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» Nonlinear mapping using particle swarm optimisation
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JCIT
2010
172views more  JCIT 2010»
14 years 4 months ago
Conditional Sensor Deployment Using Evolutionary Algorithms
Sensor deployment is a critical issue, as it affects the cost and detection capabilities of a wireless sensor network. Although many previous efforts have addressed this issue, mo...
M. Sami Soliman, Guanzheng Tan
UAI
2000
14 years 11 months ago
Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks
Particle filters (PFs) are powerful samplingbased inference/learning algorithms for dynamic Bayesian networks (DBNs). They allow us to treat, in a principled way, any type of prob...
Arnaud Doucet, Nando de Freitas, Kevin P. Murphy, ...
TIP
2010
141views more  TIP 2010»
14 years 4 months ago
Efficient Particle Filtering via Sparse Kernel Density Estimation
Particle filters (PFs) are Bayesian filters capable of modeling nonlinear, non-Gaussian, and nonstationary dynamical systems. Recent research in PFs has investigated ways to approp...
Amit Banerjee, Philippe Burlina
ICANN
2009
Springer
15 years 2 months ago
An EM Based Training Algorithm for Recurrent Neural Networks
Recurrent neural networks serve as black-box models for nonlinear dynamical systems identification and time series prediction. Training of recurrent networks typically minimizes t...
Jan Unkelbach, Yi Sun, Jürgen Schmidhuber
IJCNN
2007
IEEE
15 years 4 months ago
DHP-Based Wide-Area Coordinating Control of a Power System with a Large Wind Farm and Multiple FACTS Devices
—Wide-area coordinating control is becoming an important issue and a challenging problem in the power industry. This paper proposes a novel optimal wide-area monitor and wide-are...
Wei Qiao, Ronald G. Harley, Ganesh K. Venayagamoor...