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.
Four Level Haar Transform Architecture for Feature Extraction
2015-11-01
1066433 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Joint-transform correlator architecture for wavelet feature extraction [3075-15]
British Library Conference Proceedings | 1997
|Feature extraction by best anisotropic Haar bases in an OCR system [5298-65]
British Library Conference Proceedings | 2004
|Facial expression recognition based on Haar-like feature detection
British Library Online Contents | 2008
|