Time-scale analysis of abrupt changes corrupted by multiplicative noise

Multiplicative Abrupt Changes (ACs) have been considered in many applications. These applications include image processing (speckle) and random communication models (fading). Previous authors have shown that the Continuous Wavelet Transform (CWT) has good detection properties for ACs in additive noise. This work applies the CWT to AC detection in multiplicative noise. CWT translation invariance allows to define an AC signature. The problem then becomes signature detection in the time-scale domain. A second-order contrast criterion is defined as a measure of detection performance. This criterion depends upon the first- and second-order moments of the multiplicative process's CWT. An optimal wavelet (maximizing the contrast) is derived for an ideal step in white multiplicative noise. This wavelet is asymptotically optimal for smooth changes and can be approximated for small AC amplitudes by the Haar wavelet. Linear and quadratic suboptimal signature-based detectors are also studied. Closed-form threshold expressions are given as functions of the false alarm probability for three of the detectors. Detection performance is characterized using Receiver Operating Characteristic (ROC) curves computed from Monte-Carlo simulations

Hybridation and Fusion of Satellite and Telecommunication Network Based Positioning Methods

1. Browsing over the satellite Navigation Systems: 1.1 Basic Principles 1.2 Augmentation with external navigation means Contents 1.3 Augmentation with self-sensory means 2. Positioning with wireless communication networks: 2.1 Positioning capabilities of wireless networks 2.2 Hybridation: Fusion Algorithm

Digital spectral analysis: parametric, non-parametric and advanced methods

Digital Spectral Analysis provides a single source that offers complete coverage of the spectral analysis domain. This self-contained work includes details on advanced topics that are usually presented in scattered sources throughout the literature.The theoretical principles necessary for the understanding of spectral analysis are discussed in the first four chapters: fundamentals, digital signal processing, estimation in spectral analysis, and time-series models.An entire chapter is devoted to the non-parametric methods most widely used in industry.High resolution methods

Is H infinity filtering relevant for correlated noises in GPS navigation ?

International audienceThis paper deals with the issue of correlated noises in GPS navigation. GPS is based on the measure of the propagation delays of satellite signals. Therefore, additional delays induced when traveling through the ionosphere or the troposphere degrade GPS accuracy. These error sources are correlated, both spatially and temporally. Thus, when using an extended Kalman filter as navigation algorithm, these correlations should be taken into account to ensure that an optimal solution is obtained in terms of mean square error. Our contribution is to study, in this context, the relevance of an alternative approach well-known in the field of control engineering: the H1 filter. Also based on a state representation, this technique has the advantage of relaxing the constraints on the measurement and state noises. A comparative study with a standard extended Kalman filter and a colored extended Kalman filter is carried out to illustrate which of the above-mentioned approaches achieves the better compromise between accuracy and computational complexity

Statistical analysis of a two-layer backpropagation algorithm used for modeling nonlinear memoryless channels: The single neuron case

Abstract — Neural networks have been used for modeling the nonlinear characteristics of memoryless nonlinear channels using backpropagation (BP) learning with experimental training data. In order to better understand this neural network application, this paper studies the transient and convergence properties of a simplified two-layer neural network that uses the BP algorithm and is trained with zero mean Gaussian data. The paper studies the effects of the neural net structure, weights, initial conditions, and algorithm step size on the mean square error (MSE) of the neural net approximation. The performance analysis is based on the derivation of recursions for the mean weight update that can be used to predict the weights and the MSE over time. Monte Carlo simulations display good to excellent agreement between the actual behavior and the predictions of the theoretical model. I

Influence of cutting parameters and wear in drilling of 3D wowen carbon/epoxy composite

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Influence of cutting parameters and wear in drilling of 3D wowen carbon/epoxy composite

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Etude expérimentale de l'influence des paramètres de coupe et de l'usure de l'outil sur la qualité de percage d'un composite tissé 3D.

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Etude expérimentale de l'influence des paramètres de coupe et de l'usure de l'outil sur la qualité de percage d'un composite tissé 3D.

International audienceno abstrac