Numerical recipes: the art of scientific computing
Numerical recipes: the art of scientific computing
Monte Carlo optimization, simulation, and sensitivity of queueing networks
Monte Carlo optimization, simulation, and sensitivity of queueing networks
Multilayer feedforward networks are universal approximators
Neural Networks
SIAM Journal on Matrix Analysis and Applications
Neural network design and the complexity of learning
Neural network design and the complexity of learning
What size net gives valid generalization?
Neural Computation
Dr. Dobb's Journal
Hi-index | 0.98 |
Research has shown that artificial neural networks (ANNs) can be trained to perform function mapping tasks. In this work, ANN mappings are approximated around an operating point by third-order polynomials (3OPs). A previously unknown function can be modeled by an ANN, and a 3OP can be derived from the ANN model. In addition, the sensitivity of an output to changes in the inputs can be easily determined from these polynomials in large neighborhoods around the operating points. Examples are shown that illustrate the use of the ANN-3OP mapping approach.