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 … Mehr…
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.; PDF; Computing > Computer science > Artificial intelligence, Springer London<
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This book is the outcome of a decadeâ??s research into a speci?c architecture and associated learning mechanism for an arti?cial neural network: the - chitecture involves negative feedbac… Mehr…
This book is the outcome of a decadeâ??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 â??Negative Feedback as an Organising Principle for Arti?cial Neural Networksâ?. 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 â?¢ Dr. Darryl Charles [24] in Chapter 5. â?¢ Dr. Stephen McGlinchey [127] in Chapter 7. â?¢ Dr. Donald MacDonald [121] in Chapters 6 and 8. â?¢ 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. Books > Computer Science eBook, Springer Shop<
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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 … Mehr…
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<
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*Hebbian Learning and Negative Feedback Networks* / pdf eBook für 149.99 € / Aus dem Bereich: eBooks, Sachthemen & Ratgeber, Computer & Internet Medien > Bücher nein eBook als pdf eBooks > Sachthemen & Ratgeber > Computer & Internet, Springer-Verlag GmbH<
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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 … Mehr…
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.; PDF; Computing > Computer science > Artificial intelligence, Springer London<
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This book is the outcome of a decadeâ??s research into a speci?c architecture and associated learning mechanism for an arti?cial neural network: the - chitecture involves negative feedbac… Mehr…
This book is the outcome of a decadeâ??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 â??Negative Feedback as an Organising Principle for Arti?cial Neural Networksâ?. 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 â?¢ Dr. Darryl Charles [24] in Chapter 5. â?¢ Dr. Stephen McGlinchey [127] in Chapter 7. â?¢ Dr. Donald MacDonald [121] in Chapters 6 and 8. â?¢ 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. Books > Computer Science eBook, Springer Shop<
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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 … Mehr…
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<
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*Hebbian Learning and Negative Feedback Networks* / pdf eBook für 149.99 € / Aus dem Bereich: eBooks, Sachthemen & Ratgeber, Computer & Internet Medien > Bücher nein eBook als pdf eBooks > Sachthemen & Ratgeber > Computer & Internet, Springer-Verlag GmbH<
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Buch in der Datenbank seit 2010-06-04T03:56:41+02:00 (Berlin) Detailseite zuletzt geändert am 2024-03-12T15:40:19+01:00 (Berlin) ISBN/EAN: 9781846281181
ISBN - alternative Schreibweisen: 1-84628-118-0, 978-1-84628-118-1 Alternative Schreibweisen und verwandte Suchbegriffe: Autor des Buches: fyfe, lynda plante, romanelli marco Titel des Buches: thanks for the feedback think, learning processing
Daten vom Verlag:
Autor/in: Colin Fyfe Titel: Advanced Information and Knowledge Processing; Hebbian Learning and Negative Feedback Networks Verlag: Springer; Springer London 383 Seiten Erscheinungsjahr: 2007-06-07 London; GB Sprache: Englisch 239,00 € (DE)
EA; E107; eBook; Nonbooks, PBS / Informatik, EDV/Informatik; Künstliche Intelligenz; Verstehen; Artificial neural networks; Data mining; Exploratory data analyis; Hebbian learning; Kernel; Machine learning; Signal processing; Unsupervised learning; artificial neural network; learning; neural network; C; Artificial Intelligence; Probability and Statistics in Computer Science; Automated Pattern Recognition; Computer Modelling; Computer Science; Computer Science; Mathematik für Informatiker; Wahrscheinlichkeitsrechnung und Statistik; Mustererkennung; Computermodellierung und -simulation; Informatik; BB
Single Stream Networks.- Background.- The Negative Feedback Network.- Peer-Inhibitory Neurons.- Multiple Cause Data.- Exploratory Data Analysis.- Topology Preserving Maps.- Maximum Likelihood Hebbian Learning.- Dual Stream Networks.- Two Neural Networks for Canonical Correlation Analysis.- Alternative Derivations of CCA Networks.- Kernel and Nonlinear Correlations.- Exploratory Correlation Analysis.- Multicollinearity and Partial Least Squares.- Twinned Principal Curves.- The Future.
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