VLSI neural network implementation of a hippocampal model

Bing J. Sheu; Theodore W. Berger; Tony H. Wu; Richard H. Tsai

VLSI neural network implementation of a hippocampal model

Bing J. Sheu^*
, Theodore W. Berger
, Tony H. Wu
, Richard H. Tsai

^*Corresponding author for this work

University of Southern California

Research output: Contribution to journal › Conference article › peer-review

1 Scopus citations

Abstract

As an important portion of the brain system, the hippocampus performs cognitive functions of learning and memory. VLSI implementation of a hippocampal model has been proposed and a mixed analog-digital chip which use analog circuits for parallel computing and digital circuit for interconnection was designed. The design with one extensive hippocampal neuron has been sent for fabrication. One of the objectives of this research effort is to incorporate adequate biological constraints as possible into the hardware design.

Original language	English
Pages (from-to)	1664-1667
Number of pages	4
Journal	Proceedings - IEEE International Symposium on Circuits and Systems
Volume	3
State	Published - 1995
Externally published	Yes
Event	Proceedings of the 1995 IEEE International Symposium on Circuits and Systems-ISCAS 95. Part 3 (of 3) - Seattle, WA, USA Duration: 30 04 1995 → 03 05 1995

Cite this

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title = "VLSI neural network implementation of a hippocampal model",

abstract = "As an important portion of the brain system, the hippocampus performs cognitive functions of learning and memory. VLSI implementation of a hippocampal model has been proposed and a mixed analog-digital chip which use analog circuits for parallel computing and digital circuit for interconnection was designed. The design with one extensive hippocampal neuron has been sent for fabrication. One of the objectives of this research effort is to incorporate adequate biological constraints as possible into the hardware design.",

author = "Sheu, \{Bing J.\} and Berger, \{Theodore W.\} and Wu, \{Tony H.\} and Tsai, \{Richard H.\}",

year = "1995",

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journal = "Proceedings - IEEE International Symposium on Circuits and Systems",

issn = "0271-4310",

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

note = "Proceedings of the 1995 IEEE International Symposium on Circuits and Systems-ISCAS 95. Part 3 (of 3) ; Conference date: 30-04-1995 Through 03-05-1995",

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T1 - VLSI neural network implementation of a hippocampal model

AU - Sheu, Bing J.

AU - Berger, Theodore W.

AU - Wu, Tony H.

AU - Tsai, Richard H.

PY - 1995

Y1 - 1995

N2 - As an important portion of the brain system, the hippocampus performs cognitive functions of learning and memory. VLSI implementation of a hippocampal model has been proposed and a mixed analog-digital chip which use analog circuits for parallel computing and digital circuit for interconnection was designed. The design with one extensive hippocampal neuron has been sent for fabrication. One of the objectives of this research effort is to incorporate adequate biological constraints as possible into the hardware design.

AB - As an important portion of the brain system, the hippocampus performs cognitive functions of learning and memory. VLSI implementation of a hippocampal model has been proposed and a mixed analog-digital chip which use analog circuits for parallel computing and digital circuit for interconnection was designed. The design with one extensive hippocampal neuron has been sent for fabrication. One of the objectives of this research effort is to incorporate adequate biological constraints as possible into the hardware design.

UR - https://www.scopus.com/pages/publications/0029179518

M3 - 会议文章

AN - SCOPUS:0029179518

SN - 0271-4310

VL - 3

SP - 1664

EP - 1667

JO - Proceedings - IEEE International Symposium on Circuits and Systems

JF - Proceedings - IEEE International Symposium on Circuits and Systems

T2 - Proceedings of the 1995 IEEE International Symposium on Circuits and Systems-ISCAS 95. Part 3 (of 3)

Y2 - 30 April 1995 through 3 May 1995

ER -

VLSI neural network implementation of a hippocampal model

Abstract

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