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» Input Modeling Using Quantile Statistical Methods
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COMPSAC
2002
IEEE
14 years 19 days ago
The Method of Software Reliability Growth Models Choice Using Assumptions Matrix
The method of choice of the software reliability models based on the analysis of assumptions and compatibility both input and output parameters is offered. This method is illustra...
Vyacheslav S. Kharchenko, O. M. Tarasyuk, Vladimir...
AUTOMATICA
2006
150views more  AUTOMATICA 2006»
13 years 7 months ago
Enlarging the terminal region of nonlinear model predictive control using the support vector machine method
In this paper, Receding Horizon Model Predictive Control (RHMPC) of nonlinear systems subject to input and state constraints is considered. We propose to estimate the terminal reg...
Chong Jin Ong, Dan Sui, Elmer G. Gilbert
CDC
2009
IEEE
225views Control Systems» more  CDC 2009»
14 years 12 days ago
High performance adaptive robust control for nonlinear system with unknown input backlash
—A high performance adaptive robust control (ARC) algorithm is developed for a class of nonlinear system with unknown input backlash, parametric uncertainties and uncertain nonli...
Jian Guo, Bin Yao, Qingwei Chen, Xiaobei Wu
DAC
2006
ACM
14 years 8 months ago
Statistical timing analysis with correlated non-gaussian parameters using independent component analysis
We propose a scalable and efficient parameterized block-based statistical static timing analysis algorithm incorporating both Gaussian and non-Gaussian parameter distributions, ca...
Jaskirat Singh, Sachin S. Sapatnekar
HICSS
2006
IEEE
114views Biometrics» more  HICSS 2006»
14 years 1 months ago
New Probabilistic Method for Estimation of Equipment Failures and Development of Replacement Strategies
When large amount of statistical information about power system component failure rate is available, statistical parametric models can be developed for predictive maintenance. Oft...
Miroslav Begovic, Petar M. Djuric, Joshua Perkel, ...