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Symbolic Model Checking for Real-time Systems

by Thomas A. Henzinger, Xavier Nicollin, Joseph Sifakis, Sergio Yovine - INFORMATION AND COMPUTATION , 1992
"... We describe finite-state programs over real-numbered time in a guarded-command language with real-valued clocks or, equivalently, as finite automata with real-valued clocks. Model checking answers the question which states of a real-time program satisfy a branching-time specification (given in an ..."
Abstract - Cited by 574 (50 self) - Add to MetaCart
in an extension of CTL with clock variables). We develop an algorithm that computes this set of states symbolically as a fixpoint of a functional on state predicates, without constructing the state space. For this purpose, we introduce a -calculus on computation trees over real-numbered time. Unfortunately

Using SeDuMi 1.02, a MATLAB toolbox for optimization over symmetric cones

by Jos F. Sturm , 1998
"... SeDuMi is an add-on for MATLAB, that lets you solve optimization problems with linear, quadratic and semidefiniteness constraints. It is possible to have complex valued data and variables in SeDuMi. Moreover, large scale optimization problems are solved efficiently, by exploiting sparsity. This pape ..."
Abstract - Cited by 1334 (4 self) - Add to MetaCart
SeDuMi is an add-on for MATLAB, that lets you solve optimization problems with linear, quadratic and semidefiniteness constraints. It is possible to have complex valued data and variables in SeDuMi. Moreover, large scale optimization problems are solved efficiently, by exploiting sparsity

Particle swarm optimization

by James Kennedy, Russell Eberhart , 1995
"... eberhart @ engr.iupui.edu A concept for the optimization of nonlinear functions using particle swarm methodology is introduced. The evolution of several paradigms is outlined, and an implementation of one of the paradigms is discussed. Benchmark testing of the paradigm is described, and applications ..."
Abstract - Cited by 3535 (22 self) - Add to MetaCart
eberhart @ engr.iupui.edu A concept for the optimization of nonlinear functions using particle swarm methodology is introduced. The evolution of several paradigms is outlined, and an implementation of one of the paradigms is discussed. Benchmark testing of the paradigm is described

The Advantages of Evolutionary Computation

by David B. Fogel , 1997
"... Evolutionary computation is becoming common in the solution of difficult, realworld problems in industry, medicine, and defense. This paper reviews some of the practical advantages to using evolutionary algorithms as compared with classic methods of optimization or artificial intelligence. Specific ..."
Abstract - Cited by 536 (6 self) - Add to MetaCart
Evolutionary computation is becoming common in the solution of difficult, realworld problems in industry, medicine, and defense. This paper reviews some of the practical advantages to using evolutionary algorithms as compared with classic methods of optimization or artificial intelligence. Specific

A computational approach to edge detection

by John Canny - IEEE Transactions on Pattern Analysis and Machine Intelligence , 1986
"... Abstract-This paper describes a computational approach to edge detection. The success of the approach depends on the definition of a comprehensive set of goals for the computation of edge points. These goals must be precise enough to delimit the desired behavior of the detector while making minimal ..."
Abstract - Cited by 4621 (0 self) - Add to MetaCart
. We use the criteria in numerical optimization to derive detectors for several common image features, including step edges. On specializing the analysis to step edges, we find that there is a natural uncertainty principle between detection and localization performance, which are the two main goals

SMOTE: Synthetic Minority Over-sampling Technique

by Nitesh V. Chawla, Kevin W. Bowyer, Lawrence O. Hall, W. Philip Kegelmeyer - Journal of Artificial Intelligence Research , 2002
"... An approach to the construction of classifiers from imbalanced datasets is described. A dataset is imbalanced if the classification categories are not approximately equally represented. Often real-world data sets are predominately composed of ``normal'' examples with only a small percentag ..."
Abstract - Cited by 614 (28 self) - Add to MetaCart
-sampling the minority class involves creating synthetic minority class examples. Experiments are performed using C4.5, Ripper and a Naive Bayes classifier. The method is evaluated using the area under the Receiver Operating Characteristic curve (AUC) and the ROC convex hull strategy.

Optimization Flow Control, I: Basic Algorithm and Convergence

by Steven H. Low, David E. Lapsley - IEEE/ACM TRANSACTIONS ON NETWORKING , 1999
"... We propose an optimization approach to flow control where the objective is to maximize the aggregate source utility over their transmission rates. We view network links and sources as processors of a distributed computation system to solve the dual problem using gradient projection algorithm. In thi ..."
Abstract - Cited by 690 (64 self) - Add to MetaCart
We propose an optimization approach to flow control where the objective is to maximize the aggregate source utility over their transmission rates. We view network links and sources as processors of a distributed computation system to solve the dual problem using gradient projection algorithm

Pervasive Computing: Vision and Challenges

by M. Satyanarayanan - IEEE Personal Communications , 2001
"... This paper discusses the challenges in computer systems research posed by the emerging field of pervasive computing. It first examines the relationship of this new field to its predecessors: distributed systems and mobile computing. It then identifies four new research thrusts: effective use of smar ..."
Abstract - Cited by 670 (20 self) - Add to MetaCart
This paper discusses the challenges in computer systems research posed by the emerging field of pervasive computing. It first examines the relationship of this new field to its predecessors: distributed systems and mobile computing. It then identifies four new research thrusts: effective use

Decision-Theoretic Planning: Structural Assumptions and Computational Leverage

by Craig Boutilier, Thomas Dean, Steve Hanks - JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH , 1999
"... Planning under uncertainty is a central problem in the study of automated sequential decision making, and has been addressed by researchers in many different fields, including AI planning, decision analysis, operations research, control theory and economics. While the assumptions and perspectives ..."
Abstract - Cited by 510 (4 self) - Add to MetaCart
or plans. Planning problems commonly possess structure in the reward and value functions used to de...

RTP: A Transport Protocol for Real-Time Applications

by H. Schulzrinne, S. Casner, et al. , 1999
"... ..."
Abstract - Cited by 2394 (136 self) - Add to MetaCart
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