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Wavelet thresholding techniques are becoming popular in the signal processing community for denoising applications. Near-minimax properties were in particular established for simple threshold estimates over wide classes of regular functions. In this paper, we establish close connections between wavelet thresholding techniques and MAP estimation using exponential power prior distributions for a wide...
A new approach is proposed for estimating the direction-of-arrival (DOA) of the cyclostationary coherent signals impinging on a uniform linear array (ULA) by utilizing the spatial smoothing (SS) technique. In order to improve the robustness of the DOA estimation by exploiting the cyclic statistical information sufficiently and handling the coherence effectively, we give a cyclic algorithm with multiple...
This paper addresses the issue of Orthogonal Techniques for Blind Source Separation of periodic signals when the mixtures are corrupted with spatially correlated noises. The noise covariance matrix is assumed to be unknown. This problem is of major interest with experimental signals. We first remind that Principal Components Analysis (PCA) cannot provide a correct estimate of the signal subspace in...
This papers deals with supervised texture classification. The extracted features are the image second and third order moments. The number of possible moment lags for 2-D signals increases rapidly with the order of the moment even for small lag neighbourhoods. The paper focuses on the selection of moment lags that optimise classification performance. Lag selection also serves another purpose: it waives...
In a multipaths context, direction finding must resort to hight resolution algorithms. Classically, they operate on arrays of isotropie or identical sensors because they use the geometrical phase that the space diversity induces on the received signals. We propose to derive the standard music algorithm as the array is made up with sensor which are different from each other, assuming that their spatial...
This paper deals with the problem of quadratic minimization subject to linear equality constraints. Contrary to the standard formulation, we assume the most general case of a possibly singular quadratic form. As we explain, the existing formal solution to this problem has several drawbacks. Our new approach is free from most of these drawbacks. It has a simple physical interpretation and is relatively...
We investigate the identifiability conditions for blind and semi-blind FIR multichannel estimation in terms of channel characteristics, data length and input symbol excitation modes. Parameters are identifiable if they are determined uniquely by the probability distribution of the data. Two models are presented: in the deterministic model, both channel coefficients and input symbols are considered...
A method for the minimization of mean square error of the instantaneous frequency estimation using time-frequency distributions, in the case of a discrete optimization parameter, is presented. It does not require knowledge of the estimation bias. The method is illustrated on the adaptive window length determination in the Wigner distribution.
Subspace fitting methods have grown popular for parameter estimation in many different application, for example sensor array signal processing, blind channel identification and identification of linear state space systems. Here we show that similar procedures can be used even for data models where the noise free signal gives a full rank contribution to the covariance matrix. A general weighting is...
The low computation cost, short delay and accuracy of SINTRACK, makes it a very interesting real-time signal processing tool for detection and estimation of damped sinusoids in noise. A noise analysis, as well as a parameters' optimal adjustment analysis are provided. SINTRACK was successfully applied for detection and estimation of a HALE wing bending and torsion oscillations, validating a theoretical...
The issue of rank estimation in subspace tracking algorithms is adressed. In a recent paper, we proposed a subspace tracking algorithm, the NA-CSVD. We now extend the performance of NA-CSVD to rank tracking by coupling it with a recently proposed rank tracking technique. The paper includes an overview of typical rank+subspace tracking algorithms which, along with our proposed algorithm, are tested...
The family of MUSIC estimators is often used in the case of the spectral analysis of sinusoidal signals. One of those estimators, called ACM-MUSIC, is based on the direct estimation of the vectors which constitute the signal and noise subspaces thanks to the autocorrelation matrix. In this paper, we suggest using the iterated power method in order to improve the estimation of those vectors. Besides,...
This paper presents a three-dimensional motion estimator for use in cases where we have noisy video sequences containing one moving object on a stationary background. The motion estimator is to be used as part of an image enhancing pre-processing step. A Parallel Extended Kalman Filter (PEKF) developed by J. B. Burl is at the heart of this motion estimator, together with additional data mapping techniques...
This paper addresses the problem of detecting the presence of multiplicative noise, when the information process can be modelled by a parametric AR process. A suboptimal detector based on higher-order cumulante (HOC) is studied. This detector consists of filtering the data by the fitted AR filter. HOC of the residual data are shown to be efficient for the detection problem.
In this paper a novel and efficient approach is presented for power system switching transient analysis: The so-called Matrix Pencil Method MP, is based upon a modal decomposition of exponentially modulated sinusoids, formulated as a generalized eigen-value problem. In this paper we are interested in shunt compensated line transient voltages during auto re-closing operations. The MP method has readily...
A stochastic linear hybrid system is said to be observable if the hybrid state of the system can be uniquely determined from its output. In this paper, we derive conditions for the observability of stochastic linear hybrid systems by exploiting the information obtained from system noise characteristics. Having established the necessary criteria for observability, we study the effect of these conditions...
A novel approach to estimation of the Interaural Time Difference (ITD) from the measured Head Related Impulse Responses (HRIR) is proposed in the paper. An innovative application of the cross-correlation function that is estimated for impulse responses corresponding to adjacent sound arrival directions makes the presented method robust and immune to inherent noise components occuring in the measured...
The problem of estimating the state of discrete-time linear systems when uncertainties affect the system matrices is addressed. A quadratic cost function is considered, involving a finite number of recent measurements and a prediction vector. This leads to state the estimation problem in the form of a regularized least-squares one with uncertain data. The optimal solution (involving on-line scalar...
The present paper investigates the influence of noise on the estimation results for max-plus-linear systems. These systems are a suitable description for many processes modelled by discrete event systems. It is shown that measurements corrupted by Gaussian noise lead to a bias in the estimated values. In addition a correction factor is determined that attempts to compensate this bias.
The optimal control strategy for discrete time multiple model is described. Simulation of control and on-line estimation of model probability is shown. Robustness of stability and comparison of the classical LQ control and LQ control based on multiple models is presented.
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