Results 251 to 260 of about 6,116,423 (300)

Statistical Debugging for Simulations

ACM Transactions on Modeling and Computer Simulation, 2015
Predictions from simulations have entered the mainstream of public policy and decision-making practices. Unfortunately, methods for gaining insight into faulty simulations outputs have not kept pace. Ideally, an insight gathering method would automatically identify the cause of a faulty output and explain to the simulation developer how to
Ross Gore, Paul F. Reynolds Jr., David Kamensky, Saikou Y. Diallo, Jose J. Padilla   +4 more
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Statistical sampling of microarchitecture simulation

Proceedings 20th IEEE International Parallel & Distributed Processing Symposium, 2006
Current software-based microarchitecture simulators are many orders of magnitude slower than the hardware they simulate. Hence, most microarchitecture design studies draw their conclusions from drastically truncated benchmark simulations that are often inaccurate and misleading.
Wunderlich, Roland E., Wenisch, Thomas F., Falsafi, Babak, Hoe, James C.   +3 more
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Multivariate Statistical Simulation

Biometrics, 1989
Univariate Distributions and Their Generation. Multivariate Generation Techniques. Multivariate Normal and Related Distributions. Johnson's Translation System. Elliptically Contoured Distributions. Circular, Spherical and Related Distributions. Khintchine Distributions. Miscellaneous Distributions. Research Directions. References.
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Probability, Statistics and Simulation

2022
This book presents in a compact form the program carried out in introductory statistics courses and discusses some essential topics for research activity, such as Monte Carlo simulation techniques, methods of statistical inference, best fit and analysis of laboratory data.
Alberto Rotondi, Paolo Pedroni, Antonio Pievatolo   +2 more
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Parallel simulation of statistical multiplexers

Discrete Event Dynamic Systems: Theory and Applications, 1995
The simulation of high-speed telecommunication systems such as ATM (Asynchronous Transfer Mode) networks has generally required excessivley long run times. This paper reviews alternative approaches using parallelism to speed up simulations of discrete event systems, and telecommunication networks in particular.
Richard M. Fujimoto, Ioanis Nikolaidis, C. Anthony Cooper   +2 more
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Statistical simulation of rigid bodies

Proceedings of the 2009 ACM SIGGRAPH/Eurographics Symposium on Computer Animation, 2009
We describe a method for replacing certain stages of rigid body simulation with a statistically-based approximation. We begin by collecting statistical data regarding changes in linear and angular momentum for collisions of a given object. From this data we extract a statistical "signature" for the object, giving a compact representation of the object ...
Shu-Wei Hsu, John Keyser
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Uses and abuses of statistical simulation

Mathematical Programming, 1988
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Statistical Analysis for Queueing Simulations

Management Science, 1973
This paper presents a method for estimating the variances of sample performance measures in queueing simulations, for removing the bias in these sample measures due to initial conditions and for deriving approximating confidence intervals for the true performance measures.
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Optimized statistical analog fault simulation

Proceedings Eighth Asian Test Symposium (ATS'99), 2003
A new statistical method for analog fault simulation is presented. The method takes into account process parameter variations and aims to reduce the number of the computational expensive Monte Carlo simulations often required during analog fault simulation. The technique is illustrated by means of a fifth-order low-pass switched-capacitor filter.
Abdelhakim Khouas, Mohamed Dessouky, Anne Derieux   +2 more
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Statistical modeling for circuit simulation

Fourth International Symposium on Quality Electronic Design, 2003. Proceedings., 2004
Robust, high yield IC design requires statistical simulation, and therefore statistical models. Simple "fast" and "slow" sets of model parameters are not sufficient to predict the manufacturing variations of all measures of circuit performance for arbitrary circuit topologies, device geometries, and biases.
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