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Plausible Neural Networks for Biological Modelling (Hardcover, 2001 ed.)
Loot Price: R3,173
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Plausible Neural Networks for Biological Modelling (Hardcover, 2001 ed.)
Series: Mathematical Modelling: Theory and Applications, 13
Expected to ship within 10 - 15 working days
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This book has the unique intention of returning the mathematical
tools of neural networks to the biological realm of the nervous
system, where they originated a few decades ago. It aims to
introduce, in a didactic manner, two relatively recent developments
in neural network methodology, namely recurrence in the
architecture and the use of spiking or integrate-and-fire neurons.
In addition, the neuro-anatomical processes of synapse modification
during development, training, and memory formation are discussed as
realistic bases for weight-adjustment in neural networks. While
neural networks have many applications outside biology, where it is
irrelevant precisely which architecture and which algorithms are
used, it is essential that there is a close relationship between
the network's properties and whatever is the case in a
neuro-biological phenomenon that is being modelled or simulated in
terms of a neural network. A recurrent architecture, the use of
spiking neurons and appropriate weight update rules contribute to
the plausibility of a neural network in such a case. Therefore, in
the first half of this book the foundations are laid for the
application of neural networks as models for the various biological
phenomena that are treated in the second half of this book. These
include various neural network models of sensory and motor control
tasks that implement one or several of the requirements for
biological plausibility.
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