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On Intelligence
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by
Jeff Hawkins, Sandra Blakeslee
From the inventor of the PalmPilot comes a new and compelling theory of intelligence, brain function, and the future of intelligent machines. Written with acclaimed science writer Blakeslee, this text promises to transfigure the possibilities of the technology age.
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Neural Networks: A Comprehensive Foundation
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Simon Haykin
For graduate-level neural network courses offered in the departments of Computer Engineering, Electrical Engineering, and Computer Science. Renowned for its thoroughness and readability, this well-organized and completely up-to-date text remains the most comprehensive treatment of neural networks from an engineering perspective. Thoroughly ...
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Darwin Among the Machines: The Evolution of Global Intelligence
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George Dyson
} Darwin Among the Machines retraces the steps that led us into the digital wilderness, no less wild for being a universe of our own device. Introducing a cast of known and unknown characters, George B. Dyson traces the course of the information revolution, illuminating the lives and work of visionaries-from the time of Thomas Hobbes to the time ...
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Neuro-Fuzzy and Soft Computing: A Computational Approach to Learning and Machine Intelligence
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Jyh-Shing Roger Jang, J S R Jang, Chuen-Tsai Sun
Intended for use in courses on computational intelligence at either the college senior or first-year graduate level. This text provides the first comprehensive treatment of the methodologies underlying neuro-fuzzy and soft computing, an evolving branch within the scope of computational intelligence. The book places equal emphasis on theoretical ...
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Neural Networks and Natural Intelligence
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Stephen Grossberg
Stephen Grossberg and his colleagues at Boston University's Center for Adaptive Systems are producing some of the most exciting research in the neural network approach to making computers "think." Packed with real-time computer simulations and rigorous demonstrations of these phenomena, this book includes results on vision, speech, cognitive ...
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Neural Networks for Pattern Recognition
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Christopher M Bishop
This book provides the first comprehensive treatment of feed-forward neural networks from the perspective of statistical pattern recognition. After introducing the basic concepts of pattern recognition, the book describes techniques for modelling probability density functions, and discusses the properties and relative merits of the multi-layer ...
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The Neural Simulation Language: A System for Brain Modeling
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Alfredo Weitzenfeld, Michael A Arbib, Amanda Alexander
This volume provides a simulation environment for modular brain modeling. Neural Simulation Language (NSL) is an object-oriented language offering object-oriented protocols applicable to all levels of neural simulation. One of NSL's main strengths is that it allows for realistic modeling of the anatomy of macroscopic brain structures. The book is ...
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Artificial Life: A Report from the Frontier Where Computers Meet Biology
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by
Steven Levy
Even as molecular biologists attempt to reproduce life in vitro, another group of scientists is creating life--or something very close to it--in silico, using computers to produce "organisms" that can move, see, feed, reproduce, and die. Photos.
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Talking Nets: An Oral History of Neural Networks
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James A Anderson (Editor), Edward Rosenfeld (Editor)
Since World War II, a group of scientists has been attempting to understand the human nervous system and to build computer systems that emulate the brain's abilities. Many of the early workers in this field of neural networks came from cybernetics; others came from neuroscience, physics, electrical engineering, mathematics, psychology, even ...
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Neural Network Design
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by
Beale Hagan Demuth, Mark Beale, Martin T Hagan
This guide to neural networks includes worked problems in each chapter, and supporting software demonstrations. The authors of this work also developed the neural networks toolbox (for MathWorks) and the fuzzy systems toolbox (for PWS).
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Imitation of Life: How Biology Is Inspiring Computing
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by
Nancy Forbes
As computers and the tasks they perform become increasingly complex, researchers are looking to nature - as model and as metaphor - for inspiration. The organisation and behaviour of biological organisms present scientists with an invitation to reinvent computing for the complex tasks of the future. In Imitation of Life Nancy Forbes surveys the ...
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Artificial Life
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by
Steven Levy
The quest for artificial life is science's urgent mission to create new forms of life within computers and other artificial environments. The remarkable ability of computers to depict a system as it develops has given scientists a new way to look at evolution, intelligence, reproduction, and other key characteristics of life. Illustrations.
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Self-Organizing Maps
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by
Kohonen
The Self-Organizing Map (SOM), with its variants, is the most popular artificial neural network algorithm in the unsupervised learning category. Many fields of science have adopted the SOM as a standard analytical tool: in statistics, signal processing, control theory, financial analyses, experimental physics, chemistry and medicine. A new area is ...
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Fuzzy Logic and Neurofuzzy Applications Explained
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by
Constantin Von Altrock
A practical, step-by-step guide to fuzzy logic and NeuroFuzzy design on the PC using more than 30 case studies in a wide range of industries and applications. Includes two disks of simulation software for Microsoft Windows. Annotation copyright Book News, Inc. Portland, Or.
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In the Image of the Brain: Breaking the Barrier Between the Human Mind and Intelligent Machines
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by
Jim Jubak
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Enchanted Looms: Conscious Networks in Brains and Computers
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by
Rodney M J Cotterill
The title of this book was inspired by a passage in Charles Sherrington's Man on his Nature. When that famous physiologist died in 1952, the prospects for a scientific explanation of consciousness seemed remote. Enchanted Looms shows how the situation has changed dramatically, and provides what is probably the most wide-ranging account of the ...
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Learning from Data: Concepts, Theory, and Methods
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by
Vladimir Cherkassky, Filip M Mulier
An interdisciplinary framework for learning methodologies-covering statistics, neural networks, and fuzzy logic This book provides a unified treatment of the principles and methods for learning dependencies from data. It establishes a general conceptual framework in which various learning methods from statistics, neural networks, and fuzzy logic ...
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Neural Network Perspectives on Cognition and Adaptive Robotics
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by
Antony Browne
Featuring an international team of authors, "Neural Network Perspectives on Cognition and Adaptive Robotics" presents several approaches to the modeling of human cognition and language using neural computing techniques. It also describes how adaptive robotic systems can be produced using neural network architectures. Covering a wide range of ...
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C++ Neural Networks and Fuzzy Logic
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by
Valluru B Rao
This text teaches the core concepts of fuzzy logic and neural network technologies, including back propagation and adaptive resonance theory. It includes practical applications demonstrating pattern recognition, optimization and financial modelling. The disk includes all the source code discussed.
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Pattern Recognition and Neural Networks
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by
Brian D Ripley
Now in paperback: the most reliable account of the statistical framework for pattern recognition and machine learning. With unparalleled coverage and a wealth of case-studies this book gives valuable insight into both the theory and the enormously diverse applications (which can be found in remote sensing, astrophysics, engineering and medicine, ...
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Theory of Neural Information Processing Systems
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by
A C C Coolen, R Kuehn, P Sollich
Theory of Neural Information Processing Systems provides an explicit, coherent, and up-to-date account of the modern theory of neural information processing systems. It has been carefully developed for graduate students from any quantitative dsicipline, including mathematics, computer science, physics, engineering or biology, and has been ...
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Neural Networks: An Introduction
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by
Berndt Muller, Klaus Schulten (Editor), J L Van Hemmen (Editor)
Neural Networks presents concepts of neural-network models and techniques of parallel distributed processing in a three-step approach: - A brief overview of the neural structure of the brain and the history of neural-network modeling introduces to associative memory, preceptrons, feature-sensitive networks, learning strategies, and practical ...
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Digital Neural Networks
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by
Sun-Yuang Kung
Covering the fundamental theory and practical implementation of various neural models, this text provides a coherent exploration and a well structured presentation of the three most important aspects of the neural networks: application, algorithm and architecture. It offers working knowledge of the various neural models, the fundamental ...
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Mathematical Aspects of Spin Glasses and Neural Networks
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by
Anton Bovier
Aimed at graduates and potential researchers, this is a comprehensive introduction to the mathematical aspects of spin glasses and neural networks. It should be useful to mathematicians in probability theory and theoretical physics, and to engineers working in theoretical computer science.
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Models of Neural Networks II: Temporal Aspects of Coding and Information Processing in Biological Systems
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by
Eytan Domany (Editor), J Leo Van Hemmen (Editor), Klaus Schulten (Editor)
The theory of neural nets has two new paradigms: information coding through coherent firing of the neurons and structural feedback. As compared to traditional neural nets, spiking neurons provide an extra degree of freedom: time; this degree of freedom is realized by a coherent spiking of extensively many neurons in the network, a nonlinear ...
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