Design and implementation of a calibrating t-model neural-based a/d converter

Zheng Tang; Yuichi Shirata; Okihiko Ishizuka; Koichi Tanno

Design and implementation of a calibrating t-model neural-based a/d converter

Zheng Tang^*, Yuichi Shirata, Okihiko Ishizuka, Koichi Tanno

^*Corresponding author for this work

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Abstract

A calibrating analog-to-digital (A/D) converter employing a T-Model neural network is described. The T-Model neural-based A/D converter architecture is presented with particular emphasis on the elimination of local minimum of the Hopfield neural network. Furthermore, a teacher forcing algorithm is presented and used to synthesize the A/D converter and correct errors of the converter due to offset and device mismatch. An experimental A/D converter using standard 5-μm CMOS discrete IC circuits demonstrates high-performance analog-to-digital conversion and calibrating.

Original language	English
Pages (from-to)	553-558
Number of pages	6
Journal	IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Volume	E79-A
Issue number	4
State	Published - 1996

Keywords

A/d converter
Hopfield model, calibrating
Neural networks

ASJC Scopus subject areas

Signal Processing
Computer Graphics and Computer-Aided Design
Electrical and Electronic Engineering
Applied Mathematics

Cite this

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title = "Design and implementation of a calibrating t-model neural-based a/d converter",

abstract = "A calibrating analog-to-digital (A/D) converter employing a T-Model neural network is described. The T-Model neural-based A/D converter architecture is presented with particular emphasis on the elimination of local minimum of the Hopfield neural network. Furthermore, a teacher forcing algorithm is presented and used to synthesize the A/D converter and correct errors of the converter due to offset and device mismatch. An experimental A/D converter using standard 5-μm CMOS discrete IC circuits demonstrates high-performance analog-to-digital conversion and calibrating.",

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author = "Zheng Tang and Yuichi Shirata and Okihiko Ishizuka and Koichi Tanno",

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AU - Tang, Zheng

AU - Shirata, Yuichi

AU - Ishizuka, Okihiko

AU - Tanno, Koichi

PY - 1996

Y1 - 1996

N2 - A calibrating analog-to-digital (A/D) converter employing a T-Model neural network is described. The T-Model neural-based A/D converter architecture is presented with particular emphasis on the elimination of local minimum of the Hopfield neural network. Furthermore, a teacher forcing algorithm is presented and used to synthesize the A/D converter and correct errors of the converter due to offset and device mismatch. An experimental A/D converter using standard 5-μm CMOS discrete IC circuits demonstrates high-performance analog-to-digital conversion and calibrating.

AB - A calibrating analog-to-digital (A/D) converter employing a T-Model neural network is described. The T-Model neural-based A/D converter architecture is presented with particular emphasis on the elimination of local minimum of the Hopfield neural network. Furthermore, a teacher forcing algorithm is presented and used to synthesize the A/D converter and correct errors of the converter due to offset and device mismatch. An experimental A/D converter using standard 5-μm CMOS discrete IC circuits demonstrates high-performance analog-to-digital conversion and calibrating.

KW - A/d converter

KW - Hopfield model, calibrating

KW - Neural networks

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M3 - 学術論文

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SN - 0916-8508

VL - E79-A

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JO - IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences

JF - IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences

IS - 4

ER -

Design and implementation of a calibrating t-model neural-based a/d converter

Abstract

Keywords

ASJC Scopus subject areas

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