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GIUSEPPE COSTANTINO GIACONIA

Efficient FPGA Implementation of an Adaptive Noise Canceller

  • Authors: DI STEFANO, A; SCAGLIONE, A; GIACONIA, C
  • Publication year: 2005
  • Type: eedings
  • Key words: Electroencephalography ; Bioelectric potentials ; Evoked Potentials
  • OA Link: http://hdl.handle.net/10447/18294

Abstract

A hardware implementation of an adaptive noise canceller (ANC) is presented. It has been synthesized within an FPGA, using a modified version of the least mean square (LMS) error algorithm. The results obtained so far show a significant decrease of the required gate count when compared with a standard LMS implementation, while increasing the ANC bandwidth and signal to noise (S/N) ratio. This novel adaptive noise canceller is then useful for enhancing the S/N ratio of data collected from sensors (or sensor arrays) working in noisy environment, or dealing with potentially weak signals.