Results 1 - 10 of 45,253

The SimpleScalar tool set, version 2.0

by Doug Burger, Todd M. Austin - Computer Architecture News , 1997
"... This report describes release 2.0 of the SimpleScalar tool set, a suite of free, publicly available simulation tools that offer both detailed and high-performance simulation of modern microprocessors. The new release offers more tools and capabilities, precompiled binaries, cleaner interfaces, bette ..."
Abstract - Cited by 1844 (43 self) - Add to MetaCart
This report describes release 2.0 of the SimpleScalar tool set, a suite of free, publicly available simulation tools that offer both detailed and high-performance simulation of modern microprocessors. The new release offers more tools and capabilities, precompiled binaries, cleaner interfaces

The Player/Stage Project: Tools for Multi-Robot and Distributed Sensor Systems

by Brian P. Gerkey, Richard T. Vaughan, Andrew Howard - In Proceedings of the 11th International Conference on Advanced Robotics , 2003
"... This paper describes the Player/Stage software tools applied to multi-robot, distributed-robot and sensor network systems. Player is a robot device server that provides network transparent robot control. Player seeks to constrain controller design as little as possible; it is device independent, non ..."
Abstract - Cited by 622 (14 self) - Add to MetaCart
This paper describes the Player/Stage software tools applied to multi-robot, distributed-robot and sensor network systems. Player is a robot device server that provides network transparent robot control. Player seeks to constrain controller design as little as possible; it is device independent

Modeling and simulation of genetic regulatory systems: A literature review

by Hidde De Jong - JOURNAL OF COMPUTATIONAL BIOLOGY , 2002
"... In order to understand the functioning of organisms on the molecular level, we need to know which genes are expressed, when and where in the organism, and to which extent. The regulation of gene expression is achieved through genetic regulatory systems structured by networks of interactions between ..."
Abstract - Cited by 738 (14 self) - Add to MetaCart
DNA, RNA, proteins, and small molecules. As most genetic regulatory networks of interest involve many components connected through interlocking positive and negative feedback loops, an intuitive understanding of their dynamics is hard to obtain. As a consequence, formal methods and computer tools

Evaluating Future Microprocessors: the SimpleScalar Tool Set

by Doug Burger, Todd M. Austin, Steve Bennett , 1996
"... This document describes the SimpleScalar tool set, a collection of publicly-available simulation tools that use detailed execution -driven to simulate modern processor architectures. In this report, we give an overview of the tool set, show how to obtain, install and use it. We also discuss detail ..."
Abstract - Cited by 475 (15 self) - Add to MetaCart
This document describes the SimpleScalar tool set, a collection of publicly-available simulation tools that use detailed execution -driven to simulate modern processor architectures. In this report, we give an overview of the tool set, show how to obtain, install and use it. We also discuss

Bayesian density estimation and inference using mixtures.

by Michael D Escobar , Mike West - J. Amer. Statist. Assoc. , 1995
"... JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about J ..."
Abstract - Cited by 653 (18 self) - Add to MetaCart
mixtures of normal distributions. Efficient simulation methods are used to approximate various prior, posterior, and predictive distributions. This allows for direct inference on a variety of practical issues, including problems of local versus global smoothing, uncertainty about density estimates

lmbench: Portable Tools for Performance Analysis

by Carl Staelin, Hewlett-packard Laboratories - In USENIX Annual Technical Conference , 1996
"... lmbench: Portable tools for performance analysis lmbench is a micro-benchmark suite designed to focus attention on the basic building blocks of many common system applications, such as databases, simulations, software development, and networking. In almost all cases, the individual tests are the res ..."
Abstract - Cited by 464 (2 self) - Add to MetaCart
lmbench: Portable tools for performance analysis lmbench is a micro-benchmark suite designed to focus attention on the basic building blocks of many common system applications, such as databases, simulations, software development, and networking. In almost all cases, the individual tests

Markov Random Field Models in Computer Vision

by S. Z. Li , 1994
"... . A variety of computer vision problems can be optimally posed as Bayesian labeling in which the solution of a problem is defined as the maximum a posteriori (MAP) probability estimate of the true labeling. The posterior probability is usually derived from a prior model and a likelihood model. The l ..."
Abstract - Cited by 516 (18 self) - Add to MetaCart
. The latter relates to how data is observed and is problem domain dependent. The former depends on how various prior constraints are expressed. Markov Random Field Models (MRF) theory is a tool to encode contextual constraints into the prior probability. This paper presents a unified approach for MRF modeling

Bayes Factors

by Robert E. Kass, Adrian E. Raftery , 1995
"... In a 1935 paper, and in his book Theory of Probability, Jeffreys developed a methodology for quantifying the evidence in favor of a scientific theory. The centerpiece was a number, now called the Bayes factor, which is the posterior odds of the null hypothesis when the prior probability on the null ..."
Abstract - Cited by 1826 (74 self) - Add to MetaCart
In a 1935 paper, and in his book Theory of Probability, Jeffreys developed a methodology for quantifying the evidence in favor of a scientific theory. The centerpiece was a number, now called the Bayes factor, which is the posterior odds of the null hypothesis when the prior probability on the null

UPPAAL in a Nutshell

by Kim G. Larsen, Paul Pettersson, Wang Yi , 1997
"... . This paper presents the overall structure, the design criteria, and the main features of the tool box Uppaal. It gives a detailed user guide which describes how to use the various tools of Uppaal version 2.02 to construct abstract models of a real-time system, to simulate its dynamical behavior, ..."
Abstract - Cited by 662 (51 self) - Add to MetaCart
. This paper presents the overall structure, the design criteria, and the main features of the tool box Uppaal. It gives a detailed user guide which describes how to use the various tools of Uppaal version 2.02 to construct abstract models of a real-time system, to simulate its dynamical behavior

Survey of clustering algorithms

by Rui Xu, Donald Wunsch II - IEEE TRANSACTIONS ON NEURAL NETWORKS , 2005
"... Data analysis plays an indispensable role for understanding various phenomena. Cluster analysis, primitive exploration with little or no prior knowledge, consists of research developed across a wide variety of communities. The diversity, on one hand, equips us with many tools. On the other hand, the ..."
Abstract - Cited by 499 (4 self) - Add to MetaCart
Data analysis plays an indispensable role for understanding various phenomena. Cluster analysis, primitive exploration with little or no prior knowledge, consists of research developed across a wide variety of communities. The diversity, on one hand, equips us with many tools. On the other hand
Results 1 - 10 of 45,253