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Towards a faster symbolic aggregate approximation method [article]

Muhammad Marwan Muhammad Fuad, Pierre-François Marteau
2013 arXiv   pre-print
Pre-computed distances are calculated and stored offline to be used online to exclude a wide range of the search space using two exclusion conditions.  ...  The symbolic aggregate approximation (SAX) is one of the most competitive methods in the literature.  ...  Generally, false alarms these symbolic similarity distances were extended to are more tolerated than false dismissals, because a apply to other data types that can be transformed post-processing  ... 
arXiv:1301.5871v1 fatcat:wlvfwpkxyvc5xe3lwlobapcvva

Spectral Techniques for Solving PDE Stability Model of Vortex Rope [article]

Diana Alina Bistrian
2012 arXiv   pre-print
An L2 - projection and the collocation methods are developed assessing both analytically methodology and computational techniques using symbolic and numerical conversions.  ...  The advantages of using this methods in flow control problems are pointed out.  ...  Boundary-adapted bases of modal type are also useful in numerical approximations of hydrodynamic stability problems.  ... 
arXiv:1203.5409v1 fatcat:msjggnsfuvfunl4e7hs2fzvqjy

Classifying spatiotemporal object trajectories using unsupervised learning in the coefficient feature space

Andrew Naftel, Shehzad Khalid
2006 Multimedia Systems  
This paper proposes a novel technique for clustering and classification of object trajectory-based video motion clips using spatiotemporal function approximations.  ...  Assuming the clusters of trajectory points are distributed normally in the coefficient feature space, we propose a Mahalanobis classifier for the detection of anomalous trajectories.  ...  For example, Discrete Fourier Transforms (DFT) [14] , Discrete Wavelet Transforms (DWT) [9] , Adaptive Piecewise Constant Approximations (APCA) [27] , and Chebyshev polynomials [12] have been used  ... 
doi:10.1007/s00530-006-0058-5 fatcat:alcr5jscxzddto5dutxkmmf2vq

Fast Mesh Refinement in Pseudospectral Optimal Control [article]

N. Koeppen, I. M. Ross, L. C. Wilcox, R. J. Proulx
2019 arXiv   pre-print
The effectiveness of the resulting fast mesh refinement strategy is demonstrated by using polynomials of over a thousandth order to solve a low-thrust, long-duration orbit transfer problem.  ...  We show that the condition number increases only as √(N) in general, but is independent of N for the special case of one of the boundary points being fixed.  ...  Acknowledgment We take this opportunity to thank the anonymous reviewers for providing many detailed comments. Their comments greatly improved the quality of this paper.  ... 
arXiv:1904.12992v1 fatcat:xiyyjjavfzfyfen7rmhzn6wawy

Classification Algorithm for Person Identification and Gesture Recognition Based on Hand Gestures with Small Training Sets

Krzysztof Rzecki
2020 Sensors  
In many applications only small amounts of training data are available. This article presents a new time series classification algorithm for problems with small training sets.  ...  Classification algorithms require training data initially labelled by classes to build a model and then to be able to classify the new data.  ...  Acknowledgments: The author would like to thank Mateusz Baran for constructive criticism of the manuscript. Conflicts of Interest: The author declares no conflict of interest.  ... 
doi:10.3390/s20247279 pmid:33353008 pmcid:PMC7766068 fatcat:hrrjbpk6cbd33cb6hiupzgxi6m

Time Series Anomaly Detection for Smart Grids: A Survey [article]

Jiuqi Zhang, Di Wu, Benoit Boulet
2021 arXiv   pre-print
Various methods have been proposed for anomaly detection on power grid time-series data.  ...  This paper presents a short survey of the recent advances in anomaly detection for power grid time-series data.  ...  In a SAX implementation, the time series is first segmented into intervals, then a symbol is assigned to each segment based on the mean value.  ... 
arXiv:2107.08835v1 fatcat:boxplqijengbhhzi5jz23t54fe

Small-sample estimation of the mutational support and distribution of SARS-CoV-2

Vishal Rana, Eli Chien, Jianhao Peng, Olgica Milenkovic
2022 IEEE/ACM Transactions on Computational Biology & Bioinformatics  
For distribution estimation, we adapt the well-known Good-Turing estimator.  ...  To estimate the mutational support in the small-sample regime, we use GISAID sequencing data and our state-of-the-art polynomial estimation techniques based on new weighted and regularized Chebyshev approximation  ...  (a) Estimates using data from September 2020. (b) Estimates using data from October 2020. (c) Estimates using data from November 2020.  ... 
doi:10.1109/tcbb.2022.3165395 pmid:35385386 fatcat:shkxd2karvdvzhx3maj3mh7nki

Efficient estimation of eigenvalue counts in an interval

Edoardo Di Napoli, Eric Polizzi, Yousef Saad
2016 Numerical Linear Algebra with Applications  
Estimating the number of eigenvalues located in a given interval of a large sparse Hermitian matrix is an important problem in certain applications and it is a prerequisite of eigensolvers based on a divide-and-conquer  ...  Often an exact count is not necessary and methods based on stochastic estimates can be utilized to yield rough approximations.  ...  for the standard Chebyshev approach has the same expression as above with the Jackson coefficients g p j all set to one, so we will use the same symbol to denote both expansions.  ... 
doi:10.1002/nla.2048 fatcat:xwv24n43t5a2fgirehw34yv7hm

User Interaction Modeling and Profile Extraction in Interactive Systems: A Groupware Application Case Study

Cristina Tîrnăucă, Rafael Duque, José Montaña
2017 Sensors  
A relevant goal in human-computer interaction is to produce applications that are easy to use and well-adjusted to their users' needs.  ...  This work constitutes a methodological contribution capable of identifying the context of use in which users perform interactions with a groupware application (synchronous or asynchronous) and provides  ...  We are grateful to the referees for their constructive input. Author Contributions: Cristina Tîrnȃucȃ and José L.  ... 
doi:10.3390/s17071669 pmid:28726762 pmcid:PMC5539516 fatcat:6s26v56sazdl3lcekdb4cq5zwu

A kernel-independent treecode based on barycentric Lagrange interpolation [article]

Lei Wang, Robert Krasny, Svetlana Tlupova
2019 arXiv   pre-print
The method employs barycentric Lagrange interpolation at Chebyshev points to approximate well-separated particle-cluster interactions.  ...  A kernel-independent treecode (KITC) is presented for fast summation of particle interactions.  ...  The method employs barycentric Lagrange interpolation at Chebyshev points to approximate well-separated particle-cluster interactions.  ... 
arXiv:1902.02250v2 fatcat:joweuxc2cvd53i6thqfgnasc4y

Time-series clustering – A decade review

Saeed Aghabozorgi, Ali Seyed Shirkhorshidi, Teh Ying Wah
2015 Information Systems  
Clustering is a solution for classifying enormous data when there is not any early knowledge about classes.  ...  In this research work, the focus is on time-series data, which is one of the popular data types in clustering problems and is broadly used from gene expression data in biology to stock market analysis  ...  : [110] Finance Chebyshev Polynomials (CHEB) a Non data adaptive, Wavelet, Orthonormal - [99] Symbolic Approximation (SAX) O(n) Data adaptive Usage: [111] string processing and bioinformatics  ... 
doi:10.1016/ fatcat:pygcqxztjng5ppoifpnee5evja

Chebfun and numerical quadrature

Nicholas Hale, Lloyd N. Trefethen
2012 Science China Mathematics  
Chebfun is a Matlab-based software system that overloads Matlab's discrete operations for vectors and matrices to analogous continuous operations for functions and operators.  ...  Then we consider how such methods can be applied to quadrature problems including 2D integrals over rectangles, fractional derivatives and integrals, functions defined on unbounded intervals, and the fast  ...  For the specific problem of quadrature over a rectangle, however, one can use a product of two copies of any 1D quadrature method to get results.  ... 
doi:10.1007/s11425-012-4474-z fatcat:gcap7y7hgnfhjkrdqyllf6e2zy

A Machine Learning Algorithm for Biomedical Images Compression Using Orthogonal Transforms

Aurelle Tchagna Kouanou, Research Unity of Condensed Matter, Electronics and Signal Processing, Department of Physics, Faculty of Science, University of Dschang, P.O.Box 67 Dschang, Cameroon., Daniel Tchiotsop, René Tchinda, Christian Tchito Tchapga, Adelaide Nicole Kengnou Telem, Romanic Kengne
2018 International Journal of Image Graphics and Signal Processing  
Using the proposed method, we obtained a compression ratio greater than 99.50 percent. For some codebook size, we obtained a MSE and MAE equal to zero.  ...  Machine learning algorithm is used to calculate the centers of clusters and generates the codebook that is used for vector quantization on the transformed image.  ...  to cluster the group of images and minimum Euclidean distance as in [24] or use LBG algorithm for vector quantization like in many works.  ... 
doi:10.5815/ijigsp.2018.11.05 fatcat:cxeikihyeff2pfrcgvcuy323qq

Clustering of Time-Series Data [chapter]

Esma Ergüner Özkoç
2020 Data Mining - Methods, Applications and Systems [Working Title]  
Time-series clustering methods are examined in three main sections: data representation, similarity measure, and clustering algorithm.  ...  The scope of this chapter includes the taxonomy of time-series data clustering and the clustering of gene expression data as a case study.  ...  ) [16] , Singular Value Decomposition (SVD) [17] [18] , and Symbolic Natural Language (NLG) [19] . • Non-data adaptive methods are use fix-size parameters for the representing time-series data.  ... 
doi:10.5772/intechopen.84490 fatcat:k2njcchrkbbjjfr7k52h3zm2si

A Kernel-Independent Treecode Based on Barycentric Lagrange Interpolation

Lei Wang
2020 Communications in Computational Physics  
The method employs barycentric Lagrange interpolation at Chebyshev points to approximate well-separated particle-cluster interactions.  ...  A kernel-independent treecode (KITC) is presented for fast summation of particle interactions.  ...  We are grateful for a computer allocation on the University of Wisconsin-Milwaukee Mortimer Faculty Research Cluster. We thank Nathan Vaughn and Leighton Wilson for help with programming.  ... 
doi:10.4208/cicp.oa-2019-0177 fatcat:q7bn6nxombdnbic54tdglw3ysq
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