In a number of array signal processing applications, such as underwater source localization, the propagation medium is not homogeneous, which causes a distortion of the wavefront received by the array. In this paper, ...
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In a number of array signal processing applications, such as underwater source localization, the propagation medium is not homogeneous, which causes a distortion of the wavefront received by the array. In this paper, we consider the direction-of-arrival (DOA) estimation problem for such distorted wavefronts. In previous approaches, the so-called multiplicative noise scenario is considered based on the assumption that the distortion is random and can be parameterized by a small number of parameters. To gain robustness against mismodelling we assume a scenario in which the wavefront amplitude is distorted in a completely arbitrary way. We derive the maximum likelihood (ML) estimator of the DOA and show it can be obtained by means of a simple 1D search. The Cramer-Rao bound (CRB) for the problem at hand is derived. Numerical simulations illustrate a good performance of the estimator and show that its accuracy is comparable with that of estimators which require knowledge of the form of amplitude distortions.
This paper deals with the estimation of an unknown process transfer function in the presence of colored measurement noise. A three-step estimation procedure has been previously developed for transfer functions, the de...
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This paper deals with the estimation of an unknown process transfer function in the presence of colored measurement noise. A three-step estimation procedure has been previously developed for transfer functions, the delay steps and the orders of which are known in advance. The procedure is extended to deal with transfer functions with unknown delay steps and orders. The auto-correlation function of the error between the process output and model output is utilized for evaluating the model fitness. The effectiveness of the proposed method is demonstrated by a simulation study using a sample set of data in MATLAB.
Decomposing dynamical systems in terms of orthogonal expansions enables the modelling/approximation of a system with a finite length expansion. By flexibly tuning the basis functions to underlying system characteristi...
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Decomposing dynamical systems in terms of orthogonal expansions enables the modelling/approximation of a system with a finite length expansion. By flexibly tuning the basis functions to underlying system characteristics, the rate of convergence of these expansions can be drastically increased, leading to highly accurate models (small bias) being represented by few parameters (small variance). Additionally algorithmic and numerical aspects are favourable. A recently developed general theory for basis construction will be presented, that is a generalization of the classical Laguerre theory. The basis functions are applied in problems of identification, approximation, realization, uncertainty modelling, and adaptive filtering, particularly exploiting the property that basis function models are linearly parametrized. Besides powerful algorithms, they also provide useful analysis tools for understanding the underlying identification/approximation algorithms.
This paper proposes a genetic-based algorithm for surface reconstruction of three-dimension (3-D) objects from a group of contours representing its section plane lines. The algorithm can optimize the triangulation of ...
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This paper proposes a genetic-based algorithm for surface reconstruction of three-dimension (3-D) objects from a group of contours representing its section plane lines. The algorithm can optimize the triangulation of the surface of 3-D objects with a multi-objective optimization function to meet the needs of a wide range of applications. Further, a new crossover operator for triangulation and a new 3-D quadrilateral mutation operator are also introduced.
The use of AI techniques in control raises the problem of implementing operations with not well bounded and defined computing time, in a real time framework. In this paper, the combined used of conventional and AI con...
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The use of AI techniques in control raises the problem of implementing operations with not well bounded and defined computing time, in a real time framework. In this paper, the combined used of conventional and AI control strategies at different levels of process control is analyzed. Each control activity is split into a number of tasks, involving mandatory and optional computations. The main time constraints as well as some structures, namely the integrated and the hierarchical control structures, are reviewed and some solutions to guarantee the response time are proposed. Two applications in the control of industrial kilns are also discussed.
Services on the Internet rely on Internet applications, that is software applications distributed between clients and an Internet server relying on IP-based communication. This work demonstrates that they can benefit ...
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This paper addresses the inverse optimal robust control problem for uncertain nonlinear systems. A new version of robust backstepping is proposed in which inverse optimality is achieved through the selection of genera...
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When the air-gap flux is saturated, the conventional adaptive speed estimator cannot remove the influence of the nonlinear inductance variation. Without speed sensors, it is difficult to identify inductance variation ...
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Access to restricted spaces underwater requires a small unencumbered camera. A low cost solution has been envisaged. It consists of an hermetic capsule enclosing the camera and lights, joined to the host by an umbilic...
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Access to restricted spaces underwater requires a small unencumbered camera. A low cost solution has been envisaged. It consists of an hermetic capsule enclosing the camera and lights, joined to the host by an umbilical. Along the umbilical go six water carrying ducts. Three of them end at backwards pointing nozzles located at the capsule body. The jets of water flowing from the nozzles are controlled and their forces allow some restricted positioning of the camera. Another three ducts end at nozzles located some distance up the umbilical, and allow greater maneuverability.
In this paper, three neural network based d-step-ahead prediction strategies, i.e. a recursive d-step-ahead neural predictor, a non-recursive d-step-ahead neural predictor, and a Smith type neural predictor are presen...
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In this paper, three neural network based d-step-ahead prediction strategies, i.e. a recursive d-step-ahead neural predictor, a non-recursive d-step-ahead neural predictor, and a Smith type neural predictor are presented for time-delay compensation for nonlinear systems. Both the recursive and the non-recursive predictors have been extended to the case of long-range prediction. Finally, the proposed neural network based predictors are applied to the prediction of the manifold pressure process in an automotive engine. The predictive result of the corresponding first principles model based nonlinear predictor is also illustrated for comparison. The experimental results show that the neural network based predictive methods have obtained better performance.
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