Area efficient DA based Fir filter for EEG Classification

Abstract

Due to the recent development of digital signal processing algorithms and very large-scale integrated circuit technologies, the initial implementation obstacles of the orthogonal frequency division multiplexing (OFDM) no longer exist. Therefore, OFDM has been adopted in several digital communication systems such as digital audio broadcasting, terrestrial digital television and HDTV broadcasting. Moreover, various projects and prototypes of OFDM systems are widely used, including digital video broadcasting for digital terrestrial television (DVB-T) by the European Broadcasting Union, WLAN, and WiMAX, etc. This work presents a new technique for blind and joint estimation of symbol timing and carrier frequency offset in wireless orthogonal frequency division multiplexing (OFDM) systems. The joint estimation is achieved by sensing the interference introduced at the fast Fourier transform (FFT) output when a carrier frequency or timing offsets exist. The synchronization parameters are selected such that the interference is minimized. The proposed joint estimator is highly efficient because it does not require any overhead or channel state information. Simulation results show that the system is effective and robust even at low signal-to-noise ratios.

Authors and Affiliations

P. Dharsana

Keywords

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  • EP ID EP22192
  • DOI -
  • Views 251
  • Downloads 4

How To Cite

P. Dharsana (2016). Area efficient DA based Fir filter for EEG Classification. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 4(5), -. https://europub.co.uk/articles/-A-22192