This article presents maximisation of components tolerance together with finding optimal frequency of a periodic excitation in fault diagnosis of analogue electronic circuits. Additionally classical two-stage “detect...
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This article presents maximisation of components tolerance together with finding optimal frequency of a periodic excitation in fault diagnosis of analogue electronic circuits. Additionally classical two-stage “detection → location” diagnosis sequence is merged into single step in order to reduce test time. Presented optimisation problems are solved by means of a genetic algorithm.
A feedback controller is proposed for cancellation of magnetic resonance imaging (MRI) noise. The design of the controller takes into account specific features of the MRI noise signal. Simulation results show that a c...
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ISBN:
(纸本)9781618392800
A feedback controller is proposed for cancellation of magnetic resonance imaging (MRI) noise. The design of the controller takes into account specific features of the MRI noise signal. Simulation results show that a considerable rejection rate of the MRI noise can be obtained.
Research undertaken for the behavior of "human expert" showed that it is specific to its highly nonlinear behavior, with the effects of anticipation, integration, prediction and adapting itself to the concre...
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In this paper we propose how to exploit image textural features to improve scribble-based image colorization. The existing techniques work by propagating color from the user-added scribbles over the whole image. The c...
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In this paper, the hardware component of a new technology used to communicate with people with major neuro-locomotor disability using ocular electromyogram is presented. The signals produced by the ocular muscle, prov...
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This paper presents a new technology used for communicating with people with major neuro-locomotor disability by determining gaze direction on a monitor screen. Gaze direction is determined by pupil position through i...
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In this paper a real-time image based visual servoing scheme for a nonholonomic mobile robot is presented. The proposed method takes into account the nonholonomic motion constraint of mobile robots. As a distinctive f...
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In this paper a real-time image based visual servoing scheme for a nonholonomic mobile robot is presented. The proposed method takes into account the nonholonomic motion constraint of mobile robots. As a distinctive fact it does not require the estimation and decomposition of the homography or fundamental matrix. A switched image based controller is design, using point features, in order to solve the camera field-of-view (FOV) constraint. The proposed architecture was implemented using a real-time visual servoing system and multiple test were conducted. Experimental results are revealed and commented.
In the paper the first order sensitivity analysis is performed for a class of optimal control problems for time delay parabolic-hyperbolic equations. A singular perturbation of geometrical domain of integration is int...
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In the paper the first order sensitivity analysis is performed for a class of optimal control problems for time delay parabolic-hyperbolic equations. A singular perturbation of geometrical domain of integration is introduced in the form of a circular hole. The Steklov-Poincaré operator on a circle is defined in order to reduce the problem to regular perturbations in the truncated domain. The optimality system is differentiated with respect to the small parameter and the directional derivative of the optimal control is obtained as a solution to an auxiliary optimal control problem.
Abstract In this paper we consider the problem of noncausal identification of nonstationary, linear stochastic systems, i.e., identification based on prerecorded input/output data. We show how several competing weight...
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Abstract In this paper we consider the problem of noncausal identification of nonstationary, linear stochastic systems, i.e., identification based on prerecorded input/output data. We show how several competing weighted least squares parameter smoothers, differing in memory settings, can be combined together to yield a better and more reliable smoothing algorithm. The resulting parallel estimation scheme automatically adjusts its smoothing bandwidth to the unknown, and possibly time-varying, rate of nonstationarity of the identified system. It also allows one to account for the distribution of measurement noise, and in particular – to cope with heavy-tailed disturbances, such as Laplacian noise, or light-tailed disturbances, such as uniform noise.
Abstract The problem of identification of linear quasi-periodically varying systems is considered. This problem can be solved using generalized adaptive notch filtering (GANF) algorithms. It is shown that accuracy of ...
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Abstract The problem of identification of linear quasi-periodically varying systems is considered. This problem can be solved using generalized adaptive notch filtering (GANF) algorithms. It is shown that accuracy of system parameter estimation can be increased if the results obtained from GANF are further processed using a cascade of appropriately designed filters. The resulting generalized adaptive notch smoothing (GANS) algorithms can be employed in offline applications where causality constraints do not apply. When the instantaneous frequency of parameter changes varies in a sufficiently smooth manner, the proposed GANS algorithm, based on a new, quasi-linear model of frequency drift, outperforms the existing solutions.
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