Neural Networks Knowledge Representation (24 results)

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Taschenbuch. Condition: Neu. Knowledge Extraction with Neural Networks | Significant Patterns and their Representation in Back-Propagation Networks | Iveta Mrazova | Taschenbuch | 176 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783844329414 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.…

Condition: New. Daniel S. Levine, Manuel Aparicio IVThe second published collection based on a conference sponsored by the Metroplex Institute for Neural Dynamics -- the first is Motivation, Emotion, and Goal Direction in Neural Networks (LEA, 1992) -- th.

Softcover/Taschenbuch. Condition: Neu. Recent turbulences of global economy impose strong requirements on efficiency, flexibility, and reliability of new products and services. Unfortunately, for most techniques applicable to the design of complex adaptive systems - artificial neural networks, fuzzy logic, cluster analysis, etc. - it is still complicated to interpret what they are actually doing - especially when processing large sets of high-dimensional data. Yet understanding and correct interpretation of the knowledge extracted by the applied model represent decisive issues for the ability to detect significant, e.g. novel input patterns, to identify their characteristic features and to assess their future development. This book provides new means to handle these problems with artificial neural networks of the Back-Propagation type. Two case studies involving image classification and analysis of economical data provided by the World Bank should help shed some light on this new and exciting area, and could be useful to professionals in the field of data mining, image processing and adaptive systems, or anyone else who may be considering applying neural networks for knowledge extraction e.g. in marketing. Sprache: Englisch Gewicht in Gramm: 280.…

Buch. Condition: Neu. Neuware - The second published collection based on a conference sponsored by the Metroplex Institute for Neural Dynamics -- the first is Motivation, Emotion, and Goal Direction in Neural Networks (LEA, 1992) -- this book addresses the controversy between symbolicist artificial intelligence and neural network theory. A particular issue is how well neural networks -- well established for statistical pattern matching -- can perform the higher cognitive functions that are more often associated with symbolic approaches. This controversy has a long history, but recently erupted with arguments against the abilities of renewed neural network developments. More broadly than other attempts, the diverse contributions presented here not only address the theory and implementation of artificial neural networks for higher cognitive functions, but also critique the history of assumed epistemologies -- both neural networks and AI -- and include several neurobiological studies of human cognition as a real system to guide the further development of artificial ones. Organized into four major sections, this volume: \* outlines the history of the AI/neural network controversy, the strengths and weaknesses of both approaches, and shows the various capabilities such as generalization and discreetness as being along a broad but common continuum; \* introduces several explicit, theoretical structures demonstrating the functional equivalences of neurocomputing with the staple objects of computer science and AI, such as sets and graphs; \* shows variants on these types of networks that are applied in a variety of spheres, including reasoning from a geographic database, legal decision making, story comprehension, and performing arithmetic operations; \* discusses knowledge representation process in living organisms, including evidence from experimental psychology, behavioral neurobiology, and electroencephalographic responses to sensory stimuli.…

Condition: Sehr gut. Zustand: Sehr gut | Seiten: 528 | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.

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Condition: New. Print on Demand pp. 528 This item is printed on demand.

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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Recent turbulences of global economy impose strong requirements on efficiency, flexibility, and reliability of new products and services. Unfortunately, for most techniques applicable to the design of complex adaptive systems artificial neural networks, fuzzy logic, cluster analysis, etc. it is still complicated to interpret what they are actually doing especially when processing large sets of high-dimensional data. Yet understanding and correct interpretation of the knowledge extracted by the applied model represent decisive issues for the ability to detect significant, e.g. novel input patterns, to identify their characteristic features and to assess their future development. This book provides new means to handle these problems with artificial neural networks of the Back-Propagation type. Two case studies involving image classification and analysis of economical data provided by the World Bank should help shed some light on this new and exciting area, and could be useful to professionals in the field of data mining, image processing and adaptive systems, or anyone else who may be considering applying neural networks for knowledge extraction e.g. in marketing.…