8 The training of some types of neural networks leads to separable non-linear least squares problems. These problems may be9 ill-conditioned and require special techniques. A robus...
This paper presents a novel recurrent neural network for solving nonlinear optimization problems with inequality constraints. Under the condition that the Hessian matrix of the ass...
Artificial neural networks and genetic algorithms derived from the corresponding simulation of biology, anatomy. The paper analyzes the advantages and the disadvantages of the art...
— In this paper, a neural network approach is presented to expand the Pareto-optimal front for multiobjective optimization problems. The network is trained using results obtained...
This book covers the following topics: The biological paradigm, Threshold logic, Weighted Networks, The Perceptron, Perceptron learning, Unsupervised learning and clustering algori...