DocumentCode :
2594525
Title :
Statistical Simulation and Modeling of Nano-scale CMOS VCO Using Artificial Neural Network
Author :
Mandal, Sipra ; Pandit, Soumya
Author_Institution :
Sch. of Inf. Technol., Univ. of Calcutta, Kolkata, India
fYear :
2011
fDate :
2-7 Jan. 2011
Firstpage :
94
Lastpage :
99
Abstract :
The variation of intra-die process parameters play a significant role in determining the yield of an analog/RF circuit. This paper presents statistical results demonstrating the effect of variations of process parameters on a nano-scale CMOS voltage controlled oscillator circuit. A statistical model relating the process parameter variations and the performance variations has been constructed using artificial neural network. The constructed model shows accuracy similar to that obtained though Monte Carlo analysis technique, however, consuming much less time.
Keywords :
CMOS integrated circuits; Monte Carlo methods; electronic engineering computing; neural nets; voltage-controlled oscillators; Monte Carlo analysis; analog/RF circuit; artificial neural network; intradie process parameters; nanoscale CMOS VCO; statistical simulation; voltage controlled oscillator; Artificial neural networks; CMOS integrated circuits; Data models; Integrated circuit modeling; Semiconductor device modeling; Training; Voltage-controlled oscillators;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
VLSI Design (VLSI Design), 2011 24th International Conference on
Conference_Location :
Chennai
ISSN :
1063-9667
Print_ISBN :
978-1-61284-327-8
Electronic_ISBN :
1063-9667
Type :
conf
DOI :
10.1109/VLSID.2011.28
Filename :
5718784
Link To Document :
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