Consideration was given to the problem of functional diagnosis of the nonlinear dynamic systems by the nonparametric method distinguished for the fact that the values of some parameters of the diagnosed system need no...
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Consideration was given to the problem of functional diagnosis of the nonlinear dynamic systems by the nonparametric method distinguished for the fact that the values of some parameters of the diagnosed system need not to be known. An approach was proposed enabling fault isolation. Established were the necessary and sufficient conditions for system transformed into the canonical form required for application of the nonparametric method at diagnosis of the given nonlinear system.
We propose a nonparametric method for extraction of region of interest (ROI) based on information theory. A polygonal active contour, whose energy function is defined by Jensen-Shannon divergence, is used to drive the...
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ISBN:
(纸本)9780819469540
We propose a nonparametric method for extraction of region of interest (ROI) based on information theory. A polygonal active contour, whose energy function is defined by Jensen-Shannon divergence, is used to drive the curve to match the boundaries of the ROL Then, our method is able to solve problems involving arbitrary probability densities for the region intensity. We use this method to extract the ROI of synthesized, aerial and natural images and compare with classical statistical snake. Experimental results demonstrate the power of the proposed extraction method for ROI.
The problem of diagnosing dynamical systems described by models in the form of nonlinear differential equations with unknown coefficients (system parameters) is considered. To solve the problem, a nonparametric diagno...
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The problem of diagnosing dynamical systems described by models in the form of nonlinear differential equations with unknown coefficients (system parameters) is considered. To solve the problem, a nonparametric diagnostic method is used, which permits one to exclude the influence of unknown coefficients of the equations on the diagnosis results. The essence of the nonparametric method is presented. A new method for making decisions about the presence and type of a fault is proposed. The method takes into account model errors, uncontrolled disturbances, and measurement noise. A distinctive feature of the method is that it involves a complex combination of decision making by threshold logic with the comparison of the error (residual) signal against the fault signatures formed during the diagnosis process.
The objective of this study is to find a smooth function joining two points A and B with minimum length constrained to avoid fixed subsets. A penalized nonparametric method of finding the best path is proposed. The me...
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The objective of this study is to find a smooth function joining two points A and B with minimum length constrained to avoid fixed subsets. A penalized nonparametric method of finding the best path is proposed. The method is generalized to the situation where stochastic measurement errors are present. In this case, the proposed estimator is consistent, in the sense that as the number of observations increases the stochastic trajectory converges to the deterministic one. Two applications are immediate, searching the optimal path for an autonomous vehicle while avoiding all fixed obstacles between two points and flight planning to avoid threat or turbulence zones.
We propose a nonparametric method of estimating stochastic nonlinear dynamical system models from discrete observation. Through numerical experiments we also show the proposed method numerically works. (C) 2000 Elsevi...
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We propose a nonparametric method of estimating stochastic nonlinear dynamical system models from discrete observation. Through numerical experiments we also show the proposed method numerically works. (C) 2000 Elsevier Science B.V. All rights reserved.
The thermal relaxation times are characteristic parameters of deep levels which can be calculated by the analysis of admittance data. The contributions of these characteristic parameters can be sharp or broadened. If ...
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The thermal relaxation times are characteristic parameters of deep levels which can be calculated by the analysis of admittance data. The contributions of these characteristic parameters can be sharp or broadened. If sharp contributions are assumed the analysis procedure is called a parametric method. This procedure leads to a well-posed inverse problem but additionally the unknown number of discrete contributions must be determined. For broadened contributions a nonparametric method is used. This procedure leads to an ill-posed inverse problem but the number of contributions is determined automatically. Both kinds of analysis methods are compared with a Monte Carlo study on simulated admittance data. In addition, the parametric and nonparametric procedures are used to analyze experimental admittance data in order to obtain the deep levels and electrical properties of a semi-insulating GaAs Schottky diode. (C) 1999 Academic Press.
Consideration was given to the problem of fault diagnosis of the linear dynamic systems by the nonparametric method distinguished for the fact that the system parameters may be unknown. An approach was proposed to fau...
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Consideration was given to the problem of fault diagnosis of the linear dynamic systems by the nonparametric method distinguished for the fact that the system parameters may be unknown. An approach was proposed to fault localization. methods of making decisions from the results of diagnosis were examined.
In diseases caused by a deleterious gene mutation, knowledge of age-specific cumulative risks is necessary for medical management of mutation carriers. When pedigrees are ascertained through at least one affected indi...
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In diseases caused by a deleterious gene mutation, knowledge of age-specific cumulative risks is necessary for medical management of mutation carriers. When pedigrees are ascertained through at least one affected individual, ascertainment bias can be corrected by using a parametric method such as the Proband's phenotype Exclusion Likelihood, or PEL, that uses a survival analysis approach based on the Weibull model. This paper proposes a nonparametric method for penetrance function estimation that corrects for ascertainment on at least one affected: the Index Discarding EuclideAn Likelihood or IDEAL. IDEAL is compared with PEL, using family samples simulated from a Weibull distribution and under alternative models. We show that, under Weibull assumption and asymptotic conditions, IDEAL and PEL both provide unbiased risk estimates. However, when the true risk function deviates from a Weibull distribution, we show that the PEL might provide biased estimates while IDEAL remains unbiased. Genet. Epidemiol. 33:38-44, 2009. (C) 2008 Wiley-Liss, Inc.
The problem of fault diagnosis in hybrid systems is investigated. The hybrid systems under consideration consist of finite automaton, the set of nonlinear difference equations and so-called mode activator that coordin...
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The problem of fault diagnosis in hybrid systems is investigated. The hybrid systems under consideration consist of finite automaton, the set of nonlinear difference equations and so-called mode activator that coordinates the action of these two parts. The hybrid residual generator based on the nonparametric method is found that solves the fault diagnosis problem under certain (sufficient) solvability conditions. Examples illustrate details of the solution. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
For differentiation of phonostatistical structures of authorial styles, a method of complex analysis of differentiation of phonostatistical structures of authorial style has been developed. The method is based on a co...
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For differentiation of phonostatistical structures of authorial styles, a method of complex analysis of differentiation of phonostatistical structures of authorial style has been developed. The method is based on a combination of the three statistical methods: the Student's t-test, the Kolmogorov-Smirnov's test and the chi-square test. There is one nonparametric method (the Kolmogorov-Smirnov's test) in the proposed combination of methods. The nonparametric method does not depend on the normal distribution law and reduces time consumption for calculation. The strength of the Kolmogorov-Smirnov's test makes it possible to improve test validity of authorship attribution of a text. The method has been realized on the Java programming language which secures platform-independence. (C) 2019 The Authors. Published by Elsevier B.V.
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