Journal ArticleDOI
Desgin and comparative study of some sequential jump detection algorithms for digital signals
M. Basseville,A. Benveniste +1 more
TLDR
The purpose of this paper is to analyze the behavior of several jump detection algorithms when applied to the same real data (geophysical signals) and to compare these algorithms from different points of view: complexity, efficiency, robustness, and ability to characterize the detected jumps.Abstract:
The purpose of this paper is to analyze the behavior of several jump detection algorithms when applied to the same real data (geophysical signals) and to compare these algorithms from different points of view: complexity, efficiency, robustness, and ability to characterize the detected jumps. Three types of algorithms are investigated: "filtered derivatives" detectors, cumulative sum (cusum) tests, and Willsky's generalized likelihood ratio (GLR) algorithm. A modified version of this last test is elaborated, and a new detector, mixing GLR and cusum tests, is presented.read more
Citations
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Proceedings ArticleDOI
Detection of jumps in mean and adaptive filtering
TL;DR: Three types of detectors of sudden changes in a convenient statistical model are investigated here, and some new algorithms are presented together with a comparative study based upon application to real data (geographysical signals).
Journal ArticleDOI
Monitoring of control loop performance by CUSUM algorithms for local linear hypotheses
TL;DR: In this paper, the performance of a closed-loop by detecting whether the mean μ and the standard deviation σ of the control error belong to a fixed triangular region in the (μ, σ) -plane is shown to be a sensible approach.
Book ChapterDOI
Space-Variant Image Restoration
TL;DR: In this paper, a stochastic image-generating process is obtained describing the gray level discontinuities by a space-varying model, where only the information on edge location is needed.
Proceedings ArticleDOI
GLR-based adaptive Kalman filtering in noise removal
L. Hong,D. Brzakovic +1 more
TL;DR: A method for noise removal in image processing is described that has the capability to retain fast transients that are attributed to important changes in the images while it removes the noise added to the slow transients.
Journal ArticleDOI
FPGA-embedded Linearized Bregman Iteration algorithm for trend break detection
TL;DR: The proposed architecture of the Linearized Bregman Iteration algorithm is compared with a state-of-the-art hardware structure for sparse estimation, and the results indicate that its performance concerning trend break detection is much more pronounced while, at the same time, being the indicated solution for long datasets.
References
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Journal ArticleDOI
Paper: A survey of design methods for failure detection in dynamic systems
TL;DR: This paper surveys a number of methods for the detection of abrupt changes in stochastic dynamical systems, focusing on the class of linear systems, but the basic concepts carry over to other classes of systems.
A survey of design methods for failure detection in dynamic systems
TL;DR: A number of methods for detecting abrupt changes (such as failures) in stochastic dynamical systems are surveyed in this paper, where tradeoffs in complexity versus performance are discussed, ranging from the design of specific failure-sensitive filters, to the use of statistical tests on filter innovations, and the development of jump process formulations.
Journal ArticleDOI
A generalized likelihood ratio approach to the detection and estimation of jumps in linear systems
Alan S. Willsky,Harold L. Jones +1 more
TL;DR: In this article, the authors consider a class of stochastic linear systems that are subject to jumps of unknown magnitudes in the state variables occurring at unknown times and devise an adaptive filtering system for the detection and estimation of the jumps.
Journal ArticleDOI
Inference about the change-point from cumulative sum tests
TL;DR: In this paper, the authors examined a secondary aspect, where the departure from initial conditions has taken place in a sequence of normal random variables, where initially the mean and the variance o2 were known.
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A generalized likelihood ratio approach to the detection and estimation of jumps in linear systems
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