Please use this identifier to cite or link to this item:
|Type:||Artigo de evento|
|Title:||Immune-inspired Dynamic Optimization For Blind Spatial Equalization In Undermodeled Channels|
De Franca F.O.
De Castro L.N.
Von Zuben F.J.
|Abstract:||In this work, we propose an evolutionary-like approach to the problem of blind adaptive spatial filtering that is based on the decision-directed criterion and on the doptaiNet, an artificial immune network conceived to perform multimodal search in dynamic environments. The proposal was tested under static and time-varying undermodeled channel models, and, in all cases, its ability to find and track a solution close to the Wiener global optimum was attested. The obtained results reveal that the dopt-aiNet may decisively enhance the performance of adaptive arrays in scenarios built from elements that are representative of some aspects of real-world communication systems. © 2006 IEEE.|
|Appears in Collections:||Unicamp - Artigos e Outros Documentos|
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.