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@inproceedings{Leene:2018:10.1109/BIOCAS.2018.8584787,
author = {Leene, L and Constandinou, TG},
doi = {10.1109/BIOCAS.2018.8584787},
pages = {77--80},
publisher = {IEEE},
title = {Direct digital wavelet synthesis for embedded biomedical microsystems},
url = {http://dx.doi.org/10.1109/BIOCAS.2018.8584787},
year = {2018}
}

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TY  - CPAPER
AB  - This paper presents a compact direct digital waveletsynthesizer for extracting phase and amplitude data from corticalrecordings   using   a   feed-forward   recurrent   digital   oscillator.These measurements are essential for accurately decoding local-field-potentials  in  selected  frequency  bands.  Current  systemsextensively   to   rely   large   digital   cores   to   efficiently   performFourier  or  wavelet  transforms  which  is  not  viable  for  manyimplants. The proposed system dynamically controls oscillation togenerate frequency selective quadrature wavelets instead of usingmemory  intensive  sinusoid/cordic  look-up-tables  while  retainingrobust digital operation. A MachXO3LF Lattice FPGA is used topresent the results for a 16 bit implementation. This configurationrequires  401  registers  combined  with  283  logic  elements  andalso accommodates real-time reconfigurability to allow ultra-low-power  sensors  to  perform  spectroscopy  with  high-fidelity.
AU  - Leene,L
AU  - Constandinou,TG
DO  - 10.1109/BIOCAS.2018.8584787
EP  - 80
PB  - IEEE
PY  - 2018///
SP  - 77
TI  - Direct digital wavelet synthesis for embedded biomedical microsystems
UR  - http://dx.doi.org/10.1109/BIOCAS.2018.8584787
UR  - https://ieeexplore.ieee.org/abstract/document/8584787
UR  - http://hdl.handle.net/10044/1/63458
ER  -

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