A Statistical Model of Logic Gates for Monte Carlo Simulation Including On-Chip Variations

2007 ◽  
pp. 516-525 ◽  
Author(s):  
Francesco Centurelli ◽  
Luca Giancane ◽  
Mauro Olivieri ◽  
Giuseppe Scotti ◽  
Alessandro Trifiletti
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Statistical Model ◽  
Logic Gates ◽  
On Chip

Improved Current Statistic Model and Adaptive Filtering

2005 ◽  
Author(s):  
Hongtao Hu ◽  
Zhongliang Jing
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Statistical Model ◽  
Adaptive Filtering ◽  
Adaptive Algorithm ◽  
Tracking Algorithm ◽  
Unscented Transformation ◽  
Maneuvering Targets ◽  
Statistic Model ◽  
Simulation Results

Current statistical model needs to pre-define the value of maximum accelerations of maneuvering targets. So it may be difficult to meet all maneuvering conditions. In this paper a novel adaptive algorithm for tracking maneuvering targets is proposed. The algorithm is implemented with fuzzy-controlled current statistic model adaptive filtering and unscented transformation. The Monte Carlo simulation results show that this method outperforms the conventional tracking algorithm based on current statistical model.

Statistical Model for the Inherent Tilt of Flip-Chips

1996 ◽  
Vol 118 (1) ◽  
pp. 16-20 ◽  
Author(s):  
Lewis S. Goldmann
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Statistical Model ◽  
Closed Form ◽  
High Power ◽  
Power Electronic ◽  
Mathematical Algorithm ◽  
Flip Chips ◽  
Statistical Variation ◽  
Analytical Tools

The tilt of flip-chips is becoming increasingly important in optical and high-power electronic applications. This paper outlines the principal sources of tilt, and presents a mathematical algorithm for the statistical variation in inherent tilt, the component related to variability of solder pad dimensions. With the assistance of a Monte Carlo simulation, closed form equations are developed for several common families of symmetric pad footprints. Possible extension of the analytical tools to other important cases is discussed.

scholarly journals A STATISTICAL MODEL FOR EXPECTED CYCLE TIME OF SP-AS/RS: AN APPLICATION OF MONTE CARLO SIMULATION

2008 ◽  
Vol 22 (7-8) ◽  
pp. 824-840 ◽  
Author(s):  
Mohammadreza Vasili ◽  
Tang Sai Hong ◽  
Seyed Mahdi Homayouni ◽  
Napsiah Ismail
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Statistical Model ◽  
Cycle Time

Electron Scattering in Solids

1990 ◽  
Vol 48 (2) ◽  
pp. 4-5
Author(s):  
Ryuichi Shimizu ◽  
Ze-Jun Ding
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Angular Distribution ◽  
Elastic Scattering ◽  
Electron Scattering ◽  
Cross Sections ◽  
Expansion Method ◽  
Electron Excitation ◽  
Partial Wave Expansion ◽  
Backscattered Electrons

Monte Carlo simulation has been becoming most powerful tool to describe the electron scattering in solids, leading to more comprehensive understanding of the complicated mechanism of generation of various types of signals for microbeam analysis.The present paper proposes a practical model for the Monte Carlo simulation of scattering processes of a penetrating electron and the generation of the slow secondaries in solids. The model is based on the combined use of Gryzinski’s inner-shell electron excitation function and the dielectric function for taking into account the valence electron contribution in inelastic scattering processes, while the cross-sections derived by partial wave expansion method are used for describing elastic scattering processes. An improvement of the use of this elastic scattering cross-section can be seen in the success to describe the anisotropy of angular distribution of elastically backscattered electrons from Au in low energy region, shown in Fig.l. Fig.l(a) shows the elastic cross-sections of 600 eV electron for single Au-atom, clearly indicating that the angular distribution is no more smooth as expected from Rutherford scattering formula, but has the socalled lobes appearing at the large scattering angle.

Determination of Stoichiometry of GaAs Component in (Gaas)Ge Epitaxially Grown Thin Films by Electron Microprobe X-Ray Analysis

1990 ◽  
Vol 48 (2) ◽  
pp. 264-265
Author(s):  
D. R. Liu ◽  
S. S. Shinozaki ◽  
R. J. Baird
Keyword(s):  
Thin Film ◽  
Thin Films ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Compound Semiconductors ◽  
Energy Dispersive Analysis ◽  
X Ray ◽  
Metastable Alloys ◽  
Lower Voltage

The epitaxially grown (GaAs)Ge thin film has been arousing much interest because it is one of metastable alloys of III-V compound semiconductors with germanium and a possible candidate in optoelectronic applications. It is important to be able to accurately determine the composition of the film, particularly whether or not the GaAs component is in stoichiometry, but x-ray energy dispersive analysis (EDS) cannot meet this need. The thickness of the film is usually about 0.5-1.5 μm. If Kα peaks are used for quantification, the accelerating voltage must be more than 10 kV in order for these peaks to be excited. Under this voltage, the generation depth of x-ray photons approaches 1 μm, as evidenced by a Monte Carlo simulation and actual x-ray intensity measurement as discussed below. If a lower voltage is used to reduce the generation depth, their L peaks have to be used. But these L peaks actually are merged as one big hump simply because the atomic numbers of these three elements are relatively small and close together, and the EDS energy resolution is limited.

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