A learning algorithm for multilayer feedforward networks, RPROP (resilient propagation), is
proposed. To overcome the inherent disadvantages of pure gradient-descent, RPROP …

This book provides a self-contained and up-to-date treatment of the Monte Carlo method
and develops a common framework under which various Monte Carlo techniques can be" …

Cascade-Correlation is a new architecture and supervised learning algo (cid: 173) rithm for
artificial neural networks. Instead of just adjusting the weights in a network of fixed topology …

This paper shows that if a large neural network is used for a pattern classification problem,
and the learning algorithm finds a network with small weights that has small squared error …

A new neural network architecture is introduced for incremental supervised learning of
recognition categories and multidimensional maps in response to arbitrary sequences of …

Abstract A Fuzzy Adaptive Resonance Theory (ART) model capable of rapid stable learning
of recognition categories in response to arbitrary sequences of analog or binary input …

The nonlinear discriminant function obtained using a minimum squared error cost function
can be shown to be directly related to the nonlinear Fisher discriminant (NFD). With the …

To successfully apply evolutionary algorithms to the solution of increasingly complex
problems, we must develop effective techniques for evolving solutions in the form of …

We present a new self-organizing neural network model that has two variants. The first
variant performs unsupervised learning and can be used for data visualization, clustering …

Since the presentation of the backpropagation algorithm [1] a vast variety of improvements of
the technique for training the weights in a feed-forward neural network have been proposed …