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The theoretic ground of a locally topological method for defining a minimal attractor embedding dimension on the basis of linear and nonlinear decompositions in state-space of a dynamic system is proposed. The computer confirmation of the theoretical results is presented.
Estimation of structure and motion in computer vision systems can be performed using a dynamic systems approach, where states and parameters in a perspective system are estimated. This paper presents a new approach to the structure estimation problem, where the estimation of the 3D-positions of feature points on a moving object is reformulated as a parameter estimation problem. For each feature point,...
This work proposes a method for blind equalization of possibly non-minimum phase channels using particular infinite impulse response (IIR) filters. In this context, the transfer function of the equalizer is represented by a linear combination of specific rational basis functions. This approach estimates separately the coefficients of the linear expansion and the poles of the rational basis functions...
In this work we propose an algorithm for the estimation of high resolution color frames from a low resolution compressed color video sequence. The algorithm exploits the existing correlation between the high and low resolution frames to obtain a high resolution frame reducing the artifacts introduced by the compression process. The performance of the proposed algorithm is demonstrated experimentally.
In this paper, a fault-tolerant control method is developed for actuator and component faults. Its principle is based on the on-line nonlinear estimation of a quantity which is equal to zero in the fault-free case and equal to the fault-magnitude when a fault occurs on the system. This estimation is computed from an extended Kalman filter used as an observer. The interest of the method is to consider...
This paper presents a new method for symbol estimation in the downlink of a CDMA communication system. Our approach is based on the observation that the slowly-fading CDMA signal model may be expressed as a linear combination of the convolved independent symbol sequences. A blind source separation approach based on maximization of output entropy is used for the blind separation of the sources; the...
In this paper, different techniques for the estimation of the signal parameters and/or the channel coefficients for single-input/multiple-output systems, arc presented. These methods arc based, cither on the use of a small part of observations or on the minimization of a quadratic form with quadratic constraint. Simulations have been established and these techniques arc compared to the classical approaches.
When consensus algorithms are used in very large networks, spreading information across the whole graph requires a long time. Hence, traditional convergence analysis, studying the essential spectral radius of the transition matrix, predicts very poor performance. However, in estimation problems, it is clear that a growing number of measurements improves the quality of the estimate, and it is natural...
Discrete-time affine control systems with parameter uncertainty and exogenous disturbances are considered in the paper. Such systems are examined, where there is an a priori constraint on the Euclidean norm of the control. The nominal free system is supposed to be exponentially stable, the parameter uncertainty is cone-bounded. A saturation type state-feedback control is proposed. A sufficient condition...
The method of sample-based minimax optimization is developed for the minimization problem with an uncertain quadratic objective function subject to linear constraints. Several examples based on confidence statistical estimation are considered to define the uncertainty set. Analytical and numerical techniques are proposed for finding the optimal robust strategy.
In this paper a method is proposed that allows the identification of input-output quasi-linear parameter-varying (LPV) models based on ergodic signals. In this case the use of the instrumental variables (IV) method leads to a consistent estimation of the quasi-LPV model parameters. Moreover, an indirect closed-loop identification technique, which has been proposed for the identification of linear...
This paper summarizes the results obtained through a systematic and extensive investigation of the performance of the new system identification toolbox, SLIDENT, incorporated in the freely available Fortran 77 Subroutine Library in Control Theory (SLICOT). This toolbox provides drivers, computational routines, and Matlab or Scilab interfaces, which implement two algorithmic subspace-based approaches...
By using robust control techniques, this paper proposes an adaptive control for rigid robots with the following important features: under a parameter-dependent PE (Persistent Excitation) condition, it gives a guaranteed transient performance of tracking a smooth desired trajectory while assuring the parameter estimation error to go to a residual set of the origin arbitrarily fast. Simulations are...
Mathematical modelling of cell culture processes is particularly useful for simulation, optimisation and control. Building models for such bioprocesses presents challenges at all stages of model development. In order to achieve model simplicity, the system of mass balances for the macroscopic species involved in a reaction scheme is generally used. However, the underlying reaction scheme is usually...
In this paper, an alternative method for state estimation of a linear stochastic system under additional bounded set-theoretic disturbance is proposed as a modification of the Bayesian formulation of the problem. The solution is not optimal, but only an approximation based on maximum likelihood approximation. This approach provides superior performance in comparison with classical unknown input observer...
In this paper, we present a method for estimating the signal sources steering vector using an arbitrary planar array with omnidirectional elements. The proposed method improves the initial estimation of the signal steering vector in two steps. In the first step of this algorithm we minimize of the distance between the steering vector and the signal subspace. The second step improves the estimation...
In this paper we present an original subspace-based method for direction finding by an array of uncalibrated isotropie sensors. This iterative method has been developed in order to estimate both directions-of-arrival of non circular radiating signal sources and unknown gain and phase of sensors. The non circular sources assumption leads to an extended array data model. One of the benefits of this...
We propose a novel method for velocity estimation and detection of a moving object in an image sequence. This purpose is achieved by using discrete wavelet transform and parallel bank of extended complex Kalman filter in the transform/spatio-temporal mixed-domain. In the mixed-domain, image sequence processing is replaced by l-dimensional(l-D) complex signal processing. Then, trajectory signal with...
In this paper we develop an algorithm to improve the accuracy of the wideband signal parameter estimation. It is well known that in the presence of an unknown noise, these estimates may be grossly inaccurate. The proposed algorithm uses both the fourth order cumulant for the suppression of the gaussian noise, the transformation matrices for estimating the coherent cumulant matrix and a noneigenvector...
Complex dynamical networks emerge from the physical or information based interconnection of many dynamical systems. These networks display emergent behaviour that is best understood through knowledge of the interconnection structure of the network. We analyze and compare a variety of existing regression techniques (some sparsity inducing and other not) with a recursive sparse estimator, presented...
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