Since its founding in 1989 by Terrence Sejnowski, Neural Computation has become the leading journal in the field. Foundations of Neural Computationcollects, by topic, the most significant papers that have appeared in the journal over the past nine years.This volume of Foundations of Neural Computation, on unsupervised learning algorithms, focuses on neural network learning algorithms that do not require an explicit teacher. The goal of unsupervised learning is to extract an efficient internal representation of the statistical structure implicit in the inputs. These algorithms provide insights into the development of the cerebral cortex and implicit learning in humans. They are also of interest to engineers working in areas such as computer vision and speech recognition who seek efficient representations of raw input data.
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About the Author
Geoffrey Hinton is Professor of Computer Science at the University of Toronto.
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1 of 9 people found the following review helpful:
4.0 out of 5 stars
A good book on neural learning,
By vinayak kulkarni (Ratnagiri(MS) INDIA) - See all my reviews
This review is from: Unsupervised Learning: Foundations of Neural Computation (Computational Neuroscience) (Paperback)
After reading the table of contents of this book I came to know that this book is good in the area of neural learning. Forthmore this book is covering information on unsupervised learning & covering topics like local synaptic learning & hebbian learnig. The applications for feature extraction & sensory receptive fields are of my interest. This book is useful for UG & PG students. Thanking you,Vinayak Kulkarni Electronics department Finolex Academy of Management & Technology Ratnagiri(MS)INDIA. pin-415 037
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Inside This Book
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First Sentence:
What use can the brain make of the massive flow of sensory information that occurs without any associated rewards or punishments? Read the first page Key Phrases - Capitalized Phrases (CAPs): (learn more)
Neural Comp, New York, San Mateo, Morgan Kaufmann, Department of Computer Science, Cambridge University Press, Peter Dayan, University of Toronto, Van Essen, Vision Res, San Diego, Englewood Cliffs, Oxford University Press, Academic Press, Department of Psychology, References Atick, Time Iteration, Algorithm Enorm Training Time, Connectionist Models Summer School, Downing Street, John Wiley, Joint Conf, Machine Intelligence, Neural Syst, References Barlow New!
Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
What use can the brain make of the massive flow of sensory information that occurs without any associated rewards or punishments? Read the first page Key Phrases - Capitalized Phrases (CAPs): (learn more)
Neural Comp, New York, San Mateo, Morgan Kaufmann, Department of Computer Science, Cambridge University Press, Peter Dayan, University of Toronto, Van Essen, Vision Res, San Diego, Englewood Cliffs, Oxford University Press, Academic Press, Department of Psychology, References Atick, Time Iteration, Algorithm Enorm Training Time, Connectionist Models Summer School, Downing Street, John Wiley, Joint Conf, Machine Intelligence, Neural Syst, References Barlow New!
Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Citations (learn more)
This book cites 73
books:
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9
books
cite this book:
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- Advances in Neural Information Processing Systems 12 by Sara A. Solla on 7 pages
- Computing Neuron (Computation and Neural Systems Series) by Richard Durbin on 6 pages
- Blind Deconvolution (Prentice Hall Information and System Sciences) by Simon Haykin on page 168, page 173, and page 174
- Independent Component Analysis by Aapo Hyvärinen in Front Matter, and page 203
- Sensory Communication by Walter A. Rosenblith on page 14, and page 173
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- Graphical Models: Foundations of Neural Computation (Computational Neuroscience) by Michael I. Jordan in Front Matter (1), and Front Matter (2)
- Independent Component Analysis: Principles and Practice by Stephen Roberts in Back Matter
- Face Image Analysis by Unsupervised Learning (The Kluwer International Series in Engineering and Computer Science, Volume 612) (The Springer International Series in Engineering and Computer Science) by Marian Stewart Bartlett on page 5
- Self-Organizing Map Formation: Foundations of Neural Computation (Computational Neuroscience) by Klaus Obermayer in Front Matter
- Levels of Perception by Laurence Harris on page 267
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