Performance Analysis of the Decentralized Eigendecomposition and ESPRIT Algorithm

In this paper, we consider performance analysis of the decentralized power method for the eigendecomposition of the sample covariance matrix based on the averaging consensus protocol. An analytical expression of the second order statistics of the eigenvectors obtained from the decentralized power method which is required for computing the mean square error (MSE) of subspace-based estimators is presented. We show that the decentralized power method is not an asymptotically consistent estimator of the eigenvectors of the true measurement covariance matrix unless the averaging consensus protocol is carried out over an infinitely large number of iterations. Moreover, we introduce the decentralized ESPRIT algorithm which yields fully decentralized direction-of-arrival (DOA) estimates. Based on the performance analysis of the decentralized power method, we derive an analytical expression of the MSE of DOA estimators using the decentralized ESPRIT algorithm. The validity of our asymptotic results is demonstrated by simulations.Comment: 18 pages, 5 figures, submitted for publication in IEEE Transactions on Signal Processin

Sequential joint signal detection and signal-to-noise ratio estimation

The sequential analysis of the problem of joint signal detection and signal-to-noise ratio (SNR) estimation for a linear Gaussian observation model is considered. The problem is posed as an optimization setup where the goal is to minimize the number of samples required to achieve the desired (i) type I and type II error probabilities and (ii) mean squared error performance. This optimization problem is reduced to a more tractable formulation by transforming the observed signal and noise sequences to a single sequence of Bernoulli random variables; joint detection and estimation is then performed on the Bernoulli sequence. This transformation renders the problem easily solvable, and results in a computationally simpler sufficient statistic compared to the one based on the (untransformed) observation sequences. Experimental results demonstrate the advantages of the proposed method, making it feasible for applications having strict constraints on data storage and computation.Comment: 5 pages, Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 201

Attacks on Robust Distributed Learning Schemes via Sensitivity Curve Maximization

Distributed learning paradigms, such as federated or decentralized learning, allow a collection of agents to solve global learning and optimization problems through limited local interactions. Most such strategies rely on a mixture of local adaptation and aggregation steps, either among peers or at a central fusion center. Classically, aggregation in distributed learning is based on averaging, which is statistically efficient, but susceptible to attacks by even a small number of malicious agents. This observation has motivated a number of recent works, which develop robust aggregation schemes by employing robust variations of the mean. We present a new attack based on sensitivity curve maximization (SCM), and demonstrate that it is able to disrupt existing robust aggregation schemes by injecting small, but effective perturbations

An optimisation approach to robust estimation of mulitcomponent polynomial phase signals in non-Gaussian noise

In this paper, we address the problem of estimating the parameters of multicomponent polynomial phase signals in impulsive noise which arises in many practical situations. In the presence of this non-standard noise, existing techniques perform can poorly. We propose a nonlinear M-estimation approach to improve the existing techniques. The phase parameters are obtained by solving a nonlinear optimisation problem. A procedure is proposed to find the global minimum at low computational cost. Simulation examples show the proposed method performs better than existing method

A nonlinear M-estimation approach to robust asynchronous multiuser detection in Non-gaussian noise

A nonlinear M-estimation approach is proposed to solve the multiuser detection problem in asynchronous code-division multiple-access (CDMA) systems where the ambient noise is impulsive and the delays are not known. We treat the unknown delays as nuisance parameters and the transmitted symbols as parameters of interest. We also analyze the asymptotic performance of the proposed estimator and propose suboptimal but computationally efficient procedures for solving the nonlinear optimization function. Simulation results show considerable improvements over the conventional approaches

Understanding the Regioselectivity and Reactivity of Friedel–Crafts benzoylation Using Parr Functions

A theoretical study of the reactivity and regioselectivity of some aromatic compounds in electrophilic aromatic substitution is carried out at the B3LYP/6-31G(d) computational level. The relative reactivity of these systems is rationalized by means of the global nucleophilicity index proposed by Domingo’s group. The positional selectivity, namely o, m or p, is predicted by means of the local nucleophilicity indices [Parr fonctions]. The present study shows that the experimental trends of the relative reactivities and regioselectivities of these reactions are correctly predicted using Parr fonctions

Single-shot two-dimensional spectral interferometry for ultrafast laser-produced plasmas

This paper was published in Optics Letters and is made available as an electronic reprint with the permission of OSA. The paper can be found at the following URL on the OSA website: http://dx.doi.org/10.1364/OL.31.001917 Systematic or multiple reproduction or distribution to multiple locations via electronic or other means is prohibited and is subject to penalties under law

L'optimisation des positions de capteurs pour la détection du cliquetis dans les moteurs à explosion

In this study, we consider the problem of finding optimum sensor positions in a group of vibration sensors for knock detection. We propose a method that is less complex than holografic techniques because only signal processing and statistical tests are used . Our method is based on the linear prediction of an arbitrary sensor output from the remaining outputs in the sensor group. The relevancy of the sensor is thus characterized by the closeness to zero of the multiple coherence of its output with the remaining sensor outputs at some frequencies of interest . We choose a suitable statistic, approximate its distribution, and construct the generalized sequentially rejective Benferroni test. We have found in an experiment that the sensor position proposed by the engine manufacturer is not optimum . Experiments with a digital signal processor-based system emphasize the usefulness of this procedure . Through this procedure, we show that the performance of knock detectors strongly depends on the position of the sensor in use and can be improved significantly with moderate effort .Cette étude présente une approche permettant de déterminer les positions optimales de capteurs dans un groupe d'accéléromètres pour la détection du cliquetis dans un moteur à explosion. cette approche est moins complexe que les méthodes holographiques car nous utilisons uniquement le traitement du signal et des tests statistiques. La méthode proposée est basée sur la prédiction linéaire du signal à la sortie d'un capteur à partir des signaux obtenus aux sorties des autres capteurs du groupe. Ainsi, l'emplacement optimal d'un capteur est caractérisé par la proximité de zéro de la cohérence multiple aux fréquences intéressantes. Nous avons choisis une statistique appropriée, approximé sa loi de répartition et appliqué le test multiple à rejet séquentiel de Bonferron

The Effect of absorbing sites on the one-dimensional cellular automaton traffic flow with open boundaries

The effect of the absorbing sites with an absorbing rate $\beta_{0}$, in both one absorbing site (one way out) and two absorbing sites (two ways out) in a road, on the traffic flow phase transition is investigated using numerical simulations in the one-dimensional cellular automaton traffic flow model with open boundaries using parallel dynamics.In the case of one way out, there exist a critical position of the way out $i_{c1}$ below which the current is constant for $\beta_{0}$$<$$\beta_{0c2}$ and decreases when increasing $\beta_{0}$ for $\beta_{0}$$>$$\beta_{0c2}$. When the way out is located at a position greater than $i_{c2}$, the current increases with $\beta_{0}$ for $\beta_{0}$$<$$\beta_{0c1}$ and becomes constant for any value of $\beta_{0}$ greater than $\beta_{0c1}$. While, when the way out is located at any position between $i_{c1}$ and $i_{c2}$ ($i_{c1}$$<$$i_{c2}$), the current increases, for $\beta_{0}$$<$$\beta_{0c1}$, with $\beta_{0}$ and becomes constant for $\beta_{0c1}$$<$$\beta_{0}$$<$$\beta_{0c2}$ and decreases with $\beta_{0}$ for $\beta_{0}$$>$$\beta_{0c2}$. In the later case the density undergoes two successive first order transitions; from high density to maximal current phase at $\beta_{0}$$=$$\beta_{0c1}$ and from intermediate density to the low one at $\beta_{0}$$=$$\beta_{0c2}$. In the case of two ways out located respectively at the positions $i_{1}$ and $i_{2}$, the two successive transitions occur only when the distance $i_{2}$-$i_{1}$ separating the two ways is smaller than a critical distance $d_{c}$. Phase diagrams in the ($\alpha,\beta_{0}$), ($\beta,\beta_{0}$) and ($i_{1},\beta_{0}$) planes are established. It is found that the transitions between Free traffic, Congested traffic and maximal current phase are first order