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- W2158603902 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 dopt-aiNet, 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." @default.
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- W2158603902 date "2006-09-22" @default.
- W2158603902 modified "2023-10-06" @default.
- W2158603902 title "Immune-inspired Dynamic Optimization for Blind Spatial Equalization in Undermodeled Channels" @default.
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- W2158603902 doi "https://doi.org/10.1109/cec.2006.1688673" @default.
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