VLSI neural network architectures

R. Sridhar; Yong Chul Shin

doi:10.1109/ASIC.1993.410845

VLSI neural network architectures

R. Sridhar
, Yong Chul Shin

Department of Computer Science and Engineering

SUNY Buffalo

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

VLSI architectures for neural networks are presented. Neural networks have wide-ranging applications in classification, control, and optimization. With the need for real-time performance, VLSI neural networks have gained significant attention. Digital, analog, and mixed-mode designs are used for this application. Modular and reconfigurable designs are necessary so that various neural network models can be easily configured.

Original language	English
Title of host publication	Proceedings - 6th Annual IEEE International ASIC Conference and Exhibit, ASIC 1993
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	560-569
Number of pages	10
ISBN (Electronic)	0780313755, 9780780313750
DOIs	https://doi.org/10.1109/ASIC.1993.410845
State	Published - 1993
Event	6th Annual IEEE International ASIC Conference and Exhibit, ASIC 1993 - Rochester, United States Duration: Sep 27 1993 → Oct 1 1993

Publication series

Name	Proceedings - 6th Annual IEEE International ASIC Conference and Exhibit, ASIC 1993

Conference

Conference	6th Annual IEEE International ASIC Conference and Exhibit, ASIC 1993
Country/Territory	United States
City	Rochester
Period	09/27/93 → 10/1/93

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10.1109/ASIC.1993.410845

Cite this

@inproceedings{9e9116dbed334d88aa0daa615fcd1c1c,

title = "VLSI neural network architectures",

abstract = "VLSI architectures for neural networks are presented. Neural networks have wide-ranging applications in classification, control, and optimization. With the need for real-time performance, VLSI neural networks have gained significant attention. Digital, analog, and mixed-mode designs are used for this application. Modular and reconfigurable designs are necessary so that various neural network models can be easily configured.",

author = "R. Sridhar and Shin, \{Yong Chul\}",

note = "Publisher Copyright: {\textcopyright} 1993 IEEE.; 6th Annual IEEE International ASIC Conference and Exhibit, ASIC 1993 ; Conference date: 27-09-1993 Through 01-10-1993",

year = "1993",

doi = "10.1109/ASIC.1993.410845",

language = "English",

series = "Proceedings - 6th Annual IEEE International ASIC Conference and Exhibit, ASIC 1993",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "560--569",

booktitle = "Proceedings - 6th Annual IEEE International ASIC Conference and Exhibit, ASIC 1993",

address = "United States",

}

Sridhar, R & Shin, YC 1993, VLSI neural network architectures. in Proceedings - 6th Annual IEEE International ASIC Conference and Exhibit, ASIC 1993., 410845, Proceedings - 6th Annual IEEE International ASIC Conference and Exhibit, ASIC 1993, Institute of Electrical and Electronics Engineers Inc., pp. 560-569, 6th Annual IEEE International ASIC Conference and Exhibit, ASIC 1993, Rochester, United States, 09/27/93. https://doi.org/10.1109/ASIC.1993.410845

VLSI neural network architectures. / Sridhar, R.; Shin, Yong Chul.
Proceedings - 6th Annual IEEE International ASIC Conference and Exhibit, ASIC 1993. Institute of Electrical and Electronics Engineers Inc., 1993. p. 560-569 410845 (Proceedings - 6th Annual IEEE International ASIC Conference and Exhibit, ASIC 1993).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - VLSI neural network architectures

AU - Sridhar, R.

AU - Shin, Yong Chul

PY - 1993

Y1 - 1993

N2 - VLSI architectures for neural networks are presented. Neural networks have wide-ranging applications in classification, control, and optimization. With the need for real-time performance, VLSI neural networks have gained significant attention. Digital, analog, and mixed-mode designs are used for this application. Modular and reconfigurable designs are necessary so that various neural network models can be easily configured.

AB - VLSI architectures for neural networks are presented. Neural networks have wide-ranging applications in classification, control, and optimization. With the need for real-time performance, VLSI neural networks have gained significant attention. Digital, analog, and mixed-mode designs are used for this application. Modular and reconfigurable designs are necessary so that various neural network models can be easily configured.

UR - https://www.scopus.com/pages/publications/84889963826

U2 - 10.1109/ASIC.1993.410845

DO - 10.1109/ASIC.1993.410845

M3 - Conference contribution

AN - SCOPUS:84889963826

T3 - Proceedings - 6th Annual IEEE International ASIC Conference and Exhibit, ASIC 1993

SP - 560

EP - 569

BT - Proceedings - 6th Annual IEEE International ASIC Conference and Exhibit, ASIC 1993

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 6th Annual IEEE International ASIC Conference and Exhibit, ASIC 1993

Y2 - 27 September 1993 through 1 October 1993

ER -

VLSI neural network architectures

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