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Foreword by B.J. Copeland and D. Proudfoot.- INTRODUCTION: Turing's Anticipation of Connectionism. Alan Mathison Turing. Connectionism and Artificial Neural Networks. Historical Context and Related Work. Organization of the Book. Book Web-Site.- INTELLIGENT MACHINERY: Machines. Turing's Unorganized Machines. Formalization and Analysis of Unorganized Machines. New Unorganized Machines. Simulation of TBI-type Machines with MATLAB.- SYNTHESIS OF LOGICAL FUNCTIONS AND DIGITAL SYSTEMS WITH TURING NETWORKS: Combinational versus Sequential Systems. Synthesis of Logical Functions with A-type Networks. Synthesis of Logical Functions with TB-type Networks. Multiplexer and Demultiplexer. Delay-Unit. Shift-Register. 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 State-Space Model. Random Boolean Networks. Attractors. Network Stability and Activity. Chaos, Bifurcation, and Self-Organized Criticality. Topological Evolution and Self-Organization. Hypercomputation: Computing Beyond the Turing Limit with Turing's Neural Networks?- EPILOGUE.
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Lance Smith
reviewed Turing's Connectionism: An Investigation of Neural Network Architectures on January 09, 2010
Turing's Connectionism: An Investigation of Neural Network Architectures
This book grew out of a set of course notes for a neural networks module given as part of a Masters degree in "Intelligent Systems". The people on this course came from a wide variety of intellectual backgrounds (from philosophy, through psychology to computer science and engineering) and the author knew that he could not count on their being able to come to grips with the largely technical and mathematical approach which is often used (and in some ways easier to do). As a result he was forced to look carefully at the basic conceptual principles at work in the subject and try to recast these using ordinary language, drawing on the use of physical metaphors or analogies, and pictorial or graphical representations. I was pleasantly surprised to find that, as a result of this process, my own understanding was considerably deepened; I had now to unravel, as it were, condensed formal descriptions and say exactly how these were related to the "physical" world of artificial neurons, signals, computational processes, etc. However, the author was acutely aware that, while a litany of equations does not constitute a full description of fundamental principles, without some mathematics, a purely descriptive account runs the risk of dealing only with approximations and cannot be sharpened up to give any formulaic prescriptions. Therefore, the book introduced what author believed was just sufficient mathematics to bring the basic ideas into sharp focus.
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Add Turing's Connectionism: An Investigation of Neural Network Architectures, Christof Teuscher revives, analyzes, and simulates Turing's ideas, applying them to different types of problems, and building and training Turing's machines using evolutionary algorithms. In a little known paper entitled 'Intelligent Machinery' Turing inv, Turing's Connectionism: An Investigation of Neural Network Architectures to the inventory that you are selling on WonderClubX
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Add Turing's Connectionism: An Investigation of Neural Network Architectures, Christof Teuscher revives, analyzes, and simulates Turing's ideas, applying them to different types of problems, and building and training Turing's machines using evolutionary algorithms. In a little known paper entitled 'Intelligent Machinery' Turing inv, Turing's Connectionism: An Investigation of Neural Network Architectures to your collection on WonderClub |
