The well-known backpropagation (BP) derivative computation process for multilayer perceptrons (MLP) learning can be viewed as a simplified version of the Kelley-Bryson gradient f...
Deep Neural Networks (DNNs) denote multilayer artificial neural networks with more than one hidden layer and millions of free parameters. We propose a Generalized Discriminant An...
This paper addresses the supervised learning in which the class membership of training data are subject to uncertainty. This problem is tackled in the framework of the Dempster-Sha...
This paper proposes a multiclassification algorithm using multilayer perceptron neural network models. It tries to boost two conflicting main objectives of multiclassifiers: a high...
A learning model for coupled oscillators is proposed. The proposed learning rule takes a simple form by which the intrinsic frequencies of the component oscillators and the coupli...