FPGA implementation of biologically-inspired auto-associative memory

C. H. Ang; A. L. McEwan; A. van Schaik; C. Jin; P. H. W. Leong

doi:10.1049/el.2011.3651

FPGA implementation of biologically-inspired auto-associative memory

C. H. Ang, A. L. McEwan, A. van Schaik, C. Jin, P. H. W. Leong

MARCS Institute for Brain, Behaviour & Development

Research output: Contribution to journal › Article › peer-review

6 Citations (Scopus)

Abstract

The design of an auto-associative memory based on a spiking neural network is described. Delays rather than binary values are used to represent signals and coincidence is used to perform pattern matching. A complete implementation of the memory on a single FPGA is presented.

Original language	English
Pages (from-to)	148-149
Number of pages	2
Journal	Electronics Letters
Volume	48
Issue number	3
DOIs	https://doi.org/10.1049/el.2011.3651
Publication status	Published - 2012

Keywords

associative storage
field programmable gate arrays
neural networks (neurobiology)
pattern matching
spiking neural networks

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10.1049/el.2011.3651

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title = "FPGA implementation of biologically-inspired auto-associative memory",

abstract = "The design of an auto-associative memory based on a spiking neural network is described. Delays rather than binary values are used to represent signals and coincidence is used to perform pattern matching. A complete implementation of the memory on a single FPGA is presented.",

keywords = "associative storage, field programmable gate arrays, neural networks (neurobiology), pattern matching, spiking neural networks",

author = "Ang, {C. H.} and McEwan, {A. L.} and {van Schaik}, A. and C. Jin and Leong, {P. H. W.}",

year = "2012",

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T1 - FPGA implementation of biologically-inspired auto-associative memory

AU - Ang, C. H.

AU - McEwan, A. L.

AU - van Schaik, A.

AU - Jin, C.

AU - Leong, P. H. W.

PY - 2012

Y1 - 2012

N2 - The design of an auto-associative memory based on a spiking neural network is described. Delays rather than binary values are used to represent signals and coincidence is used to perform pattern matching. A complete implementation of the memory on a single FPGA is presented.

AB - The design of an auto-associative memory based on a spiking neural network is described. Delays rather than binary values are used to represent signals and coincidence is used to perform pattern matching. A complete implementation of the memory on a single FPGA is presented.

KW - associative storage

KW - field programmable gate arrays

KW - neural networks (neurobiology)

KW - pattern matching

KW - spiking neural networks

UR - http://handle.uws.edu.au:8081/1959.7/517853

U2 - 10.1049/el.2011.3651

DO - 10.1049/el.2011.3651

M3 - Article

SN - 0013-5194

VL - 48

SP - 148

EP - 149

JO - Electronics Letters

JF - Electronics Letters

IS - 3

ER -

FPGA implementation of biologically-inspired auto-associative memory

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Keywords

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