An efficient mapping of fuzzy ART onto a neural architecture

Matthias Blume; Sadik C. Esener

doi:10.1016/S0893-6080(96)00085-8

An efficient mapping of fuzzy ART onto a neural architecture

Matthias Blume
, Sadik C. Esener

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

14 Scopus citations

Abstract

A novel mapping of the Fuzzy ART algorithm onto a neural network architecture is described. The architecture does not utilize bi-directional synapses, weight transport, or weight duplication, and requires one fewer layer of processing elements than the architecture originally proposed by Carpenter et al. (1991a). In the new architecture, execution of the algorithm takes a constant time per input vector regardless of the relationship between the input and existing templates, and several control signals are eliminated. This mapping facilitates hardware implementation of Fuzzy ART and furthermore serves as a tool for envisioning and understanding the algorithm.

Original language	English (US)
Pages (from-to)	409-411
Number of pages	3
Journal	Neural Networks
Volume	10
Issue number	3
DOIs	https://doi.org/10.1016/S0893-6080(96)00085-8
State	Published - Apr 1997
Externally published	Yes

Funding

This research was supported by the Advanced Research Projects Agency (ARPA F49620-92-J-0520).

Funders	Funder number
Advanced Research Projects Agency	F49620-92-J-0520

Keywords

fuzzy ART
fuzzy ARTMAP
neural architecture
parallel hardware

ASJC Scopus subject areas

Cognitive Neuroscience
Artificial Intelligence

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10.1016/S0893-6080(96)00085-8

Cite this

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title = "An efficient mapping of fuzzy ART onto a neural architecture",

abstract = "A novel mapping of the Fuzzy ART algorithm onto a neural network architecture is described. The architecture does not utilize bi-directional synapses, weight transport, or weight duplication, and requires one fewer layer of processing elements than the architecture originally proposed by Carpenter et al. (1991a). In the new architecture, execution of the algorithm takes a constant time per input vector regardless of the relationship between the input and existing templates, and several control signals are eliminated. This mapping facilitates hardware implementation of Fuzzy ART and furthermore serves as a tool for envisioning and understanding the algorithm.",

keywords = "fuzzy ART, fuzzy ARTMAP, neural architecture, parallel hardware",

author = "Matthias Blume and Esener, \{Sadik C.\}",

note = "Funding Information: This research was supported by the Advanced Research Projects Agency (ARPA F49620-92-J-0520).",

year = "1997",

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doi = "10.1016/S0893-6080(96)00085-8",

language = "English (US)",

volume = "10",

pages = "409--411",

journal = "Neural Networks",

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AU - Blume, Matthias

AU - Esener, Sadik C.

N1 - Funding Information: This research was supported by the Advanced Research Projects Agency (ARPA F49620-92-J-0520).

PY - 1997/4

Y1 - 1997/4

N2 - A novel mapping of the Fuzzy ART algorithm onto a neural network architecture is described. The architecture does not utilize bi-directional synapses, weight transport, or weight duplication, and requires one fewer layer of processing elements than the architecture originally proposed by Carpenter et al. (1991a). In the new architecture, execution of the algorithm takes a constant time per input vector regardless of the relationship between the input and existing templates, and several control signals are eliminated. This mapping facilitates hardware implementation of Fuzzy ART and furthermore serves as a tool for envisioning and understanding the algorithm.

AB - A novel mapping of the Fuzzy ART algorithm onto a neural network architecture is described. The architecture does not utilize bi-directional synapses, weight transport, or weight duplication, and requires one fewer layer of processing elements than the architecture originally proposed by Carpenter et al. (1991a). In the new architecture, execution of the algorithm takes a constant time per input vector regardless of the relationship between the input and existing templates, and several control signals are eliminated. This mapping facilitates hardware implementation of Fuzzy ART and furthermore serves as a tool for envisioning and understanding the algorithm.

KW - fuzzy ART

KW - fuzzy ARTMAP

KW - neural architecture

KW - parallel hardware

UR - https://www.scopus.com/pages/publications/0031127318

UR - https://www.scopus.com/pages/publications/0031127318#tab=citedBy

U2 - 10.1016/S0893-6080(96)00085-8

DO - 10.1016/S0893-6080(96)00085-8

M3 - Article

AN - SCOPUS:0031127318

SN - 0893-6080

VL - 10

SP - 409

EP - 411

JO - Neural Networks

JF - Neural Networks

IS - 3

ER -

An efficient mapping of fuzzy ART onto a neural architecture

Abstract

Funding

Keywords

ASJC Scopus subject areas

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