Background
Caudill, Maureen was born on July 14, 1951 in Portsmouth, Ohio, United States. Daughter of Elmon C. and Harriet L. (Sisler) Caudill.
(Understanding Neural Networks is a textbook and workbook ...)
Understanding Neural Networks is a textbook and workbook that provides a unique interactive learning environment. With or without the aid of a classroom instructor, it allows students and other users to learn about neural networks while gaining practical, hands-on experience with all of the leading network models. Each model is presented as realistically as possible. Also included are chapter exercises and questions, many with illustrations. The key feature of this workbook is the software. Available for PC-ATs and compatibles and the Macintosh, these disks contain a collection of full-featured commercial-quality simulators for the most important network paradigms. The user interface is graphic and easy to use, and the simulators are consistent across all networks. The simulators can also build and train significantly large networks, allowing users to construct networks on their own with data relevant to their problems. Volume 1 covers learning, attractor networks, and hierarchical networks (including back-propagation networks). Volume 2 takes up temporal networks (including recurrent networks), self-organizing networks, higher-order networks, and such new directions in neural networks as fuzzy networks and evolutionary networks. Both volumes contain instructions on how to use the workbook, an introduction, appendixes, a table of random numbers, a glossary, a bibliography, and index.
http://www.amazon.com/gp/product/0262531003/?tag=2022091-20
(Understanding Neural Networks is a textbook and workbook ...)
Understanding Neural Networks is a textbook and workbook that provides a unique interactive learning environment. With or without the aid of a classroom instructor, it allows students and other users to learn about neural networks while gaining practical, hands-on experience with all of the leading network models. Each model is presented as realistically as possible. Also included are chapter exercises and questions, many with illustrations. The key feature of this workbook is the software. Available for PC-ATs and compatibles and the Macintosh, these disks contain a collection of full-featured commercial-quality simulators for the most important network paradigms. The user interface is graphic and easy to use, and the simulators are consistent across all networks. The simulators can also build and train significantly large networks, allowing users to construct networks on their own with data relevant to their problems. Volume 1 covers learning, attractor networks, and hierarchical networks (including back-propagation networks). Volume 2 takes up temporal networks (including recurrent networks), self-organizing networks, higher-order networks, and such new directions in neural networks as fuzzy networks and evolutionary networks. Both volumes contain instructions on how to use the workbook, an introduction, appendixes, a table of random numbers, a glossary, a bibliography, and index.
http://www.amazon.com/gp/product/026253102X/?tag=2022091-20
(Understanding Neural Networks is a textbook and workbook ...)
Understanding Neural Networks is a textbook and workbook that provides a unique interactive learning environment. With or without the aid of a classroom instructor, it allows students and other users to learn about neural networks while gaining practical, hands-on experience with all of the leading network models. Each model is presented as realistically as possible. Also included are chapter exercises and questions, many with illustrations. The key feature of this workbook is the software. Available for PC-ATs and compatibles and the Macintosh, these disks contain a collection of full-featured commercial-quality simulators for the most important network paradigms. The user interface is graphic and easy to use, and the simulators are consistent across all networks. The simulators can also build and train significantly large networks, allowing users to construct networks on their own with data relevant to their problems. Volume 1 covers learning, attractor networks, and hierarchical networks (including back-propagation networks). Volume 2 takes up temporal networks (including recurrent networks), self-organizing networks, higher-order networks, and such new directions in neural networks as fuzzy networks and evolutionary networks. Both volumes contain instructions on how to use the workbook, an introduction, appendixes, a table of random numbers, a glossary, a bibliography, and index.
http://www.amazon.com/gp/product/0262530996/?tag=2022091-20
( For centuries, people have been fascinated by the possi...)
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 neural networks, clearly explaining the underlying concepts of key neural network designs, how they are trained, and why they work. Throughout, the authors present actual applications that illustrate neural networks' utility in the new world.
http://www.amazon.com/gp/product/0262531135/?tag=2022091-20
(Understanding Neural Networks is a textbook and workbook ...)
Understanding Neural Networks is a textbook and workbook that provides a unique interactive learning environment. With or without the aid of a classroom instructor, it allows students and other users to learn about neural networks while gaining practical, hands-on experience with all of the leading network models. Each model is presented as realistically as possible. Also included are chapter exercises and questions, many with illustrations. The key feature of this workbook is the software. Available for PC-ATs and compatibles and the Macintosh, these disks contain a collection of full-featured commercial-quality simulators for the most important network paradigms. The user interface is graphic and easy to use, and the simulators are consistent across all networks. The simulators can also build and train significantly large networks, allowing users to construct networks on their own with data relevant to their problems. Volume 1 covers learning, attractor networks, and hierarchical networks (including back-propagation networks). Volume 2 takes up temporal networks (including recurrent networks), self-organizing networks, higher-order networks, and such new directions in neural networks as fuzzy networks and evolutionary networks. Both volumes contain instructions on how to use the workbook, an introduction, appendixes, a table of random numbers, a glossary, a bibliography, and index.
http://www.amazon.com/gp/product/0262531038/?tag=2022091-20
(From Arnold Schwarzenegger's Terminator, to C-3PO of the ...)
From Arnold Schwarzenegger's Terminator, to C-3PO of the Star Wars trilogy, to the comic robot-butler in Woody Allen's Sleeper, the "android" has long been a familiar figure on the American imaginative landscape. But how far removed from reality are such fictitious creations? Will there ever be an intelligent robot in our future? Neural networks expert Maureen Caudill says yes. In fact, she argues that the development of intelligent androids is a mere twenty years away. In Our Own Image reveals just how far we've come in developing an intelligent robot, describes what technical obstacles must still be cleared, and--perhaps most interesting of all--outlines the potentially massive social disruptions and tangled moral and legal dilemmas these "human machines" will cause. In a sweeping look at state-of-the-art breakthroughs in artificial intelligence, robotics, computer science, psychology, and neural networks, Caudill shows how these fields have advanced machine vision, language recognition, problem solving, memory, and other requisites of intelligent robots. She describes foot-long mechanical ants that can follow you around a room, robots that can crack eggs, shear sheep, play ping-pong, tighten wing-nuts, and other feats of dexterity. (One robot, WABOT-2, developed in Japan, can read simple sheet music and played the electric organ with the NHK Symphony Orchestra of Japan.) electric organ.) And she concludes that as our ability to make faster, smaller, cheaper computers blends with our ability to mimic the behavior of the human mind, the first truly intelligent machines come closer to fruition. But once an android has been perfected, Caudill warns, there will likely be some unexpected--and perhaps unpleasant--social changes. Androids may compete with human workers for jobs--and robots won't take vacations, won't have family problems, and might never leave the firm. Androids may also entangle our legal system in complex, difficult questions: Can an individual own an intelligent android? What rights should it have in society? Does ownership of an android imply the right to turn it off--the right to "kill" it? And does such ownership brand us as slaveholders? The existence of intelligent androids will provoke these and other questions. Caudill concludes that we will soon be forced to come up with answers if we are to learn to share the world with another intelligent species--one of our own creation.
http://www.amazon.com/gp/product/019507338X/?tag=2022091-20
(When Lyssa Cooper decides it's time to settle down, littl...)
When Lyssa Cooper decides it's time to settle down, little does she expect that the playboy-next-door would turn out to be the man of her dreams. Original.
http://www.amazon.com/gp/product/0553445553/?tag=2022091-20
writer and computer consultant
Caudill, Maureen was born on July 14, 1951 in Portsmouth, Ohio, United States. Daughter of Elmon C. and Harriet L. (Sisler) Caudill.
Bachelor, University Connecticut, 1973. Master of Arts in Teaching, Cornell University, 1974.
Customer engineer, Raytheon Data Systems, Wellesley, Massachusetts, 1975-1978;
member technical sales support staff, Hewlett-Packard Company, Wallingford, Connecticut, 1978-1981;
project programmer, Gould Ocean Systems division, Cleveland, 1982-1983;
senior software engineer, Data Systems division General Dynamics Company, San Diego, 1983-1985;
computer consultant, Rockwell International, Hughes Aircraft Corporation, Honeywell Corporation, other corporations, 1985-1989;
founder, computer consultant, Adaptics, San Diego, 1987-1989;
engineering specialist space systems division, General Dynamics, San Diego, 1989-1990;
manager technical and applications support, Science Applications International Corporation, 1990-1991;
owner, consultant, writer, NeuWorld Superior vena cava syndrome, San Diego, 1991-1993;
co-founder, director research, NeuWorld Finance, San Diego, 1993-1996. Organizer annual meetings on neural networks, San Diego, Boston, Washington, Seattle, 1987-1990. Instructor San Diego Extension in Intelligent Systems Technologies University of California, since 1990.
Presenter on neural networks, United States, Japan, Mexico, also others, since 1987.
(From Arnold Schwarzenegger's Terminator, to C-3PO of the ...)
(When Lyssa Cooper decides it's time to settle down, littl...)
( For centuries, people have been fascinated by the possi...)
(Understanding Neural Networks is a textbook and workbook ...)
(Understanding Neural Networks is a textbook and workbook ...)
(Understanding Neural Networks is a textbook and workbook ...)
(Understanding Neural Networks is a textbook and workbook ...)
Member Institute of Electrical and Electronics Engineers. F C.