Neural networks theory algorithms (48 Ergebnisse)

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hardcover. Zustand: Sehr gut. 268 Seiten; 9783110449624.2 Gewicht in Gramm: 1.

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Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 268 | Sprache: Englisch | Produktart: Bücher | The book begins with an introduction of blind equalization theory and its application in neural networks, then discusses the algorithms in recurrent networks, fuzzy networks and other frequently-studied neural networks. Each algorithm is accompanied by derivation, modeling and simulation, making the book an essential reference for electrical engineers, computer intelligence researchers and neural scientists.…

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Zustand: Gut. Zustand: Gut | Seiten: 480 | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.

Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 480 | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The book begins with an introduction of blind equalization theory and its application in neural networks, then discusses the algorithms in recurrent networks, fuzzy networks and other frequently-studied neural networks. Each algorithm is accompanied by derivation, modeling and simulation, making the book an essential reference for electrical engineers, computer intelligence researchers and neural scientists.…

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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book introduces readers to the fundamentals of artificial neural networks, with a special emphasis on evolutionary algorithms. At first, the book offers a literature review of several well-regarded evolutionary algorithms, including particle swarm and ant colony optimization, genetic algorithms and biogeography-based optimization. It then proposes evolutionary version of several types of neural networks such as feed forward neural networks, radial basis function networks, as well as recurrent neural networks and multi-later perceptron. Most of the challenges that have to be addressed when training artificial neural networks using evolutionary algorithms are discussed in detail. The book also demonstrates the application of the proposed algorithms for several purposes such as classification, clustering, approximation, and prediction problems. It provides a tutorial on how to design, adapt, and evaluate artificial neural networks as well, and includes source codes for most of the proposed techniques as supplementary materials.…

Zustand: New. 1st ed. 2019 edition NO-PA16APR2015-KAP.

Hardcover. Zustand: Brand New. 156 pages. 9.50x6.25x0.50 inches. In Stock.

Hardcover. Zustand: Brand New. 210 pages. 9.44x6.69x0.50 inches. In Stock.

Hardcover. Zustand: new. 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 multiple locations in the US or from the UK, depending on stock availability.…

Hardcover. Zustand: new. 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 UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Hardcover. Zustand: gut. 1997. Pattern Recognition Using Neural Networks: Theory and Algorithms for Engineers and Scientists In englischer Sprache. pages.

Zustand: New. In English.