipartite-entangled states, which exhibit the maximum amount of bipartite entanglement for all bipartitions, only exist for systems containing n=2 or 3 modes. We further numerically investigate the structure of these states and their frustration for n≤7 .
Gaussian maximally multipartite-entangled states
International Nuclear Information System (INIS)
Facchi, Paolo; Florio, Giuseppe; Pascazio, Saverio; Lupo, Cosmo; Mancini, Stefano
2009-01-01
We study maximally multipartite-entangled states in the context of Gaussian continuous variable quantum systems. By considering multimode Gaussian states with constrained energy, we show that perfect maximally multipartite-entangled states, which exhibit the maximum amount of bipartite entanglement for all bipartitions, only exist for systems containing n=2 or 3 modes. We further numerically investigate the structure of these states and their frustration for n≤7.
Non-Gaussian halo assembly bias
International Nuclear Information System (INIS)
Reid, Beth A.; Verde, Licia; Dolag, Klaus; Matarrese, Sabino; Moscardini, Lauro
2010-01-01
The strong dependence of the large-scale dark matter halo bias on the (local) non-Gaussianity parameter, f NL , offers a promising avenue towards constraining primordial non-Gaussianity with large-scale structure surveys. In this paper, we present the first detection of the dependence of the non-Gaussian halo bias on halo formation history using N-body simulations. We also present an analytic derivation of the expected signal based on the extended Press-Schechter formalism. In excellent agreement with our analytic prediction, we find that the halo formation history-dependent contribution to the non-Gaussian halo bias (which we call non-Gaussian halo assembly bias) can be factorized in a form approximately independent of redshift and halo mass. The correction to the non-Gaussian halo bias due to the halo formation history can be as large as 100%, with a suppression of the signal for recently formed halos and enhancement for old halos. This could in principle be a problem for realistic galaxy surveys if observational selection effects were to pick galaxies occupying only recently formed halos. Current semi-analytic galaxy formation models, for example, imply an enhancement in the expected signal of ∼ 23% and ∼ 48% for galaxies at z = 1 selected by stellar mass and star formation rate, respectively
Adaptive Laguerre-Gaussian variant of the Gaussian beam expansion method.
Cagniot, Emmanuel; Fromager, Michael; Ait-Ameur, Kamel
2009-11-01
A variant of the Gaussian beam expansion method consists in expanding the Bessel function J0 appearing in the Fresnel-Kirchhoff integral into a finite sum of complex Gaussian functions to derive an analytical expression for a Laguerre-Gaussian beam diffracted through a hard-edge aperture. However, the validity range of the approximation depends on the number of expansion coefficients that are obtained by optimization-computation directly. We propose another solution consisting in expanding J0 onto a set of collimated Laguerre-Gaussian functions whose waist depends on their number and then, depending on its argument, predicting the suitable number of expansion functions to calculate the integral recursively.
Optical propagation of the HE11 mode and Gaussian beams in hollow circular waveguides
International Nuclear Information System (INIS)
Crenn, J.P.
1993-05-01
The propagation of the HE 11 mode and Gaussian beams in hollow oversized circular waveguides is analyzed using optical theories. Different types of waveguides are considered: hollow dielectric or conducting waveguides, dielectric-lined waveguides, corrugated waveguides. General formulas are derived which give the power transmission through these different guides. The best wall materials and structures are determined from a comparison of the waveguide transmissions, at the infrared and millimeter wavelengths. The question of the coupling between the HE 11 mode and Gaussian beams is discussed and from a review of coupling coefficients derived before, an optimum value is pointed out. The problem of matching a Gaussian beam into circular waveguides in order to achieve the maximum power transmission is analyzed
Reservoir History Matching Using Ensemble Kalman Filters with Anamorphosis Transforms
Aman, Beshir M.
2012-12-01
This work aims to enhance the Ensemble Kalman Filter performance by transforming the non-Gaussian state variables into Gaussian variables to be a step closer to optimality. This is done by using univariate and multivariate Box-Cox transformation. Some History matching methods such as Kalman filter, particle filter and the ensemble Kalman filter are reviewed and applied to a test case in the reservoir application. The key idea is to apply the transformation before the update step and then transform back after applying the Kalman correction. In general, the results of the multivariate method was promising, despite the fact it over-estimated some variables.
New gaussian points for the solution of first order ordinary ...
African Journals Online (AJOL)
Numerical experiments carried out using the new Gaussian points revealed there efficiency on stiff differential equations. The results also reveal that methods using the new Gaussian points are more accurate than those using the standard Gaussian points on non-stiff initial value problems. Keywords: Gaussian points ...
Matsuoka, A J; Abbas, P J; Rubinstein, J T; Miller, C A
2000-11-01
Experimental results from humans and animals show that electrically evoked compound action potential (EAP) responses to constant-amplitude pulse train stimulation can demonstrate an alternating pattern, due to the combined effects of highly synchronized responses to electrical stimulation and refractory effects (Wilson et al., 1994). One way to improve signal representation is to reduce the level of across-fiber synchrony and hence, the level of the amplitude alternation. To accomplish this goal, we have examined EAP responses in the presence of Gaussian noise added to the pulse train stimulus. Addition of Gaussian noise at a level approximately -30 dB relative to EAP threshold to the pulse trains decreased the amount of alternation, indicating that stochastic resonance may be induced in the auditory nerve. The use of some type of conditioning stimulus such as Gaussian noise may provide a more 'normal' neural response pattern.
... for Kids ▸ Stinging Insect Matching Game Share | Stinging Insect Matching Game Stinging insects can ruin summer fun for those who are ... the difference between the different kinds of stinging insects in order to keep your summer safe and ...
DEFF Research Database (Denmark)
Bennedsen, Mikkel
Using theory on (conditionally) Gaussian processes with stationary increments developed in Barndorff-Nielsen et al. (2009, 2011), this paper presents a general semiparametric approach to conducting inference on the fractal index, α, of a time series. Our setup encompasses a large class of Gaussian...
Matching rendered and real world images by digital image processing
Mitjà, Carles; Bover, Toni; Bigas, Miquel; Escofet, Jaume
2010-05-01
Recent advances in computer-generated images (CGI) have been used in commercial and industrial photography providing a broad scope in product advertising. Mixing real world images with those rendered from virtual space software shows a more or less visible mismatching between corresponding image quality performance. Rendered images are produced by software which quality performance is only limited by the resolution output. Real world images are taken with cameras with some amount of image degradation factors as lens residual aberrations, diffraction, sensor low pass anti aliasing filters, color pattern demosaicing, etc. The effect of all those image quality degradation factors can be characterized by the system Point Spread Function (PSF). Because the image is the convolution of the object by the system PSF, its characterization shows the amount of image degradation added to any taken picture. This work explores the use of image processing to degrade the rendered images following the parameters indicated by the real system PSF, attempting to match both virtual and real world image qualities. The system MTF is determined by the slanted edge method both in laboratory conditions and in the real picture environment in order to compare the influence of the working conditions on the device performance; an approximation to the system PSF is derived from the two measurements. The rendered images are filtered through a Gaussian filter obtained from the taking system PSF. Results with and without filtering are shown and compared measuring the contrast achieved in different final image regions.
Graphical calculus for Gaussian pure states
International Nuclear Information System (INIS)
Menicucci, Nicolas C.; Flammia, Steven T.; Loock, Peter van
2011-01-01
We provide a unified graphical calculus for all Gaussian pure states, including graph transformation rules for all local and semilocal Gaussian unitary operations, as well as local quadrature measurements. We then use this graphical calculus to analyze continuous-variable (CV) cluster states, the essential resource for one-way quantum computing with CV systems. Current graphical approaches to CV cluster states are only valid in the unphysical limit of infinite squeezing, and the associated graph transformation rules only apply when the initial and final states are of this form. Our formalism applies to all Gaussian pure states and subsumes these rules in a natural way. In addition, the term 'CV graph state' currently has several inequivalent definitions in use. Using this formalism we provide a single unifying definition that encompasses all of them. We provide many examples of how the formalism may be used in the context of CV cluster states: defining the 'closest' CV cluster state to a given Gaussian pure state and quantifying the error in the approximation due to finite squeezing; analyzing the optimality of certain methods of generating CV cluster states; drawing connections between this graphical formalism and bosonic Hamiltonians with Gaussian ground states, including those useful for CV one-way quantum computing; and deriving a graphical measure of bipartite entanglement for certain classes of CV cluster states. We mention other possible applications of this formalism and conclude with a brief note on fault tolerance in CV one-way quantum computing.
Variational Gaussian approximation for Poisson data
Arridge, Simon R.; Ito, Kazufumi; Jin, Bangti; Zhang, Chen
2018-02-01
The Poisson model is frequently employed to describe count data, but in a Bayesian context it leads to an analytically intractable posterior probability distribution. In this work, we analyze a variational Gaussian approximation to the posterior distribution arising from the Poisson model with a Gaussian prior. This is achieved by seeking an optimal Gaussian distribution minimizing the Kullback-Leibler divergence from the posterior distribution to the approximation, or equivalently maximizing the lower bound for the model evidence. We derive an explicit expression for the lower bound, and show the existence and uniqueness of the optimal Gaussian approximation. The lower bound functional can be viewed as a variant of classical Tikhonov regularization that penalizes also the covariance. Then we develop an efficient alternating direction maximization algorithm for solving the optimization problem, and analyze its convergence. We discuss strategies for reducing the computational complexity via low rank structure of the forward operator and the sparsity of the covariance. Further, as an application of the lower bound, we discuss hierarchical Bayesian modeling for selecting the hyperparameter in the prior distribution, and propose a monotonically convergent algorithm for determining the hyperparameter. We present extensive numerical experiments to illustrate the Gaussian approximation and the algorithms.
Mode entanglement of Gaussian fermionic states
Spee, C.; Schwaiger, K.; Giedke, G.; Kraus, B.
2018-04-01
We investigate the entanglement of n -mode n -partite Gaussian fermionic states (GFS). First, we identify a reasonable definition of separability for GFS and derive a standard form for mixed states, to which any state can be mapped via Gaussian local unitaries (GLU). As the standard form is unique, two GFS are equivalent under GLU if and only if their standard forms coincide. Then, we investigate the important class of local operations assisted by classical communication (LOCC). These are central in entanglement theory as they allow one to partially order the entanglement contained in states. We show, however, that there are no nontrivial Gaussian LOCC (GLOCC) among pure n -partite (fully entangled) states. That is, any such GLOCC transformation can also be accomplished via GLU. To obtain further insight into the entanglement properties of such GFS, we investigate the richer class of Gaussian stochastic local operations assisted by classical communication (SLOCC). We characterize Gaussian SLOCC classes of pure n -mode n -partite states and derive them explicitly for few-mode states. Furthermore, we consider certain fermionic LOCC and show how to identify the maximally entangled set of pure n -mode n -partite GFS, i.e., the minimal set of states having the property that any other state can be obtained from one state inside this set via fermionic LOCC. We generalize these findings also to the pure m -mode n -partite (for m >n ) case.
Matching Matched Filtering with Deep Networks for Gravitational-Wave Astronomy
Gabbard, Hunter; Williams, Michael; Hayes, Fergus; Messenger, Chris
2018-04-01
We report on the construction of a deep convolutional neural network that can reproduce the sensitivity of a matched-filtering search for binary black hole gravitational-wave signals. The standard method for the detection of well-modeled transient gravitational-wave signals is matched filtering. We use only whitened time series of measured gravitational-wave strain as an input, and we train and test on simulated binary black hole signals in synthetic Gaussian noise representative of Advanced LIGO sensitivity. We show that our network can classify signal from noise with a performance that emulates that of match filtering applied to the same data sets when considering the sensitivity defined by receiver-operator characteristics.
Matching Matched Filtering with Deep Networks for Gravitational-Wave Astronomy.
Gabbard, Hunter; Williams, Michael; Hayes, Fergus; Messenger, Chris
2018-04-06
We report on the construction of a deep convolutional neural network that can reproduce the sensitivity of a matched-filtering search for binary black hole gravitational-wave signals. The standard method for the detection of well-modeled transient gravitational-wave signals is matched filtering. We use only whitened time series of measured gravitational-wave strain as an input, and we train and test on simulated binary black hole signals in synthetic Gaussian noise representative of Advanced LIGO sensitivity. We show that our network can classify signal from noise with a performance that emulates that of match filtering applied to the same data sets when considering the sensitivity defined by receiver-operator characteristics.
Directory of Open Access Journals (Sweden)
Gholamreza Anbarjafari
2015-12-01
Full Text Available Illumination problems have been an important concern in many image processing applications. The pattern of the histogram on an image introduces meaningful features; hence within the process of illumination enhancement, it is important not to destroy such information. In this paper we propose a method to enhance image illumination using Gaussian distribution mapping which also keeps the information laid on the pattern of the histogram on the original image. First a Gaussian distribution based on the mean and standard deviation of the input image will be calculated. Simultaneously a Gaussian distribution with the desired mean and standard deviation will be calculated. Then a cumulative distribution function of each of the Gaussian distributions will be calculated and used in order to map the old pixel value onto the new pixel value. Another important issue in the field of illumination enhancement is absence of a quantitative measure for the assessment of the illumination of an image. In this research work, a quantitative measure indicating the illumination state, i.e. contrast level and brightness of an image, is also proposed. The measure utilizes the estimated Gaussian distribution of the input image and the Kullback-Leibler Divergence (KLD between the estimated Gaussian and the desired Gaussian distributions to calculate the quantitative measure. The experimental results show the effectiveness and the reliability of the proposed illumination enhancement technique, as well as the proposed illumination assessment measure over conventional and state-of-the-art techniques.
Non-Gaussianity in island cosmology
International Nuclear Information System (INIS)
Piao Yunsong
2009-01-01
In this paper we fully calculate the non-Gaussianity of primordial curvature perturbation of the island universe by using the second order perturbation equation. We find that for the spectral index n s ≅0.96, which is favored by current observations, the non-Gaussianity level f NL seen in an island will generally lie between 30 and 60, which may be tested by the coming observations. In the landscape, the island universe is one of anthropically acceptable cosmological histories. Thus the results obtained in some sense mean the coming observations, especially the measurement of non-Gaussianity, will be significant to clarify how our position in the landscape is populated.
Entanglement negativity bounds for fermionic Gaussian states
Eisert, Jens; Eisler, Viktor; Zimborás, Zoltán
2018-04-01
The entanglement negativity is a versatile measure of entanglement that has numerous applications in quantum information and in condensed matter theory. It can not only efficiently be computed in the Hilbert space dimension, but for noninteracting bosonic systems, one can compute the negativity efficiently in the number of modes. However, such an efficient computation does not carry over to the fermionic realm, the ultimate reason for this being that the partial transpose of a fermionic Gaussian state is no longer Gaussian. To provide a remedy for this state of affairs, in this work, we introduce efficiently computable and rigorous upper and lower bounds to the negativity, making use of techniques of semidefinite programming, building upon the Lagrangian formulation of fermionic linear optics, and exploiting suitable products of Gaussian operators. We discuss examples in quantum many-body theory and hint at applications in the study of topological properties at finite temperature.
Robust Matching Pursuit Extreme Learning Machines
Directory of Open Access Journals (Sweden)
Zejian Yuan
2018-01-01
Full Text Available Extreme learning machine (ELM is a popular learning algorithm for single hidden layer feedforward networks (SLFNs. It was originally proposed with the inspiration from biological learning and has attracted massive attentions due to its adaptability to various tasks with a fast learning ability and efficient computation cost. As an effective sparse representation method, orthogonal matching pursuit (OMP method can be embedded into ELM to overcome the singularity problem and improve the stability. Usually OMP recovers a sparse vector by minimizing a least squares (LS loss, which is efficient for Gaussian distributed data, but may suffer performance deterioration in presence of non-Gaussian data. To address this problem, a robust matching pursuit method based on a novel kernel risk-sensitive loss (in short KRSLMP is first proposed in this paper. The KRSLMP is then applied to ELM to solve the sparse output weight vector, and the new method named the KRSLMP-ELM is developed for SLFN learning. Experimental results on synthetic and real-world data sets confirm the effectiveness and superiority of the proposed method.
Best matching theory & applications
Moghaddam, Mohsen
2017-01-01
Mismatch or best match? This book demonstrates that best matching of individual entities to each other is essential to ensure smooth conduct and successful competitiveness in any distributed system, natural and artificial. Interactions must be optimized through best matching in planning and scheduling, enterprise network design, transportation and construction planning, recruitment, problem solving, selective assembly, team formation, sensor network design, and more. Fundamentals of best matching in distributed and collaborative systems are explained by providing: § Methodical analysis of various multidimensional best matching processes § Comprehensive taxonomy, comparing different best matching problems and processes § Systematic identification of systems’ hierarchy, nature of interactions, and distribution of decision-making and control functions § Practical formulation of solutions based on a library of best matching algorithms and protocols, ready for direct applications and apps development. Design...
Directory of Open Access Journals (Sweden)
Dejan Trifunovic
2017-08-01
Full Text Available In this paper, we present the problem of matching students to schools by using different matching mechanisms. This market is specific since public schools are free and the price mechanism cannot be used to determine the optimal allocation of children in schools. Therefore, it is necessary to use different matching algorithms that mimic the market mechanism and enable us to determine the core of the cooperative game. In this paper, we will determine that it is possible to apply cooperative game theory in matching problems. This review paper is based on illustrative examples aiming to compare matching algorithms in terms of the incentive compatibility, stability and efficiency of the matching. In this paper we will present some specific problems that may occur in matching, such as improving the quality of schools, favoring minority students, the limited length of the list of preferences and generating strict priorities from weak priorities.
Invariant measures on multimode quantum Gaussian states
Lupo, C.; Mancini, S.; De Pasquale, A.; Facchi, P.; Florio, G.; Pascazio, S.
2012-12-01
We derive the invariant measure on the manifold of multimode quantum Gaussian states, induced by the Haar measure on the group of Gaussian unitary transformations. To this end, by introducing a bipartition of the system in two disjoint subsystems, we use a parameterization highlighting the role of nonlocal degrees of freedom—the symplectic eigenvalues—which characterize quantum entanglement across the given bipartition. A finite measure is then obtained by imposing a physically motivated energy constraint. By averaging over the local degrees of freedom we finally derive the invariant distribution of the symplectic eigenvalues in some cases of particular interest for applications in quantum optics and quantum information.
Invariant measures on multimode quantum Gaussian states
International Nuclear Information System (INIS)
Lupo, C.; Mancini, S.; De Pasquale, A.; Facchi, P.; Florio, G.; Pascazio, S.
2012-01-01
We derive the invariant measure on the manifold of multimode quantum Gaussian states, induced by the Haar measure on the group of Gaussian unitary transformations. To this end, by introducing a bipartition of the system in two disjoint subsystems, we use a parameterization highlighting the role of nonlocal degrees of freedom—the symplectic eigenvalues—which characterize quantum entanglement across the given bipartition. A finite measure is then obtained by imposing a physically motivated energy constraint. By averaging over the local degrees of freedom we finally derive the invariant distribution of the symplectic eigenvalues in some cases of particular interest for applications in quantum optics and quantum information.
Invariant measures on multimode quantum Gaussian states
Energy Technology Data Exchange (ETDEWEB)
Lupo, C. [School of Science and Technology, Universita di Camerino, I-62032 Camerino (Italy); Mancini, S. [School of Science and Technology, Universita di Camerino, I-62032 Camerino (Italy); Istituto Nazionale di Fisica Nucleare, Sezione di Perugia, I-06123 Perugia (Italy); De Pasquale, A. [NEST, Scuola Normale Superiore and Istituto Nanoscienze-CNR, I-56126 Pisa (Italy); Facchi, P. [Dipartimento di Matematica and MECENAS, Universita di Bari, I-70125 Bari (Italy); Istituto Nazionale di Fisica Nucleare, Sezione di Bari, I-70126 Bari (Italy); Florio, G. [Istituto Nazionale di Fisica Nucleare, Sezione di Bari, I-70126 Bari (Italy); Museo Storico della Fisica e Centro Studi e Ricerche Enrico Fermi, Piazza del Viminale 1, I-00184 Roma (Italy); Dipartimento di Fisica and MECENAS, Universita di Bari, I-70126 Bari (Italy); Pascazio, S. [Istituto Nazionale di Fisica Nucleare, Sezione di Bari, I-70126 Bari (Italy); Dipartimento di Fisica and MECENAS, Universita di Bari, I-70126 Bari (Italy)
2012-12-15
We derive the invariant measure on the manifold of multimode quantum Gaussian states, induced by the Haar measure on the group of Gaussian unitary transformations. To this end, by introducing a bipartition of the system in two disjoint subsystems, we use a parameterization highlighting the role of nonlocal degrees of freedom-the symplectic eigenvalues-which characterize quantum entanglement across the given bipartition. A finite measure is then obtained by imposing a physically motivated energy constraint. By averaging over the local degrees of freedom we finally derive the invariant distribution of the symplectic eigenvalues in some cases of particular interest for applications in quantum optics and quantum information.
Construction of Capacity Achieving Lattice Gaussian Codes
Alghamdi, Wael
2016-04-01
We propose a new approach to proving results regarding channel coding schemes based on construction-A lattices for the Additive White Gaussian Noise (AWGN) channel that yields new characterizations of the code construction parameters, i.e., the primes and dimensions of the codes, as functions of the block-length. The approach we take introduces an averaging argument that explicitly involves the considered parameters. This averaging argument is applied to a generalized Loeliger ensemble [1] to provide a more practical proof of the existence of AWGN-good lattices, and to characterize suitable parameters for the lattice Gaussian coding scheme proposed by Ling and Belfiore [3].
Gaussian processes and constructive scalar field theory
International Nuclear Information System (INIS)
Benfatto, G.; Nicolo, F.
1981-01-01
The last years have seen a very deep progress of constructive euclidean field theory, with many implications in the area of the random fields theory. The authors discuss an approach to super-renormalizable scalar field theories, which puts in particular evidence the connections with the theory of the Gaussian processes associated to the elliptic operators. The paper consists of two parts. Part I treats some problems in the theory of Gaussian processes which arise in the approach to the PHI 3 4 theory. Part II is devoted to the discussion of the ultraviolet stability in the PHI 3 4 theory. (Auth.)
Integration of non-Gaussian fields
DEFF Research Database (Denmark)
Ditlevsen, Ove Dalager; Mohr, Gunnar; Hoffmeyer, Pernille
1996-01-01
The limitations of the validity of the central limit theorem argument as applied to definite integrals of non-Gaussian random fields are empirically explored by way of examples. The purpose is to investigate in specific cases whether the asymptotic convergence to the Gaussian distribution is fast....... and Randrup-Thomsen, S. Reliability of silo ring under lognormal stochastic pressure using stochastic interpolation. Proc. IUTAM Symp., Probabilistic Structural Mechanics: Advances in Structural Reliability Methods, San Antonio, TX, USA, June 1993 (eds.: P. D. Spanos & Y.-T. Wu) pp. 134-162. Springer, Berlin...
Quantum information theory with Gaussian systems
Energy Technology Data Exchange (ETDEWEB)
Krueger, O.
2006-04-06
This thesis applies ideas and concepts from quantum information theory to systems of continuous-variables such as the quantum harmonic oscillator. The focus is on three topics: the cloning of coherent states, Gaussian quantum cellular automata and Gaussian private channels. Cloning was investigated both for finite-dimensional and for continuous-variable systems. We construct a private quantum channel for the sequential encryption of coherent states with a classical key, where the key elements have finite precision. For the case of independent one-mode input states, we explicitly estimate this precision, i.e. the number of key bits needed per input state, in terms of these parameters. (orig.)
Quantum information theory with Gaussian systems
International Nuclear Information System (INIS)
Krueger, O.
2006-01-01
This thesis applies ideas and concepts from quantum information theory to systems of continuous-variables such as the quantum harmonic oscillator. The focus is on three topics: the cloning of coherent states, Gaussian quantum cellular automata and Gaussian private channels. Cloning was investigated both for finite-dimensional and for continuous-variable systems. We construct a private quantum channel for the sequential encryption of coherent states with a classical key, where the key elements have finite precision. For the case of independent one-mode input states, we explicitly estimate this precision, i.e. the number of key bits needed per input state, in terms of these parameters. (orig.)
Model selection for Gaussian kernel PCA denoising
DEFF Research Database (Denmark)
Jørgensen, Kasper Winther; Hansen, Lars Kai
2012-01-01
We propose kernel Parallel Analysis (kPA) for automatic kernel scale and model order selection in Gaussian kernel PCA. Parallel Analysis [1] is based on a permutation test for covariance and has previously been applied for model order selection in linear PCA, we here augment the procedure to also...... tune the Gaussian kernel scale of radial basis function based kernel PCA.We evaluate kPA for denoising of simulated data and the US Postal data set of handwritten digits. We find that kPA outperforms other heuristics to choose the model order and kernel scale in terms of signal-to-noise ratio (SNR...
Daneshzand, Mohammad; Faezipour, Miad; Barkana, Buket D
2017-01-01
Deep brain stimulation (DBS) has compelling results in the desynchronization of the basal ganglia neuronal activities and thus, is used in treating the motor symptoms of Parkinson's disease (PD). Accurate definition of DBS waveform parameters could avert tissue or electrode damage, increase the neuronal activity and reduce energy cost which will prolong the battery life, hence avoiding device replacement surgeries. This study considers the use of a charge balanced Gaussian waveform pattern as a method to disrupt the firing patterns of neuronal cell activity. A computational model was created to simulate ganglia cells and their interactions with thalamic neurons. From the model, we investigated the effects of modified DBS pulse shapes and proposed a delay period between the cathodic and anodic parts of the charge balanced Gaussian waveform to desynchronize the firing patterns of the GPe and GPi cells. The results of the proposed Gaussian waveform with delay outperformed that of rectangular DBS waveforms used in in-vivo experiments. The Gaussian Delay Gaussian (GDG) waveforms achieved lower number of misses in eliciting action potential while having a lower amplitude and shorter length of delay compared to numerous different pulse shapes. The amount of energy consumed in the basal ganglia network due to GDG waveforms was dropped by 22% in comparison with charge balanced Gaussian waveforms without any delay between the cathodic and anodic parts and was also 60% lower than a rectangular charged balanced pulse with a delay between the cathodic and anodic parts of the waveform. Furthermore, by defining a Synchronization Level metric, we observed that the GDG waveform was able to reduce the synchronization of GPi neurons more effectively than any other waveform. The promising results of GDG waveforms in terms of eliciting action potential, desynchronization of the basal ganglia neurons and reduction of energy consumption can potentially enhance the performance of DBS
Directory of Open Access Journals (Sweden)
Mohammad Daneshzand
2017-08-01
Full Text Available Deep brain stimulation (DBS has compelling results in the desynchronization of the basal ganglia neuronal activities and thus, is used in treating the motor symptoms of Parkinson's disease (PD. Accurate definition of DBS waveform parameters could avert tissue or electrode damage, increase the neuronal activity and reduce energy cost which will prolong the battery life, hence avoiding device replacement surgeries. This study considers the use of a charge balanced Gaussian waveform pattern as a method to disrupt the firing patterns of neuronal cell activity. A computational model was created to simulate ganglia cells and their interactions with thalamic neurons. From the model, we investigated the effects of modified DBS pulse shapes and proposed a delay period between the cathodic and anodic parts of the charge balanced Gaussian waveform to desynchronize the firing patterns of the GPe and GPi cells. The results of the proposed Gaussian waveform with delay outperformed that of rectangular DBS waveforms used in in-vivo experiments. The Gaussian Delay Gaussian (GDG waveforms achieved lower number of misses in eliciting action potential while having a lower amplitude and shorter length of delay compared to numerous different pulse shapes. The amount of energy consumed in the basal ganglia network due to GDG waveforms was dropped by 22% in comparison with charge balanced Gaussian waveforms without any delay between the cathodic and anodic parts and was also 60% lower than a rectangular charged balanced pulse with a delay between the cathodic and anodic parts of the waveform. Furthermore, by defining a Synchronization Level metric, we observed that the GDG waveform was able to reduce the synchronization of GPi neurons more effectively than any other waveform. The promising results of GDG waveforms in terms of eliciting action potential, desynchronization of the basal ganglia neurons and reduction of energy consumption can potentially enhance the
International Nuclear Information System (INIS)
Ji, Se-Wan; Nha, Hyunchul; Kim, M S
2015-01-01
It is a topic of fundamental and practical importance how a quantum correlated state can be reliably distributed through a noisy channel for quantum information processing. The concept of quantum steering recently defined in a rigorous manner is relevant to study it under certain circumstances and here we address quantum steerability of Gaussian states to this aim. In particular, we attempt to reformulate the criterion for Gaussian steering in terms of local and global purities and show that it is sufficient and necessary for the case of steering a 1-mode system by an N-mode system. It subsequently enables us to reinforce a strong monogamy relation under which only one party can steer a local system of 1-mode. Moreover, we show that only a negative partial-transpose state can manifest quantum steerability by Gaussian measurements in relation to the Peres conjecture. We also discuss our formulation for the case of distributing a two-mode squeezed state via one-way quantum channels making dissipation and amplification effects, respectively. Finally, we extend our approach to include non-Gaussian measurements, more precisely, all orders of higher-order squeezing measurements, and find that this broad set of non-Gaussian measurements is not useful to demonstrate steering for Gaussian states beyond Gaussian measurements. (paper)
How Gaussian can our Universe be?
Cabass, G.; Pajer, E.; Schmidt, F.
2017-01-01
Gravity is a non-linear theory, and hence, barring cancellations, the initial super-horizon perturbations produced by inflation must contain some minimum amount of mode coupling, or primordial non-Gaussianity. In single-field slow-roll models, where this lower bound is saturated, non-Gaussianity is controlled by two observables: the tensor-to-scalar ratio, which is uncertain by more than fifty orders of magnitude; and the scalar spectral index, or tilt, which is relatively well measured. It is well known that to leading and next-to-leading order in derivatives, the contributions proportional to the tilt disappear from any local observable, and suspicion has been raised that this might happen to all orders, allowing for an arbitrarily low amount of primordial non-Gaussianity. Employing Conformal Fermi Coordinates, we show explicitly that this is not the case. Instead, a contribution of order the tilt appears in local observables. In summary, the floor of physical primordial non-Gaussianity in our Universe has a squeezed-limit scaling of kl2/ks2, similar to equilateral and orthogonal shapes, and a dimensionless amplitude of order 0.1 × (ns-1).
Gaussian vector fields on triangulated surfaces
DEFF Research Database (Denmark)
Ipsen, John H
2016-01-01
proven to be very useful to resolve the complex interplay between in-plane ordering of membranes and membrane conformations. In the present work we have developed a procedure for realistic representations of Gaussian models with in-plane vector degrees of freedoms on a triangulated surface. The method...
The Wehrl entropy has Gaussian optimizers
DEFF Research Database (Denmark)
De Palma, Giacomo
2018-01-01
We determine the minimum Wehrl entropy among the quantum states with a given von Neumann entropy and prove that it is achieved by thermal Gaussian states. This result determines the relation between the von Neumann and the Wehrl entropies. The key idea is proving that the quantum-classical channel...
How Gaussian can our Universe be?
Energy Technology Data Exchange (ETDEWEB)
Cabass, G. [Physics Department and INFN, Università di Roma ' ' La Sapienza' ' , P.le Aldo Moro 2, 00185, Rome (Italy); Pajer, E. [Institute for Theoretical Physics and Center for Extreme Matter and Emergent Phenomena, Utrecht University, Princetonplein 5, 3584 CC Utrecht (Netherlands); Schmidt, F., E-mail: giovanni.cabass@roma1.infn.it, E-mail: e.pajer@uu.nl, E-mail: fabians@mpa-garching.mpg.de [Max-Planck-Institut für Astrophysik, Karl-Schwarzschild-Str. 1, 85741 Garching (Germany)
2017-01-01
Gravity is a non-linear theory, and hence, barring cancellations, the initial super-horizon perturbations produced by inflation must contain some minimum amount of mode coupling, or primordial non-Gaussianity. In single-field slow-roll models, where this lower bound is saturated, non-Gaussianity is controlled by two observables: the tensor-to-scalar ratio, which is uncertain by more than fifty orders of magnitude; and the scalar spectral index, or tilt, which is relatively well measured. It is well known that to leading and next-to-leading order in derivatives, the contributions proportional to the tilt disappear from any local observable, and suspicion has been raised that this might happen to all orders, allowing for an arbitrarily low amount of primordial non-Gaussianity. Employing Conformal Fermi Coordinates, we show explicitly that this is not the case. Instead, a contribution of order the tilt appears in local observables. In summary, the floor of physical primordial non-Gaussianity in our Universe has a squeezed-limit scaling of k {sub ℓ}{sup 2}/ k {sub s} {sup 2}, similar to equilateral and orthogonal shapes, and a dimensionless amplitude of order 0.1 × ( n {sub s}−1).
Gaussian shaping filter for nuclear spectrometry
International Nuclear Information System (INIS)
Menezes, A.S.C. de.
1980-01-01
A theorical study of a gaussian shaping filter, using Pade approximation, for using in gamma spectroscopy is presented. This approximation has proved superior to the classical cascade RC integrators approximation in therms of signal-to-noise ratio and pulse simmetry. An experimental filter was designed, simulated in computer, constructed, and tested in the laboratory. (author) [pt
Asymptotic expansions for the Gaussian unitary ensemble
DEFF Research Database (Denmark)
Haagerup, Uffe; Thorbjørnsen, Steen
2012-01-01
Let g : R ¿ C be a C8-function with all derivatives bounded and let trn denote the normalized trace on the n × n matrices. In Ref. 3 Ercolani and McLaughlin established asymptotic expansions of the mean value ¿{trn(g(Xn))} for a rather general class of random matrices Xn, including the Gaussian U...
Chimera states in Gaussian coupled map lattices
Li, Xiao-Wen; Bi, Ran; Sun, Yue-Xiang; Zhang, Shuo; Song, Qian-Qian
2018-04-01
We study chimera states in one-dimensional and two-dimensional Gaussian coupled map lattices through simulations and experiments. Similar to the case of global coupling oscillators, individual lattices can be regarded as being controlled by a common mean field. A space-dependent order parameter is derived from a self-consistency condition in order to represent the collective state.
Gaussian curvature on hyperelliptic Riemann surfaces
Indian Academy of Sciences (India)
Indian Acad. Sci. (Math. Sci.) Vol. 124, No. 2, May 2014, pp. 155–167. c Indian Academy of Sciences. Gaussian curvature on hyperelliptic Riemann surfaces. ABEL CASTORENA. Centro de Ciencias Matemáticas (Universidad Nacional Autónoma de México,. Campus Morelia) Apdo. Postal 61-3 Xangari, C.P. 58089 Morelia,.
Additivity properties of a Gaussian channel
International Nuclear Information System (INIS)
Giovannetti, Vittorio; Lloyd, Seth
2004-01-01
The Amosov-Holevo-Werner conjecture implies the additivity of the minimum Renyi entropies at the output of a channel. The conjecture is proven true for all Renyi entropies of integer order greater than two in a class of Gaussian bosonic channel where the input signal is randomly displaced or where it is coupled linearly to an external environment
Modeling text with generalizable Gaussian mixtures
DEFF Research Database (Denmark)
Hansen, Lars Kai; Sigurdsson, Sigurdur; Kolenda, Thomas
2000-01-01
We apply and discuss generalizable Gaussian mixture (GGM) models for text mining. The model automatically adapts model complexity for a given text representation. We show that the generalizability of these models depends on the dimensionality of the representation and the sample size. We discuss...
Improving the gaussian effective potential: quantum mechanics
International Nuclear Information System (INIS)
Eboli, O.J.P.; Thomaz, M.T.; Lemos, N.A.
1990-08-01
In order to gain intuition for variational problems in field theory, we analyze variationally the quantum-mechanical anharmonic oscillator [(V(x)sup(k) - sub(2) x sup(2) + sup(λ) - sub(4) λ sup(4)]. Special attention is paid to improvements to the Gaussian effective potential. (author)
Open problems in Gaussian fluid queueing theory
Dȩbicki, K.; Mandjes, M.
2011-01-01
We present three challenging open problems that originate from the analysis of the asymptotic behavior of Gaussian fluid queueing models. In particular, we address the problem of characterizing the correlation structure of the stationary buffer content process, the speed of convergence to
Oracle Wiener filtering of a Gaussian signal
Babenko, A.; Belitser, E.
2011-01-01
We study the problem of filtering a Gaussian process whose trajectories, in some sense, have an unknown smoothness ß0 from the white noise of small intensity e. If we knew the parameter ß0, we would use the Wiener filter which has the meaning of oracle. Our goal is now to mimic the oracle, i.e.,
Oracle Wiener filtering of a Gaussian signal
Babenko, A.; Belitser, E.N.
2011-01-01
We study the problem of filtering a Gaussian process whose trajectories, in some sense, have an unknown smoothness β0 from the white noise of small intensity . If we knew the parameter β0, we would use the Wiener filter which has the meaning of oracle. Our goal is now to mimic the oracle, i.e.,
Perfusion Quantification Using Gaussian Process Deconvolution
DEFF Research Database (Denmark)
Andersen, Irene Klærke; Have, Anna Szynkowiak; Rasmussen, Carl Edward
2002-01-01
The quantification of perfusion using dynamic susceptibility contrast MRI (DSC-MRI) requires deconvolution to obtain the residual impulse response function (IRF). In this work, a method using the Gaussian process for deconvolution (GPD) is proposed. The fact that the IRF is smooth is incorporated...
Estimators for local non-Gaussianities
International Nuclear Information System (INIS)
Creminelli, P.; Senatore, L.; Zaldarriaga, M.
2006-05-01
We study the Likelihood function of data given f NL for the so-called local type of non-Gaussianity. In this case the curvature perturbation is a non-linear function, local in real space, of a Gaussian random field. We compute the Cramer-Rao bound for f NL and show that for small values of f NL the 3- point function estimator saturates the bound and is equivalent to calculating the full Likelihood of the data. However, for sufficiently large f NL , the naive 3-point function estimator has a much larger variance than previously thought. In the limit in which the departure from Gaussianity is detected with high confidence, error bars on f NL only decrease as 1/ln N pix rather than N pix -1/2 as the size of the data set increases. We identify the physical origin of this behavior and explain why it only affects the local type of non- Gaussianity, where the contribution of the first multipoles is always relevant. We find a simple improvement to the 3-point function estimator that makes the square root of its variance decrease as N pix -1/2 even for large f NL , asymptotically approaching the Cramer-Rao bound. We show that using the modified estimator is practically equivalent to computing the full Likelihood of f NL given the data. Thus other statistics of the data, such as the 4-point function and Minkowski functionals, contain no additional information on f NL . In particular, we explicitly show that the recent claims about the relevance of the 4-point function are not correct. By direct inspection of the Likelihood, we show that the data do not contain enough information for any statistic to be able to constrain higher order terms in the relation between the Gaussian field and the curvature perturbation, unless these are orders of magnitude larger than the size suggested by the current limits on f NL . (author)
Cosmological information in Gaussianized weak lensing signals
Joachimi, B.; Taylor, A. N.; Kiessling, A.
2011-11-01
Gaussianizing the one-point distribution of the weak gravitational lensing convergence has recently been shown to increase the signal-to-noise ratio contained in two-point statistics. We investigate the information on cosmology that can be extracted from the transformed convergence fields. Employing Box-Cox transformations to determine optimal transformations to Gaussianity, we develop analytical models for the transformed power spectrum, including effects of noise and smoothing. We find that optimized Box-Cox transformations perform substantially better than an offset logarithmic transformation in Gaussianizing the convergence, but both yield very similar results for the signal-to-noise ratio. None of the transformations is capable of eliminating correlations of the power spectra between different angular frequencies, which we demonstrate to have a significant impact on the errors in cosmology. Analytic models of the Gaussianized power spectrum yield good fits to the simulations and produce unbiased parameter estimates in the majority of cases, where the exceptions can be traced back to the limitations in modelling the higher order correlations of the original convergence. In the ideal case, without galaxy shape noise, we find an increase in the cumulative signal-to-noise ratio by a factor of 2.6 for angular frequencies up to ℓ= 1500, and a decrease in the area of the confidence region in the Ωm-σ8 plane, measured in terms of q-values, by a factor of 4.4 for the best performing transformation. When adding a realistic level of shape noise, all transformations perform poorly with little decorrelation of angular frequencies, a maximum increase in signal-to-noise ratio of 34 per cent, and even slightly degraded errors on cosmological parameters. We argue that to find Gaussianizing transformations of practical use, it will be necessary to go beyond transformations of the one-point distribution of the convergence, extend the analysis deeper into the non
Learning non-Gaussian Time Series using the Box-Cox Gaussian Process
Rios, Gonzalo; Tobar, Felipe
2018-01-01
Gaussian processes (GPs) are Bayesian nonparametric generative models that provide interpretability of hyperparameters, admit closed-form expressions for training and inference, and are able to accurately represent uncertainty. To model general non-Gaussian data with complex correlation structure, GPs can be paired with an expressive covariance kernel and then fed into a nonlinear transformation (or warping). However, overparametrising the kernel and the warping is known to, respectively, hin...
Yeung, Chuck
2018-06-01
The assumption that the local order parameter is related to an underlying spatially smooth auxiliary field, u (r ⃗,t ) , is a common feature in theoretical approaches to non-conserved order parameter phase separation dynamics. In particular, the ansatz that u (r ⃗,t ) is a Gaussian random field leads to predictions for the decay of the autocorrelation function which are consistent with observations, but distinct from predictions using alternative theoretical approaches. In this paper, the auxiliary field is obtained directly from simulations of the time-dependent Ginzburg-Landau equation in two and three dimensions. The results show that u (r ⃗,t ) is equivalent to the distance to the nearest interface. In two dimensions, the probability distribution, P (u ) , is well approximated as Gaussian except for small values of u /L (t ) , where L (t ) is the characteristic length-scale of the patterns. The behavior of P (u ) in three dimensions is more complicated; the non-Gaussian region for small u /L (t ) is much larger than that in two dimensions but the tails of P (u ) begin to approach a Gaussian form at intermediate times. However, at later times, the tails of the probability distribution appear to decay faster than a Gaussian distribution.
Performance of monitoring networks estimated from a Gaussian plume model
International Nuclear Information System (INIS)
Seebregts, A.J.; Hienen, J.F.A.
1990-10-01
In support of the ECN study on monitoring strategies after nuclear accidents, the present report describes the analysis of the performance of a monitoring network in a square grid. This network is used to estimate the distribution of the deposition pattern after a release of radioactivity into the atmosphere. The analysis is based upon a single release, a constant wind direction and an atmospheric dispersion according to a simplified Gaussian plume model. A technique is introduced to estimate the parameters in this Gaussian model based upon measurements at specific monitoring locations and linear regression, although this model is intrinsically non-linear. With these estimated parameters and the Gaussian model the distribution of the contamination due to deposition can be estimated. To investigate the relation between the network and the accuracy of the estimates for the deposition, deposition data have been generated by the Gaussian model, including a measurement error by a Monte Carlo simulation and this procedure has been repeated for several grid sizes, dispersion conditions, number of measurements per location, and errors per single measurement. The present technique has also been applied for the mesh sizes of two networks in the Netherlands, viz. the Landelijk Meetnet Radioaciviteit (National Measurement Network on Radioactivity, mesh size approx. 35 km) and the proposed Landelijk Meetnet Nucleaire Incidenten (National Measurement Network on Nuclear Incidents, mesh size approx. 15 km). The results show accuracies of 11 and 7 percent, respectively, if monitoring locations are used more than 10 km away from the postulated accident site. These figures are based upon 3 measurements per location and a dispersion during neutral weather with a wind velocity of 4 m/s. For stable weather conditions and low wind velocities, i.e. a small plume, the calculated accuracies are at least a factor 1.5 worse.The present type of analysis makes a cost-benefit approach to the
Optimal Packed String Matching
DEFF Research Database (Denmark)
Ben-Kiki, Oren; Bille, Philip; Breslauer, Dany
2011-01-01
In the packed string matching problem, each machine word accommodates – characters, thus an n-character text occupies n/– memory words. We extend the Crochemore-Perrin constantspace O(n)-time string matching algorithm to run in optimal O(n/–) time and even in real-time, achieving a factor – speed...
Ontology Matching Across Domains
2010-05-01
matching include GMO [1], Anchor-Prompt [2], and Similarity Flooding [3]. GMO is an iterative structural matcher, which uses RDF bipartite graphs to...AFRL under contract# FA8750-09-C-0058. References [1] Hu, W., Jian, N., Qu, Y., Wang, Y., “ GMO : a graph matching for ontologies”, in: Proceedings of
Large deviations for Gaussian processes in Hoelder norm
International Nuclear Information System (INIS)
Fatalov, V R
2003-01-01
Some results are proved on the exact asymptotic representation of large deviation probabilities for Gaussian processes in the Hoeder norm. The following classes of processes are considered: the Wiener process, the Brownian bridge, fractional Brownian motion, and stationary Gaussian processes with power-law covariance function. The investigation uses the method of double sums for Gaussian fields
Phase space structure of generalized Gaussian cat states
International Nuclear Information System (INIS)
Nicacio, Fernando; Maia, Raphael N.P.; Toscano, Fabricio; Vallejos, Raul O.
2010-01-01
We analyze generalized Gaussian cat states obtained by superposing arbitrary Gaussian states. The structure of the interference term of the Wigner function is always hyperbolic, surviving the action of a thermal reservoir. We also consider certain superpositions of mixed Gaussian states. An application to semiclassical dynamics is discussed.
On Alternate Relaying with Improper Gaussian Signaling
Gaafar, Mohamed
2016-06-06
In this letter, we investigate the potential benefits of adopting improper Gaussian signaling (IGS) in a two-hop alternate relaying (AR) system. Given the known benefits of using IGS in interference-limited networks, we propose to use IGS to relieve the inter-relay interference (IRI) impact on the AR system assuming no channel state information is available at the source. In this regard, we assume that the two relays use IGS and the source uses proper Gaussian signaling (PGS). Then, we optimize the degree of impropriety of the relays signal, measured by the circularity coefficient, to maximize the total achievable rate. Simulation results show that using IGS yields a significant performance improvement over PGS, especially when the first hop is a bottleneck due to weak source-relay channel gains and/or strong IRI.
On Alternate Relaying with Improper Gaussian Signaling
Gaafar, Mohamed; Amin, Osama; Ikhlef, Aissa; Chaaban, Anas; Alouini, Mohamed-Slim
2016-01-01
In this letter, we investigate the potential benefits of adopting improper Gaussian signaling (IGS) in a two-hop alternate relaying (AR) system. Given the known benefits of using IGS in interference-limited networks, we propose to use IGS to relieve the inter-relay interference (IRI) impact on the AR system assuming no channel state information is available at the source. In this regard, we assume that the two relays use IGS and the source uses proper Gaussian signaling (PGS). Then, we optimize the degree of impropriety of the relays signal, measured by the circularity coefficient, to maximize the total achievable rate. Simulation results show that using IGS yields a significant performance improvement over PGS, especially when the first hop is a bottleneck due to weak source-relay channel gains and/or strong IRI.
Direct Importance Estimation with Gaussian Mixture Models
Yamada, Makoto; Sugiyama, Masashi
The ratio of two probability densities is called the importance and its estimation has gathered a great deal of attention these days since the importance can be used for various data processing purposes. In this paper, we propose a new importance estimation method using Gaussian mixture models (GMMs). Our method is an extention of the Kullback-Leibler importance estimation procedure (KLIEP), an importance estimation method using linear or kernel models. An advantage of GMMs is that covariance matrices can also be learned through an expectation-maximization procedure, so the proposed method — which we call the Gaussian mixture KLIEP (GM-KLIEP) — is expected to work well when the true importance function has high correlation. Through experiments, we show the validity of the proposed approach.
Fractional Diffusion in Gaussian Noisy Environment
Directory of Open Access Journals (Sweden)
Guannan Hu
2015-03-01
Full Text Available We study the fractional diffusion in a Gaussian noisy environment as described by the fractional order stochastic heat equations of the following form: \\(D_t^{(\\alpha} u(t, x=\\textit{B}u+u\\cdot \\dot W^H\\, where \\(D_t^{(\\alpha}\\ is the Caputo fractional derivative of order \\(\\alpha\\in (0,1\\ with respect to the time variable \\(t\\, \\(\\textit{B}\\ is a second order elliptic operator with respect to the space variable \\(x\\in\\mathbb{R}^d\\ and \\(\\dot W^H\\ a time homogeneous fractional Gaussian noise of Hurst parameter \\(H=(H_1, \\cdots, H_d\\. We obtain conditions satisfied by \\(\\alpha\\ and \\(H\\, so that the square integrable solution \\(u\\ exists uniquely.
Extended Linear Models with Gaussian Priors
DEFF Research Database (Denmark)
Quinonero, Joaquin
2002-01-01
In extended linear models the input space is projected onto a feature space by means of an arbitrary non-linear transformation. A linear model is then applied to the feature space to construct the model output. The dimension of the feature space can be very large, or even infinite, giving the model...... a very big flexibility. Support Vector Machines (SVM's) and Gaussian processes are two examples of such models. In this technical report I present a model in which the dimension of the feature space remains finite, and where a Bayesian approach is used to train the model with Gaussian priors...... on the parameters. The Relevance Vector Machine, introduced by Tipping, is a particular case of such a model. I give the detailed derivations of the expectation-maximisation (EM) algorithm used in the training. These derivations are not found in the literature, and might be helpful for newcomers....
Interweave Cognitive Radio with Improper Gaussian Signaling
Hedhly, Wafa
2018-01-15
Improper Gaussian signaling (IGS) has proven its ability in improving the performance of underlay and overlay cognitive radio paradigms. In this paper, the interweave cognitive radio paradigm is studied when the cognitive user employs IGS. The instantaneous achievable rate performance of both the primary and secondary users are analyzed for specific secondary user sensing and detection capabilities. Next, the IGS scheme is optimized to maximize the achievable rate secondary user while satisfying a target minimum rate requirement for the primary user. Proper Gaussian signaling (PGS) scheme design is also derived to be used as benchmark of the IGS scheme design. Finally, different numerical results are introduced to show the gain reaped from adopting IGS over PGS under different system parameters. The main advantage of employing IGS is observed at low sensing and detection capabilities of the SU, lower PU direct link and higher SU interference on the PU side.
Image reconstruction under non-Gaussian noise
DEFF Research Database (Denmark)
Sciacchitano, Federica
During acquisition and transmission, images are often blurred and corrupted by noise. One of the fundamental tasks of image processing is to reconstruct the clean image from a degraded version. The process of recovering the original image from the data is an example of inverse problem. Due...... to the ill-posedness of the problem, the simple inversion of the degradation model does not give any good reconstructions. Therefore, to deal with the ill-posedness it is necessary to use some prior information on the solution or the model and the Bayesian approach. Additive Gaussian noise has been......D thesis intends to solve some of the many open questions for image restoration under non-Gaussian noise. The two main kinds of noise studied in this PhD project are the impulse noise and the Cauchy noise. Impulse noise is due to for instance the malfunctioning pixel elements in the camera sensors, errors...
Non-Markovianity of Gaussian Channels.
Torre, G; Roga, W; Illuminati, F
2015-08-14
We introduce a necessary and sufficient criterion for the non-Markovianity of Gaussian quantum dynamical maps based on the violation of divisibility. The criterion is derived by defining a general vectorial representation of the covariance matrix which is then exploited to determine the condition for the complete positivity of partial maps associated with arbitrary time intervals. Such construction does not rely on the Choi-Jamiolkowski representation and does not require optimization over states.
Recognition of Images Degraded by Gaussian Blur
Czech Academy of Sciences Publication Activity Database
Flusser, Jan; Farokhi, Sajad; Höschl, Cyril; Suk, Tomáš; Zitová, Barbara; Pedone, M.
2016-01-01
Roč. 25, č. 2 (2016), s. 790-806 ISSN 1057-7149 R&D Projects: GA ČR(CZ) GA15-16928S Institutional support: RVO:67985556 Keywords : Blurred image * object recognition * blur invariant comparison * Gaussian blur * projection operators * image moments * moment invariants Subject RIV: JD - Computer Applications, Robotics Impact factor: 4.828, year: 2016 http://library.utia.cas.cz/separaty/2016/ZOI/flusser-0454335.pdf
Adaptive multiple importance sampling for Gaussian processes
Czech Academy of Sciences Publication Activity Database
Xiong, X.; Šmídl, Václav; Filippone, M.
2017-01-01
Roč. 87, č. 8 (2017), s. 1644-1665 ISSN 0094-9655 R&D Projects: GA MŠk(CZ) 7F14287 Institutional support: RVO:67985556 Keywords : Gaussian Process * Bayesian estimation * Adaptive importance sampling Subject RIV: BB - Applied Statistics, Operational Research OBOR OECD: Statistics and probability Impact factor: 0.757, year: 2016 http://library.utia.cas.cz/separaty/2017/AS/smidl-0469804.pdf
Neutron inverse kinetics via Gaussian Processes
International Nuclear Information System (INIS)
Picca, Paolo; Furfaro, Roberto
2012-01-01
Highlights: ► A novel technique for the interpretation of experiments in ADS is presented. ► The technique is based on Bayesian regression, implemented via Gaussian Processes. ► GPs overcome the limits of classical methods, based on PK approximation. ► Results compares GPs and ANN performance, underlining similarities and differences. - Abstract: The paper introduces the application of Gaussian Processes (GPs) to determine the subcriticality level in accelerator-driven systems (ADSs) through the interpretation of pulsed experiment data. ADSs have peculiar kinetic properties due to their special core design. For this reason, classical – inversion techniques based on point kinetic (PK) generally fail to generate an accurate estimate of reactor subcriticality. Similarly to Artificial Neural Networks (ANNs), Gaussian Processes can be successfully trained to learn the underlying inverse neutron kinetic model and, as such, they are not limited to the model choice. Importantly, GPs are strongly rooted into the Bayes’ theorem which makes them a powerful tool for statistical inference. Here, GPs have been designed and trained on a set of kinetics models (e.g. point kinetics and multi-point kinetics) for homogeneous and heterogeneous settings. The results presented in the paper show that GPs are very efficient and accurate in predicting the reactivity for ADS-like systems. The variance computed via GPs may provide an indication on how to generate additional data as function of the desired accuracy.
Resonant non-Gaussianity with equilateral properties
International Nuclear Information System (INIS)
Gwyn, Rhiannon; Rummel, Markus
2012-11-01
We discuss the effect of superimposing multiple sources of resonant non-Gaussianity, which arise for instance in models of axion inflation. The resulting sum of oscillating shape contributions can be used to ''Fourier synthesize'' different non-oscillating shapes in the bispectrum. As an example we reproduce an approximately equilateral shape from the superposition of O(10) oscillatory contributions with resonant shape. This implies a possible degeneracy between the equilateral-type non-Gaussianity typical of models with non-canonical kinetic terms, such as DBI inflation, and an equilateral-type shape arising from a superposition of resonant-type contributions in theories with canonical kinetic terms. The absence of oscillations in the 2-point function together with the structure of the resonant N-point functions, imply that detection of equilateral non-Gaussianity at a level greater than the PLANCK sensitivity of f NL ∝O(5) will rule out a resonant origin. We comment on the questions arising from possible embeddings of this idea in a string theory setting.
Unitarily localizable entanglement of Gaussian states
International Nuclear Information System (INIS)
Serafini, Alessio; Adesso, Gerardo; Illuminati, Fabrizio
2005-01-01
We consider generic (mxn)-mode bipartitions of continuous-variable systems, and study the associated bisymmetric multimode Gaussian states. They are defined as (m+n)-mode Gaussian states invariant under local mode permutations on the m-mode and n-mode subsystems. We prove that such states are equivalent, under local unitary transformations, to the tensor product of a two-mode state and of m+n-2 uncorrelated single-mode states. The entanglement between the m-mode and the n-mode blocks can then be completely concentrated on a single pair of modes by means of local unitary operations alone. This result allows us to prove that the PPT (positivity of the partial transpose) condition is necessary and sufficient for the separability of (m+n)-mode bisymmetric Gaussian states. We determine exactly their negativity and identify a subset of bisymmetric states whose multimode entanglement of formation can be computed analytically. We consider explicit examples of pure and mixed bisymmetric states and study their entanglement scaling with the number of modes
Gaussian Hypothesis Testing and Quantum Illumination.
Wilde, Mark M; Tomamichel, Marco; Lloyd, Seth; Berta, Mario
2017-09-22
Quantum hypothesis testing is one of the most basic tasks in quantum information theory and has fundamental links with quantum communication and estimation theory. In this paper, we establish a formula that characterizes the decay rate of the minimal type-II error probability in a quantum hypothesis test of two Gaussian states given a fixed constraint on the type-I error probability. This formula is a direct function of the mean vectors and covariance matrices of the quantum Gaussian states in question. We give an application to quantum illumination, which is the task of determining whether there is a low-reflectivity object embedded in a target region with a bright thermal-noise bath. For the asymmetric-error setting, we find that a quantum illumination transmitter can achieve an error probability exponent stronger than a coherent-state transmitter of the same mean photon number, and furthermore, that it requires far fewer trials to do so. This occurs when the background thermal noise is either low or bright, which means that a quantum advantage is even easier to witness than in the symmetric-error setting because it occurs for a larger range of parameters. Going forward from here, we expect our formula to have applications in settings well beyond those considered in this paper, especially to quantum communication tasks involving quantum Gaussian channels.
Resonant non-Gaussianity with equilateral properties
Energy Technology Data Exchange (ETDEWEB)
Gwyn, Rhiannon [Max-Planck-Institut fuer Gravitationsphysik (Albert-Einstein-Institut), Potsdam (Germany); Rummel, Markus [Hamburg Univ. (Germany). 2. Inst. fuer Theoretische Physik; Westphal, Alexander [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany)
2012-11-15
We discuss the effect of superimposing multiple sources of resonant non-Gaussianity, which arise for instance in models of axion inflation. The resulting sum of oscillating shape contributions can be used to ''Fourier synthesize'' different non-oscillating shapes in the bispectrum. As an example we reproduce an approximately equilateral shape from the superposition of O(10) oscillatory contributions with resonant shape. This implies a possible degeneracy between the equilateral-type non-Gaussianity typical of models with non-canonical kinetic terms, such as DBI inflation, and an equilateral-type shape arising from a superposition of resonant-type contributions in theories with canonical kinetic terms. The absence of oscillations in the 2-point function together with the structure of the resonant N-point functions, imply that detection of equilateral non-Gaussianity at a level greater than the PLANCK sensitivity of f{sub NL} {proportional_to}O(5) will rule out a resonant origin. We comment on the questions arising from possible embeddings of this idea in a string theory setting.
Gaussian Process-Mixture Conditional Heteroscedasticity.
Platanios, Emmanouil A; Chatzis, Sotirios P
2014-05-01
Generalized autoregressive conditional heteroscedasticity (GARCH) models have long been considered as one of the most successful families of approaches for volatility modeling in financial return series. In this paper, we propose an alternative approach based on methodologies widely used in the field of statistical machine learning. Specifically, we propose a novel nonparametric Bayesian mixture of Gaussian process regression models, each component of which models the noise variance process that contaminates the observed data as a separate latent Gaussian process driven by the observed data. This way, we essentially obtain a Gaussian process-mixture conditional heteroscedasticity (GPMCH) model for volatility modeling in financial return series. We impose a nonparametric prior with power-law nature over the distribution of the model mixture components, namely the Pitman-Yor process prior, to allow for better capturing modeled data distributions with heavy tails and skewness. Finally, we provide a copula-based approach for obtaining a predictive posterior for the covariances over the asset returns modeled by means of a postulated GPMCH model. We evaluate the efficacy of our approach in a number of benchmark scenarios, and compare its performance to state-of-the-art methodologies.
Non-Gaussian conductivity fluctuations in semiconductors
International Nuclear Information System (INIS)
Melkonyan, S.V.
2010-01-01
A theoretical study is presented on the statistical properties of conductivity fluctuations caused by concentration and mobility fluctuations of the current carriers. It is established that mobility fluctuations result from random deviations in the thermal equilibrium distribution of the carriers. It is shown that mobility fluctuations have generation-recombination and shot components which do not satisfy the requirements of the central limit theorem, in contrast to the current carrier's concentration fluctuation and intraband component of the mobility fluctuation. It is shown that in general the mobility fluctuation consist of thermal (or intraband) Gaussian and non-thermal (or generation-recombination, shot, etc.) non-Gaussian components. The analyses of theoretical results and experimental data from literature show that the statistical properties of mobility fluctuation and of 1/f-noise fully coincide. The deviation from Gaussian statistics of the mobility or 1/f fluctuations goes hand in hand with the magnitude of non-thermal noise (generation-recombination, shot, burst, pulse noises, etc.).
Perturbative Gaussianizing transforms for cosmological fields
Hall, Alex; Mead, Alexander
2018-01-01
Constraints on cosmological parameters from large-scale structure have traditionally been obtained from two-point statistics. However, non-linear structure formation renders these statistics insufficient in capturing the full information content available, necessitating the measurement of higher order moments to recover information which would otherwise be lost. We construct quantities based on non-linear and non-local transformations of weakly non-Gaussian fields that Gaussianize the full multivariate distribution at a given order in perturbation theory. Our approach does not require a model of the fields themselves and takes as input only the first few polyspectra, which could be modelled or measured from simulations or data, making our method particularly suited to observables lacking a robust perturbative description such as the weak-lensing shear. We apply our method to simulated density fields, finding a significantly reduced bispectrum and an enhanced correlation with the initial field. We demonstrate that our method reconstructs a large proportion of the linear baryon acoustic oscillations, improving the information content over the raw field by 35 per cent. We apply the transform to toy 21 cm intensity maps, showing that our method still performs well in the presence of complications such as redshift-space distortions, beam smoothing, pixel noise and foreground subtraction. We discuss how this method might provide a route to constructing a perturbative model of the fully non-Gaussian multivariate likelihood function.
Quantum learning and universal quantum matching machine
International Nuclear Information System (INIS)
Sasaki, Masahide; Carlini, Alberto
2002-01-01
Suppose that three kinds of quantum systems are given in some unknown states vertical bar f> xN , vertical bar g 1 > xK , and vertical bar g 2 > xK , and we want to decide which template state vertical bar g 1 > or vertical bar g 2 >, each representing the feature of the pattern class C 1 or C 2 , respectively, is closest to the input feature state vertical bar f>. This is an extension of the pattern matching problem into the quantum domain. Assuming that these states are known a priori to belong to a certain parametric family of pure qubit systems, we derive two kinds of matching strategies. The first one is a semiclassical strategy that is obtained by the natural extension of conventional matching strategies and consists of a two-stage procedure: identification (estimation) of the unknown template states to design the classifier (learning process to train the classifier) and classification of the input system into the appropriate pattern class based on the estimated results. The other is a fully quantum strategy without any intermediate measurement, which we might call as the universal quantum matching machine. We present the Bayes optimal solutions for both strategies in the case of K=1, showing that there certainly exists a fully quantum matching procedure that is strictly superior to the straightforward semiclassical extension of the conventional matching strategy based on the learning process
Infographic explaining NCI-COG Pediatric MATCH, a cancer treatment clinical trial for children and adolescents, from 1 to 21 years of age, that is testing the use of precision medicine for pediatric cancers.
Data Matching Imputation System
National Oceanic and Atmospheric Administration, Department of Commerce — The DMIS dataset is a flat file record of the matching of several data set collections. Primarily it consists of VTRs, dealer records, Observer data in conjunction...
Lindén, J.; Lindberg, M.; Greggas, A.; Jylhävuori, N.; Norrgrann, H.; Lill, J. O.
2017-07-01
In addition to the main ingredients; sulfur, potassium chlorate and carbon, ordinary safety matches contain various dyes, glues etc, giving the head of the match an even texture and appealing color. Among the common reddish-brown matches there are several types, which after ignition can be attracted by a strong magnet. Before ignition the match head is generally not attracted by the magnet. An elemental analysis based on proton-induced x-ray emission was performed to single out iron as the element responsible for the observed magnetism. 57Fe Mössbauer spectroscopy was used for identifying the various types of iron-compounds, present before and after ignition, responsible for the macroscopic magnetism: Fe2O3 before and Fe3O4 after. The reaction was verified by mixing the main chemicals in the match-head with Fe2O3 in glue and mounting the mixture on a match stick. The ash residue after igniting the mixture was magnetic.
Searching for non-Gaussianity in the WMAP data
International Nuclear Information System (INIS)
Bernui, A.; Reboucas, M. J.
2009-01-01
Some analyses of recent cosmic microwave background (CMB) data have provided hints that there are deviations from Gaussianity in the WMAP CMB temperature fluctuations. Given the far-reaching consequences of such a non-Gaussianity for our understanding of the physics of the early universe, it is important to employ alternative indicators in order to determine whether the reported non-Gaussianity is of cosmological origin, and/or extract further information that may be helpful for identifying its causes. We propose two new non-Gaussianity indicators, based on skewness and kurtosis of large-angle patches of CMB maps, which provide a measure of departure from Gaussianity on large angular scales. A distinctive feature of these indicators is that they provide sky maps of non-Gaussianity of the CMB temperature data, thus allowing a possible additional window into their origins. Using these indicators, we find no significant deviation from Gaussianity in the three and five-year WMAP Internal Linear Combination (ILC) map with KQ75 mask, while the ILC unmasked map exhibits deviation from Gaussianity, quantifying therefore the WMAP team recommendation to employ the new mask KQ75 for tests of Gaussianity. We also use our indicators to test for Gaussianity the single frequency foreground unremoved WMAP three and five-year maps, and show that the K and Ka maps exhibit a clear indication of deviation from Gaussianity even with the KQ75 mask. We show that our findings are robust with respect to the details of the method.
A Monte Carlo simulation model for stationary non-Gaussian processes
DEFF Research Database (Denmark)
Grigoriu, M.; Ditlevsen, Ove Dalager; Arwade, S. R.
2003-01-01
includes translation processes and is useful for both Monte Carlo simulation and analytical studies. As for translation processes, the mixture of translation processes can have a wide range of marginal distributions and correlation functions. Moreover, these processes can match a broader range of second...... athe proposed Monte Carlo algorithm and compare features of translation processes and mixture of translation processes. Keywords: Monte Carlo simulation, non-Gaussian processes, sampling theorem, stochastic processes, translation processes......A class of stationary non-Gaussian processes, referred to as the class of mixtures of translation processes, is defined by their finite dimensional distributions consisting of mixtures of finite dimensional distributions of translation processes. The class of mixtures of translation processes...
Gaussian capacity of the quantum bosonic memory channel with additive correlated Gaussian noise
International Nuclear Information System (INIS)
Schaefer, Joachim; Karpov, Evgueni; Cerf, Nicolas J.
2011-01-01
We present an algorithm for calculation of the Gaussian classical capacity of a quantum bosonic memory channel with additive Gaussian noise. The algorithm, restricted to Gaussian input states, is applicable to all channels with noise correlations obeying certain conditions and works in the full input energy domain, beyond previous treatments of this problem. As an illustration, we study the optimal input states and capacity of a quantum memory channel with Gauss-Markov noise [J. Schaefer, Phys. Rev. A 80, 062313 (2009)]. We evaluate the enhancement of the transmission rate when using these optimal entangled input states by comparison with a product coherent-state encoding and find out that such a simple coherent-state encoding achieves not less than 90% of the capacity.
Jain, Anil K; Feng, Jianjiang
2009-06-01
The evidential value of palmprints in forensic applications is clear as about 30 percent of the latents recovered from crime scenes are from palms. While biometric systems for palmprint-based personal authentication in access control type of applications have been developed, they mostly deal with low-resolution (about 100 ppi) palmprints and only perform full-to-full palmprint matching. We propose a latent-to-full palmprint matching system that is needed in forensic applications. Our system deals with palmprints captured at 500 ppi (the current standard in forensic applications) or higher resolution and uses minutiae as features to be compatible with the methodology used by latent experts. Latent palmprint matching is a challenging problem because latent prints lifted at crime scenes are of poor image quality, cover only a small area of the palm, and have a complex background. Other difficulties include a large number of minutiae in full prints (about 10 times as many as fingerprints), and the presence of many creases in latents and full prints. A robust algorithm to reliably estimate the local ridge direction and frequency in palmprints is developed. This facilitates the extraction of ridge and minutiae features even in poor quality palmprints. A fixed-length minutia descriptor, MinutiaCode, is utilized to capture distinctive information around each minutia and an alignment-based minutiae matching algorithm is used to match two palmprints. Two sets of partial palmprints (150 live-scan partial palmprints and 100 latent palmprints) are matched to a background database of 10,200 full palmprints to test the proposed system. Despite the inherent difficulty of latent-to-full palmprint matching, rank-1 recognition rates of 78.7 and 69 percent, respectively, were achieved in searching live-scan partial palmprints and latent palmprints against the background database.
High-Order Local Pooling and Encoding Gaussians Over a Dictionary of Gaussians.
Li, Peihua; Zeng, Hui; Wang, Qilong; Shiu, Simon C K; Zhang, Lei
2017-07-01
Local pooling (LP) in configuration (feature) space proposed by Boureau et al. explicitly restricts similar features to be aggregated, which can preserve as much discriminative information as possible. At the time it appeared, this method combined with sparse coding achieved competitive classification results with only a small dictionary. However, its performance lags far behind the state-of-the-art results as only the zero-order information is exploited. Inspired by the success of high-order statistical information in existing advanced feature coding or pooling methods, we make an attempt to address the limitation of LP. To this end, we present a novel method called high-order LP (HO-LP) to leverage the information higher than the zero-order one. Our idea is intuitively simple: we compute the first- and second-order statistics per configuration bin and model them as a Gaussian. Accordingly, we employ a collection of Gaussians as visual words to represent the universal probability distribution of features from all classes. Our problem is naturally formulated as encoding Gaussians over a dictionary of Gaussians as visual words. This problem, however, is challenging since the space of Gaussians is not a Euclidean space but forms a Riemannian manifold. We address this challenge by mapping Gaussians into the Euclidean space, which enables us to perform coding with common Euclidean operations rather than complex and often expensive Riemannian operations. Our HO-LP preserves the advantages of the original LP: pooling only similar features and using a small dictionary. Meanwhile, it achieves very promising performance on standard benchmarks, with either conventional, hand-engineered features or deep learning-based features.
Area of isodensity contours in Gaussian and non-Gaussian fields
International Nuclear Information System (INIS)
Ryden, B.S.
1988-01-01
The area of isodensity contours in a smoothed density field can be measured by the contour-crossing statistic N1, the number of times per unit length that a line drawn through the density field pierces an isodensity contour. The contour-crossing statistic distinguishes between Gaussian and non-Gaussian fields and provides a measure of the effective slope of the power spectrum. The statistic is easy to apply and can be used on pencil beams and slices as well as on a three-dimensional field. 10 references
Stochastic differential calculus for Gaussian and non-Gaussian noises: A critical review
Falsone, G.
2018-03-01
In this paper a review of the literature works devoted to the study of stochastic differential equations (SDEs) subjected to Gaussian and non-Gaussian white noises and to fractional Brownian noises is given. In these cases, particular attention must be paid in treating the SDEs because the classical rules of the differential calculus, as the Newton-Leibnitz one, cannot be applied or are applicable with many difficulties. Here all the principal approaches solving the SDEs are reported for any kind of noise, highlighting the negative and positive properties of each one and making the comparisons, where it is possible.
International Nuclear Information System (INIS)
Liu Shixiong; Guo Hong; Liu Mingwei; Wu Guohua
2004-01-01
Propagation characteristics of focused Gaussian beam (FoGB) and fundamental Gaussian beam (FuGB) propagating in vacuum are investigated. Based on the Fourier transform and the angular spectral analysis, the transverse component and the second-order approximate longitudinal component of the electric field are obtained in the paraxial approximation. The electric field components, the phase velocity and the group velocity of FoGB are compared with those of FuGB. The spot size of FoGB is also discussed
International Nuclear Information System (INIS)
Tan, Cheng-Yang; Fermilab
2006-01-01
One common way for measuring the emittance of an electron beam is with the slits method. The usual approach for analyzing the data is to calculate an emittance that is a subset of the parent emittance. This paper shows an alternative way by using the method of correlations which ties the parameters derived from the beamlets to the actual parameters of the parent emittance. For parent distributions that are Gaussian, this method yields exact results. For non-Gaussian beam distributions, this method yields an effective emittance that can serve as a yardstick for emittance comparisons
Approaches for Stereo Matching
Directory of Open Access Journals (Sweden)
Takouhi Ozanian
1995-04-01
Full Text Available This review focuses on the last decade's development of the computational stereopsis for recovering three-dimensional information. The main components of the stereo analysis are exposed: image acquisition and camera modeling, feature selection, feature matching and disparity interpretation. A brief survey is given of the well known feature selection approaches and the estimation parameters for this selection are mentioned. The difficulties in identifying correspondent locations in the two images are explained. Methods as to how effectively to constrain the search for correct solution of the correspondence problem are discussed, as are strategies for the whole matching process. Reasons for the occurrence of matching errors are considered. Some recently proposed approaches, employing new ideas in the modeling of stereo matching in terms of energy minimization, are described. Acknowledging the importance of computation time for real-time applications, special attention is paid to parallelism as a way to achieve the required level of performance. The development of trinocular stereo analysis as an alternative to the conventional binocular one, is described. Finally a classification based on the test images for verification of the stereo matching algorithms, is supplied.
Non-Gaussianity from Broken Symmetries
Kolb, Edward W; Vallinotto, A; Kolb, Edward W.; Riotto, Antonio; Vallinotto, Alberto
2006-01-01
Recently we studied inflation models in which the inflaton potential is characterized by an underlying approximate global symmetry. In the first work we pointed out that in such a model curvature perturbations are generated after the end of the slow-roll phase of inflation. In this work we develop further the observational implications of the model and compute the degree of non-Gaussianity predicted in the scenario. We find that the corresponding nonlinearity parameter, $f_{NL}$, can be as large as 10^2.
First Passage Time Intervals of Gaussian Processes
Perez, Hector; Kawabata, Tsutomu; Mimaki, Tadashi
1987-08-01
The first passage time problem of a stationary Guassian process is theretically and experimentally studied. Renewal functions are derived for a time-dependent boundary and numerically calculated for a Gaussian process having a seventh-order Butterworth spectrum. The results show a multipeak property not only for the constant boundary but also for a linearly increasing boundary. The first passage time distribution densities were experimentally determined for a constant boundary. The renewal functions were shown to be a fairly good approximation to the distribution density over a limited range.
CMB constraints on running non-Gaussianity
Oppizzi, Filippo; Liguori, Michele; Renzi, Alessandro; Arroja, Frederico; Bartolo, Nicola
2017-01-01
We develop a complete set of tools for CMB forecasting, simulation and estimation of primordial running bispectra, arising from a variety of curvaton and single-field (DBI) models of Inflation. We validate our pipeline using mock CMB running non-Gaussianity realizations and test it on real data by obtaining experimental constraints on the $f_{\\rm NL}$ running spectral index, $n_{\\rm NG}$, using WMAP 9-year data. Our final bounds (68\\% C.L.) read $-0.3< n_{\\rm NG}
Turbo Equalization Using Partial Gaussian Approximation
DEFF Research Database (Denmark)
Zhang, Chuanzong; Wang, Zhongyong; Manchón, Carles Navarro
2016-01-01
This letter deals with turbo equalization for coded data transmission over intersymbol interference (ISI) channels. We propose a message-passing algorithm that uses the expectation propagation rule to convert messages passed from the demodulator and decoder to the equalizer and computes messages...... returned by the equalizer by using a partial Gaussian approximation (PGA). We exploit the specific structure of the ISI channel model to compute the latter messages from the beliefs obtained using a Kalman smoother/equalizer. Doing so leads to a significant complexity reduction compared to the initial PGA...
Optical trapping with Super-Gaussian beams
CSIR Research Space (South Africa)
Mc
2013-04-01
Full Text Available stream_source_info McLaren1_2013.pdf.txt stream_content_type text/plain stream_size 2236 Content-Encoding UTF-8 stream_name McLaren1_2013.pdf.txt Content-Type text/plain; charset=UTF-8 JT2A.34.pdf Optics in the Life... Sciences Congress Technical Digest © 2013 The Optical Society (OSA) Optical trapping with Super-Gaussian beams Melanie McLaren, Thulile Khanyile, Patience Mthunzi and Andrew Forbes* National Laser Centre, Council for Scientific and Industrial Research...
Bregman Cost for Non-Gaussian Noise
DEFF Research Database (Denmark)
Burger, Martin; Dong, Yiqiu; Sciacchitano, Federica
estimator for the Bregman cost if the image is corrupted by Gaussian noise. In this work we extend this result to other noise models with log-concave likelihood density, by introducing two related Bregman cost functions for which the CM and the MAP estimates are proper Bayes estima-tors. Moreover, we also....... From a theoretical point of view it has been argued that the MAP estimate is only in an asymptotic sense a Bayes estimator for the uniform cost function, while the CM estimate is a Bayes estimator for the means squared cost function. Recently, it has been proven that the MAP estimate is a proper Bayes...
The Experimental Verification of Gaussian Beam Coupling for ECH Transmission Line at 400 GHz
Directory of Open Access Journals (Sweden)
Choe Mun Seok
2017-01-01
Full Text Available We design a quasi-optical transmission line system for a 400 GHz gyrotron beam. The 400GHz Gaussian beam is injected to a corrugated waveguide bounced from a quasi-optical mirror. From detailed 2D field patterns of the output beam emitted from the corrugated waveguide, we analyze the mode contents and the source of non-ideal beam expansion
Confronting Passive and Active Sensors with Non-Gaussian Statistics
Directory of Open Access Journals (Sweden)
Pablo Rodríguez-Gonzálvez
2014-07-01
Full Text Available This paper has two motivations: firstly, to compare the Digital Surface Models (DSM derived by passive (digital camera and by active (terrestrial laser scanner remote sensing systems when applied to specific architectural objects, and secondly, to test how well the Gaussian classic statistics, with its Least Squares principle, adapts to data sets where asymmetrical gross errors may appear and whether this approach should be changed for a non-parametric one. The field of geomatic technology automation is immersed in a high demanding competition in which any innovation by one of the contenders immediately challenges the opponents to propose a better improvement. Nowadays, we seem to be witnessing an improvement of terrestrial photogrammetry and its integration with computer vision to overcome the performance limitations of laser scanning methods. Through this contribution some of the issues of this “technological race” are examined from the point of view of photogrammetry. A new software is introduced and an experimental test is designed, performed and assessed to try to cast some light on this thrilling match. For the case considered in this study, the results show good agreement between both sensors, despite considerable asymmetry. This asymmetry suggests that the standard Normal parameters are not adequate to assess this type of data, especially when accuracy is of importance. In this case, standard deviation fails to provide a good estimation of the results, whereas the results obtained for the Median Absolute Deviation and for the Biweight Midvariance are more appropriate measures.
Unsupervised learning of binary vectors: A Gaussian scenario
International Nuclear Information System (INIS)
Copelli, Mauro; Van den Broeck, Christian
2000-01-01
We study a model of unsupervised learning where the real-valued data vectors are isotropically distributed, except for a single symmetry-breaking binary direction B(set-membership sign){-1,+1} N , onto which the projections have a Gaussian distribution. We show that a candidate vector J undergoing Gibbs learning in this discrete space, approaches the perfect match J=B exponentially. In addition to the second-order ''retarded learning'' phase transition for unbiased distributions, we show that first-order transitions can also occur. Extending the known result that the center of mass of the Gibbs ensemble has Bayes-optimal performance, we show that taking the sign of the components of this vector (clipping) leads to the vector with optimal performance in the binary space. These upper bounds are shown generally not to be saturated with the technique of transforming the components of a special continuous vector, except in asymptotic limits and in a special linear case. Simulations are presented which are in excellent agreement with the theoretical results. (c) 2000 The American Physical Society
Generation of Stationary Non-Gaussian Time Histories with a Specified Cross-spectral Density
Directory of Open Access Journals (Sweden)
David O. Smallwood
1997-01-01
Full Text Available The paper reviews several methods for the generation of stationary realizations of sampled time histories with non-Gaussian distributions and introduces a new method which can be used to control the cross-spectral density matrix and the probability density functions (pdfs of the multiple input problem. Discussed first are two methods for the specialized case of matching the auto (power spectrum, the skewness, and kurtosis using generalized shot noise and using polynomial functions. It is then shown that the skewness and kurtosis can also be controlled by the phase of a complex frequency domain description of the random process. The general case of matching a target probability density function using a zero memory nonlinear (ZMNL function is then covered. Next methods for generating vectors of random variables with a specified covariance matrix for a class of spherically invariant random vectors (SIRV are discussed. Finally the general case of matching the cross-spectral density matrix of a vector of inputs with non-Gaussian marginal distributions is presented.
Characterisation of random Gaussian and non-Gaussian stress processes in terms of extreme responses
Directory of Open Access Journals (Sweden)
Colin Bruno
2015-01-01
Full Text Available In the field of military land vehicles, random vibration processes generated by all-terrain wheeled vehicles in motion are not classical stochastic processes with a stationary and Gaussian nature. Non-stationarity of processes induced by the variability of the vehicle speed does not form a major difficulty because the designer can have good control over the vehicle speed by characterising the histogram of instantaneous speed of the vehicle during an operational situation. Beyond this non-stationarity problem, the hard point clearly lies in the fact that the random processes are not Gaussian and are generated mainly by the non-linear behaviour of the undercarriage and the strong occurrence of shocks generated by roughness of the terrain. This non-Gaussian nature is expressed particularly by very high flattening levels that can affect the design of structures under extreme stresses conventionally acquired by spectral approaches, inherent to Gaussian processes and based essentially on spectral moments of stress processes. Due to these technical considerations, techniques for characterisation of random excitation processes generated by this type of carrier need to be changed, by proposing innovative characterisation methods based on time domain approaches as described in the body of the text rather than spectral domain approaches.
DEFF Research Database (Denmark)
Møller, Jesper; Jacobsen, Robert Dahl
We introduce a promising alternative to the usual hidden Markov tree model for Gaussian wavelet coefficients, where their variances are specified by the hidden states and take values in a finite set. In our new model, the hidden states have a similar dependence structure but they are jointly Gaus...
DEFF Research Database (Denmark)
Jacobsen, Christian Robert Dahl; Møller, Jesper
2017-01-01
We introduce new estimation methods for a subclass of the Gaussian scale mixture models for wavelet trees by Wainwright, Simoncelli and Willsky that rely on modern results for composite likelihoods and approximate Bayesian inference. Our methodology is illustrated for denoising and edge detection...
Approximation problems with the divergence criterion for Gaussian variablesand Gaussian processes
A.A. Stoorvogel; J.H. van Schuppen (Jan)
1996-01-01
textabstractSystem identification for stationary Gaussian processes includes an approximation problem. Currently the subspace algorithm for this problem enjoys much attention. This algorithm is based on a transformation of a finite time series to canonical variable form followed by a truncation.
Comparison of Gaussian and non-Gaussian Atmospheric Profile Retrievals from Satellite Microwave Data
Kliewer, A.; Forsythe, J. M.; Fletcher, S. J.; Jones, A. S.
2017-12-01
The Cooperative Institute for Research in the Atmosphere at Colorado State University has recently developed two different versions of a mixed-distribution (lognormal combined with a Gaussian) based microwave temperature and mixing ratio retrieval system as well as the original Gaussian-based approach. These retrieval systems are based upon 1DVAR theory but have been adapted to use different descriptive statistics of the lognormal distribution to minimize the background errors. The input radiance data is from the AMSU-A and MHS instruments on the NOAA series of spacecraft. To help illustrate how the three retrievals are affected by the change in the distribution we are in the process of creating a new website to show the output from the different retrievals. Here we present initial results from different dynamical situations to show how the tool could be used by forecasters as well as for educators. However, as the new retrieved values are from a non-Gaussian based 1DVAR then they will display non-Gaussian behaviors that need to pass a quality control measure that is consistent with this distribution, and these new measures are presented here along with initial results for checking the retrievals.
School Library Media Activities Monthly, 1996
1996-01-01
Giving students a chance to associate numbers with subjects can be useful in speeding their location of desired print or nonprint materials and helping students feel independent when browsing. A matching game for helping students learn the Dewey numbers is presented. Instructions for the library media specialist or teacher, instructions for…
Directory of Open Access Journals (Sweden)
Nima Tabatabaei
2018-04-01
Full Text Available Conventional infrared thermography techniques, including pulsed and lock-in thermography, have shown great potential for non-destructive evaluation of broad spectrum of materials, spanning from metals to polymers to biological tissues. However, performance of these techniques is often limited due to the diffuse nature of thermal wave fields, resulting in an inherent compromise between inspection depth and depth resolution. Recently, matched-filter thermography has been introduced as a means for overcoming this classic limitation to enable depth-resolved subsurface thermal imaging and improving axial/depth resolution. This paper reviews the basic principles and experimental results of matched-filter thermography: first, mathematical and signal processing concepts related to matched-fileting and pulse compression are discussed. Next, theoretical modeling of thermal-wave responses to matched-filter thermography using two categories of pulse compression techniques (linear frequency modulation and binary phase coding are reviewed. Key experimental results from literature demonstrating the maintenance of axial resolution while inspecting deep into opaque and turbid media are also presented and discussed. Finally, the concept of thermal coherence tomography for deconvolution of thermal responses of axially superposed sources and creation of depth-selective images in a diffusion-wave field is reviewed.
DEFF Research Database (Denmark)
Hartelius, Karsten; Carstensen, Jens Michael
2003-01-01
A method for locating distorted grid structures in images is presented. The method is based on the theories of template matching and Bayesian image restoration. The grid is modeled as a deformable template. Prior knowledge of the grid is described through a Markov random field (MRF) model which r...
Gallistel, C. R.; King, Adam Philip; Gottlieb, Daniel; Balci, Fuat; Papachristos, Efstathios B.; Szalecki, Matthew; Carbone, Kimberly S.
2007-01-01
Experimentally naive mice matched the proportions of their temporal investments (visit durations) in two feeding hoppers to the proportions of the food income (pellets per unit session time) derived from them in three experiments that varied the coupling between the behavioral investment and food income, from no coupling to strict coupling.…
Functional Dual Adaptive Control with Recursive Gaussian Process Model
International Nuclear Information System (INIS)
Prüher, Jakub; Král, Ladislav
2015-01-01
The paper deals with dual adaptive control problem, where the functional uncertainties in the system description are modelled by a non-parametric Gaussian process regression model. Current approaches to adaptive control based on Gaussian process models are severely limited in their practical applicability, because the model is re-adjusted using all the currently available data, which keeps growing with every time step. We propose the use of recursive Gaussian process regression algorithm for significant reduction in computational requirements, thus bringing the Gaussian process-based adaptive controllers closer to their practical applicability. In this work, we design a bi-criterial dual controller based on recursive Gaussian process model for discrete-time stochastic dynamic systems given in an affine-in-control form. Using Monte Carlo simulations, we show that the proposed controller achieves comparable performance with the full Gaussian process-based controller in terms of control quality while keeping the computational demands bounded. (paper)
A Gaussian Approximation Potential for Silicon
Bernstein, Noam; Bartók, Albert; Kermode, James; Csányi, Gábor
We present an interatomic potential for silicon using the Gaussian Approximation Potential (GAP) approach, which uses the Gaussian process regression method to approximate the reference potential energy surface as a sum of atomic energies. Each atomic energy is approximated as a function of the local environment around the atom, which is described with the smooth overlap of atomic environments (SOAP) descriptor. The potential is fit to a database of energies, forces, and stresses calculated using density functional theory (DFT) on a wide range of configurations from zero and finite temperature simulations. These include crystalline phases, liquid, amorphous, and low coordination structures, and diamond-structure point defects, dislocations, surfaces, and cracks. We compare the results of the potential to DFT calculations, as well as to previously published models including Stillinger-Weber, Tersoff, modified embedded atom method (MEAM), and ReaxFF. We show that it is very accurate as compared to the DFT reference results for a wide range of properties, including low energy bulk phases, liquid structure, as well as point, line, and plane defects in the diamond structure.
Statistics of peaks of Gaussian random fields
International Nuclear Information System (INIS)
Bardeen, J.M.; Bond, J.R.; Kaiser, N.; Szalay, A.S.; Stanford Univ., CA; California Univ., Berkeley; Cambridge Univ., England; Fermi National Accelerator Lab., Batavia, IL)
1986-01-01
A set of new mathematical results on the theory of Gaussian random fields is presented, and the application of such calculations in cosmology to treat questions of structure formation from small-amplitude initial density fluctuations is addressed. The point process equation is discussed, giving the general formula for the average number density of peaks. The problem of the proper conditional probability constraints appropriate to maxima are examined using a one-dimensional illustration. The average density of maxima of a general three-dimensional Gaussian field is calculated as a function of heights of the maxima, and the average density of upcrossing points on density contour surfaces is computed. The number density of peaks subject to the constraint that the large-scale density field be fixed is determined and used to discuss the segregation of high peaks from the underlying mass distribution. The machinery to calculate n-point peak-peak correlation functions is determined, as are the shapes of the profiles about maxima. 67 references
Versatile Gaussian probes for squeezing estimation
Rigovacca, Luca; Farace, Alessandro; Souza, Leonardo A. M.; De Pasquale, Antonella; Giovannetti, Vittorio; Adesso, Gerardo
2017-05-01
We consider an instance of "black-box" quantum metrology in the Gaussian framework, where we aim to estimate the amount of squeezing applied on an input probe, without previous knowledge on the phase of the applied squeezing. By taking the quantum Fisher information (QFI) as the figure of merit, we evaluate its average and variance with respect to this phase in order to identify probe states that yield good precision for many different squeezing directions. We first consider the case of single-mode Gaussian probes with the same energy, and find that pure squeezed states maximize the average quantum Fisher information (AvQFI) at the cost of a performance that oscillates strongly as the squeezing direction is changed. Although the variance can be brought to zero by correlating the probing system with a reference mode, the maximum AvQFI cannot be increased in the same way. A different scenario opens if one takes into account the effects of photon losses: coherent states represent the optimal single-mode choice when losses exceed a certain threshold and, moreover, correlated probes can now yield larger AvQFI values than all single-mode states, on top of having zero variance.
Finite Range Decomposition of Gaussian Processes
Brydges, C D; Mitter, P K
2003-01-01
Let $D$ be the finite difference Laplacian associated to the lattice $bZ^{d}$. For dimension $dge 3$, $age 0$ and $L$ a sufficiently large positive dyadic integer, we prove that the integral kernel of the resolvent $G^{a}:=(a-D)^{-1}$ can be decomposed as an infinite sum of positive semi-definite functions $ V_{n} $ of finite range, $ V_{n} (x-y) = 0$ for $|x-y|ge O(L)^{n}$. Equivalently, the Gaussian process on the lattice with covariance $G^{a}$ admits a decomposition into independent Gaussian processes with finite range covariances. For $a=0$, $ V_{n} $ has a limiting scaling form $L^{-n(d-2)}Gamma_{ c,ast }{bigl (frac{x-y}{ L^{n}}bigr )}$ as $nrightarrow infty$. As a corollary, such decompositions also exist for fractional powers $(-D)^{-alpha/2}$, $0
Matching Supernovae to Galaxies
Kohler, Susanna
2016-12-01
developed a new automated algorithm for matching supernovae to their host galaxies. Their work builds on currently existing algorithms and makes use of information about the nearby galaxies, accounts for the uncertainty of the match, and even includes a machine learning component to improve the matching accuracy.Gupta and collaborators test their matching algorithm on catalogs of galaxies and simulated supernova events to quantify how well the algorithm is able to accurately recover the true hosts.Successful MatchingThe matching algorithms accuracy (purity) as a function of the true supernova-host separation, the supernova redshift, the true hosts brightness, and the true hosts size. [Gupta et al. 2016]The authors find that when the basic algorithm is run on catalog data, it matches supernovae to their hosts with 91% accuracy. Including the machine learning component, which is run after the initial matching algorithm, improves the accuracy of the matching to 97%.The encouraging results of this work which was intended as a proof of concept suggest that methods similar to this could prove very practical for tackling future survey data. And the method explored here has use beyond matching just supernovae to their host galaxies: it could also be applied to other extragalactic transients, such as gamma-ray bursts, tidal disruption events, or electromagnetic counterparts to gravitational-wave detections.CitationRavi R. Gupta et al 2016 AJ 152 154. doi:10.3847/0004-6256/152/6/154
Directory of Open Access Journals (Sweden)
Georgios C Manikis
Full Text Available The purpose of this study was to compare the performance of four diffusion models, including mono and bi-exponential both Gaussian and non-Gaussian models, in diffusion weighted imaging of rectal cancer.Nineteen patients with rectal adenocarcinoma underwent MRI examination of the rectum before chemoradiation therapy including a 7 b-value diffusion sequence (0, 25, 50, 100, 500, 1000 and 2000 s/mm2 at a 1.5T scanner. Four different diffusion models including mono- and bi-exponential Gaussian (MG and BG and non-Gaussian (MNG and BNG were applied on whole tumor volumes of interest. Two different statistical criteria were recruited to assess their fitting performance, including the adjusted-R2 and Root Mean Square Error (RMSE. To decide which model better characterizes rectal cancer, model selection was relied on Akaike Information Criteria (AIC and F-ratio.All candidate models achieved a good fitting performance with the two most complex models, the BG and the BNG, exhibiting the best fitting performance. However, both criteria for model selection indicated that the MG model performed better than any other model. In particular, using AIC Weights and F-ratio, the pixel-based analysis demonstrated that tumor areas better described by the simplest MG model in an average area of 53% and 33%, respectively. Non-Gaussian behavior was illustrated in an average area of 37% according to the F-ratio, and 7% using AIC Weights. However, the distributions of the pixels best fitted by each of the four models suggest that MG failed to perform better than any other model in all patients, and the overall tumor area.No single diffusion model evaluated herein could accurately describe rectal tumours. These findings probably can be explained on the basis of increased tumour heterogeneity, where areas with high vascularity could be fitted better with bi-exponential models, and areas with necrosis would mostly follow mono-exponential behavior.
Relative entropy as a measure of entanglement for Gaussian states
Institute of Scientific and Technical Information of China (English)
Lu Huai-Xin; Zhao Bo
2006-01-01
In this paper, we derive an explicit analytic expression of the relative entropy between two general Gaussian states. In the restriction of the set for Gaussian states and with the help of relative entropy formula and Peres-Simon separability criterion, one can conveniently obtain the relative entropy entanglement for Gaussian states. As an example,the relative entanglement for a two-mode squeezed thermal state has been obtained.
[Propensity score matching in SPSS].
Huang, Fuqiang; DU, Chunlin; Sun, Menghui; Ning, Bing; Luo, Ying; An, Shengli
2015-11-01
To realize propensity score matching in PS Matching module of SPSS and interpret the analysis results. The R software and plug-in that could link with the corresponding versions of SPSS and propensity score matching package were installed. A PS matching module was added in the SPSS interface, and its use was demonstrated with test data. Score estimation and nearest neighbor matching was achieved with the PS matching module, and the results of qualitative and quantitative statistical description and evaluation were presented in the form of a graph matching. Propensity score matching can be accomplished conveniently using SPSS software.
Overlay Spectrum Sharing using Improper Gaussian Signaling
Amin, Osama; Abediseid, Walid; Alouini, Mohamed-Slim
2016-01-01
in overlay cognitive radio system, where the secondary transmitter broadcasts a mixture of two different signals. The first signal is selected from the PGS scheme to match the primary message transmission. On the other hand, the second signal is chosen
Gaussian beam-to-slab waveguide coupler by graded index photonic crystal lens
International Nuclear Information System (INIS)
Bahari, B; Abrishamian, M S
2013-01-01
In this numerical study, a Gaussian beam-to-slab waveguide coupler for both modes of TM and TE has been studied. For this purpose, a concrete structure is suggested, in which the graded index photonic crystal lens and the slab waveguide are in the same structure composed of Si material, and can be fabricated with a single-step lithography process. For maximum power coupling, half-holes have been used as an input matching layer. Power coupling of 80% over a 450 nm bandwidth for the TM mode, and 60% over a 180 nm bandwidth for the TE mode is achieved. (paper)
Prediction and retrodiction with continuously monitored Gaussian states
DEFF Research Database (Denmark)
Zhang, Jinglei; Mølmer, Klaus
2017-01-01
Gaussian states of quantum oscillators are fully characterized by the mean values and the covariance matrix of their quadrature observables. We consider the dynamics of a system of oscillators subject to interactions, damping, and continuous probing which maintain their Gaussian state property......(t)$ to Gaussian states implies that the matrix $E(t)$ is also fully characterized by a vector of mean values and a covariance matrix. We derive the dynamical equations for these quantities and we illustrate their use in the retrodiction of measurements on Gaussian systems....
Geometry of perturbed Gaussian states and quantum estimation
International Nuclear Information System (INIS)
Genoni, Marco G; Giorda, Paolo; Paris, Matteo G A
2011-01-01
We address the non-Gaussianity (nG) of states obtained by weakly perturbing a Gaussian state and investigate the relationships with quantum estimation. For classical perturbations, i.e. perturbations to eigenvalues, we found that the nG of the perturbed state may be written as the quantum Fisher information (QFI) distance minus a term depending on the infinitesimal energy change, i.e. it provides a lower bound to statistical distinguishability. Upon moving on isoenergetic surfaces in a neighbourhood of a Gaussian state, nG thus coincides with a proper distance in the Hilbert space and exactly quantifies the statistical distinguishability of the perturbations. On the other hand, for perturbations leaving the covariance matrix unperturbed, we show that nG provides an upper bound to the QFI. Our results show that the geometry of non-Gaussian states in the neighbourhood of a Gaussian state is definitely not trivial and cannot be subsumed by a differential structure. Nevertheless, the analysis of perturbations to a Gaussian state reveals that nG may be a resource for quantum estimation. The nG of specific families of perturbed Gaussian states is analysed in some detail with the aim of finding the maximally non-Gaussian state obtainable from a given Gaussian one. (fast track communication)
Gaussian polynomials and content ideal in trivial extensions
International Nuclear Information System (INIS)
Bakkari, C.; Mahdou, N.
2006-12-01
The goal of this paper is to exhibit a class of Gaussian non-coherent rings R (with zero-divisors) such that wdim(R) = ∞ and fPdim(R) is always at most one and also exhibits a new class of rings (with zerodivisors) which are neither locally Noetherian nor locally domain where Gaussian polynomials have a locally principal content. For this purpose, we study the possible transfer of the 'Gaussian' property and the property 'the content ideal of a Gaussian polynomial is locally principal' to various trivial extension contexts. This article includes a brief discussion of the scopes and limits of our result. (author)
Robust matching for voice recognition
Higgins, Alan; Bahler, L.; Porter, J.; Blais, P.
1994-10-01
This paper describes an automated method of comparing a voice sample of an unknown individual with samples from known speakers in order to establish or verify the individual's identity. The method is based on a statistical pattern matching approach that employs a simple training procedure, requires no human intervention (transcription, work or phonetic marketing, etc.), and makes no assumptions regarding the expected form of the statistical distributions of the observations. The content of the speech material (vocabulary, grammar, etc.) is not assumed to be constrained in any way. An algorithm is described which incorporates frame pruning and channel equalization processes designed to achieve robust performance with reasonable computational resources. An experimental implementation demonstrating the feasibility of the concept is described.
Energy Technology Data Exchange (ETDEWEB)
Wang, Yuan-Mei; Li, Jun-Gang, E-mail: jungl@bit.edu.cn; Zou, Jian
2017-06-15
Highlights: • Adaptive measurement strategy is used to detect the presence of a magnetic field. • Gaussian Ornstein–Uhlenbeck noise and non-Gaussian noise have been considered. • Weaker magnetic fields may be more easily detected than some stronger ones. - Abstract: By using the adaptive measurement method we study how to detect whether a weak magnetic field is actually present or not under Gaussian noise and non-Gaussian noise. We find that the adaptive measurement method can effectively improve the detection accuracy. For the case of Gaussian noise, we find the stronger the magnetic field strength, the easier for us to detect the magnetic field. Counterintuitively, for non-Gaussian noise, some weaker magnetic fields are more likely to be detected rather than some stronger ones. Finally, we give a reasonable physical interpretation.
Adaptive Discrete Hypergraph Matching.
Yan, Junchi; Li, Changsheng; Li, Yin; Cao, Guitao
2018-02-01
This paper addresses the problem of hypergraph matching using higher-order affinity information. We propose a solver that iteratively updates the solution in the discrete domain by linear assignment approximation. The proposed method is guaranteed to converge to a stationary discrete solution and avoids the annealing procedure and ad-hoc post binarization step that are required in several previous methods. Specifically, we start with a simple iterative discrete gradient assignment solver. This solver can be trapped in an -circle sequence under moderate conditions, where is the order of the graph matching problem. We then devise an adaptive relaxation mechanism to jump out this degenerating case and show that the resulting new path will converge to a fixed solution in the discrete domain. The proposed method is tested on both synthetic and real-world benchmarks. The experimental results corroborate the efficacy of our method.
Electromagnetic wave matching device
International Nuclear Information System (INIS)
Hirata, Yosuke; Mitsunaka, Yoshika; Hayashi, Ken-ichi; Ito, Yasuyuki.
1997-01-01
The present invention provides a matching device capable of increasing an efficiency of combining beams of electromagnetic waves outputted from an output window of a gyrotron which is expected for plasma heating of a thermonuclear reactor and an electromagnetic wave transmission system as high as possible. Namely, an electromagnetic wave matching device reflects beams of electromagnetic waves incident from an inlet by a plurality of phase correction mirrors and combines them to an external transmission system through an exit. In this case, the phase correction mirrors change the phase of the beams of electromagnetic waves incident to the phase correction mirrors by a predetermined amount corresponding to the position of the reflection mirrors. Then, the beams of electromagnetic waves outputted, for example, from a gyrotron can properly be shaped as desired for the intensity and the phase. As a result, combination efficiency with the transmission system can be increased. (I.S.)
Yan, Yuan
2017-07-13
Gaussian likelihood inference has been studied and used extensively in both statistical theory and applications due to its simplicity. However, in practice, the assumption of Gaussianity is rarely met in the analysis of spatial data. In this paper, we study the effect of non-Gaussianity on Gaussian likelihood inference for the parameters of the Matérn covariance model. By using Monte Carlo simulations, we generate spatial data from a Tukey g-and-h random field, a flexible trans-Gaussian random field, with the Matérn covariance function, where g controls skewness and h controls tail heaviness. We use maximum likelihood based on the multivariate Gaussian distribution to estimate the parameters of the Matérn covariance function. We illustrate the effects of non-Gaussianity of the data on the estimated covariance function by means of functional boxplots. Thanks to our tailored simulation design, a comparison of the maximum likelihood estimator under both the increasing and fixed domain asymptotics for spatial data is performed. We find that the maximum likelihood estimator based on Gaussian likelihood is overall satisfying and preferable than the non-distribution-based weighted least squares estimator for data from the Tukey g-and-h random field. We also present the result for Gaussian kriging based on Matérn covariance estimates with data from the Tukey g-and-h random field and observe an overall satisfactory performance.
Yan, Yuan; Genton, Marc G.
2017-01-01
Gaussian likelihood inference has been studied and used extensively in both statistical theory and applications due to its simplicity. However, in practice, the assumption of Gaussianity is rarely met in the analysis of spatial data. In this paper, we study the effect of non-Gaussianity on Gaussian likelihood inference for the parameters of the Matérn covariance model. By using Monte Carlo simulations, we generate spatial data from a Tukey g-and-h random field, a flexible trans-Gaussian random field, with the Matérn covariance function, where g controls skewness and h controls tail heaviness. We use maximum likelihood based on the multivariate Gaussian distribution to estimate the parameters of the Matérn covariance function. We illustrate the effects of non-Gaussianity of the data on the estimated covariance function by means of functional boxplots. Thanks to our tailored simulation design, a comparison of the maximum likelihood estimator under both the increasing and fixed domain asymptotics for spatial data is performed. We find that the maximum likelihood estimator based on Gaussian likelihood is overall satisfying and preferable than the non-distribution-based weighted least squares estimator for data from the Tukey g-and-h random field. We also present the result for Gaussian kriging based on Matérn covariance estimates with data from the Tukey g-and-h random field and observe an overall satisfactory performance.
IBS for non-gaussian distributions
International Nuclear Information System (INIS)
Fedotov, A.; Sidorin, A.O.; Smirnov, A.V.
2010-01-01
In many situations distribution can significantly deviate from Gaussian which requires accurate treatment of IBS. Our original interest in this problem was motivated by the need to have an accurate description of beam evolution due to IBS while distribution is strongly affected by the external electron cooling force. A variety of models with various degrees of approximation were developed and implemented in BETACOOL in the past to address this topic. A more complete treatment based on the friction coefficient and full 3-D diffusion tensor was introduced in BETACOOL at the end of 2007 under the name 'local IBS model'. Such a model allowed us calculation of IBS for an arbitrary beam distribution. The numerical benchmarking of this local IBS algorithm and its comparison with other models was reported before. In this paper, after briefly describing the model and its limitations, they present its comparison with available experimental data.
Optical vortex scanning inside the Gaussian beam
International Nuclear Information System (INIS)
Masajada, J; Leniec, M; Augustyniak, I
2011-01-01
We discussed a new scanning method for optical vortex-based scanning microscopy. The optical vortex is introduced into the incident Gaussian beam by a vortex lens. Then the beam with the optical vortex is focused by an objective and illuminates the sample. By changing the position of the vortex lens we can shift the optical vortex position at the sample plane. By adjusting system parameters we can get 30 times smaller shift at the sample plane compared to the vortex lens shift. Moreover, if the range of vortex shifts is smaller than 3% of the beam radius in the sample plane the amplitude and phase distribution around the phase dislocation remains practically unchanged. Thus we can scan the sample topography precisely with an optical vortex
White Gaussian Noise - Models for Engineers
Jondral, Friedrich K.
2018-04-01
This paper assembles some information about white Gaussian noise (WGN) and its applications. It starts from a description of thermal noise, i. e. the irregular motion of free charge carriers in electronic devices. In a second step, mathematical models of WGN processes and their most important parameters, especially autocorrelation functions and power spectrum densities, are introduced. In order to proceed from mathematical models to simulations, we discuss the generation of normally distributed random numbers. The signal-to-noise ratio as the most important quality measure used in communications, control or measurement technology is accurately introduced. As a practical application of WGN, the transmission of quadrature amplitude modulated (QAM) signals over additive WGN channels together with the optimum maximum likelihood (ML) detector is considered in a demonstrative and intuitive way.
Gaussian process regression for geometry optimization
Denzel, Alexander; Kästner, Johannes
2018-03-01
We implemented a geometry optimizer based on Gaussian process regression (GPR) to find minimum structures on potential energy surfaces. We tested both a two times differentiable form of the Matérn kernel and the squared exponential kernel. The Matérn kernel performs much better. We give a detailed description of the optimization procedures. These include overshooting the step resulting from GPR in order to obtain a higher degree of interpolation vs. extrapolation. In a benchmark against the Limited-memory Broyden-Fletcher-Goldfarb-Shanno optimizer of the DL-FIND library on 26 test systems, we found the new optimizer to generally reduce the number of required optimization steps.
Gaussian elimination is not optimal, revisited
DEFF Research Database (Denmark)
Macedo, Hugo Daniel
2016-01-01
We refactor the universal law for the tensor product to express matrix multiplication as the product . MN of two matrices . M and . N thus making possible to use such matrix product to encode and transform algorithms performing matrix multiplication using techniques from linear algebra. We explore...... the end results are equations involving matrix products, our exposition builds upon previous works on the category of matrices (and the related category of finite vector spaces) which we extend by showing: why the direct sum . (⊕,0) monoid is not closed, a biproduct encoding of Gaussian elimination...... such possibility and show two stepwise refinements transforming the composition . MN into the Naïve and Strassen's matrix multiplication algorithms. The inspection of the stepwise transformation of the composition of matrices . MN into the Naïve matrix multiplication algorithm evidences that the steps...
Tunnelling through a Gaussian random barrier
International Nuclear Information System (INIS)
Bezak, Viktor
2008-01-01
A thorough analysis of the tunnelling of electrons through a laterally inhomogeneous rectangular barrier is presented. The barrier height is defined as a statistically homogeneous Gaussian random function. In order to simplify calculations, we assume that the electron energy is low enough in comparison with the mean value of the barrier height. The randomness of the barrier height is defined vertically by a constant variance and horizontally by a finite correlation length. We present detailed calculations of the angular probability density for the tunnelled electrons (i.e. for the scattering forwards). The tunnelling manifests a remarkably diffusive character if the wavelength of the electrons is comparable with the correlation length of the barrier
Gaussian process regression for tool wear prediction
Kong, Dongdong; Chen, Yongjie; Li, Ning
2018-05-01
To realize and accelerate the pace of intelligent manufacturing, this paper presents a novel tool wear assessment technique based on the integrated radial basis function based kernel principal component analysis (KPCA_IRBF) and Gaussian process regression (GPR) for real-timely and accurately monitoring the in-process tool wear parameters (flank wear width). The KPCA_IRBF is a kind of new nonlinear dimension-increment technique and firstly proposed for feature fusion. The tool wear predictive value and the corresponding confidence interval are both provided by utilizing the GPR model. Besides, GPR performs better than artificial neural networks (ANN) and support vector machines (SVM) in prediction accuracy since the Gaussian noises can be modeled quantitatively in the GPR model. However, the existence of noises will affect the stability of the confidence interval seriously. In this work, the proposed KPCA_IRBF technique helps to remove the noises and weaken its negative effects so as to make the confidence interval compressed greatly and more smoothed, which is conducive for monitoring the tool wear accurately. Moreover, the selection of kernel parameter in KPCA_IRBF can be easily carried out in a much larger selectable region in comparison with the conventional KPCA_RBF technique, which helps to improve the efficiency of model construction. Ten sets of cutting tests are conducted to validate the effectiveness of the presented tool wear assessment technique. The experimental results show that the in-process flank wear width of tool inserts can be monitored accurately by utilizing the presented tool wear assessment technique which is robust under a variety of cutting conditions. This study lays the foundation for tool wear monitoring in real industrial settings.
Higher-Order Hybrid Gaussian Kernel in Meshsize Boosting Algorithm
African Journals Online (AJOL)
In this paper, we shall use higher-order hybrid Gaussian kernel in a meshsize boosting algorithm in kernel density estimation. Bias reduction is guaranteed in this scheme like other existing schemes but uses the higher-order hybrid Gaussian kernel instead of the regular fixed kernels. A numerical verification of this scheme ...
Convergence of posteriors for discretized log Gaussian Cox processes
DEFF Research Database (Denmark)
Waagepetersen, Rasmus Plenge
2004-01-01
In Markov chain Monte Carlo posterior computation for log Gaussian Cox processes (LGCPs) a discretization of the continuously indexed Gaussian field is required. It is demonstrated that approximate posterior expectations computed from discretized LGCPs converge to the exact posterior expectations...... when the cell sizes of the discretization tends to zero. The effect of discretization is studied in a data example....
Comparing Fixed and Variable-Width Gaussian Networks
Czech Academy of Sciences Publication Activity Database
Kůrková, Věra; Kainen, P.C.
2014-01-01
Roč. 57, September (2014), s. 23-28 ISSN 0893-6080 R&D Projects: GA MŠk(CZ) LD13002 Institutional support: RVO:67985807 Keywords : Gaussian radial and kernel networks * Functionally equivalent networks * Universal approximators * Stabilizers defined by Gaussian kernels * Argminima of error functionals Subject RIV: IN - Informatics, Computer Science Impact factor: 2.708, year: 2014
Two-photon optics of Bessel-Gaussian modes
CSIR Research Space (South Africa)
McLaren, M
2013-09-01
Full Text Available In this paper we consider geometrical two-photon optics of Bessel-Gaussian modes generated in spontaneous parametric down-conversion of a Gaussian pump beam. We provide a general theoretical expression for the orbital angular momentum (OAM) spectrum...
Application Of Shared Gamma And Inverse-Gaussian Frailty Models ...
African Journals Online (AJOL)
Shared Gamma and Inverse-Gaussian Frailty models are used to analyze the survival times of patients who are clustered according to cancer/tumor types under Parametric Proportional Hazard framework. The result of the ... However, no evidence is strong enough for preference of either Gamma or Inverse Gaussian Frailty.
Optimality of Gaussian attacks in continuous-variable quantum cryptography.
Navascués, Miguel; Grosshans, Frédéric; Acín, Antonio
2006-11-10
We analyze the asymptotic security of the family of Gaussian modulated quantum key distribution protocols for continuous-variables systems. We prove that the Gaussian unitary attack is optimal for all the considered bounds on the key rate when the first and second momenta of the canonical variables involved are known by the honest parties.
Degeneracy of energy levels of pseudo-Gaussian oscillators
International Nuclear Information System (INIS)
Iacob, Theodor-Felix; Iacob, Felix; Lute, Marina
2015-01-01
We study the main features of the isotropic radial pseudo-Gaussian oscillators spectral properties. This study is made upon the energy levels degeneracy with respect to orbital angular momentum quantum number. In a previous work [6] we have shown that the pseudo-Gaussian oscillators belong to the class of quasi-exactly solvable models and an exact solution has been found
Directory of Open Access Journals (Sweden)
Rajeev D S Raizada
Full Text Available Spatial smoothness is helpful when averaging fMRI signals across multiple subjects, as it allows different subjects' corresponding brain areas to be pooled together even if they are slightly misaligned. However, smoothing is usually not applied when performing multivoxel pattern-based analyses (MVPA, as it runs the risk of blurring away the information that fine-grained spatial patterns contain. It would therefore be desirable, if possible, to carry out pattern-based analyses which take unsmoothed data as their input but which produce smooth images as output. We show here that the Gaussian Naive Bayes (GNB classifier does precisely this, when it is used in "searchlight" pattern-based analyses. We explain why this occurs, and illustrate the effect in real fMRI data. Moreover, we show that analyses using GNBs produce results at the multi-subject level which are statistically robust, neurally plausible, and which replicate across two independent data sets. By contrast, SVM classifiers applied to the same data do not generate a replication, even if the SVM-derived searchlight maps have smoothing applied to them. An additional advantage of GNB classifiers for searchlight analyses is that they are orders of magnitude faster to compute than more complex alternatives such as SVMs. Collectively, these results suggest that Gaussian Naive Bayes classifiers may be a highly non-naive choice for multi-subject pattern-based fMRI studies.
Remacha, Clément; Coëtmellec, Sébastien; Brunel, Marc; Lebrun, Denis
2013-02-01
Wavelet analysis provides an efficient tool in numerous signal processing problems and has been implemented in optical processing techniques, such as in-line holography. This paper proposes an improvement of this tool for the case of an elliptical, astigmatic Gaussian (AEG) beam. We show that this mathematical operator allows reconstructing an image of a spherical particle without compression of the reconstructed image, which increases the accuracy of the 3D location of particles and of their size measurement. To validate the performance of this operator we have studied the diffraction pattern produced by a particle illuminated by an AEG beam. This study used mutual intensity propagation, and the particle is defined as a chirped Gaussian sum. The proposed technique was applied and the experimental results are presented.
Effects of a modulated vortex structure on the diffraction dynamics of ring Airy Gaussian beams.
Huang, Xianwei; Shi, Xiaohui; Deng, Zhixiang; Bai, Yanfeng; Fu, Xiquan
2017-09-01
The evolution of the ring Airy Gaussian beams with a modulated vortex in free space is numerically investigated. Compared with the unmodulated vortex, the unique property is that the beam spots first break up, and then gather. The evolution of the beams is influenced by the parameters of the vortex modulation, and the splitting phenomenon gets enhanced with multiple rings becoming light spots if the modulation depth increases. The symmetric branch pattern of the beam spots gets changed when the number of phase folds increases, and the initial modulation phase only impacts the angle of the beam spots. Moreover, a large distribution factor correlates to a hollow Gaussian vortex shape and weakens the splitting and gathering trend. By changing the initial parameters of the vortex modulation and the distribution factor, the peak intensity is greatly affected. In addition, the energy flow and the angular momentum are elucidated with the beam evolution features being confirmed.
Matching with transfer matrices
International Nuclear Information System (INIS)
Perez-Alvarez, R.; Velasco, V.R.; Garcia-Moliner, F.; Rodriguez-Coppola, H.
1987-10-01
An ABC configuration - which corresponds to various systems of physical interest, such as a barrier or a quantum well - is studied by combining a surface Green function matching analysis of the entire system with a description of the intermediate (B) region in terms of a transfer matrix in the sense of Mora et al. (1985). This hybrid approach proves very useful when it is very difficult to construct the corresponding Green function G B . An application is made to the calculation of quantised subband levels in a parabolic quantum well. Further possibilities of extension of this approach are pointed out. (author). 27 refs, 1 tab
Coaxial pulse matching transformer
International Nuclear Information System (INIS)
Ledenev, V.V.; Khimenko, L.T.
1986-01-01
This paper describes a coaxial pulse matching transformer with comparatively simple design, increased mechanical strength, and low stray inductance. The transformer design makes it easy to change the turns ratio. The circuit of the device and an expression for the current multiplication factor are presented; experiments confirm the efficiency of the transformer. Apparatus with a coaxial transformer for producing high-power pulsed magnetic fields is designed (current pulses of 1-10 MA into a load and a natural frequency of 100 kHz)
Ultrawide Bandwidth Receiver Based on a Multivariate Generalized Gaussian Distribution
Ahmed, Qasim Zeeshan
2015-04-01
Multivariate generalized Gaussian density (MGGD) is used to approximate the multiple access interference (MAI) and additive white Gaussian noise in pulse-based ultrawide bandwidth (UWB) system. The MGGD probability density function (pdf) is shown to be a better approximation of a UWB system as compared to multivariate Gaussian, multivariate Laplacian and multivariate Gaussian-Laplacian mixture (GLM). The similarity between the simulated and the approximated pdf is measured with the help of modified Kullback-Leibler distance (KLD). It is also shown that MGGD has the smallest KLD as compared to Gaussian, Laplacian and GLM densities. A receiver based on the principles of minimum bit error rate is designed for the MGGD pdf. As the requirement is stringent, the adaptive implementation of the receiver is also carried out in this paper. Training sequence of the desired user is the only requirement when implementing the detector adaptively. © 2002-2012 IEEE.
Gaussian cloning of coherent states with known phases
International Nuclear Information System (INIS)
Alexanian, Moorad
2006-01-01
The fidelity for cloning coherent states is improved over that provided by optimal Gaussian and non-Gaussian cloners for the subset of coherent states that are prepared with known phases. Gaussian quantum cloning duplicates all coherent states with an optimal fidelity of 2/3. Non-Gaussian cloners give optimal single-clone fidelity for a symmetric 1-to-2 cloner of 0.6826. Coherent states that have known phases can be cloned with a fidelity of 4/5. The latter is realized by a combination of two beam splitters and a four-wave mixer operated in the nonlinear regime, all of which are realized by interaction Hamiltonians that are quadratic in the photon operators. Therefore, the known Gaussian devices for cloning coherent states are extended when cloning coherent states with known phases by considering a nonbalanced beam splitter at the input side of the amplifier
Yu, Haitao; Sun, Hui; Shen, Jianqi; Tropea, Cameron
2018-03-01
The primary rainbow observed when light is scattered by a spherical drop has been exploited in the past to measure drop size and relative refractive index. However, if higher spatial resolution is required in denser drop ensembles/sprays, and to avoid then multiple drops simultaneously appearing in the measurement volume, a highly focused beam is desirable, inevitably with a Gaussian intensity profile. The present study examines the primary rainbow pattern resulting when a Gaussian beam is scattered by a spherical drop and estimates the attainable accuracy when extracting size and refractive index. The scattering is computed using generalized Lorenz-Mie theory (GLMT) and Debye series decomposition of the Gaussian beam scattering. The results of these simulations show that the measurement accuracy is dependent on both the beam waist radius and the position of the drop in the beam waist.
Plasma focus matching conditions
International Nuclear Information System (INIS)
Soliman, H.M.; Masoud, M.M.; Elkhalafawy, T.A.
1988-01-01
A snow-plough and slug models have been used to obtain the optimum matching conditions of the plasma in the focus. The dimensions of the plasma focus device are, inner electrode radius = 2 cm, outer electrode radius = 5.5 cm, and its length = 8 cm. It was found that the maximum magnetic energy of 12.26 kJ has to be delivered to plasma focus whose density is 10 19 /cm 3 at focusing time of 2.55 μs and with total external inductance of 24.2 n H. The same method is used to evaluate the optimum matching conditions for the previous coaxial discharge system which had inner electrode radius = 1.6 cm, outer electrode radius = 3.3 cm and its length = 31.5 cm. These conditions are charging voltage = 12 kV, capacity of the condenser bank = 430 μf, plasma focus density = 10 19 /cm 3 focusing time = 8 μs and total external inductance = 60.32 n H.3 fig., 2 tab
International Nuclear Information System (INIS)
Tsuchida, Takahiro; Kimura, Koji
2015-01-01
Equivalent non-Gaussian excitation method is proposed to obtain the moments up to the fourth order of the response of systems under non-Gaussian random excitation. The excitation is prescribed by the probability density and power spectrum. Moment equations for the response can be derived from the stochastic differential equations for the excitation and the system. However, the moment equations are not closed due to the nonlinearity of the diffusion coefficient in the equation for the excitation. In the proposed method, the diffusion coefficient is replaced with the equivalent diffusion coefficient approximately to obtain a closed set of the moment equations. The square of the equivalent diffusion coefficient is expressed by the second-order polynomial. In order to demonstrate the validity of the method, a linear system to non-Gaussian excitation with generalized Gaussian distribution is analyzed. The results show the method is applicable to non-Gaussian excitation with the widely different kurtosis and bandwidth. (author)
Anatomy Ontology Matching Using Markov Logic Networks
Directory of Open Access Journals (Sweden)
Chunhua Li
2016-01-01
Full Text Available The anatomy of model species is described in ontologies, which are used to standardize the annotations of experimental data, such as gene expression patterns. To compare such data between species, we need to establish relationships between ontologies describing different species. Ontology matching is a kind of solutions to find semantic correspondences between entities of different ontologies. Markov logic networks which unify probabilistic graphical model and first-order logic provide an excellent framework for ontology matching. We combine several different matching strategies through first-order logic formulas according to the structure of anatomy ontologies. Experiments on the adult mouse anatomy and the human anatomy have demonstrated the effectiveness of proposed approach in terms of the quality of result alignment.
Body Weight and Matching with a Physically Attractive Romantic Partner
Carmalt, Julie H.; Cawley, John; Joyner, Kara; Sobal, Jeffery
2008-01-01
Matching and attribute trade are two perspectives used to explain mate selection. We investigated patterns of matching and trade, focusing on obesity, using Add Health Romantic Pair data (N = 1,405 couples). Obese individuals, relative to healthy weight individuals, were less likely to have physically attractive partners, with this disadvantage…
Cao, Zhicheng; Schmid, Natalia A.
2015-05-01
Matching facial images across electromagnetic spectrum presents a challenging problem in the field of biometrics and identity management. An example of this problem includes cross spectral matching of active infrared (IR) face images or thermal IR face images against a dataset of visible light images. This paper describes a new operator named Composite Multi-Lobe Descriptor (CMLD) for facial feature extraction in cross spectral matching of near-infrared (NIR) or short-wave infrared (SWIR) against visible light images. The new operator is inspired by the design of ordinal measures. The operator combines Gaussian-based multi-lobe kernel functions, Local Binary Pattern (LBP), generalized LBP (GLBP) and Weber Local Descriptor (WLD) and modifies them into multi-lobe functions with smoothed neighborhoods. The new operator encodes both the magnitude and phase responses of Gabor filters. The combining of LBP and WLD utilizes both the orientation and intensity information of edges. Introduction of multi-lobe functions with smoothed neighborhoods further makes the proposed operator robust against noise and poor image quality. Output templates are transformed into histograms and then compared by means of a symmetric Kullback-Leibler metric resulting in a matching score. The performance of the multi-lobe descriptor is compared with that of other operators such as LBP, Histogram of Oriented Gradients (HOG), ordinal measures, and their combinations. The experimental results show that in many cases the proposed method, CMLD, outperforms the other operators and their combinations. In addition to different infrared spectra, various standoff distances from close-up (1.5 m) to intermediate (50 m) and long (106 m) are also investigated in this paper. Performance of CMLD is evaluated for of each of the three cases of distances.
Hong, Namki; Yoon, Han Gyul; Seo, Da Hea; Park, Seho; Kim, Seung Il; Sohn, Joo Hyuk; Rhee, Yumie
2017-09-01
Management of metabolic complications of long-term adjuvant endocrine therapy in early breast cancer remained an unmet need. We aimed to compare the effects of tamoxifen (TMX) and aromatase inhibitors (AIs) on the risk of fatty liver in conjunction with longitudinal changes in the serum lipid parameters. Among 1203 subjects who were taking adjuvant TMX or AI (anastrozole or letrozole) without fatty liver at baseline, those taking TMX or AI were 1:1 matched on the propensity score. The primary outcome was newly developed fatty liver detected on annual liver ultrasonography. Among 328 matched subjects (mean age 53.5 years, body mass index 22.9 kg/m 2 ), 62 cases of fatty liver in the TMX group and 41 cases in the AI group were detected in a total of 987.4 person-years. The incidence rate of fatty liver was higher in the TMX group than in the AI group (128.7 versus 81.1 per 1000 person-years, P = 0.021), particularly within the first 2 years of therapy. TMX was associated with an increased 5-year risk of newly developed fatty liver (adjusted hazard ratio 1.61, P = 0.030) compared with AI independent of obesity and cholesterol level. Subjects who developed fatty liver had higher triglycerides (TGs) and lower high-density lipoprotein cholesterol (HDL-C) level at baseline than those without, which was sustained during follow-up despite the serum cholesterol-lowering effect of TMX. TMX independently increased the 5-year risk of newly developed fatty liver compared with AI in postmenopausal women with early breast cancer. Our findings suggest the need for considering the risk of fatty liver as a different adverse event profile between AI and TMX, particularly in patients with obesity, high TGs and low HDL-C. Copyright © 2017 Elsevier Ltd. All rights reserved.
Job Searchers, Job Matches and the Elasticity of Matching
Broersma, L.; van Ours, J.C.
1998-01-01
This paper stresses the importance of a specification of the matching function in which the measure of job matches corresponds to the measure of job searchers. In many empirical studies on the matching function this requirement has not been fulfilled because it is difficult to find information about
Mark, T A; Gallistel, C R
1994-01-01
Rats responded on concurrent variable interval schedules of brain stimulation reward in 2-trial sessions. Between trials, there was a 16-fold reversal in the relative rate of reward. In successive, narrow time windows, the authors compared the ratio of the times spent on the 2 levers to the ratio of the rewards received. Time-allocation ratios tracked wide, random fluctuations in the reward ratio. The adjustment to the midsession reversal in relative rate of reward was largely completed within 1 interreward interval on the leaner schedule. Both results were unaffected by a 16-fold change in the combined rates of reward. The large, rapid, scale-invariant shifts in time-allocation ratios that underlie matching behavior imply that the subjective relative rate of reward can be determined by a very few of the most recent interreward intervals and that this estimate can directly determine the ratio of the expected stay durations.
Electromagnetic wave matching device
International Nuclear Information System (INIS)
Hirata, Yosuke; Mitsunaka, Yoshika; Hayashi, Ken-ichi; Ito, Yasuyuki.
1997-01-01
The present invention provides an electromagnetic wave matching capable of reducing a cost for the transmission system in a system of using electromagnetic waves for plasma heating of a thermonuclear reactor. Namely, incident electromagnetic waves are reflected by using a plurality of phase correction mirrors. The reflected electromagnetic waves are connected to an external transmission system through an exit. The phase correction mirrors have such a shape to receive a plurality of beam-like electromagnetic waves and output electromagnetic waves by the number different from the number of the received electromagnetic wave beams having a predetermined distribution. Further, at least two of the phase correction mirrors have such a shape to change the phase of the electromagnetic waves beams incident to the reflection surface of the phase correction mirrors by a predetermined amount corresponding to the position of the reflection surface. Then, the cost for transmission system can greatly be reduced. (I.S.)
Primordial non-Gaussianity from LAMOST surveys
International Nuclear Information System (INIS)
Gong Yan; Wang Xin; Chen Xuelei; Zheng Zheng
2010-01-01
The primordial non-Gaussianity (PNG) in the matter density perturbation is a very powerful probe of the physics of the very early Universe. The local PNG can induce a distinct scale-dependent bias on the large scale structure distribution of galaxies and quasars, which could be used for constraining it. We study the detection limits of PNG from the surveys of the LAMOST telescope. The cases of the main galaxy survey, the luminous red galaxy (LRG) survey, and the quasar survey of different magnitude limits are considered. We find that the Main1 sample (i.e. the main galaxy survey which is one magnitude deeper than the SDSS main galaxy survey, or r NL are |f NL | NL | NL | is between 50 and 103, depending on the magnitude limit of the survey. With Planck-like priors on cosmological parameters, the quasar survey with g NL | < 43 (2σ). We also discuss the possibility of further tightening the constraint by using the relative bias method proposed by Seljak.
A Decentralized Receiver in Gaussian Interference
Directory of Open Access Journals (Sweden)
Christian D. Chapman
2018-04-01
Full Text Available Bounds are developed on the maximum communications rate between a transmitter and a fusion node aided by a cluster of distributed receivers with limited resources for cooperation, all in the presence of an additive Gaussian interferer. The receivers cannot communicate with one another and can only convey processed versions of their observations to the fusion center through a Local Array Network (LAN with limited total throughput. The effectiveness of each bound’s approach for mitigating a strong interferer is assessed over a wide range of channels. It is seen that, if resources are shared effectively, even a simple quantize-and-forward strategy can mitigate an interferer 20 dB stronger than the signal in a diverse range of spatially Ricean channels. Monte-Carlo experiments for the bounds reveal that, while achievable rates are stable when varying the receiver’s observed scattered-path to line-of-sight signal power, the receivers must adapt how they share resources in response to this change. The bounds analyzed are proven to be achievable and are seen to be tight with capacity when LAN resources are either ample or limited.
Bayesian nonparametric adaptive control using Gaussian processes.
Chowdhary, Girish; Kingravi, Hassan A; How, Jonathan P; Vela, Patricio A
2015-03-01
Most current model reference adaptive control (MRAC) methods rely on parametric adaptive elements, in which the number of parameters of the adaptive element are fixed a priori, often through expert judgment. An example of such an adaptive element is radial basis function networks (RBFNs), with RBF centers preallocated based on the expected operating domain. If the system operates outside of the expected operating domain, this adaptive element can become noneffective in capturing and canceling the uncertainty, thus rendering the adaptive controller only semiglobal in nature. This paper investigates a Gaussian process-based Bayesian MRAC architecture (GP-MRAC), which leverages the power and flexibility of GP Bayesian nonparametric models of uncertainty. The GP-MRAC does not require the centers to be preallocated, can inherently handle measurement noise, and enables MRAC to handle a broader set of uncertainties, including those that are defined as distributions over functions. We use stochastic stability arguments to show that GP-MRAC guarantees good closed-loop performance with no prior domain knowledge of the uncertainty. Online implementable GP inference methods are compared in numerical simulations against RBFN-MRAC with preallocated centers and are shown to provide better tracking and improved long-term learning.
Quantity precommitment and price matching
DEFF Research Database (Denmark)
Tumennasan, Norovsambuu
We revisit the question of whether price matching is anti-competitive in a capacity constrained duopoly setting. We show that the effect of price matching depends on capacity. Specifically, price matching has no effect when capacity is relatively low, but it benefits the firms when capacity...... is relatively high. Interestingly, when capacity is in an intermediate range, price matching benefits only the small firm but does not affect the large firm in any way. Therefore, one has to consider capacity seriously when evaluating if price matching is anti-competitive. If the firms choose their capacities...... simultaneously before pricing decisions, then the effect of price matching is either pro-competitive or ambiguous. We show that if the cost of capacity is high, then price matching can only (weakly) decrease the market price. On the other hand, if the cost of capacity is low, then the effect of price matching...
Iris Matching Based on Personalized Weight Map.
Dong, Wenbo; Sun, Zhenan; Tan, Tieniu
2011-09-01
Iris recognition typically involves three steps, namely, iris image preprocessing, feature extraction, and feature matching. The first two steps of iris recognition have been well studied, but the last step is less addressed. Each human iris has its unique visual pattern and local image features also vary from region to region, which leads to significant differences in robustness and distinctiveness among the feature codes derived from different iris regions. However, most state-of-the-art iris recognition methods use a uniform matching strategy, where features extracted from different regions of the same person or the same region for different individuals are considered to be equally important. This paper proposes a personalized iris matching strategy using a class-specific weight map learned from the training images of the same iris class. The weight map can be updated online during the iris recognition procedure when the successfully recognized iris images are regarded as the new training data. The weight map reflects the robustness of an encoding algorithm on different iris regions by assigning an appropriate weight to each feature code for iris matching. Such a weight map trained by sufficient iris templates is convergent and robust against various noise. Extensive and comprehensive experiments demonstrate that the proposed personalized iris matching strategy achieves much better iris recognition performance than uniform strategies, especially for poor quality iris images.
Spatial competition with intermediated matching
van Raalte, C.L.J.P.; Webers, H.M.
1995-01-01
This paper analyzes the spatial competition in commission fees between two match makers. These match makers serve as middlemen between buyers and sellers who are located uniformly on a circle. The profits of the match makers are determined by their respective market sizes. A limited willingness to
Boltzmann-Gaussian transition under specific noise effect
International Nuclear Information System (INIS)
Anh, Chu Thuy; Lan, Nguyen Tri; Viet, Nguyen Ai
2014-01-01
It is observed that a short time data set of market returns presents almost symmetric Boltzmann distribution whereas a long time data set tends to show a Gaussian distribution. To understand this universal phenomenon, many hypotheses which are spreading in a wide range of interdisciplinary research were proposed. In current work, the effects of background fluctuations on symmetric Boltzmann distribution is investigated. The numerical calculation is performed to show that the Gaussian noise may cause the transition from initial Boltzmann distribution to Gaussian one. The obtained results would reflect non-dynamic nature of the transition under consideration.
Legendre Duality of Spherical and Gaussian Spin Glasses
International Nuclear Information System (INIS)
Genovese, Giuseppe; Tantari, Daniele
2015-01-01
The classical result of concentration of the Gaussian measure on the sphere in the limit of large dimension induces a natural duality between Gaussian and spherical models of spin glass. We analyse the Legendre variational structure linking the free energies of these two systems, in the spirit of the equivalence of ensembles of statistical mechanics. Our analysis, combined with the previous work (Barra et al., J. Phys. A: Math. Theor. 47, 155002, 2014), shows that such models are replica symmetric. Lastly, we briefly discuss an application of our result to the study of the Gaussian Hopfield model
Controllable gaussian-qubit interface for extremal quantum state engineering.
Adesso, Gerardo; Campbell, Steve; Illuminati, Fabrizio; Paternostro, Mauro
2010-06-18
We study state engineering through bilinear interactions between two remote qubits and two-mode gaussian light fields. The attainable two-qubit states span the entire physically allowed region in the entanglement-versus-global-purity plane. Two-mode gaussian states with maximal entanglement at fixed global and marginal entropies produce maximally entangled two-qubit states in the corresponding entropic diagram. We show that a small set of parameters characterizing extremally entangled two-mode gaussian states is sufficient to control the engineering of extremally entangled two-qubit states, which can be realized in realistic matter-light scenarios.
Legendre Duality of Spherical and Gaussian Spin Glasses
Energy Technology Data Exchange (ETDEWEB)
Genovese, Giuseppe, E-mail: giuseppe.genovese@math.uzh.ch [Universität Zürich, Institut für Mathematik (Switzerland); Tantari, Daniele, E-mail: daniele.tantari@sns.it [Scuola Normale Superiore di Pisa, Centro Ennio de Giorgi (Italy)
2015-12-15
The classical result of concentration of the Gaussian measure on the sphere in the limit of large dimension induces a natural duality between Gaussian and spherical models of spin glass. We analyse the Legendre variational structure linking the free energies of these two systems, in the spirit of the equivalence of ensembles of statistical mechanics. Our analysis, combined with the previous work (Barra et al., J. Phys. A: Math. Theor. 47, 155002, 2014), shows that such models are replica symmetric. Lastly, we briefly discuss an application of our result to the study of the Gaussian Hopfield model.
Methods to characterize non-Gaussian noise in TAMA
International Nuclear Information System (INIS)
Ando, Masaki; Arai, K; Takahashi, R; Tatsumi, D; Beyersdorf, P; Kawamura, S; Miyoki, S; Mio, N; Moriwaki, S; Numata, K; Kanda, N; Aso, Y; Fujimoto, M-K; Tsubono, K; Kuroda, K
2003-01-01
We present a data characterization method for the main output signal of the interferometric gravitational-wave detector, in particular targeting at effective detection of burst gravitational waves from stellar core collapse. The time scale of non-Gaussian events is evaluated in this method, and events with longer time scale than real signals are rejected as non-Gaussian noises. As a result of data analysis using 1000 h of real data with the interferometric gravitational-wave detector TAMA300, the false-alarm rate was improved 10 3 times with this non-Gaussian noise evaluation and rejection method
Coincidence Imaging and interference with coherent Gaussian beams
Institute of Scientific and Technical Information of China (English)
CAI Yang-jian; ZHU Shi-yao
2006-01-01
we present a theoretical study of coincidence imaging and interference with coherent Gaussian beams The equations for the coincidence image formation and interference fringes are derived,from which it is clear that the imaging is due to the corresponding focusing in the two paths .The quality and visibility of the images and fringes can be high simultaneously.The nature of the coincidence imaging and interference between quantum entangled photon pairs and coherent Gaussian beams are different .The coincidence image with coherent Gaussian beams is due to intensity-intensity correspondence,a classical nature,while that with entangled photon pairs is due to the amplitude correlation a quantum nature.
Quantum Teamwork for Unconditional Multiparty Communication with Gaussian States
Zhang, Jing; Adesso, Gerardo; Xie, Changde; Peng, Kunchi
2009-08-01
We demonstrate the capability of continuous variable Gaussian states to communicate multipartite quantum information. A quantum teamwork protocol is presented according to which an arbitrary possibly entangled multimode state can be faithfully teleported between two teams each comprising many cooperative users. We prove that N-mode Gaussian weighted graph states exist for arbitrary N that enable unconditional quantum teamwork implementations for any arrangement of the teams. These perfect continuous variable maximally multipartite entangled resources are typical among pure Gaussian states and are unaffected by the entanglement frustration occurring in multiqubit states.
A note on moving average models for Gaussian random fields
DEFF Research Database (Denmark)
Hansen, Linda Vadgård; Thorarinsdottir, Thordis L.
The class of moving average models offers a flexible modeling framework for Gaussian random fields with many well known models such as the Matérn covariance family and the Gaussian covariance falling under this framework. Moving average models may also be viewed as a kernel smoothing of a Lévy...... basis, a general modeling framework which includes several types of non-Gaussian models. We propose a new one-parameter spatial correlation model which arises from a power kernel and show that the associated Hausdorff dimension of the sample paths can take any value between 2 and 3. As a result...
Detection Performance of Signals in Dependent Noise From a Gaussian Mixture Uncertainty Class
National Research Council Canada - National Science Library
Gerlach, K
1998-01-01
... (correlated) multivariate noise from a Gaussian mixture uncertainty class. This uncertainty class is defined using upper and lower bounding functions on the univariate Gaussian mixing distribution function...
International Nuclear Information System (INIS)
Tsuchida, Takahiro; Kimura, Koji
2016-01-01
Equivalent non-Gaussian excitation method is proposed to obtain the response moments up to the 4th order of dynamic systems under non-Gaussian random excitation. The non-Gaussian excitation is prescribed by the probability density and the power spectrum, and is described by an Ito stochastic differential equation. Generally, moment equations for the response, which are derived from the governing equations for the excitation and the system, are not closed due to the nonlinearity of the diffusion coefficient in the equation for the excitation even though the system is linear. In the equivalent non-Gaussian excitation method, the diffusion coefficient is replaced with the equivalent diffusion coefficient approximately to obtain a closed set of the moment equations. The square of the equivalent diffusion coefficient is expressed by a quadratic polynomial. In numerical examples, a linear system subjected to nonGaussian excitations with bimodal and Rayleigh distributions is analyzed by using the present method. The results show that the method yields the variance, skewness and kurtosis of the response with high accuracy for non-Gaussian excitation with the widely different probability densities and bandwidth. The statistical moments of the equivalent non-Gaussian excitation are also investigated to describe the feature of the method. (paper)
International Nuclear Information System (INIS)
Strandlie, A.; Wroldsen, J.
2006-01-01
If any of the probability densities involved in track fitting deviate from the Gaussian assumption, it is plausible that a non-linear estimator which better takes the actual shape of the distribution into account can do better. One such non-linear estimator is the Gaussian-sum filter, which is adequate if the distributions under consideration can be approximated by Gaussian mixtures. The main purpose of this paper is to present a Gaussian-sum filter for track fitting, based on a two-component approximation of the distribution of angular deflections due to multiple scattering. In a simulation study within a linear track model the Gaussian-sum filter is shown to be a competitive alternative to the Kalman filter. Scenarios at various momenta and with various maximum number of components in the Gaussian-sum filter are considered. Particularly at low momenta the Gaussian-sum filter yields a better estimate of the uncertainties than the Kalman filter, and it is also slightly more precise than the latter
International Nuclear Information System (INIS)
Yu, Jie; Chen, Kuilin; Mori, Junichi; Rashid, Mudassir M.
2013-01-01
Optimizing wind power generation and controlling the operation of wind turbines to efficiently harness the renewable wind energy is a challenging task due to the intermittency and unpredictable nature of wind speed, which has significant influence on wind power production. A new approach for long-term wind speed forecasting is developed in this study by integrating GMCM (Gaussian mixture copula model) and localized GPR (Gaussian process regression). The time series of wind speed is first classified into multiple non-Gaussian components through the Gaussian mixture copula model and then Bayesian inference strategy is employed to incorporate the various non-Gaussian components using the posterior probabilities. Further, the localized Gaussian process regression models corresponding to different non-Gaussian components are built to characterize the stochastic uncertainty and non-stationary seasonality of the wind speed data. The various localized GPR models are integrated through the posterior probabilities as the weightings so that a global predictive model is developed for the prediction of wind speed. The proposed GMCM–GPR approach is demonstrated using wind speed data from various wind farm locations and compared against the GMCM-based ARIMA (auto-regressive integrated moving average) and SVR (support vector regression) methods. In contrast to GMCM–ARIMA and GMCM–SVR methods, the proposed GMCM–GPR model is able to well characterize the multi-seasonality and uncertainty of wind speed series for accurate long-term prediction. - Highlights: • A novel predictive modeling method is proposed for long-term wind speed forecasting. • Gaussian mixture copula model is estimated to characterize the multi-seasonality. • Localized Gaussian process regression models can deal with the random uncertainty. • Multiple GPR models are integrated through Bayesian inference strategy. • The proposed approach shows higher prediction accuracy and reliability
Organizations must match assets
International Nuclear Information System (INIS)
Carley, G.R.
1991-01-01
The unprofitable state of the Canadian oil industry, the adverse economic environment, the difficulty of finding capital, and the diminishing resources of conventional lighter crude oil make it necessary for Canadian oil companies to match their organizations and their financing to their assets. This is illustrated according to the experience of Saskoil, a Saskatchewan oil and gas company. An increasing production of oil and natural gas, and an increasing amount of new oil production as heavy oil, led to organizational changes such as the purchase of an asphalt plant to provide the company with downstream experience, establishing a working group to explore and develop heavy oil resources, and forming a company to manage non-core assets. The latter company, Pasqua Resources, manages assets such as small properties and ownership interests in order to increase the operating efficiency of Saskoil. Pasqua provides Saskoil with a corporate and organizational vehicle to accommodate partnerships and joint venture capital invested in property purchase opportunities, and to manage any of Saskoil's divestiture activities
Optimal multicopy asymmetric Gaussian cloning of coherent states
Fiurášek, Jaromír; Cerf, Nicolas J.
2007-05-01
We investigate the asymmetric Gaussian cloning of coherent states which produces M copies from N input replicas in such a way that the fidelity of each copy may be different. We show that the optimal asymmetric Gaussian cloning can be performed with a single phase-insensitive amplifier and an array of beam splitters. We obtain a simple analytical expression characterizing the set of optimal asymmetric Gaussian cloning machines and prove the optimality of these cloners using the formalism of Gaussian completely positive maps and semidefinite programming techniques. We also present an alternative implementation of the asymmetric cloning machine where the phase-insensitive amplifier is replaced with a beam splitter, heterodyne detector, and feedforward.
Making tensor factorizations robust to non-gaussian noise.
Energy Technology Data Exchange (ETDEWEB)
Chi, Eric C. (Rice University, Houston, TX); Kolda, Tamara Gibson
2011-03-01
Tensors are multi-way arrays, and the CANDECOMP/PARAFAC (CP) tensor factorization has found application in many different domains. The CP model is typically fit using a least squares objective function, which is a maximum likelihood estimate under the assumption of independent and identically distributed (i.i.d.) Gaussian noise. We demonstrate that this loss function can be highly sensitive to non-Gaussian noise. Therefore, we propose a loss function based on the 1-norm because it can accommodate both Gaussian and grossly non-Gaussian perturbations. We also present an alternating majorization-minimization (MM) algorithm for fitting a CP model using our proposed loss function (CPAL1) and compare its performance to the workhorse algorithm for fitting CP models, CP alternating least squares (CPALS).
Simple form for the Gaussian equations in curved space
International Nuclear Information System (INIS)
Mazzitelli, F.D.; Paz, J.P.
1988-01-01
We show that the variational Gaussian equations for λphi 4 theory in an arbitrary background gravitational field admit a simple form, which allows the use of a Schwinger-DeWitt-type expansion in order to renormalize them
Optimal multicopy asymmetric Gaussian cloning of coherent states
International Nuclear Information System (INIS)
Fiurasek, Jaromir; Cerf, Nicolas J.
2007-01-01
We investigate the asymmetric Gaussian cloning of coherent states which produces M copies from N input replicas in such a way that the fidelity of each copy may be different. We show that the optimal asymmetric Gaussian cloning can be performed with a single phase-insensitive amplifier and an array of beam splitters. We obtain a simple analytical expression characterizing the set of optimal asymmetric Gaussian cloning machines and prove the optimality of these cloners using the formalism of Gaussian completely positive maps and semidefinite programming techniques. We also present an alternative implementation of the asymmetric cloning machine where the phase-insensitive amplifier is replaced with a beam splitter, heterodyne detector, and feedforward
Quantifying entanglement in two-mode Gaussian states
Tserkis, Spyros; Ralph, Timothy C.
2017-12-01
Entangled two-mode Gaussian states are a key resource for quantum information technologies such as teleportation, quantum cryptography, and quantum computation, so quantification of Gaussian entanglement is an important problem. Entanglement of formation is unanimously considered a proper measure of quantum correlations, but for arbitrary two-mode Gaussian states no analytical form is currently known. In contrast, logarithmic negativity is a measure that is straightforward to calculate and so has been adopted by most researchers, even though it is a less faithful quantifier. In this work, we derive an analytical lower bound for entanglement of formation of generic two-mode Gaussian states, which becomes tight for symmetric states and for states with balanced correlations. We define simple expressions for entanglement of formation in physically relevant situations and use these to illustrate the problematic behavior of logarithmic negativity, which can lead to spurious conclusions.
Super-resolving random-Gaussian apodized photon sieve.
Sabatyan, Arash; Roshaninejad, Parisa
2012-09-10
A novel apodized photon sieve is presented in which random dense Gaussian distribution is implemented to modulate the pinhole density in each zone. The random distribution in dense Gaussian distribution causes intrazone discontinuities. Also, the dense Gaussian distribution generates a substantial number of pinholes in order to form a large degree of overlap between the holes in a few innermost zones of the photon sieve; thereby, clear zones are formed. The role of the discontinuities on the focusing properties of the photon sieve is examined as well. Analysis shows that secondary maxima have evidently been suppressed, transmission has increased enormously, and the central maxima width is approximately unchanged in comparison to the dense Gaussian distribution. Theoretical results have been completely verified by experiment.
Mimicking an amplitude damping channel for Laguerre Gaussian Modes
CSIR Research Space (South Africa)
Dudley, Angela L
2010-10-01
Full Text Available An amplitude damping channel for Laguerre-Gaussian (LG) modes is presented. Experimentally the action of the channel on LG modes is in good agreement with that predicted theoretically....
Scalable Gaussian Processes and the search for exoplanets
CERN. Geneva
2015-01-01
Gaussian Processes are a class of non-parametric models that are often used to model stochastic behavior in time series or spatial data. A major limitation for the application of these models to large datasets is the computational cost. The cost of a single evaluation of the model likelihood scales as the third power of the number of data points. In the search for transiting exoplanets, the datasets of interest have tens of thousands to millions of measurements with uneven sampling, rendering naive application of a Gaussian Process model impractical. To attack this problem, we have developed robust approximate methods for Gaussian Process regression that can be applied at this scale. I will describe the general problem of Gaussian Process regression and offer several applicable use cases. Finally, I will present our work on scaling this model to the exciting field of exoplanet discovery and introduce a well-tested open source implementation of these new methods.
Schweiner, Frank; Laturner, Jeanine; Main, Jörg; Wunner, Günter
2017-11-01
Until now only for specific crossovers between Poissonian statistics (P), the statistics of a Gaussian orthogonal ensemble (GOE), or the statistics of a Gaussian unitary ensemble (GUE) have analytical formulas for the level spacing distribution function been derived within random matrix theory. We investigate arbitrary crossovers in the triangle between all three statistics. To this aim we propose an according formula for the level spacing distribution function depending on two parameters. Comparing the behavior of our formula for the special cases of P→GUE, P→GOE, and GOE→GUE with the results from random matrix theory, we prove that these crossovers are described reasonably. Recent investigations by F. Schweiner et al. [Phys. Rev. E 95, 062205 (2017)2470-004510.1103/PhysRevE.95.062205] have shown that the Hamiltonian of magnetoexcitons in cubic semiconductors can exhibit all three statistics in dependence on the system parameters. Evaluating the numerical results for magnetoexcitons in dependence on the excitation energy and on a parameter connected with the cubic valence band structure and comparing the results with the formula proposed allows us to distinguish between regular and chaotic behavior as well as between existent or broken antiunitary symmetries. Increasing one of the two parameters, transitions between different crossovers, e.g., from the P→GOE to the P→GUE crossover, are observed and discussed.
Energy Technology Data Exchange (ETDEWEB)
Kenfack, Lionel Tenemeza, E-mail: kenfacklionel300@gmail.com [Mesoscopic and Multilayer Structure Laboratory, Department of Physics, Faculty of Science, University of Dschang, PO Box: 67 Dschang (Cameroon); Tchoffo, Martin; Fai, Lukong Cornelius [Mesoscopic and Multilayer Structure Laboratory, Department of Physics, Faculty of Science, University of Dschang, PO Box: 67 Dschang (Cameroon); Fouokeng, Georges Collince [Mesoscopic and Multilayer Structure Laboratory, Department of Physics, Faculty of Science, University of Dschang, PO Box: 67 Dschang (Cameroon); Laboratoire de Génie des Matériaux, Pôle Recherche-Innovation-Entrepreneuriat (PRIE), Institut Universitaire de la Côte, BP 3001 Douala (Cameroon)
2017-04-15
We address the entanglement dynamics of a three-qubit system interacting with a classical fluctuating environment described either by a Gaussian or non-Gaussian noise in three different configurations namely: common, independent and mixed environments. Specifically, we focus on the Ornstein-Uhlenbeck (OU) noise and the random telegraph noise (RTN). The qubits are prepared in a state composed of a Greenberger-Horne-Zeilinger (GHZ) and a W state. With the help of the tripartite negativity, we show that the entanglement evolution is not only affected by the type of system-environment coupling but also by the kind and the memory properties of the considered noise. We also compared the dynamics induced by the two kinds of noise and we find that even if both noises have a Lorentzian spectrum, the effects of the OU noise cannot be in a simple way deduced from those of the RTN and vice-versa. In addition, we show that the entanglement can be indefinitely preserved when the qubits are coupled to the environmental noise in a common environment (CE). Finally, the presence or absence of peculiar phenomena such as entanglement revivals (ER) and entanglement sudden death (ESD) is observed.
International Nuclear Information System (INIS)
Kenfack, Lionel Tenemeza; Tchoffo, Martin; Fai, Lukong Cornelius; Fouokeng, Georges Collince
2017-01-01
We address the entanglement dynamics of a three-qubit system interacting with a classical fluctuating environment described either by a Gaussian or non-Gaussian noise in three different configurations namely: common, independent and mixed environments. Specifically, we focus on the Ornstein-Uhlenbeck (OU) noise and the random telegraph noise (RTN). The qubits are prepared in a state composed of a Greenberger-Horne-Zeilinger (GHZ) and a W state. With the help of the tripartite negativity, we show that the entanglement evolution is not only affected by the type of system-environment coupling but also by the kind and the memory properties of the considered noise. We also compared the dynamics induced by the two kinds of noise and we find that even if both noises have a Lorentzian spectrum, the effects of the OU noise cannot be in a simple way deduced from those of the RTN and vice-versa. In addition, we show that the entanglement can be indefinitely preserved when the qubits are coupled to the environmental noise in a common environment (CE). Finally, the presence or absence of peculiar phenomena such as entanglement revivals (ER) and entanglement sudden death (ESD) is observed.
Non-gaussianity versus nonlinearity of cosmological perturbations.
Verde, L
2001-06-01
Following the discovery of the cosmic microwave background, the hot big-bang model has become the standard cosmological model. In this theory, small primordial fluctuations are subsequently amplified by gravity to form the large-scale structure seen today. Different theories for unified models of particle physics, lead to different predictions for the statistical properties of the primordial fluctuations, that can be divided in two classes: gaussian and non-gaussian. Convincing evidence against or for gaussian initial conditions would rule out many scenarios and point us toward a physical theory for the origin of structures. The statistical distribution of cosmological perturbations, as we observe them, can deviate from the gaussian distribution in several different ways. Even if perturbations start off gaussian, nonlinear gravitational evolution can introduce non-gaussian features. Additionally, our knowledge of the Universe comes principally from the study of luminous material such as galaxies, but galaxies might not be faithful tracers of the underlying mass distribution. The relationship between fluctuations in the mass and in the galaxies distribution (bias), is often assumed to be local, but could well be nonlinear. Moreover, galaxy catalogues use the redshift as third spatial coordinate: the resulting redshift-space map of the galaxy distribution is nonlinearly distorted by peculiar velocities. Nonlinear gravitational evolution, biasing, and redshift-space distortion introduce non-gaussianity, even in an initially gaussian fluctuation field. I investigate the statistical tools that allow us, in principle, to disentangle the above different effects, and the observational datasets we require to do so in practice.
GAUSSIAN 76: an ab initio molecular orbital program
International Nuclear Information System (INIS)
Binkley, J.S.; Whiteside, R.; Hariharan, P.C.; Seeger, R.; Hehre, W.J.; Lathan, W.A.; Newton, M.D.; Ditchfield, R.; Pople, J.A.
Gaussian 76 is a general-purpose computer program for ab initio Hartree-Fock molecular orbital calculations. It can handle basis sets involving s, p and d-type gaussian functions. Certain standard sets (STO-3G, 4-31G, 6-31G*, etc.) are stored internally for easy use. Closed shell (RHF) or unrestricted open shell (UHF) wave functions can be obtained. Facilities are provided for geometry optimization to potential minima and for limited potential surface scans
Gaussian Process Regression for WDM System Performance Prediction
DEFF Research Database (Denmark)
Wass, Jesper; Thrane, Jakob; Piels, Molly
2017-01-01
Gaussian process regression is numerically and experimentally investigated to predict the bit error rate of a 24 x 28 CiBd QPSK WDM system. The proposed method produces accurate predictions from multi-dimensional and sparse measurement data.......Gaussian process regression is numerically and experimentally investigated to predict the bit error rate of a 24 x 28 CiBd QPSK WDM system. The proposed method produces accurate predictions from multi-dimensional and sparse measurement data....
Revisiting non-Gaussianity from non-attractor inflation models
Cai, Yi-Fu; Chen, Xingang; Namjoo, Mohammad Hossein; Sasaki, Misao; Wang, Dong-Gang; Wang, Ziwei
2018-05-01
Non-attractor inflation is known as the only single field inflationary scenario that can violate non-Gaussianity consistency relation with the Bunch-Davies vacuum state and generate large local non-Gaussianity. However, it is also known that the non-attractor inflation by itself is incomplete and should be followed by a phase of slow-roll attractor. Moreover, there is a transition process between these two phases. In the past literature, this transition was approximated as instant and the evolution of non-Gaussianity in this phase was not fully studied. In this paper, we follow the detailed evolution of the non-Gaussianity through the transition phase into the slow-roll attractor phase, considering different types of transition. We find that the transition process has important effect on the size of the local non-Gaussianity. We first compute the net contribution of the non-Gaussianities at the end of inflation in canonical non-attractor models. If the curvature perturbations keep evolving during the transition—such as in the case of smooth transition or some sharp transition scenarios—the Script O(1) local non-Gaussianity generated in the non-attractor phase can be completely erased by the subsequent evolution, although the consistency relation remains violated. In extremal cases of sharp transition where the super-horizon modes freeze immediately right after the end of the non-attractor phase, the original non-attractor result can be recovered. We also study models with non-canonical kinetic terms, and find that the transition can typically contribute a suppression factor in the squeezed bispectrum, but the final local non-Gaussianity can still be made parametrically large.
Identification and estimation of non-Gaussian structural vector autoregressions
DEFF Research Database (Denmark)
Lanne, Markku; Meitz, Mika; Saikkonen, Pentti
-Gaussian components is, without any additional restrictions, identified and leads to (essentially) unique impulse responses. We also introduce an identification scheme under which the maximum likelihood estimator of the non-Gaussian SVAR model is consistent and asymptotically normally distributed. As a consequence......, additional economic identifying restrictions can be tested. In an empirical application, we find a negative impact of a contractionary monetary policy shock on financial markets, and clearly reject the commonly employed recursive identifying restrictions....
Libera, Arianna; de Barros, Felipe P. J.; Riva, Monica; Guadagnini, Alberto
2017-10-01
Our study is keyed to the analysis of the interplay between engineering factors (i.e., transient pumping rates versus less realistic but commonly analyzed uniform extraction rates) and the heterogeneous structure of the aquifer (as expressed by the probability distribution characterizing transmissivity) on contaminant transport. We explore the joint influence of diverse (a) groundwater pumping schedules (constant and variable in time) and (b) representations of the stochastic heterogeneous transmissivity (T) field on temporal histories of solute concentrations observed at an extraction well. The stochastic nature of T is rendered by modeling its natural logarithm, Y = ln T, through a typical Gaussian representation and the recently introduced Generalized sub-Gaussian (GSG) model. The latter has the unique property to embed scale-dependent non-Gaussian features of the main statistics of Y and its (spatial) increments, which have been documented in a variety of studies. We rely on numerical Monte Carlo simulations and compute the temporal evolution at the well of low order moments of the solute concentration (C), as well as statistics of the peak concentration (Cp), identified as the environmental performance metric of interest in this study. We show that the pumping schedule strongly affects the pattern of the temporal evolution of the first two statistical moments of C, regardless the nature (Gaussian or non-Gaussian) of the underlying Y field, whereas the latter quantitatively influences their magnitude. Our results show that uncertainty associated with C and Cp estimates is larger when operating under a transient extraction scheme than under the action of a uniform withdrawal schedule. The probability density function (PDF) of Cp displays a long positive tail in the presence of time-varying pumping schedule. All these aspects are magnified in the presence of non-Gaussian Y fields. Additionally, the PDF of Cp displays a bimodal shape for all types of pumping
International Nuclear Information System (INIS)
Tsoukalas, L.
2002-01-01
Funding used to support a portion of the Nuclear Engineering Educational Activities. Upgrade of teaching labs, student support to attend professional conferences, salary support for graduate students. The US Department of Energy (DOE) has funded Purdue University School of Nuclear Engineering during the period of five academic years covered in this report starting in the academic year 1996-97 and ending in the academic year 2000-2001. The total amount of funding for the grant received from DOE is $416K. In the 1990's, Nuclear Engineering Education in the US experienced a significant slow down. Student enrollment, research support, number of degrees at all levels (BS, MS, and PhD), number of accredited programs, University Research and Training Reactors, all went through a decline to alarmingly low levels. Several departments closed down, while some were amalgamated with other academic units (Mechanical Engineering, Chemical Engineering, etc). The School of Nuclear Engineering at Purdue University faced a major challenge when in the mid 90's our total undergraduate enrollment for the Sophomore, Junior and Senior Years dropped in the low 30's. The DOE Matching Grant program greatly strengthened Purdue's commitment to the Nuclear Engineering discipline and has helped to dramatically improve our undergraduate and graduate enrollment, attract new faculty and raise the School of Nuclear Engineering status within the University and in the National scene (our undergraduate enrollment has actually tripled and stands at an all time high of over 90 students; total enrollment currently exceeds 110 students). In this final technical report we outline and summarize how the grant was expended at Purdue University
Current inversion induced by colored non-Gaussian noise
International Nuclear Information System (INIS)
Bag, Bidhan Chandra; Hu, Chin-Kung
2009-01-01
We study a stochastic process driven by colored non-Gaussian noises. For the flashing ratchet model we find that there is a current inversion in the variation of the current with the half-cycle period which accounts for the potential on–off operation. The current inversion almost disappears if one switches from non-Gaussian (NG) to Gaussian (G) noise. We also find that at low value of the asymmetry parameter of the potential the mobility controlled current is more negative for NG noise as compared to G noise. But at large magnitude of the parameter the diffusion controlled positive current is higher for the former than for the latter. On increasing the noise correlation time (τ), keeping the noise strength fixed, the mean velocity of a particle first increases and then decreases after passing through a maximum if the noise is non-Gaussian. For Gaussian noise, the current monotonically decreases. The current increases with the noise parameter p, 0< p<5/3, which is 1 for Gaussian noise
Passivity and practical work extraction using Gaussian operations
International Nuclear Information System (INIS)
Brown, Eric G; Huber, Marcus; Friis, Nicolai
2016-01-01
Quantum states that can yield work in a cyclical Hamiltonian process form one of the primary resources in the context of quantum thermodynamics. Conversely, states whose average energy cannot be lowered by unitary transformations are called passive. However, while work may be extracted from non-passive states using arbitrary unitaries, the latter may be hard to realize in practice. It is therefore pertinent to consider the passivity of states under restricted classes of operations that can be feasibly implemented. Here, we ask how restrictive the class of Gaussian unitaries is for the task of work extraction. We investigate the notion of Gaussian passivity, that is, we present necessary and sufficient criteria identifying all states whose energy cannot be lowered by Gaussian unitaries. For all other states we give a prescription for the Gaussian operations that extract the maximal amount of energy. Finally, we show that the gap between passivity and Gaussian passivity is maximal, i.e., Gaussian-passive states may still have a maximal amount of energy that is extractable by arbitrary unitaries, even under entropy constraints. (paper)
Superstatistical generalised Langevin equation: non-Gaussian viscoelastic anomalous diffusion
Ślęzak, Jakub; Metzler, Ralf; Magdziarz, Marcin
2018-02-01
Recent advances in single particle tracking and supercomputing techniques demonstrate the emergence of normal or anomalous, viscoelastic diffusion in conjunction with non-Gaussian distributions in soft, biological, and active matter systems. We here formulate a stochastic model based on a generalised Langevin equation in which non-Gaussian shapes of the probability density function and normal or anomalous diffusion have a common origin, namely a random parametrisation of the stochastic force. We perform a detailed analysis demonstrating how various types of parameter distributions for the memory kernel result in exponential, power law, or power-log law tails of the memory functions. The studied system is also shown to exhibit a further unusual property: the velocity has a Gaussian one point probability density but non-Gaussian joint distributions. This behaviour is reflected in the relaxation from a Gaussian to a non-Gaussian distribution observed for the position variable. We show that our theoretical results are in excellent agreement with stochastic simulations.
Non-Gaussianity from inflation: theory and observations
Bartolo, N.; Komatsu, E.; Matarrese, S.; Riotto, A.
2004-11-01
This is a review of models of inflation and of their predictions for the primordial non-Gaussianity in the density perturbations which are thought to be at the origin of structures in the Universe. Non-Gaussianity emerges as a key observable to discriminate among competing scenarios for the generation of cosmological perturbations and is one of the primary targets of present and future Cosmic Microwave Background satellite missions. We give a detailed presentation of the state-of-the-art of the subject of non-Gaussianity, both from the theoretical and the observational point of view, and provide all the tools necessary to compute at second order in perturbation theory the level of non-Gaussianity in any model of cosmological perturbations. We discuss the new wave of models of inflation, which are firmly rooted in modern particle physics theory and predict a significant amount of non-Gaussianity. The review is addressed to both astrophysicists and particle physicists and contains useful tables which summarize the theoretical and observational results regarding non-Gaussianity.
Back to Normal! Gaussianizing posterior distributions for cosmological probes
Schuhmann, Robert L.; Joachimi, Benjamin; Peiris, Hiranya V.
2014-05-01
We present a method to map multivariate non-Gaussian posterior probability densities into Gaussian ones via nonlinear Box-Cox transformations, and generalizations thereof. This is analogous to the search for normal parameters in the CMB, but can in principle be applied to any probability density that is continuous and unimodal. The search for the optimally Gaussianizing transformation amongst the Box-Cox family is performed via a maximum likelihood formalism. We can judge the quality of the found transformation a posteriori: qualitatively via statistical tests of Gaussianity, and more illustratively by how well it reproduces the credible regions. The method permits an analytical reconstruction of the posterior from a sample, e.g. a Markov chain, and simplifies the subsequent joint analysis with other experiments. Furthermore, it permits the characterization of a non-Gaussian posterior in a compact and efficient way. The expression for the non-Gaussian posterior can be employed to find analytic formulae for the Bayesian evidence, and consequently be used for model comparison.
International Nuclear Information System (INIS)
Essa, K.S.M.
2009-01-01
The analytical solution of the atmospheric diffusion equation for a point source gives the ground-level concentration profiles. It depends on the wind speed ua nd vertical dispersion coefficient σ z expressed by Pasquill power laws. Both σ z and u are functions of downwind distance, stability and source elevation, while for the ground-level emission u is constant. In the neutral and stable conditions, the Gaussian plume model and finite difference numerical methods with wind speed in power law and the vertical dispersion coefficient in exponential law are estimated. This work shows that the estimated ground-level concentrations of the Gaussian model for high-level source and numerical finite difference method are very match fit to the observed ground-level concentrations of the Gaussian model
Most Recent Match Queries in On-Line Suffix Trees
DEFF Research Database (Denmark)
Larsson, N. Jesper
2014-01-01
A suffix tree is able to efficiently locate a pattern in an indexed string, but not in general the most recent copy of the pattern in an online stream, which is desirable in some applications. We study the most general version of the problem of locating a most recent match: supporting queries...
Scaled unscented transform Gaussian sum filter: Theory and application
Luo, Xiaodong
2010-05-01
In this work we consider the state estimation problem in nonlinear/non-Gaussian systems. We introduce a framework, called the scaled unscented transform Gaussian sum filter (SUT-GSF), which combines two ideas: the scaled unscented Kalman filter (SUKF) based on the concept of scaled unscented transform (SUT) (Julier and Uhlmann (2004) [16]), and the Gaussian mixture model (GMM). The SUT is used to approximate the mean and covariance of a Gaussian random variable which is transformed by a nonlinear function, while the GMM is adopted to approximate the probability density function (pdf) of a random variable through a set of Gaussian distributions. With these two tools, a framework can be set up to assimilate nonlinear systems in a recursive way. Within this framework, one can treat a nonlinear stochastic system as a mixture model of a set of sub-systems, each of which takes the form of a nonlinear system driven by a known Gaussian random process. Then, for each sub-system, one applies the SUKF to estimate the mean and covariance of the underlying Gaussian random variable transformed by the nonlinear governing equations of the sub-system. Incorporating the estimations of the sub-systems into the GMM gives an explicit (approximate) form of the pdf, which can be regarded as a "complete" solution to the state estimation problem, as all of the statistical information of interest can be obtained from the explicit form of the pdf (Arulampalam et al. (2002) [7]). In applications, a potential problem of a Gaussian sum filter is that the number of Gaussian distributions may increase very rapidly. To this end, we also propose an auxiliary algorithm to conduct pdf re-approximation so that the number of Gaussian distributions can be reduced. With the auxiliary algorithm, in principle the SUT-GSF can achieve almost the same computational speed as the SUKF if the SUT-GSF is implemented in parallel. As an example, we will use the SUT-GSF to assimilate a 40-dimensional system due to
Matching theory for wireless networks
Han, Zhu; Saad, Walid
2017-01-01
This book provides the fundamental knowledge of the classical matching theory problems. It builds up the bridge between the matching theory and the 5G wireless communication resource allocation problems. The potentials and challenges of implementing the semi-distributive matching theory framework into the wireless resource allocations are analyzed both theoretically and through implementation examples. Academics, researchers, engineers, and so on, who are interested in efficient distributive wireless resource allocation solutions, will find this book to be an exceptional resource. .
Probability matching and strategy availability
J. Koehler, Derek; Koehler, Derek J.; James, Greta
2010-01-01
Findings from two experiments indicate that probability matching in sequential choice arises from an asymmetry in strategy availability: The matching strategy comes readily to mind, whereas a superior alternative strategy, maximizing, does not. First, compared with the minority who spontaneously engage in maximizing, the majority of participants endorse maximizing as superior to matching in a direct comparison when both strategies are described. Second, when the maximizing strategy is brought...
An Incentive Theory of Matching
Brown, Alessio J. G.; Merkl, Christian; Snower, Dennis J.
2010-01-01
This paper examines the labour market matching process by distinguishing its two component stages: the contact stage, in which job searchers make contact with employers and the selection stage, in which they decide whether to match. We construct a theoretical model explaining two-sided selection through microeconomic incentives. Firms face adjustment costs in responding to heterogeneous variations in the characteristics of workers and jobs. Matches and separations are described through firms'...
International Nuclear Information System (INIS)
Nishimichi, Takahiro
2012-01-01
The large-scale clustering pattern of biased tracers is known to be a powerful probe of the non-Gaussianities in the primordial fluctuations. The so-called scale-dependent bias has been reported in various type of models of primordial non-Gaussianities. We focus on local-type non-Gaussianities, and unify the derivations in the literature of the scale-dependent bias in the presence of multiple Gaussian source fields as well as higher-order coupling to cover the models described by frequently-discussed f NL , g NL and t NL parameterization. We find that the resultant power spectrum is characterized by two parameters responsible for the shape and the amplitude of the scale-dependent bias in addition to the Gaussian bias factor. We show how (a generalized version of) Suyama-Yamaguchi inequality between f NL and t NL can directly be accessible from the observed power spectrum through the dependence on our new parameter which controls the shape of the scale-dependent bias. The other parameter for the amplitude of the scale-dependent bias is shown to be useful to distinguish the simplest quadratic non-Gaussianities (i.e., f NL -type) from higher-order ones (g NL and higher), if one measures it from multiple species of galaxies or clusters of galaxies. We discuss the validity and limitations of our analytic results by comparison with numerical simulations in an accompanying paper
DOE Matching Grant Program; FINAL
International Nuclear Information System (INIS)
Dr Marvin Adams
2002-01-01
OAK 270 - The DOE Matching Grant Program provided$50,000.00 to the Dept of N.E. at TAMU, matching a gift of$50,000.00 from TXU Electric. The$100,000.00 total was spent on scholarships, departmental labs, and computing network
Matching score based face recognition
Boom, B.J.; Beumer, G.M.; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.
2006-01-01
Accurate face registration is of vital importance to the performance of a face recognition algorithm. We propose a new method: matching score based face registration, which searches for optimal alignment by maximizing the matching score output of a classifier as a function of the different
Platform pricing in matching markets
Goos, M.; van Cayseele, P.; Willekens, B.
2011-01-01
This paper develops a simple model of monopoly platform pricing accounting for two pertinent features of matching markets. 1) The trading process is characterized by search and matching frictions implying limits to positive cross-side network effects and the presence of own-side congestion.
Statistical methods for history matching
DEFF Research Database (Denmark)
Johansen, Kent
Denne afhandling beskriver statistiske metoder til history matching af olieproduktion. History matching er en vigtig del af driften af et oliefelt og er ofte forbundet med problemer relateret til kompleksiteten af reservoiret og selve størrelsen af reservoirsimuleringsmodellen. Begrebet history m...
Role model and prototype matching
DEFF Research Database (Denmark)
Lykkegaard, Eva; Ulriksen, Lars
2016-01-01
’ meetings with the role models affected their thoughts concerning STEM students and attending university. The regular self-to-prototype matching process was shown in real-life role-models meetings to be extended to a more complex three-way matching process between students’ self-perceptions, prototype...
Gaussian Graphical Models Identify Networks of Dietary Intake in a German Adult Population.
Iqbal, Khalid; Buijsse, Brian; Wirth, Janine; Schulze, Matthias B; Floegel, Anna; Boeing, Heiner
2016-03-01
Data-reduction methods such as principal component analysis are often used to derive dietary patterns. However, such methods do not assess how foods are consumed in relation to each other. Gaussian graphical models (GGMs) are a set of novel methods that can address this issue. We sought to apply GGMs to derive sex-specific dietary intake networks representing consumption patterns in a German adult population. Dietary intake data from 10,780 men and 16,340 women of the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam cohort were cross-sectionally analyzed to construct dietary intake networks. Food intake for each participant was estimated using a 148-item food-frequency questionnaire that captured the intake of 49 food groups. GGMs were applied to log-transformed intakes (grams per day) of 49 food groups to construct sex-specific food networks. Semiparametric Gaussian copula graphical models (SGCGMs) were used to confirm GGM results. In men, GGMs identified 1 major dietary network that consisted of intakes of red meat, processed meat, cooked vegetables, sauces, potatoes, cabbage, poultry, legumes, mushrooms, soup, and whole-grain and refined breads. For women, a similar network was identified with the addition of fried potatoes. Other identified networks consisted of dairy products and sweet food groups. SGCGMs yielded results comparable to those of GGMs. GGMs are a powerful exploratory method that can be used to construct dietary networks representing dietary intake patterns that reveal how foods are consumed in relation to each other. GGMs indicated an apparent major role of red meat intake in a consumption pattern in the studied population. In the future, identified networks might be transformed into pattern scores for investigating their associations with health outcomes. © 2016 American Society for Nutrition.
Capacity and optimal collusion attack channels for Gaussian fingerprinting games
Wang, Ying; Moulin, Pierre
2007-02-01
In content fingerprinting, the same media covertext - image, video, audio, or text - is distributed to many users. A fingerprint, a mark unique to each user, is embedded into each copy of the distributed covertext. In a collusion attack, two or more users may combine their copies in an attempt to "remove" their fingerprints and forge a pirated copy. To trace the forgery back to members of the coalition, we need fingerprinting codes that can reliably identify the fingerprints of those members. Researchers have been focusing on designing or testing fingerprints for Gaussian host signals and the mean square error (MSE) distortion under some classes of collusion attacks, in terms of the detector's error probability in detecting collusion members. For example, under the assumptions of Gaussian fingerprints and Gaussian attacks (the fingerprinted signals are averaged and then the result is passed through a Gaussian test channel), Moulin and Briassouli1 derived optimal strategies in a game-theoretic framework that uses the detector's error probability as the performance measure for a binary decision problem (whether a user participates in the collusion attack or not); Stone2 and Zhao et al. 3 studied average and other non-linear collusion attacks for Gaussian-like fingerprints; Wang et al. 4 stated that the average collusion attack is the most efficient one for orthogonal fingerprints; Kiyavash and Moulin 5 derived a mathematical proof of the optimality of the average collusion attack under some assumptions. In this paper, we also consider Gaussian cover signals, the MSE distortion, and memoryless collusion attacks. We do not make any assumption about the fingerprinting codes used other than an embedding distortion constraint. Also, our only assumptions about the attack channel are an expected distortion constraint, a memoryless constraint, and a fairness constraint. That is, the colluders are allowed to use any arbitrary nonlinear strategy subject to the above
Skewness and kurtosis analysis for non-Gaussian distributions
Celikoglu, Ahmet; Tirnakli, Ugur
2018-06-01
In this paper we address a number of pitfalls regarding the use of kurtosis as a measure of deviations from the Gaussian. We treat kurtosis in both its standard definition and that which arises in q-statistics, namely q-kurtosis. We have recently shown that the relation proposed by Cristelli et al. (2012) between skewness and kurtosis can only be verified for relatively small data sets, independently of the type of statistics chosen; however it fails for sufficiently large data sets, if the fourth moment of the distribution is finite. For infinite fourth moments, kurtosis is not defined as the size of the data set tends to infinity. For distributions with finite fourth moments, the size, N, of the data set for which the standard kurtosis saturates to a fixed value, depends on the deviation of the original distribution from the Gaussian. Nevertheless, using kurtosis as a criterion for deciding which distribution deviates further from the Gaussian can be misleading for small data sets, even for finite fourth moment distributions. Going over to q-statistics, we find that although the value of q-kurtosis is finite in the range of 0 < q < 3, this quantity is not useful for comparing different non-Gaussian distributed data sets, unless the appropriate q value, which truly characterizes the data set of interest, is chosen. Finally, we propose a method to determine the correct q value and thereby to compute the q-kurtosis of q-Gaussian distributed data sets.
Generation of Quasi-Gaussian Pulses Based on Correlation Techniques
Directory of Open Access Journals (Sweden)
POHOATA, S.
2012-02-01
Full Text Available The Gaussian pulses have been mostly used within communications, where some applications can be emphasized: mobile telephony (GSM, where GMSK signals are used, as well as the UWB communications, where short-period pulses based on Gaussian waveform are generated. Since the Gaussian function signifies a theoretical concept, which cannot be accomplished from the physical point of view, this should be expressed by using various functions, able to determine physical implementations. New techniques of generating the Gaussian pulse responses of good precision are approached, proposed and researched in this paper. The second and third order derivatives with regard to the Gaussian pulse response are accurately generated. The third order derivates is composed of four individual rectangular pulses of fixed amplitudes, being easily to be generated by standard techniques. In order to generate pulses able to satisfy the spectral mask requirements, an adequate filter is necessary to be applied. This paper emphasizes a comparative analysis based on the relative error and the energy spectra of the proposed pulses.
Gaussianization for fast and accurate inference from cosmological data
Schuhmann, Robert L.; Joachimi, Benjamin; Peiris, Hiranya V.
2016-06-01
We present a method to transform multivariate unimodal non-Gaussian posterior probability densities into approximately Gaussian ones via non-linear mappings, such as Box-Cox transformations and generalizations thereof. This permits an analytical reconstruction of the posterior from a point sample, like a Markov chain, and simplifies the subsequent joint analysis with other experiments. This way, a multivariate posterior density can be reported efficiently, by compressing the information contained in Markov Chain Monte Carlo samples. Further, the model evidence integral (I.e. the marginal likelihood) can be computed analytically. This method is analogous to the search for normal parameters in the cosmic microwave background, but is more general. The search for the optimally Gaussianizing transformation is performed computationally through a maximum-likelihood formalism; its quality can be judged by how well the credible regions of the posterior are reproduced. We demonstrate that our method outperforms kernel density estimates in this objective. Further, we select marginal posterior samples from Planck data with several distinct strongly non-Gaussian features, and verify the reproduction of the marginal contours. To demonstrate evidence computation, we Gaussianize the joint distribution of data from weak lensing and baryon acoustic oscillations, for different cosmological models, and find a preference for flat Λcold dark matter. Comparing to values computed with the Savage-Dickey density ratio, and Population Monte Carlo, we find good agreement of our method within the spread of the other two.
Non-Gaussian Methods for Causal Structure Learning.
Shimizu, Shohei
2018-05-22
Causal structure learning is one of the most exciting new topics in the fields of machine learning and statistics. In many empirical sciences including prevention science, the causal mechanisms underlying various phenomena need to be studied. Nevertheless, in many cases, classical methods for causal structure learning are not capable of estimating the causal structure of variables. This is because it explicitly or implicitly assumes Gaussianity of data and typically utilizes only the covariance structure. In many applications, however, non-Gaussian data are often obtained, which means that more information may be contained in the data distribution than the covariance matrix is capable of containing. Thus, many new methods have recently been proposed for using the non-Gaussian structure of data and inferring the causal structure of variables. This paper introduces prevention scientists to such causal structure learning methods, particularly those based on the linear, non-Gaussian, acyclic model known as LiNGAM. These non-Gaussian data analysis tools can fully estimate the underlying causal structures of variables under assumptions even in the presence of unobserved common causes. This feature is in contrast to other approaches. A simulated example is also provided.
Consistency relations for sharp inflationary non-Gaussian features
Energy Technology Data Exchange (ETDEWEB)
Mooij, Sander; Palma, Gonzalo A.; Panotopoulos, Grigoris [Departamento de Física, Facultad de Ciencias Físicas y Matemáticas, Universidad de Chile, Blanco Encalada 2008, Santiago (Chile); Soto, Alex, E-mail: sander.mooij@ing.uchile.cl, E-mail: gpalmaquilod@ing.uchile.cl, E-mail: gpanotop@ing.uchile.cl, E-mail: gatogeno@gmail.com [Departamento de Física, Facultad de Ciencias, Universidad de Chile, Las Palmeras 3425, Ñuñoa, Santiago (Chile)
2016-09-01
If cosmic inflation suffered tiny time-dependent deviations from the slow-roll regime, these would induce the existence of small scale-dependent features imprinted in the primordial spectra, with their shapes and sizes revealing information about the physics that produced them. Small sharp features could be suppressed at the level of the two-point correlation function, making them undetectable in the power spectrum, but could be amplified at the level of the three-point correlation function, offering us a window of opportunity to uncover them in the non-Gaussian bispectrum. In this article, we show that sharp features may be analyzed using only data coming from the three point correlation function parametrizing primordial non-Gaussianity. More precisely, we show that if features appear in a particular non-Gaussian triangle configuration (e.g. equilateral, folded, squeezed), these must reappear in every other configuration according to a specific relation allowing us to correlate features across the non-Gaussian bispectrum. As a result, we offer a method to study scale-dependent features generated during inflation that depends only on data coming from measurements of non-Gaussianity, allowing us to omit data from the power spectrum.
Consistency relations for sharp inflationary non-Gaussian features
International Nuclear Information System (INIS)
Mooij, Sander; Palma, Gonzalo A.; Panotopoulos, Grigoris; Soto, Alex
2016-01-01
If cosmic inflation suffered tiny time-dependent deviations from the slow-roll regime, these would induce the existence of small scale-dependent features imprinted in the primordial spectra, with their shapes and sizes revealing information about the physics that produced them. Small sharp features could be suppressed at the level of the two-point correlation function, making them undetectable in the power spectrum, but could be amplified at the level of the three-point correlation function, offering us a window of opportunity to uncover them in the non-Gaussian bispectrum. In this article, we show that sharp features may be analyzed using only data coming from the three point correlation function parametrizing primordial non-Gaussianity. More precisely, we show that if features appear in a particular non-Gaussian triangle configuration (e.g. equilateral, folded, squeezed), these must reappear in every other configuration according to a specific relation allowing us to correlate features across the non-Gaussian bispectrum. As a result, we offer a method to study scale-dependent features generated during inflation that depends only on data coming from measurements of non-Gaussianity, allowing us to omit data from the power spectrum.
Efficient line matching with homography
Shen, Yan; Dai, Yuxing; Zhu, Zhiliang
2018-03-01
In this paper, we propose a novel approach to line matching based on homography. The basic idea is to use cheaply obtainable matched points to boost the similarity between two images. Two types of homography method, which are estimated by direct linear transformation, transform images and extract their similar parts, laying a foundation for the use of optical flow tracking. The merit of the similarity is that rapid matching can be achieved by regionalizing line segments and local searching. For multiple homography estimation that can perform better than one global homography, we introduced the rank-one modification method of singular value decomposition to reduce the computation cost. The proposed approach results in point-to-point matches, which can be utilized with state-of-the-art point-match-based structures from motion (SfM) frameworks seamlessly. The outstanding performance and feasible robustness of our approach are demonstrated in this paper.
Estimation of Seismic Wavelets Based on the Multivariate Scale Mixture of Gaussians Model
Directory of Open Access Journals (Sweden)
Jing-Huai Gao
2009-12-01
Full Text Available This paper proposes a new method for estimating seismic wavelets. Suppose a seismic wavelet can be modeled by a formula with three free parameters (scale, frequency and phase. We can transform the estimation of the wavelet into determining these three parameters. The phase of the wavelet is estimated by constant-phase rotation to the seismic signal, while the other two parameters are obtained by the Higher-order Statistics (HOS (fourth-order cumulant matching method. In order to derive the estimator of the Higher-order Statistics (HOS, the multivariate scale mixture of Gaussians (MSMG model is applied to formulating the multivariate joint probability density function (PDF of the seismic signal. By this way, we can represent HOS as a polynomial function of second-order statistics to improve the anti-noise performance and accuracy. In addition, the proposed method can work well for short time series.
Haptic spatial matching in near peripersonal space.
Kaas, Amanda L; Mier, Hanneke I van
2006-04-01
Research has shown that haptic spatial matching at intermanual distances over 60 cm is prone to large systematic errors. The error pattern has been explained by the use of reference frames intermediate between egocentric and allocentric coding. This study investigated haptic performance in near peripersonal space, i.e. at intermanual distances of 60 cm and less. Twelve blindfolded participants (six males and six females) were presented with two turn bars at equal distances from the midsagittal plane, 30 or 60 cm apart. Different orientations (vertical/horizontal or oblique) of the left bar had to be matched by adjusting the right bar to either a mirror symmetric (/ \\) or parallel (/ /) position. The mirror symmetry task can in principle be performed accurately in both an egocentric and an allocentric reference frame, whereas the parallel task requires an allocentric representation. Results showed that parallel matching induced large systematic errors which increased with distance. Overall error was significantly smaller in the mirror task. The task difference also held for the vertical orientation at 60 cm distance, even though this orientation required the same response in both tasks, showing a marked effect of task instruction. In addition, men outperformed women on the parallel task. Finally, contrary to our expectations, systematic errors were found in the mirror task, predominantly at 30 cm distance. Based on these findings, we suggest that haptic performance in near peripersonal space might be dominated by different mechanisms than those which come into play at distances over 60 cm. Moreover, our results indicate that both inter-individual differences and task demands affect task performance in haptic spatial matching. Therefore, we conclude that the study of haptic spatial matching in near peripersonal space might reveal important additional constraints for the specification of adequate models of haptic spatial performance.
The urology residency matching program in practice.
Teichman, J M; Anderson, K D; Dorough, M M; Stein, C R; Optenberg, S A; Thompson, I M
2000-06-01
We evaluate behaviors and attitudes among resident applicants and program directors related to the American Urological Association (AUA) residency matching program and recommend changes to improve the match. Written questionnaires were mailed to 519 resident applicants and 112 program directors after the 1999 American Urological Association match. Subjects were asked about their observations, behaviors and opinions towards the match. Questionnaires were returned by 230 resident applicants and 94 program directors (44% and 83% response rates, respectively.) Of the resident applicants 75% spent $1,001 to $5,000 for interviewing. Of the program directors 47% recalled that applicants asked how programs would rank the applicant and 61% of applicants recalled that program directors asked applicants how they would rank programs. Dishonesty was acknowledged by 31% of program directors and 44% of resident applicants. Of program directors 82% thought applicants "lied", while 67% of applicants thought that programs "lied" (quotations indicate questionnaire language). Participants characterized their own dishonesty as "just playing the game" or they "did not feel badly." Of program directors 81% and of applicants 61% were "skeptical" or "did not believe" when informed they were a "high" or "number 1" selection. Being asked about marital status was recalled by 91% of male and 100% of female (p = 0. 02), if they had children by 53% of male and 67% of female, (p = 0. 03), and intent to have children by 25% of male and 62% of female (p match code rules frequently. Program directors and resident applicants are skeptical of each other. Patterns of faculty behavior differ based on applicant gender. Interviews are costly for applicants. We recommend that 1) programs adopt policies to enhance fairness, 2) applications be filed electronically, 3) programs assist resident applicants with interview accommodation to reduce financial burden and 4) a post-interview code of limited or
The match-to-match variation of match-running in elite female soccer.
Trewin, Joshua; Meylan, César; Varley, Matthew C; Cronin, John
2018-02-01
The purpose of this study was to examine the match-to-match variation of match-running in elite female soccer players utilising GPS, using full-match and rolling period analyses. Longitudinal study. Elite female soccer players (n=45) from the same national team were observed during 55 international fixtures across 5 years (2012-2016). Data was analysed using a custom built MS Excel spreadsheet as full-matches and using a rolling 5-min analysis period, for all players who played 90-min matches (files=172). Variation was examined using co-efficient of variation and 90% confidence limits, calculated following log transformation. Total distance per minute exhibited the smallest variation when both the full-match and peak 5-min running periods were examined (CV=6.8-7.2%). Sprint-efforts were the most variable during a full-match (CV=53%), whilst high-speed running per minute exhibited the greatest variation in the post-peak 5-min period (CV=143%). Peak running periods were observed as slightly more variable than full-match analyses, with the post-peak period very-highly variable. Variability of accelerations (CV=17%) and Player Load (CV=14%) was lower than that of high-speed actions. Positional differences were also present, with centre backs exhibiting the greatest variation in high-speed movements (CV=41-65%). Practitioners and researchers should account for within player variability when examining match performances. Identification of peak running periods should be used to assist worst case scenarios. Whilst micro-sensor technology should be further examined as to its viable use within match-analyses. Copyright © 2017 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.
Non-Gaussianity from tachyonic preheating in hybrid inflation
International Nuclear Information System (INIS)
Barnaby, Neil; Cline, James M.
2007-01-01
In a previous work we showed that large non-Gaussianities and nonscale-invariant distortions in the cosmic microwave background power spectrum can be generated in hybrid inflation models, due to the contributions of the tachyon (waterfall) field to the second order curvature perturbation. Here we clarify, correct, and extend those results. We show that large non-Gaussianity occurs only when the tachyon remains light throughout inflation, whereas n=4 contamination to the spectrum is the dominant effect when the tachyon is heavy. We find constraints on the parameters of warped-throat brane-antibrane inflation from non-Gaussianity. For F-term and D-term inflation models from supergravity, we obtain nontrivial constraints from the spectral distortion effect. We also establish that our analysis applies to complex tachyon fields
Continuous-variable quantum teleportation with non-Gaussian resources
International Nuclear Information System (INIS)
Dell'Anno, F.; De Siena, S.; Albano, L.; Illuminati, F.
2007-01-01
We investigate continuous variable quantum teleportation using non-Gaussian states of the radiation field as entangled resources. We compare the performance of different classes of degaussified resources, including two-mode photon-added and two-mode photon-subtracted squeezed states. We then introduce a class of two-mode squeezed Bell-like states with one-parameter dependence for optimization. These states interpolate between and include as subcases different classes of degaussified resources. We show that optimized squeezed Bell-like resources yield a remarkable improvement in the fidelity of teleportation both for coherent and nonclassical input states. The investigation reveals that the optimal non-Gaussian resources for continuous variable teleportation are those that most closely realize the simultaneous maximization of the content of entanglement, the degree of affinity with the two-mode squeezed vacuum, and the, suitably measured, amount of non-Gaussianity
Generation of correlated finite alphabet waveforms using gaussian random variables
Ahmed, Sajid
2016-01-13
Various examples of methods and systems are provided for generation of correlated finite alphabet waveforms using Gaussian random variables in, e.g., radar and communication applications. In one example, a method includes mapping an input signal comprising Gaussian random variables (RVs) onto finite-alphabet non-constant-envelope (FANCE) symbols using a predetermined mapping function, and transmitting FANCE waveforms through a uniform linear array of antenna elements to obtain a corresponding beampattern. The FANCE waveforms can be based upon the mapping of the Gaussian RVs onto the FANCE symbols. In another example, a system includes a memory unit that can store a plurality of digital bit streams corresponding to FANCE symbols and a front end unit that can transmit FANCE waveforms through a uniform linear array of antenna elements to obtain a corresponding beampattern. The system can include a processing unit that can encode the input signal and/or determine the mapping function.
Outage performance of cognitive radio systems with Improper Gaussian signaling
Amin, Osama
2015-06-14
Improper Gaussian signaling has proved its ability to improve the achievable rate of the systems that suffer from interference compared with proper Gaussian signaling. In this paper, we first study impact of improper Gaussian signaling on the performance of the cognitive radio system by analyzing the outage probability of both the primary user (PU) and the secondary user (SU). We derive exact expression of the SU outage probability and upper and lower bounds for the PU outage probability. Then, we design the SU signal by adjusting its transmitted power and the circularity coefficient to minimize the SU outage probability while maintaining a certain PU quality-of-service. Finally, we evaluate the proposed bounds and adaptive algorithms by numerical results.
Non-Gaussianity in a quasiclassical electronic circuit
Suzuki, Takafumi J.; Hayakawa, Hisao
2017-05-01
We study the non-Gaussian dynamics of a quasiclassical electronic circuit coupled to a mesoscopic conductor. Non-Gaussian noise accompanying the nonequilibrium transport through the conductor significantly modifies the stationary probability density function (PDF) of the flux in the dissipative circuit. We incorporate weak quantum fluctuation of the dissipative LC circuit with a stochastic method and evaluate the quantum correction of the stationary PDF. Furthermore, an inverse formula to infer the statistical properties of the non-Gaussian noise from the stationary PDF is derived in the classical-quantum crossover regime. The quantum correction is indispensable to correctly estimate the microscopic transfer events in the QPC with the quasiclassical inverse formula.
Nonparametric estimation of stochastic differential equations with sparse Gaussian processes.
García, Constantino A; Otero, Abraham; Félix, Paulo; Presedo, Jesús; Márquez, David G
2017-08-01
The application of stochastic differential equations (SDEs) to the analysis of temporal data has attracted increasing attention, due to their ability to describe complex dynamics with physically interpretable equations. In this paper, we introduce a nonparametric method for estimating the drift and diffusion terms of SDEs from a densely observed discrete time series. The use of Gaussian processes as priors permits working directly in a function-space view and thus the inference takes place directly in this space. To cope with the computational complexity that requires the use of Gaussian processes, a sparse Gaussian process approximation is provided. This approximation permits the efficient computation of predictions for the drift and diffusion terms by using a distribution over a small subset of pseudosamples. The proposed method has been validated using both simulated data and real data from economy and paleoclimatology. The application of the method to real data demonstrates its ability to capture the behavior of complex systems.
Topological recursion for Gaussian means and cohomological field theories
Andersen, J. E.; Chekhov, L. O.; Norbury, P.; Penner, R. C.
2015-12-01
We introduce explicit relations between genus-filtrated s-loop means of the Gaussian matrix model and terms of the genus expansion of the Kontsevich-Penner matrix model (KPMM), which is the generating function for volumes of discretized (open) moduli spaces M g,s disc (discrete volumes). Using these relations, we express Gaussian means in all orders of the genus expansion as polynomials in special times weighted by ancestor invariants of an underlying cohomological field theory. We translate the topological recursion of the Gaussian model into recurrence relations for the coefficients of this expansion, which allows proving that they are integers and positive. We find the coefficients in the first subleading order for M g,1 for all g in three ways: using the refined Harer-Zagier recursion, using the Givental-type decomposition of the KPMM, and counting diagrams explicitly.
Standard sirens and dark sector with Gaussian process*
Directory of Open Access Journals (Sweden)
Cai Rong-Gen
2018-01-01
Full Text Available The gravitational waves from compact binary systems are viewed as a standard siren to probe the evolution of the universe. This paper summarizes the potential and ability to use the gravitational waves to constrain the cosmological parameters and the dark sector interaction in the Gaussian process methodology. After briefly introducing the method to reconstruct the dark sector interaction by the Gaussian process, the concept of standard sirens and the analysis of reconstructing the dark sector interaction with LISA are outlined. Furthermore, we estimate the constraint ability of the gravitational waves on cosmological parameters with ET. The numerical methods we use are Gaussian process and the Markov-Chain Monte-Carlo. Finally, we also forecast the improvements of the abilities to constrain the cosmological parameters with ET and LISA combined with the Planck.
Cosmic microwave background power asymmetry from non-Gaussian modulation.
Schmidt, Fabian; Hui, Lam
2013-01-04
Non-Gaussianity in the inflationary perturbations can couple observable scales to modes of much longer wavelength (even superhorizon), leaving as a signature a large-angle modulation of the observed cosmic microwave background power spectrum. This provides an alternative origin for a power asymmetry that is otherwise often ascribed to a breaking of statistical isotropy. The non-Gaussian modulation effect can be significant even for typical ~10(-5) perturbations while respecting current constraints on non-Gaussianity if the squeezed limit of the bispectrum is sufficiently infrared divergent. Just such a strongly infrared-divergent bispectrum has been claimed for inflation models with a non-Bunch-Davies initial state, for instance. Upper limits on the observed cosmic microwave background power asymmetry place stringent constraints on the duration of inflation in such models.
Generation of correlated finite alphabet waveforms using gaussian random variables
Ahmed, Sajid; Alouini, Mohamed-Slim; Jardak, Seifallah
2016-01-01
Various examples of methods and systems are provided for generation of correlated finite alphabet waveforms using Gaussian random variables in, e.g., radar and communication applications. In one example, a method includes mapping an input signal comprising Gaussian random variables (RVs) onto finite-alphabet non-constant-envelope (FANCE) symbols using a predetermined mapping function, and transmitting FANCE waveforms through a uniform linear array of antenna elements to obtain a corresponding beampattern. The FANCE waveforms can be based upon the mapping of the Gaussian RVs onto the FANCE symbols. In another example, a system includes a memory unit that can store a plurality of digital bit streams corresponding to FANCE symbols and a front end unit that can transmit FANCE waveforms through a uniform linear array of antenna elements to obtain a corresponding beampattern. The system can include a processing unit that can encode the input signal and/or determine the mapping function.
Gaussian Process Interpolation for Uncertainty Estimation in Image Registration
Wachinger, Christian; Golland, Polina; Reuter, Martin; Wells, William
2014-01-01
Intensity-based image registration requires resampling images on a common grid to evaluate the similarity function. The uncertainty of interpolation varies across the image, depending on the location of resampled points relative to the base grid. We propose to perform Bayesian inference with Gaussian processes, where the covariance matrix of the Gaussian process posterior distribution estimates the uncertainty in interpolation. The Gaussian process replaces a single image with a distribution over images that we integrate into a generative model for registration. Marginalization over resampled images leads to a new similarity measure that includes the uncertainty of the interpolation. We demonstrate that our approach increases the registration accuracy and propose an efficient approximation scheme that enables seamless integration with existing registration methods. PMID:25333127
Primordial non-Gaussian features from DBI Galileon inflation
International Nuclear Information System (INIS)
Choudhury, Sayantan; Pal, Supratik
2015-01-01
We have studied primordial non-Gaussian features of a model of potential-driven single field DBI Galileon inflation. We have computed the bispectrum from the three-point correlation function considering all possible cross correlations between the scalar and tensor modes of the proposed setup. Further, we have computed the trispectrum from a four-point correlation function considering the contribution from contact interaction, and scalar and graviton exchange diagrams in the in-in picture. Finally we have obtained the non-Gaussian consistency conditions from the four-point correlator, which results in partial violation of the Suyama-Yamaguchi four-point consistency relation. This further leads to the conclusion that sufficient primordial non-Gaussianities can be obtained from DBI Galileon inflation. (orig.)
Non-Gaussian diffusion in static disordered media
Luo, Liang; Yi, Ming
2018-04-01
Non-Gaussian diffusion is commonly considered as a result of fluctuating diffusivity, which is correlated in time or in space or both. In this work, we investigate the non-Gaussian diffusion in static disordered media via a quenched trap model, where the diffusivity is spatially correlated. Several unique effects due to quenched disorder are reported. We analytically estimate the diffusion coefficient Ddis and its fluctuation over samples of finite size. We show a mechanism of population splitting in the non-Gaussian diffusion. It results in a sharp peak in the distribution of displacement P (x ,t ) around x =0 , that has frequently been observed in experiments. We examine the fidelity of the coarse-grained diffusion map, which is reconstructed from particle trajectories. Finally, we propose a procedure to estimate the correlation length in static disordered environments, where the information stored in the sample-to-sample fluctuation has been utilized.
Self-assembled structures of Gaussian nematic particles.
Nikoubashman, Arash; Likos, Christos N
2010-03-17
We investigate the stable crystalline configurations of a nematic liquid crystal made of soft parallel ellipsoidal particles interacting via a repulsive, anisotropic Gaussian potential. For this purpose, we use genetic algorithms (GA) in order to predict all relevant and possible solid phase candidates into which this fluid can freeze. Subsequently we present and discuss the emerging novel structures and the resulting zero-temperature phase diagram of this system. The latter features a variety of crystalline arrangements, in which the elongated Gaussian particles in general do not align with any one of the high-symmetry crystallographic directions, a compromise arising from the interplay and competition between anisotropic repulsions and crystal ordering. Only at very strong degrees of elongation does a tendency of the Gaussian nematics to align with the longest axis of the elementary unit cell emerge.
Gaussian white noise as a resource for work extraction.
Dechant, Andreas; Baule, Adrian; Sasa, Shin-Ichi
2017-03-01
We show that uncorrelated Gaussian noise can drive a system out of equilibrium and can serve as a resource from which work can be extracted. We consider an overdamped particle in a periodic potential with an internal degree of freedom and a state-dependent friction, coupled to an equilibrium bath. Applying additional Gaussian white noise drives the system into a nonequilibrium steady state and causes a finite current if the potential is spatially asymmetric. The model thus operates as a Brownian ratchet, whose current we calculate explicitly in three complementary limits. Since the particle current is driven solely by additive Gaussian white noise, this shows that the latter can potentially perform work against an external load. By comparing the extracted power to the energy injection due to the noise, we discuss the efficiency of such a ratchet.
Speed-up Template Matching through Integral Image based Weak Classifiers
Wu, t.; Toet, A.
2014-01-01
Template matching is a widely used pattern recognition method, especially in industrial inspection. However, the computational costs of traditional template matching increase dramatically with both template-and scene imagesize. This makes traditional template matching less useful for many (e.g.
POOR TEXTURAL IMAGE MATCHING BASED ON GRAPH THEORY
Directory of Open Access Journals (Sweden)
S. Chen
2016-06-01
Full Text Available Image matching lies at the heart of photogrammetry and computer vision. For poor textural images, the matching result is affected by low contrast, repetitive patterns, discontinuity or occlusion, few or homogeneous textures. Recently, graph matching became popular for its integration of geometric and radiometric information. Focused on poor textural image matching problem, it is proposed an edge-weight strategy to improve graph matching algorithm. A series of experiments have been conducted including 4 typical landscapes: Forest, desert, farmland, and urban areas. And it is experimentally found that our new algorithm achieves better performance. Compared to SIFT, doubled corresponding points were acquired, and the overall recall rate reached up to 68%, which verifies the feasibility and effectiveness of the algorithm.
Matching by Monotonic Tone Mapping.
Kovacs, Gyorgy
2018-06-01
In this paper, a novel dissimilarity measure called Matching by Monotonic Tone Mapping (MMTM) is proposed. The MMTM technique allows matching under non-linear monotonic tone mappings and can be computed efficiently when the tone mappings are approximated by piecewise constant or piecewise linear functions. The proposed method is evaluated in various template matching scenarios involving simulated and real images, and compared to other measures developed to be invariant to monotonic intensity transformations. The results show that the MMTM technique is a highly competitive alternative of conventional measures in problems where possible tone mappings are close to monotonic.
MATCHING IN INFORMAL FINANCIAL INSTITUTIONS.
Eeckhout, Jan; Munshi, Kaivan
2010-09-01
This paper analyzes an informal financial institution that brings heterogeneous agents together in groups. We analyze decentralized matching into these groups, and the equilibrium composition of participants that consequently arises. We find that participants sort remarkably well across the competing groups, and that they re-sort immediately following an unexpected exogenous regulatory change. These findings suggest that the competitive matching model might have applicability and bite in other settings where matching is an important equilibrium phenomenon. (JEL: O12, O17, G20, D40).
Perturbative corrections for approximate inference in gaussian latent variable models
DEFF Research Database (Denmark)
Opper, Manfred; Paquet, Ulrich; Winther, Ole
2013-01-01
Expectation Propagation (EP) provides a framework for approximate inference. When the model under consideration is over a latent Gaussian field, with the approximation being Gaussian, we show how these approximations can systematically be corrected. A perturbative expansion is made of the exact b...... illustrate on tree-structured Ising model approximations. Furthermore, they provide a polynomial-time assessment of the approximation error. We also provide both theoretical and practical insights on the exactness of the EP solution. © 2013 Manfred Opper, Ulrich Paquet and Ole Winther....
Bayesian analysis of log Gaussian Cox processes for disease mapping
DEFF Research Database (Denmark)
Benes, Viktor; Bodlák, Karel; Møller, Jesper
We consider a data set of locations where people in Central Bohemia have been infected by tick-borne encephalitis, and where population census data and covariates concerning vegetation and altitude are available. The aims are to estimate the risk map of the disease and to study the dependence...... of the risk on the covariates. Instead of using the common area level approaches we consider a Bayesian analysis for a log Gaussian Cox point process with covariates. Posterior characteristics for a discretized version of the log Gaussian Cox process are computed using markov chain Monte Carlo methods...
Polarization coupling of vector Bessel–Gaussian beams
International Nuclear Information System (INIS)
Takeuchi, Ryushi; Kozawa, Yuichi; Sato, Shunichi
2013-01-01
We report polarization coupling of radial and azimuthal electric field components of a vector light beam as predicted by the fact that the vector Helmholtz equation is expressed as coupled differential equations in cylindrical coordinates. To clearly observe the polarization variation of a beam as it propagates, higher order transverse modes of a vector Bessel–Gaussian beam were generated by a gain distribution modulation technique, which created a narrow ring-shaped gain region in a Nd:YVO 4 crystal. The polarization coupling was confirmed by the observation that the major polarization component of a vector Bessel–Gaussian beam alternates between radial and azimuthal components along with the propagation. (paper)
Gaussian-state entanglement in a quantum beat laser
International Nuclear Information System (INIS)
Tahira, Rabia; Ikram, Manzoor; Nha, Hyunchul; Zubairy, M. Suhail
2011-01-01
Recently quantum beat lasers have been considered as a source of entangled radiation [S. Qamar, F. Ghafoor, M. Hillery, and M. S. Zubairy, Phys. Rev. A 77, 062308 (2008)]. We investigate and quantify the entanglement of this system when the initial cavity modes are prepared in a Gaussian two-mode state, one being a nonclassical state and the other a thermal state. It is investigated how the output entanglement varies with the nonclassicality of the input Gaussian state, thermal noise, and the strength of the driving field.
Neural pulse frequency modulation of an exponentially correlated Gaussian process
Hutchinson, C. E.; Chon, Y.-T.
1976-01-01
The effect of NPFM (Neural Pulse Frequency Modulation) on a stationary Gaussian input, namely an exponentially correlated Gaussian input, is investigated with special emphasis on the determination of the average number of pulses in unit time, known also as the average frequency of pulse occurrence. For some classes of stationary input processes where the formulation of the appropriate multidimensional Markov diffusion model of the input-plus-NPFM system is possible, the average impulse frequency may be obtained by a generalization of the approach adopted. The results are approximate and numerical, but are in close agreement with Monte Carlo computer simulation results.
Local features with large spiky non-Gaussianities during inflation
International Nuclear Information System (INIS)
Abolhasani, Ali Akbar; Firouzjahi, Hassan; Khosravi, Shahram; Sasaki, Misao
2012-01-01
We provide a dynamical mechanism to generate localized features during inflation. The local feature is due to a sharp waterfall phase transition which is coupled to the inflaton field. The key effect is the contributions of waterfall quantum fluctuations which induce a sharp peak on the curvature perturbation which can be as large as the background curvature perturbation from inflaton field. Due to non-Gaussian nature of waterfall quantum fluctuations a large spike non-Gaussianity is produced which is narrowly peaked at modes which leave the Hubble radius at the time of phase transition. The large localized peaks in power spectrum and bispectrum can have interesting consequences on CMB anisotropies
Coulomb Final State Interactions for Gaussian Wave Packets
Wiedemann, Urs Achim; Heinz, Ulrich W
1999-01-01
Two-particle like-sign and unlike-sign correlations including Coulomb final state interactions are calculated for Gaussian wave packets emitted from a Gaussian source. We show that the width of the wave packets can be fully absorbed into the spatial and momentum space widths of an effective emission function for plane wave states, and that Coulomb final state interaction effects are sensitive only to the latter, but not to the wave packet width itself. Results from analytical and numerical calculations are compared with recently published work by other authors.
Permutation entropy of fractional Brownian motion and fractional Gaussian noise
International Nuclear Information System (INIS)
Zunino, L.; Perez, D.G.; Martin, M.T.; Garavaglia, M.; Plastino, A.; Rosso, O.A.
2008-01-01
We have worked out theoretical curves for the permutation entropy of the fractional Brownian motion and fractional Gaussian noise by using the Bandt and Shiha [C. Bandt, F. Shiha, J. Time Ser. Anal. 28 (2007) 646] theoretical predictions for their corresponding relative frequencies. Comparisons with numerical simulations show an excellent agreement. Furthermore, the entropy-gap in the transition between these processes, observed previously via numerical results, has been here theoretically validated. Also, we have analyzed the behaviour of the permutation entropy of the fractional Gaussian noise for different time delays
Power variation for Gaussian processes with stationary increments
DEFF Research Database (Denmark)
Barndorff-Nielsen, Ole Eiler; Corcuera, J.M.; Podolskij, Mark
2009-01-01
We develop the asymptotic theory for the realised power variation of the processes X=•G, where G is a Gaussian process with stationary increments. More specifically, under some mild assumptions on the variance function of the increments of G and certain regularity conditions on the path of the pr......We develop the asymptotic theory for the realised power variation of the processes X=•G, where G is a Gaussian process with stationary increments. More specifically, under some mild assumptions on the variance function of the increments of G and certain regularity conditions on the path...... a chaos representation....
Pulsed homodyne Gaussian quantum tomography with low detection efficiency
Esposito, M.; Benatti, F.; Floreanini, R.; Olivares, S.; Randi, F.; Titimbo, K.; Pividori, M.; Novelli, F.; Cilento, F.; Parmigiani, F.; Fausti, D.
2014-04-01
Pulsed homodyne quantum tomography usually requires a high detection efficiency, limiting its applicability in quantum optics. Here, it is shown that the presence of low detection efficiency (<50%) does not prevent the tomographic reconstruction of quantum states of light, specifically, of Gaussian states. This result is obtained by applying the so-called ‘minimax’ adaptive reconstruction of the Wigner function to pulsed homodyne detection. In particular, we prove, by both numerical and real experiments, that an effective discrimination of different Gaussian quantum states can be achieved. Our finding paves the way to a more extensive use of quantum tomographic methods, even in physical situations in which high detection efficiency is unattainable.
Pulsed homodyne Gaussian quantum tomography with low detection efficiency
International Nuclear Information System (INIS)
Esposito, M; Benatti, F; Randi, F; Titimbo, K; Pividori, M; Parmigiani, F; Fausti, D; Floreanini, R; Olivares, S; Novelli, F; Cilento, F
2014-01-01
Pulsed homodyne quantum tomography usually requires a high detection efficiency, limiting its applicability in quantum optics. Here, it is shown that the presence of low detection efficiency (<50) does not prevent the tomographic reconstruction of quantum states of light, specifically, of Gaussian states. This result is obtained by applying the so-called ‘minimax’ adaptive reconstruction of the Wigner function to pulsed homodyne detection. In particular, we prove, by both numerical and real experiments, that an effective discrimination of different Gaussian quantum states can be achieved. Our finding paves the way to a more extensive use of quantum tomographic methods, even in physical situations in which high detection efficiency is unattainable
Propagation of Gaussian Beams through Active GRIN Materials
International Nuclear Information System (INIS)
Gomez-Varela, A I; Flores-Arias, M T; Bao-Varela, C; Gomez-Reino, C; De la Fuente, X
2011-01-01
We discussed light propagation through an active GRIN material that exhibits loss or gain. Effects of gain or loss in GRIN materials can be phenomenologically taken into account by using a complex refractive index in the wave equation. This work examines the implication of using a complex refractive index on light propagation in an active GRIN material illuminated by a non-uniform monochromatic wave described by a Gaussian beam. We analyze how a Gaussian beam is propagated through the active material in order to characterize it by the beam parameters and the transverse irradiance distribution.
Modulation depth of Michelson interferometer with Gaussian beam.
Välikylä, Tuomas; Kauppinen, Jyrki
2011-12-20
Mirror misalignment or the tilt angle of the Michelson interferometer can be estimated from the modulation depth measured with collimated monochromatic light. The intensity of the light beam is usually assumed to be uniform, but, for example, with gas lasers it generally has a Gaussian distribution, which makes the modulation depth less sensitive to the tilt angle. With this assumption, the tilt angle may be underestimated by about 50%. We have derived a mathematical model for modulation depth with a circular aperture and Gaussian beam. The model reduces the error of the tilt angle estimate to below 1%. The results of the model have been verified experimentally.
Pedagogical introduction to the entropy of entanglement for Gaussian states
Demarie, Tommaso F.
2018-05-01
In quantum information theory, the entropy of entanglement is a standard measure of bipartite entanglement between two partitions of a composite system. For a particular class of continuous variable quantum states, the Gaussian states, the entropy of entanglement can be expressed elegantly in terms of symplectic eigenvalues, elements that characterise a Gaussian state and depend on the correlations of the canonical variables. We give a rigorous step-by-step derivation of this result and provide physical insights, together with an example that can be useful in practice for calculations.
Gaussian basis functions for highly oscillatory scattering wavefunctions
Mant, B. P.; Law, M. M.
2018-04-01
We have applied a basis set of distributed Gaussian functions within the S-matrix version of the Kohn variational method to scattering problems involving deep potential energy wells. The Gaussian positions and widths are tailored to the potential using the procedure of Bačić and Light (1986 J. Chem. Phys. 85 4594) which has previously been applied to bound-state problems. The placement procedure is shown to be very efficient and gives scattering wavefunctions and observables in agreement with direct numerical solutions. We demonstrate the basis function placement method with applications to hydrogen atom–hydrogen atom scattering and antihydrogen atom–hydrogen atom scattering.
An optical tweezer in asymmetrical vortex Bessel-Gaussian beams
Energy Technology Data Exchange (ETDEWEB)
Kotlyar, V. V.; Kovalev, A. A., E-mail: alexeysmr@mail.ru; Porfirev, A. P. [Image Processing Systems Institute, 151 Molodogvardeiskaya St., 443001 Samara (Russian Federation); Department of Technical cybernetics, Samara State Aerospace University, Samara 443086 (Russian Federation)
2016-07-14
We study an optical micromanipulation that comprises trapping, rotating, and transporting 5-μm polystyrene microbeads in asymmetric Bessel-Gaussian (BG) laser beams. The beams that carry orbital angular momentum are generated by means of a liquid crystal microdisplay and focused by a microobjective with a numerical aperture of NA = 0.85. We experimentally show that given a constant topological charge, the rate of microparticle motion increases near linearly with increasing asymmetry of the BG beam. Asymmetric BG beams can be used instead of conventional Gaussian beam for trapping and transferring live cells without thermal damage.
Multimodal Personal Verification Using Likelihood Ratio for the Match Score Fusion
Directory of Open Access Journals (Sweden)
Long Binh Tran
2017-01-01
Full Text Available In this paper, the authors present a novel personal verification system based on the likelihood ratio test for fusion of match scores from multiple biometric matchers (face, fingerprint, hand shape, and palm print. In the proposed system, multimodal features are extracted by Zernike Moment (ZM. After matching, the match scores from multiple biometric matchers are fused based on the likelihood ratio test. A finite Gaussian mixture model (GMM is used for estimating the genuine and impostor densities of match scores for personal verification. Our approach is also compared to some different famous approaches such as the support vector machine and the sum rule with min-max. The experimental results have confirmed that the proposed system can achieve excellent identification performance for its higher level in accuracy than different famous approaches and thus can be utilized for more application related to person verification.
Toward Practical Secure Stable Matching
Directory of Open Access Journals (Sweden)
Riazi M. Sadegh
2017-01-01
Full Text Available The Stable Matching (SM algorithm has been deployed in many real-world scenarios including the National Residency Matching Program (NRMP and financial applications such as matching of suppliers and consumers in capital markets. Since these applications typically involve highly sensitive information such as the underlying preference lists, their current implementations rely on trusted third parties. This paper introduces the first provably secure and scalable implementation of SM based on Yao’s garbled circuit protocol and Oblivious RAM (ORAM. Our scheme can securely compute a stable match for 8k pairs four orders of magnitude faster than the previously best known method. We achieve this by introducing a compact and efficient sub-linear size circuit. We even further decrease the computation cost by three orders of magnitude by proposing a novel technique to avoid unnecessary iterations in the SM algorithm. We evaluate our implementation for several problem sizes and plan to publish it as open-source.
Probability matching and strategy availability.
Koehler, Derek J; James, Greta
2010-09-01
Findings from two experiments indicate that probability matching in sequential choice arises from an asymmetry in strategy availability: The matching strategy comes readily to mind, whereas a superior alternative strategy, maximizing, does not. First, compared with the minority who spontaneously engage in maximizing, the majority of participants endorse maximizing as superior to matching in a direct comparison when both strategies are described. Second, when the maximizing strategy is brought to their attention, more participants subsequently engage in maximizing. Third, matchers are more likely than maximizers to base decisions in other tasks on their initial intuitions, suggesting that they are more inclined to use a choice strategy that comes to mind quickly. These results indicate that a substantial subset of probability matchers are victims of "underthinking" rather than "overthinking": They fail to engage in sufficient deliberation to generate a superior alternative to the matching strategy that comes so readily to mind.
Computing solutions for matching games
Biró, Péter; Kern, Walter; Paulusma, Daniël
2012-01-01
A matching game is a cooperative game (N, v) defined on a graph G = (N, E) with an edge weighting w : E → R+. The player set is N and the value of a coalition S ⊆ N is defined as the maximum weight of a matching in the subgraph induced by S. First we present an O(nm+n2 log n) algorithm that tests if
Probability Matching, Fast and Slow
Koehler, Derek J.; James, Greta
2014-01-01
A prominent point of contention among researchers regarding the interpretation of probability-matching behavior is whether it represents a cognitively sophisticated, adaptive response to the inherent uncertainty of the tasks or settings in which it is observed, or whether instead it represents a fundamental shortcoming in the heuristics that support and guide human decision making. Put crudely, researchers disagree on whether probability matching is "smart" or "dumb." Here, we consider eviden...
Matching games with partial information
Laureti, Paolo; Zhang, Yi-Cheng
2003-06-01
We analyze different ways of pairing agents in a bipartite matching problem, with regard to its scaling properties and to the distribution of individual “satisfactions”. Then we explore the role of partial information and bounded rationality in a generalized Marriage Problem, comparing the benefits obtained by self-searching and by a matchmaker. Finally we propose a modified matching game intended to mimic the way consumers’ information makes firms to enhance the quality of their products in a competitive market.
Directory of Open Access Journals (Sweden)
Vladimir Katkovnik
2018-05-01
Full Text Available We study the problem of multiwavelength absolute phase retrieval from noisy diffraction patterns. The system is lensless with multiwavelength coherent input light beams and random phase masks applied for wavefront modulation. The light beams are formed by light sources radiating all wavelengths simultaneously. A sensor equipped by a Color Filter Array (CFA is used for spectral measurement registration. The developed algorithm targeted on optimal phase retrieval from noisy observations is based on maximum likelihood technique. The algorithm is specified for Poissonian and Gaussian noise distributions. One of the key elements of the algorithm is an original sparse modeling of the multiwavelength complex-valued wavefronts based on the complex-domain block-matching 3D filtering. Presented numerical experiments are restricted to noisy Poissonian observations. They demonstrate that the developed algorithm leads to effective solutions explicitly using the sparsity for noise suppression and enabling accurate reconstruction of absolute phase of high-dynamic range.
Ruffato, G.; Carli, M.; Massari, M.; Romanato, F.
2015-03-01
The work of design, fabrication and characterization of spiral phase plates for the generation of Laguerre-Gaussian (LG) beams with non-null radial index is presented. Samples were fabricated by electron beam lithography on polymethylmethacrylate layers over glass substrates. The optical response of these phase optical elements was measured and the purity of the experimental beams was investigated in terms of Laguerre-Gaussian modes contributions. The farfield intensity pattern was compared with theoretical models and numerical simulations, while the expected phase features were confirmed by interferometric analyses. The high quality of the output beams confirms the applicability of these phase plates for the generation of high-order Laguerre-Gaussian beams. A novel application consisting in the design of computer-generated holograms encoding information for light beams carrying phase singularities is shown. A numerical code based on iterative Fourier transform algorithm has been developed for the computation of the phase pattern of phase-only diffractive optical element for illumination under LG beams. Numerical analysis and preliminary experimental results confirm the applicability of these devices as high-security optical elements.
Zhong, Shangping; Chen, Tianshun; He, Fengying; Niu, Yuzhen
2014-09-01
For a practical pattern classification task solved by kernel methods, the computing time is mainly spent on kernel learning (or training). However, the current kernel learning approaches are based on local optimization techniques, and hard to have good time performances, especially for large datasets. Thus the existing algorithms cannot be easily extended to large-scale tasks. In this paper, we present a fast Gaussian kernel learning method by solving a specially structured global optimization (SSGO) problem. We optimize the Gaussian kernel function by using the formulated kernel target alignment criterion, which is a difference of increasing (d.i.) functions. Through using a power-transformation based convexification method, the objective criterion can be represented as a difference of convex (d.c.) functions with a fixed power-transformation parameter. And the objective programming problem can then be converted to a SSGO problem: globally minimizing a concave function over a convex set. The SSGO problem is classical and has good solvability. Thus, to find the global optimal solution efficiently, we can adopt the improved Hoffman's outer approximation method, which need not repeat the searching procedure with different starting points to locate the best local minimum. Also, the proposed method can be proven to converge to the global solution for any classification task. We evaluate the proposed method on twenty benchmark datasets, and compare it with four other Gaussian kernel learning methods. Experimental results show that the proposed method stably achieves both good time-efficiency performance and good classification performance. Copyright © 2014 Elsevier Ltd. All rights reserved.
Support agnostic Bayesian matching pursuit for block sparse signals
Masood, Mudassir
2013-05-01
A fast matching pursuit method using a Bayesian approach is introduced for block-sparse signal recovery. This method performs Bayesian estimates of block-sparse signals even when the distribution of active blocks is non-Gaussian or unknown. It is agnostic to the distribution of active blocks in the signal and utilizes a priori statistics of additive noise and the sparsity rate of the signal, which are shown to be easily estimated from data and no user intervention is required. The method requires a priori knowledge of block partition and utilizes a greedy approach and order-recursive updates of its metrics to find the most dominant sparse supports to determine the approximate minimum mean square error (MMSE) estimate of the block-sparse signal. Simulation results demonstrate the power and robustness of our proposed estimator. © 2013 IEEE.
Sparse reconstruction using distribution agnostic bayesian matching pursuit
Masood, Mudassir
2013-11-01
A fast matching pursuit method using a Bayesian approach is introduced for sparse signal recovery. This method performs Bayesian estimates of sparse signals even when the signal prior is non-Gaussian or unknown. It is agnostic on signal statistics and utilizes a priori statistics of additive noise and the sparsity rate of the signal, which are shown to be easily estimated from data if not available. The method utilizes a greedy approach and order-recursive updates of its metrics to find the most dominant sparse supports to determine the approximate minimum mean-square error (MMSE) estimate of the sparse signal. Simulation results demonstrate the power and robustness of our proposed estimator. © 2013 IEEE.
Vision-based adaptive cruise control using pattern matching
CSIR Research Space (South Africa)
Kanjee, R
2013-10-01
Full Text Available input generated by the control system does not directly induce a traction force on the car tires. In an electric vehicle, the throttle position is processed by the engine controller and is mapped proportionally to the motor’s angular velocity. For our... simulation, this mapping was obtained from the manufacturer’s datasheet of the electric motor controller being used in the hybrid car. The manufacturer also supplies a speed-torque curve. An approximate equation was obtained using a linear curve fitting...
Computationally Secure Pattern Matching in the Presence of Malicious Adversaries
DEFF Research Database (Denmark)
Hazay, Carmit; Toft, Tomas
2010-01-01
simulation in the presence of malicious, polynomial-time adversaries (assuming that ElGamal encryption is semantically secure) and exhibits computation and communication costs of O(n + m) in a constant round complexity. In addition to the above, we propose a collection of protocols for variations...
The Logical Basis of Evaluation Order and Pattern-Matching
2009-04-17
various people in the 1930s, particularly Wittgenstein (“It is what is regarded as the justification of an assertion that constitutes the sense of the...assertion” [ Wittgenstein , 1974, I,§40]), and Brouwer-Heyting-Kolmogorov in their interpretations of intuitionistic logic [Heyting, 1974, Kolmogorov, 1932...Technical Report CMU-CS-02-101, Department of Computer Science, Carnegie Mellon University, 2002. Revised May 2003. Ludwig Wittgenstein
Paint stripping with high power flattened Gaussian beams
CSIR Research Space (South Africa)
Forbes, A
2009-08-01
Full Text Available In this paper the researchers present results on improved paint stripping performance with an intra-cavity generated Flattened Gaussian Beam (FGB). A resonator with suitable diffractive optical elements was designed in order to produce a single mode...
Mixed Gaussian-Impulse Noise Image Restoration Via Total Variation
2012-05-01
deblurring under impulse noise ,” J. Math. Imaging Vis., vol. 36, pp. 46–53, January 2010. [5] B. Li, Q. Liu, J. Xu, and X. Luo, “A new method for removing......Several Total Variation (TV) regularization methods have recently been proposed to address denoising under mixed Gaussian and impulse noise . While
Representation and properties of a class of conditionally Gaussian processes
DEFF Research Database (Denmark)
Barndorff-Nielsen, Ole Eiler; Pedersen, Jan
2009-01-01
It is shown that the class of conditionally Gaussian processes with independent increments is stable under marginalisation and conditioning. Moreover, in general such processes can be represented as integrals of a time changed Brownian motion where the time change and the integrand are jointly in...
Prediction and retrodiction with continuously monitored Gaussian states
Zhang, Jinglei; Mølmer, Klaus
2017-12-01
Gaussian states of quantum oscillators are fully characterized by the mean values and the covariance matrix of their quadrature observables. We consider the dynamics of a system of oscillators subject to interactions, damping, and continuous probing which maintain their Gaussian state property. Such dynamics is found in many physical systems that can therefore be efficiently described by the ensuing effective representation of the density matrix ρ (t ) . Our probabilistic knowledge about the outcome of measurements on a quantum system at time t is not only governed by ρ (t ) conditioned on the evolution and measurement outcomes obtained until time t but is also modified by any information acquired after t . It was shown [S. Gammelmark, B. Julsgaard, and K. Mølmer, Phys. Rev. Lett. 111, 160401 (2013), 10.1103/PhysRevLett.111.160401] that this information is represented by a supplementary matrix, E (t ) . We show here that the restriction of the dynamics of ρ (t ) to Gaussian states implies that the matrix E (t ) is also fully characterized by a vector of mean values and a covariance matrix. We derive the dynamical equations for these quantities and we illustrate their use in the retrodiction of measurements on Gaussian systems.
Poisson and Gaussian approximation of weighted local empirical processes
Einmahl, J.H.J.
1995-01-01
We consider the local empirical process indexed by sets, a greatly generalized version of the well-studied uniform tail empirical process. We show that the weak limit of weighted versions of this process is Poisson under certain conditions, whereas it is Gaussian in other situations. Our main
Scaled unscented transform Gaussian sum filter: Theory and application
Luo, Xiaodong; Moroz, Irene M.; Hoteit, Ibrahim
2010-01-01
the SUKF to estimate the mean and covariance of the underlying Gaussian random variable transformed by the nonlinear governing equations of the sub-system. Incorporating the estimations of the sub-systems into the GMM gives an explicit (approximate) form
Lifting Primordial Non-Gaussianity Above the Noise
Welling, Yvette; Woude, Drian van der; Pajer, Enrico
2016-01-01
Primordial non-Gaussianity (PNG) in Large Scale Structures is obfuscated by the many additional sources of non-linearity. Within the Effective Field Theory approach to Standard Perturbation Theory, we show that matter non-linearities in the bispectrum can be modeled sufficiently well to strengthen
Robust Gaussian Process Regression with a Student-t Likelihood
Jylänki, P.P.; Vanhatalo, J.; Vehtari, A.
2011-01-01
This paper considers the robust and efficient implementation of Gaussian process regression with a Student-t observation model, which has a non-log-concave likelihood. The challenge with the Student-t model is the analytically intractable inference which is why several approximative methods have
Asymptotics of sums of lognormal random variables with Gaussian copula
DEFF Research Database (Denmark)
Asmussen, Søren; Rojas-Nandayapa, Leonardo
2008-01-01
Let (Y1, ..., Yn) have a joint n-dimensional Gaussian distribution with a general mean vector and a general covariance matrix, and let Xi = eYi, Sn = X1 + ⋯ + Xn. The asymptotics of P (Sn > x) as n → ∞ are shown to be the same as for the independent case with the same lognormal marginals. In part...