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@inproceedings{Faliagkas:2015,
author = {Faliagkas, K and Leene, L and Constandinou, TG},
pages = {3000--3003},
publisher = {IEEE},
title = {A Novel Neural Recording System Utilising Continuous Time Energy Based Compression},
year = {2015}
}

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TY  - CPAPER
AB  - This work presents a new data compression methodthat uses an energy operator to exploit the correlated energy inneural recording features in order to achieve adaptive sampling.This approach enhances conventional data converter topologieswith the power saving of asynchronous systems while maintaininglow complexity & high efficiency. The proposed scheme enablesthe transmission of 0:7kS/s, while preserving the features of thesignal with an accuracy of 95%. It is also shown that the operationof the system is not susceptible to noise, even for signals with 1dBSNR. The whole system consumes 3:94mWwith an estimated areaof 0:093mm2.
AU  - Faliagkas,K
AU  - Leene,L
AU  - Constandinou,TG
EP  - 3003
PB  - IEEE
PY  - 2015///
SP  - 3000
TI  - A Novel Neural Recording System Utilising Continuous Time Energy Based Compression
ER  -

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