Hebbian Learning and Negative Feedback Networks

€ 165,49
Bisher € 176,49
Lieferbar innerhalb von 2-3 Tagen
Januar 2005



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.


Part I - Single Stream Networks
The Negative Feedback Network
Peer-Inhibitory Neurons
Multiple Cause Data
Exploratory Data Analysis
Topology Preserving Maps
Maximum Likelihood Hebbian Learning
Part II - 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
App. A. Negative Feedback Artificial Neural Networks
B. Previous Factor Analysis Models
C. Related Models for ICA
D. Previous Dual Stream Approaches
E. Data Sets


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)
EAN: 9781852338831
ISBN: 1852338830
Untertitel: 'Advanced Information and Knowledge Processing'. 2005. Auflage. Book. Sprache: Englisch.
Verlag: Springer
Erscheinungsdatum: Januar 2005
Seitenanzahl: 404 Seiten
Format: gebunden
Es gibt zu diesem Artikel noch keine Bewertungen.Kundenbewertung schreiben