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On-line detection of continuous changes in stochastic processes

Kohei Miyaguchi, Kenji Yamanishi
2015 2015 IEEE International Conference on Data Science and Advanced Analytics (DSAA)  
We are concerned with detecting continuous changes in stochastic processes. In conventional studies on non-stationary stochastic processes, it is often assumed that changes occur abruptly.  ...  The contribution of this paper is as follows: We first propose a novel characterization of processes for continuous changes.  ...  , and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.  ... 
doi:10.1109/dsaa.2015.7344783 dblp:conf/dsaa/MiyaguchiY15 fatcat:zdmliiadlvalnapceahyqr73vq

Retrospective Change-Points Detection for Multidimensional Time Series of Arbitrary Nature: Model-Free Technology Based on the ϵ-Complexity Theory

Alexandra Piryatinska, Boris Darkhovsky
2021 Entropy  
Change-points are the moments at which the changes in generating mechanism occur. Our method is based on the new theory of ϵ-complexity of individual continuous vector functions and is model-free.  ...  We consider a retrospective change-point detection problem for multidimensional time series of arbitrary nature (in particular, panel data).  ...  We thank the anonymous reviewers for their careful reading of our manuscript and their insightful comments and suggestions. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/e23121626 pmid:34945932 pmcid:PMC8700035 fatcat:fhb7yhlk2zhgfbblnoeyievhwy

Multiscale PCA with application to multivariate statistical process monitoring

Bhavik R. Bakshi
1998 AIChE Journal  
for easiest detection of deterministic changes in the measurements.  ...  In addition to improving the ability to detect deterministic changes, monitoring by MSPCA also simultaneously extracts those features that represent abnormal operation.  ...  Prem Goel and Xiaotong Shen of the Department of Statistics at Ohio State for extensive discussions on the statistical aspects of this work; the Abnormal Situation Management consortium, Mr.  ... 
doi:10.1002/aic.690440712 fatcat:ursk4v4ic5af7kb4trspawvtcu

Two Notes About Adaptive Filters for Volatility Parameter

Reza Habibi
2012 International Journal of Algebra and Statistics  
This paper consider the adaptive filtering problem in a semi-martingale process for trend and volatility parameters under the stochastic volatility assumption.  ...  First, we consider the Black-Scholes model for volatility and then we extend our results to the other models for volatility process. A conclusion section is also given.  ...  Concluding Remarks In this paper, we considered adaptive estimation of volatility parameter of a semi-martingale process. We proposed two approaches.  ... 
doi:10.20454/ijas.2012.371 fatcat:dapvagrtsrhi7kyt46sidzi2wm

Adaptive Stochastic Resonance Method Based on Quantum Genetic Algorithm and its Application in Dynamic Characteristic Identification of Bridge GNSS Monitoring Data

Xinpeng Wang, Shengxiang Huang, Guanqing Li, Wen Zhang, Chenfeng Li, Yarong Wang
2020 IEEE Access  
Analyzing the simulation signals not only verifies the validity and scientificity of the method, but also analyzes its frequency extraction effect in the approximate error range of target frequency with  ...  To solve this problem, the present study proposes a new adaptive stochastic resonance method based on quantum genetic algorithm with known frequency as optimal parameter.  ...  Moreover, the red solid line representing the SNR of the signals processed by QGA-ASR in FIGURE 4 (a) and (b) are above the blue solid line of the signals processed by GA-ASR in most cases, thereby indicating  ... 
doi:10.1109/access.2020.3002889 fatcat:wclzs33ukrez7mzwhofbh5abxq

Optimal Stochastic Control in the Interception Problem of a Randomly Tacking Vehicle

Andrey A. Galyaev, Pavel V. Lysenko, Evgeny Y. Rubinovich
2021 Mathematics  
An analytical estimation of this detection probability is proposed.  ...  This article considers the mathematical aspects of the problem of the optimal interception of a mobile search vehicle moving along random tacks on a given route and searching for a target, which travels  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/math9192386 fatcat:vn6hy225lrh25krn427hd5kglq

Recursive integral equations for the detection of counting processes

Francois B. Dolivo, Frederick J. Beutler
1976 Applied Mathematics and Optimization  
on detection of a stochastic signal in white noise.  ...  A recursive stochastic integral equation for the detection of counting processes is derived from a previously known formula [5] of the likelihood ratio.  ...  By (At) we denote a real valued stochastic process defined on R +, the positive real line and by a Counting Process (CP) we mean Let (~) be a right-continuous increasing family of o-subalgebras of ~ with  ... 
doi:10.1007/bf02106191 fatcat:ggtby6qnzfgwthsdp2uryzmvcu

Page 52 of Automation and Remote Control Vol. 53, Issue 1 [page]

1992 Automation and Remote Control  
Silaev UDC 519.217:517.977.57 An algorithm is given for on-line estimation of the time of change of the statistical characteristics of a Markov chain.  ...  Methods of sequential statistical analysis have been applied previously [1-3, 6, 7] to the closely related problems of optimal detection of sudden changes in the properties of stochastic processes.  ... 

Stochastic thermal feedback in switching measurements of superconducting nanobridge caused by overheated electrons and phonons [article]

Maciej Zgirski, Marek Foltyn, Alexander Savin, Konrad Norowski
2021 arXiv   pre-print
As a result, an artificial intricate stochastic process with adjustable strength of correlation is produced.  ...  Due to its extreme sensitivity on the control parameter, i.e. electric current, temperature or magnetic field, it offers opportunity for ultra-sensitive detection.  ...  Similarly one may expect to see the transition for small change in magnetic flux if instead of the single junction one uses a SQUID.  ... 
arXiv:2003.04221v2 fatcat:oyzlbm3q7zagxnbx2onbwhltsa

A mathematical framework for new fault detection schemes in nonlinear stochastic continuous-time dynamical systems

Pedro J. Zufiria
2012 Applied Mathematics and Computation  
These schemes are based on a stochastic process, called the residual, which reflects the system behavior and whose changes are to be detected.  ...  In this work, a mathematical unifying framework for designing new fault detection schemes in nonlinear stochastic continuous-time dynamical systems is developed.  ...  Acknowledgement This work has been partially supported by project MTM2007-62064 of the Plan Nacional de I+D+i, MEyC, Spain, project MTM2010-15102 of Ministerio de Ciencia e Innovación, Spain, and by projects  ... 
doi:10.1016/j.amc.2012.05.024 fatcat:gonjopyenbclzp5naspwy2bynq

Stochastic Acceleration and Nonthermal Radiation in Clusters of Galaxies

Pasquale Blasi
2000 Astrophysical Journal  
We calculate the distribution of electrons in clusters of galaxies, resulting from thermalization processes in the presence of stochastic acceleration due to plasma waves.  ...  The non-thermal tail of electrons can generate as bremsstrahlung emission a flux of hard X-rays compatible with the ones recently detected in some clusters of galaxies.  ...  This is due to the fact that the spectrum of waves is required to not change in our treatment, so that a continuous energy input is required to compensate the damping of the waves.  ... 
doi:10.1086/312551 pmid:10702120 fatcat:y3r6ykepyneebeclznqguwlhfq

Charge displacements in a single potassium ion channel macromolecule during gating

Y.H. Mika, Y. Palti
1994 Biophysical Journal  
The transients most likely represent apparent deterministic stages in the gating process.  ...  The measured charge displacements show: 1) a slow component, -2 fA above baseline level, assumed to represent stochastic conformational changes, and 2) transients, the most significant of which occur 1.1  ...  This research was supported in part by the Rappaport Institute and GIF grants.  ... 
doi:10.1016/s0006-3495(94)80619-8 pmid:7819483 pmcid:PMC1225508 fatcat:suxbluupdzcp5on4i57hlcqgoq

Author index volume 20

1985 Stochastic Processes and their Applications  
Sumita Nayak, S.S., Almost sure limit points of independent copies of sample (1) H., Periodic regeneration Vaman, H.J., Optimum online detection of parameter changes in two linear models Wilson, J.G.  ...  J. de Mare, Generation of random processes for fatigue testing (1)149-156 Imkeller, P., A stochastic calculus for continuous N-parameter strong martingales (1) l-40 Karr, A.F., State estimation for Cox  ... 
doi:10.1016/0304-4149(85)90225-x fatcat:pvpt6jgzlja65jufttgcgaofym

A formulation for fault detection in stochastic continuous-time dynamical systems

Pedro J. Zufiria
2009 International Journal of Computer Mathematics  
This formulation is based on the definition of a pre-Hilbert space so that orthogonal projection techniques, based on the statistics of the involved stochastic processes can be applied.  ...  In this work, a general formulation for fault detection in stochastic continuoustime dynamical systems is presented.  ...  Acknowledgements This work has been partially supported by project MTM2007-62064 of the Plan National de I+D+i, MEyC, Spain, and by project CCG07-UPM/000-3278 of the Universidad Politecnica de Madrid (  ... 
doi:10.1080/00207160802702426 fatcat:xvxs3zoawnhiraxpladeosmgj4

A Sampling-Based Method for Robust and Efficient Fault Detection in Industrial Automation Processes [chapter]

Stefan Windmann, Oliver Niggemann
2018 IMPROVE - Innovative Modelling Approaches for Production Systems to Raise Validatable Efficiency  
Continuous process behaviour in the particular system modes is modeled with stochastic state space models, which incorporate neural networks.  ...  In the present work, fault detection in industrial automation processes is investigated.  ...  Fault detection with stochastic process models In this section, the prior work on fault detection with stochastic process models is described.  ... 
doi:10.1007/978-3-662-57805-6_5 fatcat:vissk3ef5zb5thbt5bw6g54xh4
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