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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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Linux+ Guide to Linux Certification
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Jason W Eckert, M John Schitka
Comp TIA has revised the Linux+ Certification to meet industry demands by reducing its focus on hardware terminology and increasing its focus on the configuration of network services and security. It has also been updated for use with Red Hat Fedora Core 2.
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Statistical Mechanics of Learning
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by
A Engel, C Van Den Broeck
Learning is one of the things that humans do naturally, and it has always been a challenge for us to understand the process. Nowadays this challenge has another dimension as we try to build machines that are able to learn and to undertake tasks such as datamining, image processing and pattern recognition. We can formulate a simple framework, ...
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Lab Manual for Network+ Guide to Networks, 4th
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by
Michael Grice
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Neural Networks for Pattern Recognition
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by
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 Computational Brain
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by
Patricia S Churchland, Terrence J Sejnowski
How do groups of neurons interact to enable the organism to see, decide, and move appropriately? What are the principles whereby networks of neurons represent and compute? These are the central questions probed by "The Computational Brain". Churchland and Sejnowski address the foundational ideas of the emerging field of computational neuroscience, ...
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Cellular Neural Networks and Visual Computing: Foundations and Applications
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by
Leon O Chua, Tamas Roska
Cellular Nonlinear/neural Network (CNN) technology is both a revolutionary concept and an experimentally proven new computing paradigm. Analogic cellular computers based on CNNs are set to change the way analog signals are processed and are paving the way to an entire new analog computing industry. This unique undergraduate level textbook includes ...
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Total Recall: How the E-Memory Revolution Will Change Everything
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by
Gordon Bell, C Gordon Bell, Jim Gemmell
Bell and Gemmell chronicle their 1998 experiment to record Bell's entire life digitally. Foreseeing the coming explosion of digital memory capacity and ubiquitous sensing devices, Bell set out to create a database of everything he did, saw, read, ate, felt--his whole life experience.
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Information Theory, Inference and Learning Algorithms
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by
David MacKay
Information theory and inference, taught together in this exciting textbook, lie at the heart of many important areas of modern technology - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics and cryptography. The book introduces theory in tandem with applications. ...
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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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Neural and Adaptive Systems: Fundamentals Through Simulations
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by
Jos? C Principe, Neil R Euliano, W Curt Lefebvre
Develop New Insight into the Behavior of Adaptive Systems This one-of-a-kind interactive book and CD-ROM will help you develop a better understanding of the behavior of adaptive systems. Developed as part of a project aimed at innovating the teaching of adaptive systems in science and engineering, it unifies the concepts of neural networks and ...
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Fundamentals of Neural Networks: Architectures, Algorithms and Applications
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by
Laurene V Fausett
An exceptionally clear, thorough introduction to neural networks written at an elementary level. Written with the beginning student in mind, the text features systematic discussions of all major neural networks and fortifies the reader's understanding with many examples. An exceptionally clear, thorough introduction to neural networks written at ...
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Cognizers: Neural Networks and Machines That Think
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R. Colin Johnson, Chappell Brown
One of the most dramatic developments in computer science has been the effort to create machines that duplicate the neurotransmitter biology of the human brain. Describing for the general reader how human neural networks work, the authors explain in this text how this new technology could be the breakthrough that makes artificial intelligence a ...
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Neural Networks and Learning Machines
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by
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. Refocused, revised ...
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Feedback Networks: Theory and Circuit Applications
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by
John Choma, W K Chen
This book addresses the theoretical and practical circuit and system concepts that underpin the design of reliable and reproducible, high performance, monolithic feedback circuits. It is intended for practicing electronics engineers and students who wish to acquire an insightful understanding of the ways in which open loop topologies, closed loop ...
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Building Neural Networks
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by
David M Skapura, Peter S Gordon (Editor)
This practical introduction describes the kinds of real-world problems neural network technology can solve. Surveying a range of neural network applications, the book demonstrates the construction and operation of artificial neural systems. Through numerous examples, the author explains the process of building neural-network applications that ...
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Neural Networks and Fuzzy Systems: A Dynamical Systems Approach to Machine Intelligence
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by
Bart Kosko, Ph.D.
Combining neural networks and fuzzy systems, this presents neural networks as trainable dynamical systems and develops mechanisms and principles of adaption, self-organization, covergence and global stability. It also includes the new geometric theory of fuzzy sets, systems and associative memories. Kosko shows how to apply fuzzy theory to ...
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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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Neural Networks in C++: An Object-Oriented Framework for Building Connectionist Systems
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by
Adam Blum
Following an introduction to neural networks, this text describes the basics of object-orientation for potential users. Sample applications are developed and demonstrated in a variety of areas, including image recognition, text processing and forecasting. Program listings for the these applications are provided in their entirety using Borland C++ ...
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Neural Network and Fuzzy Logic Applications in C/C++
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by
Stephen T Welstead
Using an engineering and science perspective, it explores diverse neural network, fuzzy logic and genetic algorithm techniques, plus developing applications best suited for each of the methods discussed. Sample results are described and judgment made as to how well each application worked. The book/disk set includes an object-oriented user ...
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Talking Nets: An Oral History of Neural Networks
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by
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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Naturally Intelligent Systems
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by
Maureen Caudill, Charles Butler
For centuries, people have been fascinated by the possibility of building an artificial system that behaves intelligently. Now there is a new entry in this arena - neural networks. "Naturally Intelligent Systems" offers a comprehensive introduction to these exciting systems. It provides a technically accurate, yet down-to-earth discussion of ...
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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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An Introduction to the Modeling of Neural Networks
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by
Peretto
This text is a beginning graduate-level introduction to neural networks, focussing on current theoretical models, examining what these models can reveal about how the brain functions, and discussing the ramifications for psychology, artificial intelligence and the construction of a new generation of intelligent computers. The book is divided into ...
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Darwin Among the Machines: The Evolution of Global Intelligence
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by
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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