ARTIFICIAL NEURAL-NETWORK TECHNIQUES FOR THE ESTIMATION OF THICK-FILM RESISTANCE

被引：0
|
作者：
HOSKINS, BG
HASKARD, MR
机构：
[1] Microelectronics Centre, University of South Australia, Ingle Farm, 5096
来源：
MICROELECTRONICS JOURNAL | 1995年 / 26卷 / 01期
关键词：
D O I：
10.1016/0026-2692(95)98908-A
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Artificial neural network techniques are investigated as an alternative to parametric modelling for the estimation of fired thick-film resistor values. Multi-layer neural network models are constructed from resistor substrate test data. The connectionist models are developed through training procedures, allowing subsequent fired-value prediction. These non-parametric approaches do not require the functional form of the model to be known. The techniques are suitable for use in computer aided design environments.
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页码：9 / 16
页数：8
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