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Pattern Recognition Using Neural Networks: Theory and Algorithms for Engineers and Scientists - Couverture rigide
Synopsis
Pattern Regcognition with Neural Networks covers traditional linear pattern recognition and its nonlinear extension via neural networks from an algorithmic approach. The author has written a real-world practical "why-and-how" text that provides a refreshing contrast to competing texts' thoeretical appraoch and "pie-in-the-sky" claims. The text explores mulitple layered preceptrons and describes network types such as functional link, radial basis function, learning vector quantanization and self-organizing. The author also discusses recent clustering methods. This text is suitable for an advanced undergraduate course in pattern recognition or neural networks, and is also useful as a reference and a resource.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Présentation de l'éditeur
Pattern Regcognition with Neural Networks covers traditional linear pattern recognition and its nonlinear extension via neural networks from an algorithmic approach. The author has written a real-world practical "why-and-how" text that provides a refreshing contrast to competing texts' thoeretical appraoch and "pie-in-the-sky" claims. The text explores mulitple layered preceptrons and describes network types such as functional link, radial basis function, learning vector quantanization and self-organizing. The author also discusses recent clustering methods. This text is suitable for an advanced undergraduate course in pattern recognition or neural networks, and is also useful as a reference and a resource.
Revue de presse
This is a fairly comprehensive introduction to feedforward neutral networks...............the book is accessible and would be well-suited to serve as a text for its intended audience (Short Book Review Vol. 17 No. 3)
`... makes its subject easy to understand by offering intuitive explanations and examples... lives up to its claim as a practical neural network text and will be an excellent resource for those who want to implement neural networks, rather than just learn the theory.' Scientific Computing World, September 1997
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
- ÉditeurOxford University Press Inc
- Date d'édition1997
- ISBN 10 0195079205
- ISBN 13 9780195079203
- ReliureRelié
- Langueanglais
- Nombre de pages480
- Coordonnées du fabricantnon disponible
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Pattern Recognition Using Neural Networks: Theory and Algorithms for Engineers and Scientists
Edité par
OXFORD UNIV PR, 1997
ISBN 10 : 0195079205
ISBN 13 : 9780195079203
Ancien ou d'occasion
Couverture rigide
Vendeur : Buchpark, Trebbin, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Etat : Gut. Zustand: Gut | Seiten: 480 | Sprache: Englisch | Produktart: Bücher. N° de réf. du vendeur 1204424/3
Quantité disponible : 2 disponible(s)
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Pattern Recognition Using Neural Networks (Hardcover)
Edité par
Oxford University Press Inc, New York, 1997
ISBN 10 : 0195079205
ISBN 13 : 9780195079203
Neuf
Couverture rigide
Vendeur : AussieBookSeller, Truganina, VIC, Australie
Évaluation du vendeur 5 sur 5 étoiles
Hardcover. Etat : new. Hardcover. Pattern Recognition Using Neural Networks covers traditional linear pattern recognition and its nonlinear extension via neural networks. The approach is algorithmic for easy implementation on a computer, which makes this a refreshing what-why-and-how text that contrasts with the theoretical approach and pie-in-the-sky hyperbole of many books on neural networks. It covers the standard decision-theoretic pattern recognition of clustering via minimum distance,graphical and structural methods, and Bayesian discrimination. Pattern recognizers evolve across the sections into perceptrons, a layer of perceptrons, multiple-layered perceptrons, functionallink nets, and radial basis function networks. Other networks covered in the process are learning vector quantization networks, self-organizing maps, and recursive neural networks. Backpropagation is derived in complete detail for one and two hidden layers for both unipolar and bipolar sigmoid activation functions. The more efficient fullpropagation, quickpropagation, cascade correlation, and various methods such as strategic search, conjugate gradients, and genetic algorithms are described.Advanced methods are also described, including the full training algorithms for radial basis function networks and random vector functional link nets, as well as competitive learning networks and fuzzyclustering algorithms. Special topics covered include: feature engineering data engineering neural engineering of network architectures validation and verification of the trained networks This textbook is ideally suited for a senior undergraduate or graduate course in pattern recognition or neural networks for students in computer science, electrical engineering, and computer engineering. It is also a useful reference andresource for researchers and professionals. A text covering traditional linear pattern recognition and its nonlinear extension via neural networks. The approach is algorithmic for easy implementation on a computer. It covers the standard decision-theoretic pattern recognition of clustering via minimum distance, graphical and structural methods, and Bayesian discrimination. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. N° de réf. du vendeur 9780195079203
Quantité disponible : 1 disponible(s)
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Pattern Recognition Using Neural Networks : Theory and Algorithms for Engineers and Scientists
Edité par
Oxford University Press, 1997
ISBN 10 : 0195079205
ISBN 13 : 9780195079203
Neuf
Couverture rigide
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. N° de réf. du vendeur 73690-n
Quantité disponible : Plus de 20 disponibles
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Pattern Recognition Using Neural Networks : Theory and Algorithms for Engineers and Scientists
Edité par
Oxford University Press, 1997
ISBN 10 : 0195079205
ISBN 13 : 9780195079203
Neuf
Couverture rigide
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. N° de réf. du vendeur 73690-n
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PATTERN RECOGNITION USING NEUR
Edité par
Oxford University Press, 1997
ISBN 10 : 0195079205
ISBN 13 : 9780195079203
Neuf
Couverture rigide
Vendeur : moluna, Greven, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. KlappentextrnrnPattern Recognition Using Neural Networks covers traditional linear pattern recognition and its nonlinear extension via neural networks. The approach is algorithmic for easy implementation on a computer, which makes this a refres. N° de réf. du vendeur 897460756
Quantité disponible : Plus de 20 disponibles
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Pattern Recognition Using Neural Networks : Theory and Algorithms for Engineers and Scientists
Edité par
Oxford University Press, 1997
ISBN 10 : 0195079205
ISBN 13 : 9780195079203
Ancien ou d'occasion
Couverture rigide
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Évaluation du vendeur 5 sur 5 étoiles
Etat : As New. Unread book in perfect condition. N° de réf. du vendeur 73690
Quantité disponible : Plus de 20 disponibles
Image fournie par le vendeur
Pattern Recognition Using Neural Networks : Theory and Algorithms for Engineers and Scientists
Edité par
Oxford University Press, 1997
ISBN 10 : 0195079205
ISBN 13 : 9780195079203
Ancien ou d'occasion
Couverture rigide
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Etat : As New. Unread book in perfect condition. N° de réf. du vendeur 73690
Quantité disponible : Plus de 20 disponibles
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Pattern Recognition Using Neural Networks (Hardcover)
Edité par
Oxford University Press Inc, New York, 1997
ISBN 10 : 0195079205
ISBN 13 : 9780195079203
Neuf
Couverture rigide
Vendeur : CitiRetail, Stevenage, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Hardcover. Etat : new. Hardcover. Pattern Recognition Using Neural Networks covers traditional linear pattern recognition and its nonlinear extension via neural networks. The approach is algorithmic for easy implementation on a computer, which makes this a refreshing what-why-and-how text that contrasts with the theoretical approach and pie-in-the-sky hyperbole of many books on neural networks. It covers the standard decision-theoretic pattern recognition of clustering via minimum distance,graphical and structural methods, and Bayesian discrimination. Pattern recognizers evolve across the sections into perceptrons, a layer of perceptrons, multiple-layered perceptrons, functionallink nets, and radial basis function networks. Other networks covered in the process are learning vector quantization networks, self-organizing maps, and recursive neural networks. Backpropagation is derived in complete detail for one and two hidden layers for both unipolar and bipolar sigmoid activation functions. The more efficient fullpropagation, quickpropagation, cascade correlation, and various methods such as strategic search, conjugate gradients, and genetic algorithms are described.Advanced methods are also described, including the full training algorithms for radial basis function networks and random vector functional link nets, as well as competitive learning networks and fuzzyclustering algorithms. Special topics covered include: feature engineering data engineering neural engineering of network architectures validation and verification of the trained networks This textbook is ideally suited for a senior undergraduate or graduate course in pattern recognition or neural networks for students in computer science, electrical engineering, and computer engineering. It is also a useful reference andresource for researchers and professionals. A text covering traditional linear pattern recognition and its nonlinear extension via neural networks. The approach is algorithmic for easy implementation on a computer. It covers the standard decision-theoretic pattern recognition of clustering via minimum distance, graphical and structural methods, and Bayesian discrimination. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9780195079203
Quantité disponible : 1 disponible(s)
Image d'archives
Pattern Recognition Using Neural Networks (Hardcover)
Edité par
Oxford University Press Inc, New York, 1997
ISBN 10 : 0195079205
ISBN 13 : 9780195079203
Neuf
Couverture rigide
Vendeur : Grand Eagle Retail, Fairfield, OH, Etats-Unis
Évaluation du vendeur 5 sur 5 étoiles
Hardcover. Etat : new. Hardcover. Pattern Recognition Using Neural Networks covers traditional linear pattern recognition and its nonlinear extension via neural networks. The approach is algorithmic for easy implementation on a computer, which makes this a refreshing what-why-and-how text that contrasts with the theoretical approach and pie-in-the-sky hyperbole of many books on neural networks. It covers the standard decision-theoretic pattern recognition of clustering via minimum distance,graphical and structural methods, and Bayesian discrimination. Pattern recognizers evolve across the sections into perceptrons, a layer of perceptrons, multiple-layered perceptrons, functionallink nets, and radial basis function networks. Other networks covered in the process are learning vector quantization networks, self-organizing maps, and recursive neural networks. Backpropagation is derived in complete detail for one and two hidden layers for both unipolar and bipolar sigmoid activation functions. The more efficient fullpropagation, quickpropagation, cascade correlation, and various methods such as strategic search, conjugate gradients, and genetic algorithms are described.Advanced methods are also described, including the full training algorithms for radial basis function networks and random vector functional link nets, as well as competitive learning networks and fuzzyclustering algorithms. Special topics covered include: feature engineering data engineering neural engineering of network architectures validation and verification of the trained networks This textbook is ideally suited for a senior undergraduate or graduate course in pattern recognition or neural networks for students in computer science, electrical engineering, and computer engineering. It is also a useful reference andresource for researchers and professionals. A text covering traditional linear pattern recognition and its nonlinear extension via neural networks. The approach is algorithmic for easy implementation on a computer. It covers the standard decision-theoretic pattern recognition of clustering via minimum distance, graphical and structural methods, and Bayesian discrimination. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9780195079203
Quantité disponible : 1 disponible(s)
Image d'archives
Pattern Recognition Using Neural Networks
Edité par
Oxford University Press, 1997
ISBN 10 : 0195079205
ISBN 13 : 9780195079203
Ancien ou d'occasion
Couverture rigide
Vendeur : OM Books, Sevilla, SE, Espagne
Évaluation du vendeur 5 sur 5 étoiles
Etat : Usado - bueno. N° de réf. du vendeur 9780195079203
Quantité disponible : 1 disponible(s)