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IJON
2002
154views more  IJON 2002»
14 years 11 months ago
Nonlinear model predictive control of a cutting process
Nonlinear model predictive control (MPC) of a simulated chaotic cutting process is presented. The nonlinear MPC combines a neural-network model and a genetic-algorithm-based optim...
Primoz Potocnik, Igor Grabec
TASLP
2002
109views more  TASLP 2002»
14 years 11 months ago
Particle methods for Bayesian modeling and enhancement of speech signals
This paper applies time-varying autoregressive (TVAR) models with stochastically evolving parameters to the problem of speech modeling and enhancement. The stochastic evolution mod...
Jaco Vermaak, Christophe Andrieu, Arnaud Doucet, S...
ESANN
2006
15 years 1 months ago
Margin based Active Learning for LVQ Networks
In this article, we extend a local prototype-based learning model by active learning, which gives the learner the capability to select training samples during the model adaptation...
Frank-Michael Schleif, Barbara Hammer, Thomas Vill...
IJCNN
2006
IEEE
15 years 5 months ago
A Heuristic for Free Parameter Optimization with Support Vector Machines
— A heuristic is proposed to address free parameter selection for Support Vector Machines, with the goals of improving generalization performance and providing greater insensitiv...
Matthew Boardman, Thomas P. Trappenberg
ISNN
2005
Springer
15 years 5 months ago
Support Vector Regression for Software Reliability Growth Modeling and Prediction
In this work, we propose to apply support vector regression (SVR) to build software reliability growth model (SRGM). SRGM is an important aspect in software reliability engineering...
Fei Xing, Ping Guo