000150307 001__ 150307
000150307 005__ 20251017144549.0
000150307 0247_ $$2doi$$a10.1016/j.dsp.2014.09.004
000150307 0248_ $$2sideral$$a102736
000150307 037__ $$aART-2015-102736
000150307 041__ $$aeng
000150307 100__ $$0(orcid)0000-0001-5175-3166$$aFernandez-Bes, Jesus
000150307 245__ $$aDistributed estimation in diffusion networks using affine least-squares combiners
000150307 260__ $$c2015
000150307 5060_ $$aAccess copy available to the general public$$fUnrestricted
000150307 5203_ $$aWe propose a diffusion scheme for adaptive networks, where each node obtains an estimate of a common unknown parameter vector by combining a local estimate with the combined estimates received from neighboring nodes. The combination weights are adapted in order to minimize the mean-square error of the network employing a local least-squares (LS) cost function. This adaptive diffusion network with LS combiners (ADN-LS) is analyzed, deriving expressions for its network mean-square deviation that characterize the convergence and steady-state performance of the algorithm. Experiments carried out in stationary and tracking scenarios show that our proposal outperforms a state-of-art scheme for adapting the weights of diffusion networks (ACW algorithm from [10]), both during convergence and in tracking situations. Despite its good convergence behavior, our proposal may present a slightly worse steady-state performance in stationary or slowly-changing scenarios with respect to ACW due to the error inherent to the least-squares adaptation with sliding window. Therefore, to take advantage of these different behaviors, we also propose a hybrid scheme based on a convex combination of the ADN-LS and ACW algorithms.
000150307 540__ $$9info:eu-repo/semantics/openAccess$$aAll rights reserved$$uhttp://www.europeana.eu/rights/rr-f/
000150307 590__ $$a1.444$$b2015
000150307 591__ $$aENGINEERING, ELECTRICAL & ELECTRONIC$$b112 / 255 = 0.439$$c2015$$dQ2$$eT2
000150307 592__ $$a0.566$$b2015
000150307 593__ $$aSignal Processing$$c2015$$dQ2
000150307 593__ $$aElectrical and Electronic Engineering$$c2015$$dQ2
000150307 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion
000150307 700__ $$aAzpicueta-Ruiz, Luis A.
000150307 700__ $$aArenas-García, Jerónimo
000150307 700__ $$aSilva, Magno T.M.
000150307 773__ $$g36 (2015), 1-14$$pDigit. signal process.$$tDIGITAL SIGNAL PROCESSING$$x1051-2004
000150307 8564_ $$s1092234$$uhttps://zaguan.unizar.es/record/150307/files/texto_completo.pdf$$yPostprint
000150307 8564_ $$s1566859$$uhttps://zaguan.unizar.es/record/150307/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint
000150307 909CO $$ooai:zaguan.unizar.es:150307$$particulos$$pdriver
000150307 951__ $$a2025-10-17-14:11:02
000150307 980__ $$aARTICLE