Christof Teuscher
Turing's Connectionism
An Investigation of Neural Network Architectures
C. Teuscher. Turing's
Connectionism. An Investigation of Neural Network Architectures.
SpringerVerlag,
London, 2002. ISBN: 1852334754.
Catalog of new English books by SpringerVerlag that features
"Turing's Connectionism".
October issue, 1 page [55kB]
Description:
Turing's connectionism provides a detailed and indepth analysis of
Turing's almost forgotten ideas on connectionist machines. In a little
known paper entitled "Intelligent Machinery", Turing already
investigated connectionist models as early as 1948. Unfortunately, his
work was dismissed by his employer as a "schoolboy essay" and went
unpublished until 1968, 14 years after his death. In this book,
Christof Teuscher analyzes all aspects of Turing's "unorganized
machines". Turing himself also proposed a sort of genetic algorithm to
train the networks. This idea has been resumed by the author and
genetic algorithms are used to build and train Turing's unorganized
machines. Teuscher's work starts from Turing's initial ideas, but
importantly goes beyond them. Many new kinds of machines and new
aspects are considered, e.g., hardware implementation, analysis of the
complex dynamics of the networks, hypercomputation, and learning
algorithms.
Table of contents:
Download complete table of contents in pdf format. [55kB]
Foreword by B. J. Copeland and D. Proudfoot
Preface
Acknowledgments
INTRODUCTION:
Turing's Anticipation of Connectionism
Alan Mathison Turing
Connectionism and Artificial Neural Networks
Historical Context and Related Work
Organization of the Book
Book WebSite
INTELLIGENT MACHINERY:
Machines
Turing's Unorganized Machines
Formalization and Analysis of Unorganized Machines
New Unorganized Machines
Simulation of TBItype Machines with MATLAB
SYNTHESIS OF LOGICAL FUNCTIONS AND DIGITAL SYSTEMS
WITH TURING NETWORKS:
Combinational versus Sequential Systems
Synthesis of Logical Functions with Atype Networks
Synthesis of Logical Functions with TBtype Networks
Multiplexer and Demultiplexer
DelayUnit
ShiftRegister
How to Design Complex Systems
Hardware Implementation
ORGANIZING UNORGANIZED MACHINES:
Evolutionary Algorithms
Evolutionary Artificial Neural Networks
Example: Evolve Networks that Regenerate Bitstreams
Signal Processing in Turing Networks
Pattern Classification
Examples: Pattern Classification with Genetic Algorithms
A Learning Algorithm for Turing Networks
NETWORK PROPERTIES AND CHARACTERISTICS:
General Properties
Computational Power
State Machines
Threshold Logic
Dynamical Systems and the StateSpace Model
Random Boolean Networks
Attractors
Network Stability and Activity
Chaos, Bifurcation, and SelfOrganized Criticality
Topological Evolution and SelfOrganization
Hypercomputation: Computing Beyond the Turing Limit with
Turing's Neural Networks?
EPILOGUE
