Search results for "Signal Processing"
showing 10 items of 2451 documents
Corrigendum to three papers that deal with “Anti”-Bayesian Pattern Recognition [Pattern Recognition]
2014
In the papers 1 (Thomas and Oommen, 2013), 2 (Oommen and Thomas, 2014) and 3 (Thomas and Oommen, 2013), and their associated conference versions cited in those papers, we had introduced a new method of so-called "Anti"-Bayesian Pattern Recognition (PR) which achieved the classification using only a few (sometimes as few as two) points distant from the mean. While the PR strategy, in and of itself, is accurate, the claim that it was based on the Order Statistics (OS) of the distributions of the features is not. The PR and classification results are rather founded on the symmetric quantiles and not on the symmetric OSs. This brief paper corrects the flawed claim presented in those papers. Hig…
Multi-layer intrusion detection system with ExtraTrees feature selection, extreme learning machine ensemble, and softmax aggregation
2019
Abstract Recent advances in intrusion detection systems based on machine learning have indeed outperformed other techniques, but struggle with detecting multiple classes of attacks with high accuracy. We propose a method that works in three stages. First, the ExtraTrees classifier is used to select relevant features for each type of attack individually for each (ELM). Then, an ensemble of ELMs is used to detect each type of attack separately. Finally, the results of all ELMs are combined using a softmax layer to refine the results and increase the accuracy further. The intuition behind our system is that multi-class classification is quite difficult compared to binary classification. So, we…
Application of optimized artificial intelligence algorithm to evaluate the heating energy demand of non-residential buildings at European level
2019
Abstract A reliable preliminary forecast of heating energy demand of a building by using a detailed dynamic simulation software typically requires an in-depth knowledge of the thermal balance, several input data and a very skilled user. The authors will describe how to use Artificial Neural Networks to predict the demand for thermal energy linked to the winter climatization of non-residential buildings. To train the neural network it was necessary to develop an accurate energy database that represents the basis of the training of a specific Artificial Neural Networks. Data came from detailed dynamic simulations performed in the TRNSYS environment. The models were built according to the stan…
A COMPARATIVE STUDY OF PHENOMENOLOGICAL MODELS OF MR BRAKE BASED ON NEURAL NETWORKS APPROACH
2013
In this paper a full-scale commercially available magnetorheological (MR) brake installed in a semi-active suspension (SAS) system is modeled and simulated. Two well-known phenomenological hysteresis models are explored: Bouc–Wen and Dahl ones. In particular, influence of their parameters on the response is evaluated and assessed. The next step is to introduce the artificial neural networks and discuss their application in the field of systems identification. Subsequently, two feedforward neural networks are created and trained to estimate parameters characterizing each of the MR damper models described. The semi-active suspension (SAS) system equipped with a MR brake is described and the …
Connectionist models of face processing: A survey
1994
Abstract Connectionist models of face recognition, identification, and categorization have appeared recently in several disciplines, including psychology, computer science, and engineering. We present a review of these models with the goal of complementing a recent survey by Samal and Iyengar [Pattern Recognition25, 65–77 (1992)] of nonconnectionist approaches to the problem of the automatic face recognition. We concentrate on models that use linear autoassociative networks, nonlinear autoassociative (or compression) and/or heteroassociative backpropagation networks. One advantage of these models over some nonconnectionist approaches is that analyzable features emerge naturally from image-b…
Measurement of the atmospheric ?µ energy spectrum from 100 GeV to 200 TeV with the ANTARES telescope
2013
Atmospheric neutrinos are produced during cascades initiated by the interaction of primary cosmic rays with air nuclei. In this paper, a measurement of the atmospheric energy spectrum in the energy range 0.1-200 TeV is presented, using data collected by the ANTARES underwater neutrino telescope from 2008 to 2011. Overall, the measured flux is similar to 25 % higher than predicted by the conventional neutrino flux, and compatible with the measurements reported in ice. The flux is compatible with a single power-law dependence with spectral index gamma (meas)=3.58 +/- 0.12. With the present statistics the contribution of prompt neutrinos cannot be established.
Reconstruction of inclined air showers detected with the Pierre Auger Observatory
2014
We describe the method devised to reconstruct inclined cosmic-ray air showers with zenith angles greater than $60^\circ$ detected with the surface array of the Pierre Auger Observatory. The measured signals at the ground level are fitted to muon density distributions predicted with atmospheric cascade models to obtain the relative shower size as an overall normalization parameter. The method is evaluated using simulated showers to test its performance. The energy of the cosmic rays is calibrated using a sub-sample of events reconstructed with both the fluorescence and surface array techniques. The reconstruction method described here provides the basis of complementary analyses including an…
Are fast radio bursts the most likely electromagnetic counterpart of neutron star mergers resulting in prompt collapse?
2018
Inspiraling and merging binary neutron stars (BNSs) are important sources of both gravitational waves and coincident electromagnetic counterparts. If the BNS total mass is larger than a threshold value, a black hole ensues promptly after merger. Through a statistical study in conjunction with recent LIGO/Virgo constraints on the nuclear equation of state, we estimate that up to $\sim 25\%$ of BNS mergers may result in prompt collapse. Moreover, we find that most models of the BNS mass function we study here predict that the majority of prompt-collapse BNS mergers have $q\gtrsim 0.8$. Prompt-collapse BNS mergers with mass ratio $q \gtrsim 0.8$ may not be accompanied by detectable kilonovae o…
Ultrahigh energy neutrinos in the Mediterranean: Detecting ντ and νμ with a km3 telescope
2007
23 pages, 13 figures.-- PACS nrs.: 95.85.Ry, 95.55.Vj, 13.15.+g.-- ISI Article Identifier: 000245928000025.-- ArXiv pre-print available at: http://arxiv.org/abs/astro-ph/0609241
Multiple expansions for energy and momenta carried by gravitational waves
2007
We present expressions for the energy, linear momentum and angular momentum carried away from an isolated system by gravitational radiation based on spin-weighted spherical harmonics decomposition of the Weyl scalar $\Psi_4$. We also show that the expressions derived are equivalent to the common expressions obtained when using a framework based on perturbations of a Schwazschild background. The main idea is to collect together all the different expressions in a uniform and consistent way. The formulae presented here are directly applicable to the calculation of the radiated energy, linear momentum and angular momentum starting from the gravitational waveforms which are typically extracted f…