EmerNet book: Emergent Neural Computational Architectures

[Stefan.Wermter]

Emergent Neural Computational Architectures
based on Neuroscience

Stefan Wermter, Jim Austin, David Willshaw
2001, Springer, Heidelberg, 577p

For more detailed information, table of contents, abstracts
and chapters see:

http://www.his.sunderland.ac.uk/emernet/newbook.html

Summary:
This book is the result of a series of International
Workshops organised by the EmerNet project on
Emergent Neural Computational Architectures based
on Neuroscience sponsored by the Engineering and
Physical Sciences Research Council (EPSRC). The
overall aim of the book is to present a broad spectrum
of current research into biologically inspired
computational systems and hence encourage the
emergence of new computational approaches based
on neuroscience. It is generally understood that the
present approaches for computing do not have the
performance, flexibility and reliability of biological
information processing systems. Although there is a
massive body of knowledge regarding how processing
occurs in the brain and central nervous system this has
had little impact on mainstream computing so far.

The process of developing biologically inspired
computerised systems involves the examination of the
functionality and architecture of the brain with an
emphasis on the information processing activities.
Biologically inspired computerised systems address
neural computation from the position of both
neuroscience, and computing by using experimental
evidence to create general neuroscience-inspired
systems.

The book focuses on the main research areas of
modular organisation and robustness, timing and
synchronisation, and learning and memory storage.
The issues considered as part of these include: How
can the modularity in the brain be used to produce
large scale computational architectures? How does
the human memory manage to continue to operate
despite failure of its components? How does the brain
synchronise its processing? How does the brain
compute with relatively slow computing elements but
still achieve rapid and real-time performance? How
can we build computational models of these processes
and architectures? How can we design incremental
learning algorithms and dynamic memory
architectures? How can the natural information
processing systems be exploited for artificial
computational methods?

Emergent Neural Computational Architectures based on
Neuroscience can be ordered from Springer-Verlag using the
booking form and accessed on-line using the appropriate login
and password from Springer.

http://www.his.sunderland.ac.uk/emernet/newbook.html
http://www.springer.de/cgi-bin/search_book.pl?isbn=3-540-42363-X
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Professor Stefan Wermter
Chair for Intelligent Systems
University of Sunderland
Centre of Informatics, SCET
St Peters Way
Sunderland SR6 0DD
United Kingdom

phone: +44 191 515 3279
fax:   +44 191 515 3553
email: stefan.wermter at sunderland.ac.uk
http://www.his.sunderland.ac.uk/~cs0stw/
http://www.his.sunderland.ac.uk/
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