Projects per year
Abstract
This paper proposes a bio-processor for neural signal analysis. The
device architecture features an analogue Front-End and a Process
Element, the latter can be scaled as an array. Rather than a single
dedicated algorithm, the Process Element supports multiple analysis
modes, utilising the analogue behaviour of memristors. When used as part
of an array structure, each Process Element can be programmed
independently and furthermore, the array elements can be electrically
interconnected in an arbitrary manner. The device facilitates an
inter-network of in-memory computation units, i.e. an inter-network of
functions. This supports construction of a system that is highly
scalable, re-configurable and thus adaptive. The device enables
multi-functional neural recording and processing, for early stage signal
exploration. The device has been implemented using a standard 180nm
CMOS process with the addition of back-end-of-line (BEOL) memristor
deposition.
1
Although targeted at neural signal analysis, the device and the
architecture described is considered general purpose and may find
application within other disciplines.
Original language | English |
---|---|
Title of host publication | 2023 IEEE Biomedical Circuits and Systems Conference (BioCAS) |
Publisher | Institute of Electrical and Electronics Engineers |
DOIs | |
Publication status | E-pub ahead of print - 18 Jan 2024 |
Event | Artificial Intelligence BioMedical Circuits And Systems For Health - Westin Harbour Castle Hotel, Toronto, Canada Duration: 19 Oct 2023 → 21 Oct 2023 https://2023.ieee-biocas.org/ |
Publication series
Name | IEEE Biomedical Circuits and Systems (BIOCAS) |
---|---|
Publisher | IEEE |
ISSN (Print) | 2163-4025 |
ISSN (Electronic) | 2766-4465 |
Conference
Conference | Artificial Intelligence BioMedical Circuits And Systems For Health |
---|---|
Abbreviated title | BIOCAS 2023 |
Country/Territory | Canada |
City | Toronto |
Period | 19/10/23 → 21/10/23 |
Internet address |
Fingerprint
Dive into the research topics of 'An Integrated CMOS/Memristor Bio-Processor for Re-Configurable Neural Signal Processing'. Together they form a unique fingerprint.-
AI MeTLLE: Memristive Technologies for Lifelong Learning Embedded AI Hardware (AI MeTLLE)
Prodromakis, T. (Principal Investigator)
1/05/22 → 31/12/29
Project: Research
-
FORTE: Functional Oxide Reconfigurable Technologies (FORTE): A Programme Grant
Koch, D. (Principal Investigator), Prodromakis, T. (Principal Investigator), Constandinou, T. G. (Co-investigator), Dudek, P. (Co-investigator) & Papavassiliou, C. (Co-investigator)
Engineering and Physical Sciences Research Council
1/05/22 → 30/03/25
Project: Research