ISBN: 9789819814688 - advanced randomized neural networks for pattern analysis: 1 (advances in pattern analysis and intelligent sensing) (12 resultados)

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  • Idioma: Inglés

    Editorial: World Scientific Publishing Company, 2025

    9819814685 / 9789819814688

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    Librería: PBShop.store UK, Fairford, GLOS, Reino UnidoPBShop.store UK

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    EUR 139,95

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    Cantidad disponible: 15 disponibles

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

  • Idioma: Inglés

    Editorial: WSPC, 2025

    9819814685 / 9789819814688

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    Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices

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  • Idioma: Inglés

    Editorial: WSPC, 2025

    9819814685 / 9789819814688

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    Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books

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    EUR 149,86

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  • Idioma: Inglés

    Editorial: WSPC, 2025

    9819814685 / 9789819814688

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    Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices

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    Condición: Usado - Como Nuevo

    EUR 152,97

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    Condición: As New. Unread book in perfect condition.

  • Idioma: Inglés

    Editorial: WSPC, 2025

    9819814685 / 9789819814688

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    Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK

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    Condición: Nuevo

    EUR 139,94

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  • Idioma: Inglés

    Editorial: World Scientific Publishing Co Pte Ltd, SG, 2025

    9819814685 / 9789819814688

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    Librería: Rarewaves.com USA, London, LONDO, Reino UnidoRarewaves.com USA

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    Condición: Nuevo

    EUR 164,77

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    Cantidad disponible: Más de 20 disponibles

    Hardback. Condición: New. This book is the culmination of our research in the recent decade on randomized neural networks with data-dependent supervision mechanisms. Traditional randomized neural networks mainly focused on constructing various deep neural networks with data independent random weights, ignoring the impact of the number of nodes and scope of parameters on the universal approximation property (UAP) of randomized neural networks. Comprising of 15 chapters, Advanced Randomized Neural Networks for Pattern Analysis introduces systematic solutions for advanced data-dependent stochastic configuration networks, namely algorithms that assign random parameters and construct network structures incrementally. The book is segmented into three major sections - neural networks optimization, robust data analysis, and deep fusion learning - that feature the successful performance of advanced randomized neural networks in various pattern analysis problems. We anticipate that both researchers and engineers in the field of artificial neural networks, particularly pattern recognition and medical diagnosis, will find this book and the associated algorithms useful, and we hope that anyone with an interest in the related research field will find the book enjoyable and informative.…

  • Idioma: Inglés

    Editorial: WSPC, 2025

    9819814685 / 9789819814688

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    Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK

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    Condición: Usado - Como Nuevo

    EUR 153,22

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    Condición: As New. Unread book in perfect condition.

  • Idioma: Inglés

    Editorial: World Scientific Publishing Co Pte Ltd, 2025

    9819814685 / 9789819814688

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    Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books

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    Condición: Nuevo

    EUR 185,75

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    Cantidad disponible: 2 disponibles

    Hardcover. Condición: Brand New. 368 pages. 3.94x3.94x2.36 inches. In Stock.

  • Idioma: Inglés

    Editorial: World Scientific Publishing Co Pte Ltd, SG, 2025

    9819814685 / 9789819814688

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    Librería: Rarewaves.com UK, London, Reino UnidoRarewaves.com UK

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    Condición: Nuevo

    EUR 160,93

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    Hardback. Condición: New. This book is the culmination of our research in the recent decade on randomized neural networks with data-dependent supervision mechanisms. Traditional randomized neural networks mainly focused on constructing various deep neural networks with data independent random weights, ignoring the impact of the number of nodes and scope of parameters on the universal approximation property (UAP) of randomized neural networks. Comprising of 15 chapters, Advanced Randomized Neural Networks for Pattern Analysis introduces systematic solutions for advanced data-dependent stochastic configuration networks, namely algorithms that assign random parameters and construct network structures incrementally. The book is segmented into three major sections - neural networks optimization, robust data analysis, and deep fusion learning - that feature the successful performance of advanced randomized neural networks in various pattern analysis problems. We anticipate that both researchers and engineers in the field of artificial neural networks, particularly pattern recognition and medical diagnosis, will find this book and the associated algorithms useful, and we hope that anyone with an interest in the related research field will find the book enjoyable and informative.…

  • Idioma: Inglés

    Editorial: World Scientific, 2025

    9819814685 / 9789819814688

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    Librería: preigu, Osnabrück, Alemaniapreigu

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    Condición: Nuevo

    EUR 135,75

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    Buch. Condición: Neu. ADVANCED RANDOMIZED NEURAL NETWORKS FOR PATTERN ANALYSIS | Zhang Chenglong | Buch | Englisch | 2025 | World Scientific | EAN 9789819814688 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.…

  • Idioma: Inglés

    Editorial: World Scientific Publishing Co Pte Ltd, Singapore, 2025

    9819814685 / 9789819814688

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    Librería: CitiRetail, Stevenage, Reino UnidoCitiRetail

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    EUR 167,86

    Envío por EUR 44,18 
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    Cantidad disponible: 1 disponible

    Hardcover. Condición: new. Hardcover. This book is the culmination of our research in the recent decade on randomized neural networks with data-dependent supervision mechanisms. Traditional randomized neural networks mainly focused on constructing various deep neural networks with data independent random weights, ignoring the impact of the number of nodes and scope of parameters on the universal approximation property (UAP) of randomized neural networks. Comprising of 15 chapters, Advanced Randomized Neural Networks for Pattern Analysis introduces systematic solutions for advanced data-dependent stochastic configuration networks, namely algorithms that assign random parameters and construct network structures incrementally. The book is segmented into three major sections neural networks optimization, robust data analysis, and deep fusion learning that feature the successful performance of advanced randomized neural networks in various pattern analysis problems. We anticipate that both researchers and engineers in the field of artificial neural networks, particularly pattern recognition and medical diagnosis, will find this book and the associated algorithms useful, and we hope that anyone with an interest in the related research field will find the book enjoyable and informative. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

  • Idioma: Inglés

    Editorial: World Scientific, 2025

    9819814685 / 9789819814688

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    Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH

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    Condición: Nuevo

    EUR 176,32

    Envío por EUR 35,00 
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    Cantidad disponible: 2 disponibles

    Buch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book is the culmination of our research in the recent decade on randomized neural networks with data-dependent supervision mechanisms. Traditional randomized neural networks mainly focused on constructing various deep neural networks with data independent random weights, ignoring the impact of the number of nodes and scope of parameters on the universal approximation property (UAP) of randomized neural networks. Comprising of 15 chapters, Advanced Randomized Neural Networks for Pattern Analysis introduces systematic solutions for advanced data-dependent stochastic configuration networks, namely algorithms that assign random parameters and construct network structures incrementally. The book is segmented into three major sections - neural networks optimization, robust data analysis, and deep fusion learning - that feature the successful performance of advanced randomized neural networks in various pattern analysis problems. We anticipate that both researchers and engineers in the field of artificial neural networks, particularly pattern recognition and medical diagnosis, will find this book and the associated algorithms useful, and we hope that anyone with an interest in the related research field will find the book enjoyable and informative.…