DocumentCode
2731204
Title
Performance modeling of analog circuits via neural networks: the design process view
Author
Sobecks, Brian ; Nevin, Joseph ; Helmicki, Arthur
Author_Institution
Motorola Inc., Schaumburg, IL, USA
fYear
1998
fDate
9-12 Aug 1998
Firstpage
28
Lastpage
32
Abstract
This paper presents a novel framework for modeling the performance of analog circuits and a methodology for constructing the corresponding models. The methodology uses simulator data to iteratively train neural networks in order to produce very accurate multivariate nonlinear models, which can be instantaneously evaluated. Results are presented for circuits at various levels of abstraction
Keywords
analogue integrated circuits; circuit simulation; hardware description languages; integrated circuit design; integrated circuit modelling; neural nets; abstraction levels; analog circuits; design process view; iterative training; multivariate nonlinear models; neural networks; performance modeling; simulator data; Analog circuits; Circuit simulation; Circuit synthesis; Circuit topology; Measurement; Neural networks; Predictive models; Process design; Signal design; Vehicles;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 1998. Proceedings. 1998 Midwest Symposium on
Conference_Location
Notre Dame, IN
Print_ISBN
0-8186-8914-5
Type
conf
DOI
10.1109/MWSCAS.1998.759428
Filename
759428
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