Lecture Notes in Computer Science
1 primary work
Book 540
Artificial Neural Networks
Published 28 August 1991
Artificial neural networks are massively parallel
interconnected networks ofsimple elements which are
intended to interact with the objects of the real world in
the same way as biological nervous systems do. Interest in
these networks is due to the opinion that they are able to
perform tasks like image and speech recognition that have
only been implemented in limited ways by traditional
computing methods.
This book includes invited lectures and the full
contributions to the International Workshop onArtificial
Neural Networks held in Granada, Spain, September 17-19,
1991. The workshop was sponsored by the IEEE Computer
Society, the Spanish Association for Computing and
Automatics, and the University of Granada. The contributions
were selected by an international program committee; the
authors of the papers come from 12 countries. The book is
organized in six sections, covering: - Neural network
theories and neural models - Biological perspectives -
Neural network architectures and algorithms - Software
developments and tools - Hardware implementations -
Applications.
interconnected networks ofsimple elements which are
intended to interact with the objects of the real world in
the same way as biological nervous systems do. Interest in
these networks is due to the opinion that they are able to
perform tasks like image and speech recognition that have
only been implemented in limited ways by traditional
computing methods.
This book includes invited lectures and the full
contributions to the International Workshop onArtificial
Neural Networks held in Granada, Spain, September 17-19,
1991. The workshop was sponsored by the IEEE Computer
Society, the Spanish Association for Computing and
Automatics, and the University of Granada. The contributions
were selected by an international program committee; the
authors of the papers come from 12 countries. The book is
organized in six sections, covering: - Neural network
theories and neural models - Biological perspectives -
Neural network architectures and algorithms - Software
developments and tools - Hardware implementations -
Applications.