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Full-Text Articles in Engineering
Training Radial Basis Neural Networks With The Extended Kalman Filter, Daniel J. Simon
Training Radial Basis Neural Networks With The Extended Kalman Filter, Daniel J. Simon
Electrical and Computer Engineering Faculty Publications
Radial basis function (RBF) neural networks provide attractive possibilities for solving signal processing and pattern classification problems. Several algorithms have been proposed for choosing the RBF prototypes and training the network. The selection of the RBF prototypes and the network weights can be viewed as a system identification problem. As such, this paper proposes the use of the extended Kalman filter for the learning procedure. After the user chooses how many prototypes to include in the network, the Kalman filter simultaneously solves for the prototype vectors and the weight matrix. A decoupled extended Kalman filter is then proposed in order …
An Intelligent System For Monitoring The Microgravity Environment Quality On-Board The International Space Station, Paul P. Lin, Kenol Jules
An Intelligent System For Monitoring The Microgravity Environment Quality On-Board The International Space Station, Paul P. Lin, Kenol Jules
Mechanical Engineering Faculty Publications
An intelligent system for monitoring the microgravity environment quality on-board the International Space Station is presented. The monitoring system uses a new approach combining Kohonen's self-organizing feature map, learning vector quantization, and a back propagation neural network to recognize and classify the known and unknown patterns. Finally, fuzzy logic is used to assess the level of confidence associated with each vibrating source activation detected by the system.