Verwandte Artikel zu Hebbian Learning and Negative Feedback Networks (Advanced...
Hebbian Learning and Negative Feedback Networks (Advanced Information and Knowledge Processing) - Softcover
Inhaltsangabe
A state of the art specialist monograph on artificial neural networks which use Hebbian learning, covering a wide range of real experiments and which displays how it’s approaches can be applied to analyse real problems. The book has a thorough approach and brings together a wide range of concepts into a coherent whole. Colin Fyfe writes with authority, and is a well-known, experienced researcher who has led a team working in this area at Paisley.
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
Críticas
From the reviews of the first edition:
"This book is concerned with developing unsupervised learning procedures and building self organizing network modules that can capture regularities of the environment. ... the book provides a detailed introduction to Hebbian learning and negative feedback neural networks and is suitable for self-study or instruction in an introductory course." (Nicolae S. Mera, Zentralblatt MATH, Vol. 1069, 2005)
Reseña del editor
The central idea of Hebbian Learning and Negative Feedback Networks is that artificial neural networks using negative feedback of activation can use simple Hebbian learning to self-organise so that they uncover interesting structures in data sets. Two variants are considered: the first uses a single stream of data to self-organise. By changing the learning rules for the network, it is shown how to perform Principal Component Analysis, Exploratory Projection Pursuit, Independent Component Analysis, Factor Analysis and a variety of topology preserving mappings for such data sets.
The second variants use two input data streams on which they self-organise. In their basic form, these networks are shown to perform Canonical Correlation Analysis, the statistical technique which finds those filters onto which projections of the two data streams have greatest correlation.
The book encompasses a wide range of real experiments and displays how the approaches it formulates can be applied to the analysis of real problems.
„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
EUR 226,89
EUR 28,83 für den Versand von Vereinigtes Königreich nach Deutschland
Versandziele, Kosten & DauerNeu kaufen
Diesen Artikel anzeigen
EUR 136,16
Gratis für den Versand innerhalb von/der Deutschland
Versandziele, Kosten & DauerWeitere beliebte Ausgaben desselben Titels
Suchergebnisse für Hebbian Learning and Negative Feedback Networks (Advanced...
Foto des Verkäufers
Hebbian Learning and Negative Feedback Networks
Verlag:
Springer London, 2010
ISBN 10: 1849969450
ISBN 13: 9781849969451
Neu
Kartoniert / Broschiert
Anbieter: moluna, Greven, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Kartoniert / Broschiert. Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Concentrates on one specific architecture and learning rule which no other book doesState of the art in artificial neural networks which use Hebbian learningA comparative study of a variety of techniques that have been drawn from extensions. Bestandsnummer des Verkäufers 4289001
Anzahl: Mehr als 20 verfügbar
Foto des Verkäufers
Hebbian Learning and Negative Feedback Networks
Print-on-DemandAnbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book is the outcome of a decade's research into a speci c architecture and associated learning mechanism for an arti cial neural network: the - chitecture involves negative feedback and the learning mechanism is simple Hebbian learning. The research began with my own thesis at the University of Strathclyde, Scotland, under Professor Douglas McGregor which culminated with me being awarded a PhD in 1995 [52], the title of which was 'Negative Feedback as an Organising Principle for Arti cial Neural Networks'. Naturally enough, having established this theme, when I began to sup- vise PhD students of my own, we continued to develop this concept and this book owes much to the research and theses of these students at the Applied Computational Intelligence Research Unit in the University of Paisley. Thus we discuss work from - Dr. Darryl Charles [24] in Chapter 5. - Dr. Stephen McGlinchey [127] in Chapter 7. - Dr. Donald MacDonald [121] in Chapters 6 and 8. - Dr. Emilio Corchado [29] in Chapter 8. We brie y discuss one simulation from the thesis of Dr. Mark Girolami [58] in Chapter 6 but do not discuss any of the rest of his thesis since it has already appeared in book form [59]. We also must credit Cesar Garcia Osorio, a current PhD student, for the comparative study of the two Exploratory Projection Pursuit networks in Chapter 8. All of Chapters 3 to 8 deal with single stream arti cial neural networks. 404 pp. Englisch. Bestandsnummer des Verkäufers 9781849969451
Anzahl: 2 verfügbar
Foto des Verkäufers
Hebbian Learning and Negative Feedback Networks
Verlag:
Springer London, Springer London Okt 2010, 2010
ISBN 10: 1849969450
ISBN 13: 9781849969451
Neu
Taschenbuch
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book is the outcome of a decade¿s research into a speci c architecture and associated learning mechanism for an arti cial neural network: the - chitecture involves negative feedback and the learning mechanism is simple Hebbian learning. The research began with my own thesis at the University of Strathclyde, Scotland, under Professor Douglas McGregor which culminated with me being awarded a PhD in 1995 [52], the title of which was ¿Negative Feedback as an Organising Principle for Arti cial Neural Networks¿. Naturally enough, having established this theme, when I began to sup- vise PhD students of my own, we continued to develop this concept and this book owes much to the research and theses of these students at the Applied Computational Intelligence Research Unit in the University of Paisley. Thus we discuss work from ¿ Dr. Darryl Charles [24] in Chapter 5. ¿ Dr. Stephen McGlinchey [127] in Chapter 7. ¿ Dr. Donald MacDonald [121] in Chapters 6 and 8. ¿ Dr. Emilio Corchado [29] in Chapter 8. We brie y discuss one simulation from the thesis of Dr. Mark Girolami [58] in Chapter 6 but do not discuss any of the rest of his thesis since it has already appeared in book form [59]. We also must credit Cesar Garcia Osorio, a current PhD student, for the comparative study of the two Exploratory Projection Pursuit networks in Chapter 8. All of Chapters 3 to 8 deal with single stream arti cial neural networks.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 404 pp. Englisch. Bestandsnummer des Verkäufers 9781849969451
Anzahl: 1 verfügbar
Foto des Verkäufers
Hebbian Learning and Negative Feedback Networks
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book is the outcome of a decade's research into a speci c architecture and associated learning mechanism for an arti cial neural network: the - chitecture involves negative feedback and the learning mechanism is simple Hebbian learning. The research began with my own thesis at the University of Strathclyde, Scotland, under Professor Douglas McGregor which culminated with me being awarded a PhD in 1995 [52], the title of which was 'Negative Feedback as an Organising Principle for Arti cial Neural Networks'. Naturally enough, having established this theme, when I began to sup- vise PhD students of my own, we continued to develop this concept and this book owes much to the research and theses of these students at the Applied Computational Intelligence Research Unit in the University of Paisley. Thus we discuss work from - Dr. Darryl Charles [24] in Chapter 5. - Dr. Stephen McGlinchey [127] in Chapter 7. - Dr. Donald MacDonald [121] in Chapters 6 and 8. - Dr. Emilio Corchado [29] in Chapter 8. We brie y discuss one simulation from the thesis of Dr. Mark Girolami [58] in Chapter 6 but do not discuss any of the rest of his thesis since it has already appeared in book form [59]. We also must credit Cesar Garcia Osorio, a current PhD student, for the comparative study of the two Exploratory Projection Pursuit networks in Chapter 8. All of Chapters 3 to 8 deal with single stream arti cial neural networks. Bestandsnummer des Verkäufers 9781849969451
Anzahl: 1 verfügbar
Beispielbild für diese ISBN
Hebbian Learning and Negative Feedback Networks
Anbieter: Books Puddle, New York, NY, USA
Verkäuferbewertung 4 von 5 Sternen
Zustand: New. pp. xviii + 383 1st Edition. Bestandsnummer des Verkäufers 262142939
Anzahl: 4 verfügbar
Beispielbild für diese ISBN
Hebbian Learning and Negative Feedback Networks
Print-on-DemandAnbieter: Biblios, Frankfurt am main, HESSE, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Zustand: New. PRINT ON DEMAND pp. xviii + 383. Bestandsnummer des Verkäufers 182142929
Anzahl: 4 verfügbar
Beispielbild für diese ISBN
Hebbian Learning and Negative Feedback Networks
Print-on-DemandAnbieter: Majestic Books, Hounslow, Vereinigtes Königreich
Verkäuferbewertung 5 von 5 Sternen
Zustand: New. Print on Demand pp. xviii + 383. Bestandsnummer des Verkäufers 5704964
Anzahl: 4 verfügbar
Beispielbild für diese ISBN
Hebbian Learning and Negative Feedback Networks (Advanced Information and Knowledge Processing)
Anbieter: Mispah books, Redhill, SURRE, Vereinigtes Königreich
Verkäuferbewertung 4 von 5 Sternen
Paperback. Zustand: Like New. Like New. book. Bestandsnummer des Verkäufers ERICA79618499694506
Anzahl: 1 verfügbar
Beispielbild für diese ISBN
Hebbian Learning and Negative Feedback Networks (Advanced Information and Knowledge Processing)
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
Verkäuferbewertung 5 von 5 Sternen
Paperback. Zustand: Brand New. 401 pages. 9.13x6.06x1.02 inches. In Stock. Bestandsnummer des Verkäufers zk1849969450
Anzahl: 1 verfügbar