Acquire the tools for understanding new architectures and algorithms of dynamical recurrent networks (DRNs) from this valuable field guide, which documents recent forays into artificial intelligence, control theory, and connectionism. This unbiased introduction to DRNs and their application to time-series problems (such as classification and prediction) provides a comprehensive overview of the recent explosion of leading research in this prolific field.
A Field Guide to Dynamical Recurrent Networks emphasizes the issues driving the development of this class of network structures. It provides a solid foundation in DRN systems theory and practice using consistent notation and terminology. Theoretical presentations are supplemented with applications ranging from cognitive modeling to financial forecasting.
A Field Guide to Dynamical Recurrent Networks will enable engineers, research scientists, academics, and graduate students to apply DRNs to various real-world problems and learn about different areas of active research. It provides both state-of-the-art information and a road map to the future of cutting-edge dynamical recurrent networks.
"synopsis" may belong to another edition of this title.
About the Editors John F. Kolen has explored the computational capabilities of dynamical recurrent networks on a wide range of projects: computer tomography of ballistic tests, autonomous science on extraterrestrial sensor platforms, and laser marksmanship modeling. His research interests include neural networks, distributed processing, philosophy of computation, and computer gaming. Dr. Kolen is a member of the Institute for Human and Machine Cognition at the University of West Florida.
Stefan C. Kremer's research interests include connectionist networks (the subject of his 1996 thesis "A Theory of Grammatical Induction in the Connectionist Paradigm"), genetic algorithms, signal processing, grammar induction, and image processing. He is an assistant professor of computing and information science at the University of Guelph, Ontario, Canada, and is a founding member of the Guelph Natural Computation Research Group.
Electrical Engineering A Field Guide to Dynamical Recurrent Networks Acquire the tools for understanding new architectures and algorithms of dynamical recurrent networks (DRNs) from this valuable field guide, which documents recent forays into artificial intelligence, control theory, and connectionism. This unbiased introduction to DRNs and their application to time-series problems (such as classification and prediction) provides a comprehensive overview of the recent explosion of leading research in this prolific field. A Field Guide to Dynamical Recurrent Networks emphasizes the issues driving the development of this class of network structures. It provides a solid foundation in DRN systems theory and practice using consistent notation and terminology. Theoretical presentations are supplemented with applications ranging from cognitive modeling to financial forecasting. A Field Guide to Dynamical Recurrent Networks will enable engineers, research scientists, academics, and graduate students to apply DRNs to various real-world problems and learn about different areas of active research. It provides both state-of-the-art information and a road map to the future of cutting-edge dynamical recurrent networks.
Electrical Engineering A Field Guide to Dynamical Recurrent Networks Acquire the tools for understanding new architectures and algorithms of dynamical recurrent networks (DRNs) from this valuable field guide, which documents recent forays into artificial intelligence, control theory, and connectionism. This unbiased introduction to DRNs and their application to time-series problems (such as classification and prediction) provides a comprehensive overview of the recent explosion of leading research in this prolific field. A Field Guide to Dynamical Recurrent Networks emphasizes the issues driving the development of this class of network structures. It provides a solid foundation in DRN systems theory and practice using consistent notation and terminology. Theoretical presentations are supplemented with applications ranging from cognitive modeling to financial forecasting. A Field Guide to Dynamical Recurrent Networks will enable engineers, research scientists, academics, and graduate students to apply DRNs to various real-world problems and learn about different areas of active research. It provides both state-of-the-art information and a road map to the future of cutting-edge dynamical recurrent networks.
"About this title" may belong to another edition of this title.
Seller: Brook Bookstore On Demand, Napoli, NA, Italy
Condition: new. Seller Inventory # 59fa65bee14d4a1534c19ee9a7e99989
Quantity: Over 20 available
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000. Seller Inventory # FW-9780780353695
Quantity: 15 available
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
Hardback. Condition: New. Acquire the tools for understanding new architectures and algorithms of dynamical recurrent networks (DRNs) from this valuable field guide, which documents recent forays into artificial intelligence, control theory, and connectionism. This unbiased introduction to DRNs and their application to time-series problems (such as classification and prediction) provides a comprehensive overview of the recent explosion of leading research in this prolific field. A Field Guide to Dynamical Recurrent Networks emphasizes the issues driving the development of this class of network structures. It provides a solid foundation in DRN systems theory and practice using consistent notation and terminology. Theoretical presentations are supplemented with applications ranging from cognitive modeling to financial forecasting. A Field Guide to Dynamical Recurrent Networks will enable engineers, research scientists, academics, and graduate students to apply DRNs to various real-world problems and learn about different areas of active research. It provides both state-of-the-art information and a road map to the future of cutting-edge dynamical recurrent networks. Seller Inventory # LU-9780780353695
Quantity: 2 available
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Condition: New. In English. Seller Inventory # ria9780780353695_new
Quantity: Over 20 available
Seller: Majestic Books, Hounslow, United Kingdom
Condition: New. pp. xxx + 421 Illus. Seller Inventory # 7471653
Quantity: 3 available
Seller: Chiron Media, Wallingford, United Kingdom
Hardcover. Condition: New. Seller Inventory # 6666-WLY-9780780353695
Quantity: Over 20 available
Seller: Books Puddle, New York, NY, U.S.A.
Condition: New. pp. xxx + 421. Seller Inventory # 26376314
Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
Condition: New. Editor(s): Kolen, John F.; Kremer, Stefan C. Num Pages: 464 pages. BIC Classification: TJK; UYQN. Category: (P) Professional & Vocational. Dimension: 252 x 185 x 28. Weight in Grams: 950. . 2001. 1st Edition. Hardcover. . . . . Seller Inventory # V9780780353695
Quantity: Over 20 available
Seller: Revaluation Books, Exeter, United Kingdom
Hardcover. Condition: Brand New. 1st edition. 464 pages. 10.00x7.00x1.00 inches. In Stock. Seller Inventory # __0780353692
Quantity: 2 available
Seller: Rarewaves.com UK, London, United Kingdom
Hardback. Condition: New. Acquire the tools for understanding new architectures and algorithms of dynamical recurrent networks (DRNs) from this valuable field guide, which documents recent forays into artificial intelligence, control theory, and connectionism. This unbiased introduction to DRNs and their application to time-series problems (such as classification and prediction) provides a comprehensive overview of the recent explosion of leading research in this prolific field. A Field Guide to Dynamical Recurrent Networks emphasizes the issues driving the development of this class of network structures. It provides a solid foundation in DRN systems theory and practice using consistent notation and terminology. Theoretical presentations are supplemented with applications ranging from cognitive modeling to financial forecasting. A Field Guide to Dynamical Recurrent Networks will enable engineers, research scientists, academics, and graduate students to apply DRNs to various real-world problems and learn about different areas of active research. It provides both state-of-the-art information and a road map to the future of cutting-edge dynamical recurrent networks. Seller Inventory # LU-9780780353695
Quantity: 2 available