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A numerical procedure for filtering and efficient high-order signal differentiation

Salim Ibrir, Sette Diop (2004)

International Journal of Applied Mathematics and Computer Science

In this paper, we propose a numerical algorithm for filtering and robust signal differentiation. The numerical procedure is based on the solution of a simplified linear optimization problem. A compromise between smoothing and fidelity with respect to the measurable data is achieved by the computation of an optimal regularization parameter that minimizes the Generalized Cross Validation criterion (GCV). Simulation results are given to highlight the effectiveness of the proposed procedure.

Adaptive tests for periodic signal detection with applications to laser vibrometry

Magalie Fromont, Céline Lévy-leduc (2006)

ESAIM: Probability and Statistics

Initially motivated by a practical issue in target detection via laser vibrometry, we are interested in the problem of periodic signal detection in a Gaussian fixed design regression framework. Assuming that the signal belongs to some periodic Sobolev ball and that the variance of the noise is known, we first consider the problem from a minimax point of view: we evaluate the so-called minimax separation rate which corresponds to the minimal l2-distance between the signal and zero so that the detection...

Application of the random field theory in PET imaging - injection dose optimization

Jiří Dvořák, Jiří Boldyš, Magdaléna Skopalová, Otakar Bělohlávek (2013)


This work presents new application of the random field theory in medical imaging. Results from both integral geometry and random field theory can be used to detect locations with significantly increased radiotracer uptake in images from positron emission tomography (PET). The assumptions needed to use these results are verified on a set of real and simulated phantom images. The proposed method of detecting activation (locations with increased radiotracer concentration) is used to quantify the quality...

Classification Trees as a Technique for Creating Anomaly-Based Intrusion Detection Systems

Jecheva, Veselina, Nikolova, Evgeniya (2009)

Serdica Journal of Computing

Intrusion detection is a critical component of security information systems. The intrusion detection process attempts to detect malicious attacks by examining various data collected during processes on the protected system. This paper examines the anomaly-based intrusion detection based on sequences of system calls. The point is to construct a model that describes normal or acceptable system activity using the classification trees approach. The created database is utilized as a basis for distinguishing...

Consensus and trajectory tracking of SISO linear multi-agent systems under switching communication topologies and formation changes

Carlos López-Limón, Javier Ruiz, Alejandro Cervantes-Herrera, Antonio Ramírez-Treviño (2013)


The simultaneous problem of consensus and trajectory tracking of linear multi-agent systems is considered in this paper, where the dynamics of each agent is represented by a single-input single-output linear system. In order to solve this problem, a distributed control strategy is proposed in this work, where the trajectory and the formation of the agents are achieved asymptotically even in the presence of switching communication topologies and smooth formation changes, and ensuring the closed-loop...

Detection of influential points by convex hull volume minimization

Petr Tichavský, Pavel Boček (1998)


A method of geometrical characterization of multidimensional data sets, including construction of the convex hull of the data and calculation of the volume of the convex hull, is described. This technique, together with the concept of minimum convex hull volume, can be used for detection of influential points or outliers in multiple linear regression. An approximation to the true concept is achieved by ordering the data into a linear sequence such that the volume of the convex hull of the first...

Gravitational waves from coalescing binaries: a hierarchical signal detection strategy

S. Mohanty, S. Dhurandhar (1997)

Banach Center Publications

The detection of gravitational waves from coalescing compact binaries would be a computationally intensive process if a single bank of template waveforms (i.e., a one step search) is used. We present, in this paper, an alternative method which is a hierarchical search strategy involving two template banks. We show that the computational power required by such a two step search, for an on-line detection of the one parameter family of Newtonian signals, is 1/8 of that required when an on-line one...

Inverse problem for networks of laser interferometers

Piotr Jaranowski (1997)

Banach Center Publications

Estimation of the parameters of the gravitational-wave signal from a coalescing binary by a network of laser interferometers is considered. A generalization of the solution of the inverse problem found previously for the network of 3 detectors to the network of N detectors is given. Maximum likelihood and least squares estimators are applied to obtain the solution. Accuracy of the estimation of the parameters is assessed from the inverse of the Fisher information matrix. The results of the Monte...

Wavelet transform and binary coalescence detection

Jean-Michel Innocent, Bruno Torrésani (1997)

Banach Center Publications

We give a short account of some time-frequency methods which are relevant in the context of gravity waves detection. We focus on the case of wavelet analysis which we believe is particularly appropriate. We show how wavelet transforms can lead to efficient algorithms for detection and parameter estimation of binary coalescence signals. In addition, we give in an appendix some of the ingredients needed for the construction of discrete wavelet decompositions and corresponding fast algorithms.

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