Intelligent Engineering Systems Through Artificial Neural Networks: Neural Networks, Fuzzy Logic and Evolutionary Programming : Proceedings of the Artificial Neural Networks in Engineering (ANNIE '96) Conference, Held November 10-13, 1996, in St. Louis, Missouri, U.S.A.. Smart engineering systemsCihan H. Dagli |
Contents
Flexible Modular Architecture for Changing Environments | 5 |
Three Techniques for Extracting Rules from Feedforward Networks | 23 |
A Binary Three Layered Neural Network with Switched Error Perturbation | 35 |
Copyright | |
100 other sections not shown
Common terms and phrases
adaptive amacrine cells application approach architecture Artificial Neural Networks autonomous agents backpropagation behavior binary space bipolar cell classification complex Computer convergence in binary correct binary outputs correlation dimension data set decision defined dynamic Engineering environment equation estimator evaluation expected new MAE extracted rules feedforward field amacrine cell Figure Full-RE fuzzy logic Genetic Algorithms gray correlation Hamming distance hidden node hidden units Hopfield Hopfield networks incremental initial input patterns input samples interaction iteration layer learning algorithm linear Lyapunov exponent MAE in region mapping matrix membership functions method minimizing neural net neurons noise nonlinear number of hidden number of training ontogenetic optimal paper parameters performance point from region predators prediction problem proposed retina robot rule extraction rule sets sigmoid sigmoidal function signal simulation step stochastic target technique test inputs training inputs training patterns update variables VC dimension vector weights