arXiv · cond-mat/9704098
Phase Transitions of Neural Networks
Abstract
The cooperative behaviour of interacting neurons and synapses is studied using models and methods from statistical physics. The competition between training error and entropy may lead to discontinuous properties of the neural network. This is demonstrated for a few examples: Perceptron, associative memory, learning from examples, generalization, multilayer networks, structure recognition, Bayesian estimate, on-line training, noise estimation and time series generation.
Explore related subjects
Keep this discovery
Wolfgang Kinzel. 1997-04-11. Phase Transitions of Neural Networks. https://doi.org/10.1080/13642819808205038
Cite the original work for its findings. Save a collection to share your selection of sources.