Now, for the first time, publication of the landmark work in
backpropagation Scientists, engineers, statisticians, operations
researchers, and other investigators involved in neural networks
have long sought direct access to Paul Werbos's groundbreaking,
much-cited 1974 Harvard doctoral thesis, The Roots of
Backpropagation, which laid the foundation of backpropagation. Now,
with the publication of its full text, these practitioners can go
straight to the original material and gain a deeper, practical
understanding of this unique mathematical approach to social
studies and related fields. In addition, Werbos has provided three
more recent research papers, which were inspired by his original
work, and a new guide to the field. Originally written for readers
who lacked any knowledge of neural nets, The Roots of
Backpropagation firmly established both its historical and
continuing significance as it:
* Demonstrates the ongoing value and new potential of
backpropagation
* Creates a wealth of sound mathematical tools useful across
disciplines
* Sets the stage for the emerging area of fast automatic
differentiation
* Describes new designs for forecasting and control which exploit
backpropagation
* Unifies concepts from Freud, Jung, biologists, and others into a
new mathematical picture of the human mind and how it works
* Certifies the viability of Deutsch's model of nationalism as a
predictive tool--as well as the utility of extensions of this
central paradigm
"What a delight it was to see Paul Werbos rediscover Freud's
version of 'back-propagation.' Freud was adamant (in The Project
for a Scientific Psychology) that selective learning could only
take place if the presynaptic neuron was as influenced as is the
postsynaptic neuron during excitation. Such activation of both
sides of the contact barrier (Freud's name for the synapse) was
accomplished by reducing synaptic resistance by the absorption of
'energy' at the synaptic membranes. Not bad for 1895 But Werbos
1993 is even better." --Karl H. Pribram Professor Emeritus,
Stanford University
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