Cargando…
Hebbian Learning and Negative Feedback Networks
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 Universi...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
London :
Springer London : Imprint: Springer,
2005.
|
| Edición: | 1st ed. 2005. |
| Colección: | Advanced Information and Knowledge Processing,
|
| Temas: | |
| Acceso en línea: | Texto Completo |
MARC
| LEADER | 00000nam a22000005i 4500 | ||
|---|---|---|---|
| 001 | 978-1-84628-118-1 | ||
| 003 | DE-He213 | ||
| 005 | 20220117123634.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 100301s2005 xxk| s |||| 0|eng d | ||
| 020 | |a 9781846281181 |9 978-1-84628-118-1 | ||
| 024 | 7 | |a 10.1007/b138856 |2 doi | |
| 050 | 4 | |a Q334-342 | |
| 050 | 4 | |a TA347.A78 | |
| 072 | 7 | |a UYQ |2 bicssc | |
| 072 | 7 | |a COM004000 |2 bisacsh | |
| 072 | 7 | |a UYQ |2 thema | |
| 082 | 0 | 4 | |a 006.3 |2 23 |
| 100 | 1 | |a Fyfe, Colin. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Hebbian Learning and Negative Feedback Networks |h [electronic resource] / |c by Colin Fyfe. |
| 250 | |a 1st ed. 2005. | ||
| 264 | 1 | |a London : |b Springer London : |b Imprint: Springer, |c 2005. | |
| 300 | |a XVIII, 383 p. |b online resource. | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 347 | |a text file |b PDF |2 rda | ||
| 490 | 1 | |a Advanced Information and Knowledge Processing, |x 2197-8441 | |
| 505 | 0 | |a 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. | |
| 520 | |a 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. | ||
| 650 | 0 | |a Artificial intelligence. | |
| 650 | 0 | |a Computer science-Mathematics. | |
| 650 | 0 | |a Mathematical statistics. | |
| 650 | 0 | |a Pattern recognition systems. | |
| 650 | 0 | |a Computer simulation. | |
| 650 | 0 | |a Computer science. | |
| 650 | 1 | 4 | |a Artificial Intelligence. |
| 650 | 2 | 4 | |a Probability and Statistics in Computer Science. |
| 650 | 2 | 4 | |a Automated Pattern Recognition. |
| 650 | 2 | 4 | |a Computer Modelling. |
| 650 | 2 | 4 | |a Computer Science. |
| 710 | 2 | |a SpringerLink (Online service) | |
| 773 | 0 | |t Springer Nature eBook | |
| 776 | 0 | 8 | |i Printed edition: |z 9781848007956 |
| 776 | 0 | 8 | |i Printed edition: |z 9781849969451 |
| 776 | 0 | 8 | |i Printed edition: |z 9781852338831 |
| 830 | 0 | |a Advanced Information and Knowledge Processing, |x 2197-8441 | |
| 856 | 4 | 0 | |u https://doi.uam.elogim.com/10.1007/b138856 |z Texto Completo |
| 912 | |a ZDB-2-SCS | ||
| 912 | |a ZDB-2-SXCS | ||
| 950 | |a Computer Science (SpringerNature-11645) | ||
| 950 | |a Computer Science (R0) (SpringerNature-43710) | ||