4,446 research outputs found
Sparse Distributed Learning Based on Diffusion Adaptation
No full textThis article proposes diffusion LMS strategies for distributed estimation over adaptive networks that are able to exploit sparsity in the underlying system model. The approach relies on convex regularization, common in compressive sensing, to enhance the detection of sparsity via a diffusive process over the network. The resulting algorithms endow networks with learning abilities and allow them to learn the sparse structure from the incoming data in real-time, and also to track variations in the sparsity of the model. We provide convergence and mean-square performance analysis of the proposed method and show under what conditions it outperforms the unregularized diffusion version. We also show how to adaptively select the regularization parameter. Simulation results illustrate the advantage of the proposed filters for sparse data recovery.AS
Sparse distributed learning based on diffusion adaptation
No full textThis article proposes diffusion LMS strategies for distributed estimation over adaptive networks that are able to exploit sparsity in the underlying system model. The approach relies on convex regularization, common in compressive sensing, to enhance the detection of sparsity via a diffusive process over the network. The resulting algorithms endow networks with learning abilities and allow them to learn the sparse structure from the incoming data in real-time, and also to track variations in the sparsity of the model. We provide convergence and mean-square performance analysis of the proposed method and show under what conditions it outperforms the unregularized diffusion version. We also show how to adaptively select the regularization parameter. Simulation results illustrate the advantage of the proposed filters for sparse data recovery
2° Maison de 'Ali pacha Bourhâm
No full textSayyed Ahmad el-, Farnall Harry, Bahgat Ali, Simaïka Marcus H., Sayed Metoualli. 2° Maison de 'Ali pacha Bourhâm. In: Comité de Conservation des Monuments de l'Art Arabe. Fascicule 33, exercice 1920-1924, 1928. pp. 299-300
Decentralized resource assignment in cognitive networks based on swarming mechanisms over random graphs
No full textThis paper proposes a distributed resource assignment strategy for cognitive networks mimicking a swarm foraging mechanism, assuming that the communication among the cognitive nodes is impaired by random link failures and quantization noise. Using results from stochastic approximation theory, we propose a swarm mechanism that converges almost surely to a final allocation even in the presence of imperfect communication scenarios. The theoretical findings are corroborated by numerical results showing that the only effect of the random link failures is to decrease the convergence rate of the algorithm. We propose then a fast swarming approach, robust to random disturbances, that adapts its behavior with respect to the interference power perceived by every node, thus increasing the speed of convergence and improving the resource allocation capabilities
1° Mosquée d'Abou Ali
No full textSimaïka Marcus H., Greg Robert Hyde, Lacau Pierre, Ahmad Ali Hasan, Sayed Metoualli, 'Amrusi Ahmad Fahmi al-, Sayyed Ahmad el-, Pauty Edmond. 1° Mosquée d'Abou Ali. In: Comité de Conservation des Monuments de l'Art Arabe. Fascicule 36, exercice 1930-1932, 1936. pp. 89-90
Sparse diffusion LMS for distributed adaptive estimation
No full textThe goal of this paper is to propose diffusion LMS techniques for distributed estimation over adaptive networks, which are able to exploit sparsity in the underlying system model. The approach relies on convex regularization, common in compressive sensing, to improve the performance of the diffusion strategies. We provide convergence and performance analysis of the proposed method, showing under what conditions it outperforms the unregularized diffusion version. Simulation results illustrate the advantage of the proposed filter under the sparsity assumption on the true coefficient vector. © 2012 IEEE
Exact asymptotics of distributed detection over adaptive networks
No full textIn [1], an important step toward the characterization of distributed detection over adaptive networks has been made by establishing the fundamental scaling law of the error probabilities. However, empirical evidence reported in [1] revealed that a refined asymptotic analysis is necessary in order to capture the exact impact of network connectivity on the detection performance of each individual agent. Here we address this open issue by exploiting the framework of exact asymptotics
A bio-inspired fast swarming algorithm for dynamic radio access
No full textThe goal of this paper is to propose a bio-inspired algorithm for decentralized dynamic access in cognitive radio systems. We study an improved social foraging swarm model that lets every node allocate its resources (power/bits) in the frequency regions where the interference is minimum while avoiding collisions with other nodes. The proposed approach adapts its behavior with respect to the interference power perceived by every node, thus increasing the speed of convergence and reducing the reaction time needed by the algorithm to react to dynamic changes in the environment. The presence of random disturbances such as link failures, quantization noise and estimation errors is taken into account in the convergence analysis. Numerical results illustrate the performance of the proposed algorithm. © 2011 IEEE
a) Mosquée de Mohammad 'Ali pacha
No full textSimaïka Marcus H., Greg Robert Hyde, Lacau Pierre, Ahmad Ali Hasan, Sayed Metoualli, 'Amrusi Ahmad Fahmi al-, Sayyed Ahmad el-, Pauty Edmond. a) Mosquée de Mohammad 'Ali pacha. In: Comité de Conservation des Monuments de l'Art Arabe. Fascicule 36, exercice 1930-1932, 1936. pp. 92-94
Syriac-Arabic Glosses of Isho bar Ali. Volume 1
No full textThese two volumes constitute the second part (nun-taw) of the Syriac-Arabic dictionary of the 10th cent. physician Isho bar Ali (the first half of the dictionary had been published in 1874 by G. Hoffmann). Each Syriac word is defined in Arabic, often with more than one Arabic equivalent; in addition, the author deals not just with individual Syriac words, but in some cases with phrases. Gottheil used 21 manuscripts (from Oxford, London, Paris, Berlin, Leiden, and Rome) for this edition, and he has supplied a thorough critical apparatus; the manuscripts are described in the introduction. While some manuscripts give the Arabic glosses in Syriac characters (i.e. Garshuni), Gottheil has presented them here in Arabic script. These two volumes will be of great interest to Syriac lexicographers and those who study interactions between Syriac and Arabic.Contains an English introduction by Richard J.H. Gotthei
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