A drift-diffusion/Monte Carlo simulation methodology for Si/sub 1-x/Ge/sub x/ HBT design

2002 ◽  
Vol 49 (7) ◽  
pp. 1242-1249 ◽  
Author(s):  
P. Palestri ◽  
M. Mastrapasqua ◽  
A. Pacelli ◽  
C.A. King
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Drift Diffusion ◽  
Diffusion Monte Carlo ◽  
Simulation Methodology

Super-efficiency and Approximate Super-efficiency in Monte Carlo Simulation Methodology

2014 ◽  
Vol 2 ◽  
pp. 213-216
Author(s):  
Cheng-An Yang ◽  
Kung Yao ◽  
Ken Umeno ◽  
Ezio Biglieri
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Super Efficiency ◽  
Simulation Methodology

A Monte Carlo Approach to Estimating the Significance of Segregation

1984 ◽  
Vol 16 (2) ◽  
pp. 225-231 ◽  
Author(s):  
A Findlay ◽  
Anne Findlay
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Case Studies ◽  
Spatial Statistics ◽  
Null Hypothesis ◽  
Dissimilarity Index ◽  
Monte Carlo Approach ◽  
Simulation Methodology ◽  
Simulation Techniques ◽  
Social Segregation

Simulation techniques are not new to geography, but they have focused traditionally on attempts to replicate observed patterns rather than on seeking to assist in the formulation of a null hypothesis. The benefits and problems of a Monte Carlo simulation methodology are examined with reference to the latter objective. The flexibility of the approach in the evaluation of spatial statistics is shown to be considerable. Specific case studies are pursued which exemplify its potential in the investigation of social segregation using familiar measures such as the dissimilarity index and the P* index.

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