Издательство CRC Press, 2000, -358 pp.Neural networks are a new generation of information processing paradigms designed to mimic some of the behaviors of the human brain. These networks have gained tremendous popularity due to their ability to learn, recall and generalize from training data. A number of neural network paradigms have been reported in the last four decades, and in the last decade the neural networks have been refined and widely used by researchers and application engineers.
The main purpose of this book is to report recent advances in neural network paradigms and their applications. It is impossible to include all recent advances in this book; hence, only a sample has been included.A neuro-symbolic hybrid intelligent architecture with applications
New radial basis neural networks and their application in a large-scale handwritten digit recognition problem
Efficient neural network-based methodology for the design of multiple classifiers
Learning fine motion in robotics: design and experiments
A new neural network for adaptive pattern recognition of multichannel input signals
Lateral priming adaptive resonance theory (LAPART)-2: innovation in ART
Neural network learning in a travel reservation domain
Recent advances in neural network applications in process control
Monitoring internal combustion engines by neural network based virtual sensing
Neural architectures of fuzzy Petri nets
