Neural Networks: Theory, Algorithms, Simulation, and Applications (Hardcover)
Language: English
Published by Springer Nature Switzerland AG, Cham, 2026
- Hardcover
- New
Seller: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
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Condition: New
£ 188.88
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Add to basketItem description from seller
Hardcover. This book offers a comprehensive and up-to-date exploration of one of the most transformative areas of modern computing. This edited book brings together leading researchers and practitioners to present both foundational principles and cutting-edge advances in neural network science.Beginning with the mathematical and theoretical underpinnings of neural computation, the book systematically develops key learning paradigms, architectures, and optimization algorithms. It then bridges theory with practice through detailed discussions of simulation methodologies and performance analysis, enabling readers to model, test, and validate neural systems effectively.A distinctive strength of this book lies in its broad coverage of real-world applications, including pattern recognition, computer vision, natural language processing, biomedical engineering, signal and image processing, financial forecasting, and intelligent control systems. Each chapter highlights practical insights, case studies, and emerging trends, making the content highly relevant to both academia and industry.Designed as a reference for graduate students, researchers, and professionals, this book provides a balanced blend of rigor and accessibility. By integrating theory, algorithms, simulation techniques, and applications within a single framework, this book serves as an essential resource for understanding and advancing the next generation of intelligent systems. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…
Seller Inventory # 9783032187499
- Title
- Neural Networks: Theory, Algorithms, Simulation, and Applications (Hardcover)
- Author
- Lakhveer Kaur
- Publisher
- Springer Nature Switzerland AG, Cham
- Publication year
- 2026
- Condition
- new
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 3032187494
- ISBN 13
- 9783032187499
This book offers a comprehensive and up-to-date exploration of one of the most transformative areas of modern computing. This edited book brings together leading researchers and practitioners to present both foundational principles and cutting-edge advances in neural network science.
Beginning with the mathematical and theoretical underpinnings of neural computation, the book systematically develops key learning paradigms, architectures, and optimization algorithms. It then bridges theory with practice through detailed discussions of simulation methodologies and performance analysis, enabling readers to model, test, and validate neural systems effectively.
A distinctive strength of this book lies in its broad coverage of real-world applications, including pattern recognition, computer vision, natural language processing, biomedical engineering, signal and image processing, financial forecasting, and intelligent control systems. Each chapter highlights practical insights, case studies, and emerging trends, making the content highly relevant to both academia and industry.
Designed as a reference for graduate students, researchers, and professionals, this book provides a balanced blend of rigor and accessibility. By integrating theory, algorithms, simulation techniques, and applications within a single framework, this book serves as an essential resource for understanding and advancing the next generation of intelligent systems.
"Synopsis" may belong to another edition of this title.
From the Back Cover
This book offers a comprehensive and up-to-date exploration of one of the most transformative areas of modern computing. This edited book brings together leading researchers and practitioners to present both foundational principles and cutting-edge advances in neural network science.
Beginning with the mathematical and theoretical underpinnings of neural computation, the book systematically develops key learning paradigms, architectures, and optimization algorithms. It then bridges theory with practice through detailed discussions of simulation methodologies and performance analysis, enabling readers to model, test, and validate neural systems effectively.
A distinctive strength of this book lies in its broad coverage of real-world applications, including pattern recognition, computer vision, natural language processing, biomedical engineering, signal and image processing, financial forecasting, and intelligent control systems. Each chapter highlights practical insights, case studies, and emerging trends, making the content highly relevant to both academia and industry.
Designed as a reference for graduate students, researchers, and professionals, this book provides a balanced blend of rigor and accessibility. By integrating theory, algorithms, simulation techniques, and applications within a single framework, this book serves as an essential resource for understanding and advancing the next generation of intelligent systems.
"About the title" may belong to another edition of this title.
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