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Powerline communication systems are nowadays suffering from a very hostile environment, and impulsive chaotic noise is one of the major concerns, and in general every noise with an amplitude higher than the received signal. In this paper, we offer an efficient general system architecture to cancel a great variety of powerline noises. Using a fuzzy inference network, the noise is modeled during a training period, and evaluated during the reception of data. Through periodic training, the systems adapts to the changes of the noise characteristics. We have evaluated the computational cost of the algorithm and compared its time cost for several different implementations, obtaining satisfactory results.
Date of Conference: 6-8 April 2005