Citation

BibTex format

@inbook{Shepherd:2014:10.1007/978-1-4471-6374-9_7,
author = {Shepherd, LM and Constandinou, TG and Toumazou, C},
booktitle = {Body Sensor Networks},
doi = {10.1007/978-1-4471-6374-9_7},
pages = {273--299},
publisher = {Springer London},
title = {Towards ultra-low power bio-inspired processing},
url = {http://dx.doi.org/10.1007/978-1-4471-6374-9_7},
year = {2014}
}

RIS format (EndNote, RefMan)

TY  - CHAP
AB - The natural world is analogue and yet the modern microelectronic world with which we interact represents real world data using discrete quantities manipulated by logic. In the human space, we are entering a new wave of body-worn biosensor technology for medical diagnostics and therapy. This new trend is beginning to see the processing interface move back to using continuous quantities, which are more or less in line with the biological processes. We label this computational paradigm “bio-inspired” because of the ability of silicon chip technology which enables the use of inherent device physics, allowing us to approach the computational efficiencies of biology. From a conceptual viewpoint, this has led to a number of more specific morphologies including neuromorphic and retinomorphic processing. These have led scientists to model biological systems such as the cochlea and retina and gain not only superior computational resource efficiency (to conventional hearing aid or camera technology), but also an increased understanding of biological and neurological processes.
AU - Shepherd,LM
AU - Constandinou,TG
AU - Toumazou,C
DO - 10.1007/978-1-4471-6374-9_7
EP - 299
PB - Springer London
PY - 2014///
SN - 9781447163732
SP - 273
TI - Towards ultra-low power bio-inspired processing
T1 - Body Sensor Networks
UR - http://dx.doi.org/10.1007/978-1-4471-6374-9_7
UR - http://link.springer.com/chapter/10.1007/978-1-4471-6374-9_7
ER -