Biomedical Electronic Devices have been developed as aid in some neurological conditions like epilepsy and Parkinson. Those devices require low-power systems in order to guarantee portability and continuous operation from weeks to years. Therefore, the present work proposes a simplified architecture for Haar Wavelet Transform used as feature extraction in the spike sorting process. The architecture achieves a reduction of 46% on the number of multipliers needed in a direct architecture. As result of the reduction onmultiplication, the rounding off error in the proposed architecture is also reduced achieving zero error in spike sorting classification.


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    Titel :

    Four Level Haar Transform Architecture for Feature Extraction




    Erscheinungsdatum :

    2015-11-01


    Format / Umfang :

    1066433 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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