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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Neuromorphic Intelligence | Learning, Architectures and Large-Scale Systems | Shuangming Yang (u. a.) | Taschenbuch | Synthesis Lectures on Engineering, Science, and Technology | xix | Englisch | 2025 | Springer | EAN 9783031578755 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Lingua: Inglese
Editore: Springer, Berlin|Springer Nature Switzerland|Springer, 2024
ISBN 10: 3031578724 ISBN 13: 9783031578724
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Aggiungi al carrelloGebunden. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book provides a valuable resource on the design of neuromorphic intelligence, which serves as a computational foundation for building compact and low-power brain-inspired intelligent systems. The book introduces novel spiking neural network learning.
Lingua: Inglese
Editore: Springer, Springer Mai 2025, 2025
ISBN 10: 3031578759 ISBN 13: 9783031578755
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book provides a valuable resource on the design of neuromorphic intelligence, which serves as a computational foundation for building compact and low-power brain-inspired intelligent systems. The book introduces novel spiking neural network learning algorithms, including spike-based learning based on the multi-compartment model and spike-based learning with information theory. These offer important insights and academic value for readers to grasp the latest advances in neural-inspired learning. Additionally, the book presents insights and approaches to the design of scalable neuromorphic architectures, which are crucial foundations for achieving highly cognitive and energy-efficient computing systems. Furthermore, the book introduces representative large-scale neuromorphic systems and reviews several recently implemented large-scale digital neuromorphic systems by the authors, providing corresponding application scenarios.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 260 pp. Englisch.
Lingua: Inglese
Editore: Springer, Springer Mai 2024, 2024
ISBN 10: 3031578724 ISBN 13: 9783031578724
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
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Aggiungi al carrelloBuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book provides a valuable resource on the design of neuromorphic intelligence, which serves as a computational foundation for building compact and low-power brain-inspired intelligent systems. The book introduces novel spiking neural network learning algorithms, including spike-based learning based on the multi-compartment model and spike-based learning with information theory. These offer important insights and academic value for readers to grasp the latest advances in neural-inspired learning. Additionally, the book presents insights and approaches to the design of scalable neuromorphic architectures, which are crucial foundations for achieving highly cognitive and energy-efficient computing systems. Furthermore, the book introduces representative large-scale neuromorphic systems and reviews several recently implemented large-scale digital neuromorphic systems by the authors, providing corresponding application scenarios.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 260 pp. Englisch.
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Aggiungi al carrelloBuch. Condizione: Neu. Neuromorphic Intelligence | Learning, Architectures and Large-Scale Systems | Shuangming Yang (u. a.) | Buch | Synthesis Lectures on Engineering, Science, and Technology | xix | Englisch | 2024 | Springer | EAN 9783031578724 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.
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EUR 73,83
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Aggiungi al carrelloBuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The rapid development of deep learning has led to groundbreaking advancements across various fields, from computer vision to natural language processing and beyond. Information theory, as a mathematical foundation for understanding data representation, learning, and communication, has emerged as a powerful tool in advancing deep learning methods. This Special Issue, 'Information-Theoretic Methods in Deep Learning: Theory and Applications', presents cutting-edge research that bridges the gap between information theory and deep learning. It covers theoretical developments, innovative methodologies, and practical applications, offering new insights into the optimization, generalization, and interpretability of deep learning models. The collection includes contributions on: Theoretical frameworks combining information theory with deep learning architectures; Entropy-based and information bottleneck methods for model compression and generalization; Mutual information estimation for feature selection and representation learning; Applications of information-theoretic principles in natural language processing, computer vision, and neural network optimization.
Da: preigu, Osnabrück, Germania
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Aggiungi al carrelloBuch. Condizione: Neu. Information-Theoretic Methods in Deep Learning | Theory and Applications | Buch | Englisch | 2025 | MDPI AG | EAN 9783725829828 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.