Yuxuan wang (44 resultados)

Hardcover. Condición: As New. No Jacket. Pages are clean and are not marred by notes or folds of any kind. ~ ThriftBooks: Read More, Spend Less.

hardcover. Condición: Very Good.

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Hardback. Condición: New.

Hardback. Condición: New. Quantum machine learning (QML) is revolutionizing artificial intelligence by leveraging the power of quantum computing to access previously unimaginable computational possibilities. However, the field remains fragmented-balancing rigorous quantum theory with practical AI applications remains a challenge. This book bridges this gap, offering a systematic, hands-on guide for AI researchers, ML practitioners, and computer scientists eager to explore this emerging frontier. It provides a cohesive roadmap, covering everything from fundamental quantum computing principles to state-of-the-art QML techniques. Readers will explore quantum kernel methods, quantum neural networks, and quantum Transformers, gaining insight into their theoretical foundations, performance advantages, and practical implementations. The book's code demonstrations offer hands-on experience, ensuring that readers can move beyond theory to real-world applications.Designed for those with an AI or ML background, this tutorial does not assume prior expertise in quantum computing. Instead, it presents complex concepts with clarity, making it an essential resource for researchers, graduate students, and industry professionals eager to stay ahead in the quantum AI revolution. Whether you seek to understand quantum speedups, develop quantum-based models, or explore future research directions, this book provides the foundation you need to engage with QML and shape the future of intelligent computing.…

HRD. Condición: New. New Book. Shipped from UK. Established seller since 2000.

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hardcover. Condición: New.

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Hardcover. Condición: Brand New. 220 pages. 9.26x6.11x9.21 inches. In Stock.

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hardcover. Condición: New. In shrink wrap. Looks like an interesting title.

Hardback. Condición: New. Quantum machine learning (QML) is revolutionizing artificial intelligence by leveraging the power of quantum computing to access previously unimaginable computational possibilities. However, the field remains fragmented-balancing rigorous quantum theory with practical AI applications remains a challenge. This book bridges this gap, offering a systematic, hands-on guide for AI researchers, ML practitioners, and computer scientists eager to explore this emerging frontier. It provides a cohesive roadmap, covering everything from fundamental quantum computing principles to state-of-the-art QML techniques. Readers will explore quantum kernel methods, quantum neural networks, and quantum Transformers, gaining insight into their theoretical foundations, performance advantages, and practical implementations. The book's code demonstrations offer hands-on experience, ensuring that readers can move beyond theory to real-world applications.Designed for those with an AI or ML background, this tutorial does not assume prior expertise in quantum computing. Instead, it presents complex concepts with clarity, making it an essential resource for researchers, graduate students, and industry professionals eager to stay ahead in the quantum AI revolution. Whether you seek to understand quantum speedups, develop quantum-based models, or explore future research directions, this book provides the foundation you need to engage with QML and shape the future of intelligent computing.…

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Condición: New. 1st edition NO-PA16APR2015-KAP.

Condición: As New. Unread book in perfect condition.

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Paperback. Condición: New. This book presents novel state estimation methods for several classes of networked multi-rate systems including state estimation methods for networked multi-rate systems with various complex networked-induced phenomena and communication protocols. The systems investigated include stochastic nonlinear systems, time-delay systems, linear repetitive processes, and artificial neural networks. The techniques used are mainly the Lyapunov stability theory, the optimal estimation theory, the lifting technique, and certain convex optimization method.FeaturesGives a systematic investigation of the state estimation of multi-rate systemsDiscusses results on state estimation problems under network-induced complexitiesStudies different kinds of multi-rate systems including multi-rate nonlinear systems, multi-rate neural networks, and multi-rate linear repetitive processesExplores network-enhanced complexities and communication protocolsIncludes case studies showing the applicability of developed estimation algorithms including practical examples like DC servo systems and continuous stirred tank reactor systemsAnalysis and Synthesis for Networked Multi-Rate Systems is aimed at graduate students and researchers in signal processing, control systems, and electrical engineering.…

Paperback. Condición: Brand New. 259 pages. 9.18x6.12x9.21 inches. In Stock.

Hardback. Condición: New. Quantum machine learning (QML) is revolutionizing artificial intelligence by leveraging the power of quantum computing to access previously unimaginable computational possibilities. However, the field remains fragmented-balancing rigorous quantum theory with practical AI applications remains a challenge. This book bridges this gap, offering a systematic, hands-on guide for AI researchers, ML practitioners, and computer scientists eager to explore this emerging frontier. It provides a cohesive roadmap, covering everything from fundamental quantum computing principles to state-of-the-art QML techniques. Readers will explore quantum kernel methods, quantum neural networks, and quantum Transformers, gaining insight into their theoretical foundations, performance advantages, and practical implementations. The book's code demonstrations offer hands-on experience, ensuring that readers can move beyond theory to real-world applications.Designed for those with an AI or ML background, this tutorial does not assume prior expertise in quantum computing. Instead, it presents complex concepts with clarity, making it an essential resource for researchers, graduate students, and industry professionals eager to stay ahead in the quantum AI revolution. Whether you seek to understand quantum speedups, develop quantum-based models, or explore future research directions, this book provides the foundation you need to engage with QML and shape the future of intelligent computing.…

Paperback. Condición: New. This book presents novel state estimation methods for several classes of networked multi-rate systems including state estimation methods for networked multi-rate systems with various complex networked-induced phenomena and communication protocols. The systems investigated include stochastic nonlinear systems, time-delay systems, linear repetitive processes, and artificial neural networks. The techniques used are mainly the Lyapunov stability theory, the optimal estimation theory, the lifting technique, and certain convex optimization method.FeaturesGives a systematic investigation of the state estimation of multi-rate systemsDiscusses results on state estimation problems under network-induced complexitiesStudies different kinds of multi-rate systems including multi-rate nonlinear systems, multi-rate neural networks, and multi-rate linear repetitive processesExplores network-enhanced complexities and communication protocolsIncludes case studies showing the applicability of developed estimation algorithms including practical examples like DC servo systems and continuous stirred tank reactor systemsAnalysis and Synthesis for Networked Multi-Rate Systems is aimed at graduate students and researchers in signal processing, control systems, and electrical engineering.…

Condición: New.

Condición: New.

Condición: New.