Four Level Wavelet Haar Transform Architecture for Feature Extraction
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abstract
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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%25 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. © 2015 IEEE.
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discrete haar wavelet transform; DWT Haar; dynamic power; Efficient architecture; feature extraction; Signal processing; spike sorting Architecture; Automotive engineering; Extraction; Feature extraction; Neurology; Signal processing; Discrete haar wavelet transforms; DWT Haar; Dynamic Power; Efficient architecture; Spike-sorting; Wavelet transforms
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