Emergent componential coding of a handwritten image database by neural self-organisation

Network: Computation in Neural Systems

Volumn 9, Issue 4, 1998, Pages 433-447

  Webber, Chris J S ^a  

^a DEFENCE SCIENCE AND TECHNOLOGY LABORATORY   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; ARTIFICIAL NEURAL NETWORK; AUTOMATED PATTERN RECOGNITION; BAYES THEOREM; HANDWRITING; HUMAN; PROBABILITY;

BAYES THEOREM; HANDWRITING; HUMANS; MARKOV CHAINS; NEURAL NETWORKS (COMPUTER); PATTERN RECOGNITION, AUTOMATED;

EID: 26444441501     PISSN: 0954898X     EISSN: None     Source Type: Journal    
DOI: 10.1088/0954-898X_9_4_003     Document Type: Article

References (23)

1. Barlow H B 1989 Unsupervised learning Neural Comput. 1 295-311
2. Bell A J and Sejnowski T J 1997 The 'independent components' of natural scenes are edge filters Vision Res. submitted
3. CEDAR 1992 USPS Office of Advanced Technology database of handwritten cities, states, ZIP codes, digits, and alphabetic characters Center of Excellence for Document Analysis and Recognition Image Database CD-ROM 1
4. Dayan P and Hinton G E 1996 Varieties of Helmholtz machine Neural Networks 9 1385-403
5. Field D J 1994 What is the goal of sensory coding? Neural Comput. 6 559-601
6. Foldiak P 1990 Forming sparse representations by local anti-Hebbian learning Biol. Cybern. 64 165-70
7. Friedman J H and Tukey J W 1974 A projection pursuit algorithm for exploratory data analysis IEEE Trans. Comput. C-23 881-90
8. Hebb D O 1949 The Organisation of Behavior (New York: Wiley)
9. Hinton G E, Dayan P, Frey B J and Neal R M 1995 The wake-sleep algorithm for unsupervised neural networks Science 268 1158-61
10. Hinton G E and Zemel R 1994 Autoencoders, minimum description-length and Helmholtz free energy Advances in Neural Information Processing Systems 6 ed J Cowan, G Tesauro and J Alspector (San Mateo, CA: Morgan Kaufman) pp 3-10
11. Lee D D and Seung H S 1997 Unsupervised learning by convex and conic coding Advances in Neural Information Processing Systems 9 (Cambridge, MA: MIT Press) pp 515-21
12. Luttrell S P 1995 Designing analysable networks Handbook of Neural Computation (Oxford: Oxford University Press)
13. - 1997 A unified model of density models and auto-encoders Preprint N197039-NNM, Isaac Newton Institute, obtainable from http://www.newton.cam.ac.uk/preprints.html
14. - 1998 A Bayesian analysis of complementary approaches to training self-organising stochastic networks Technical Report DERA/CIS/CIS5/TR97165, Information Centre, DERA, Malvern, UK
15. Oja E 1982 A simplified neuron model as a principal component analyser J. Math. Biol. 15 267-73
16. Olshausen B A and Field D J 1996 Emergence of simple-cell receptive field properties by learning a sparse code for natural images Nature 381 607-9
17. - 1997 Sparse coding with an overcomplete basis set: a strategy employed by VI? Vision Res. 37 3311-25
18. Saund E 1995 A multiple cause mixture model for unsupervised learning Neural Comput. 7 57-71
19. Webber C J S 1991 Self-organisation of position- and deformation-tolerant neural representations Network: Comput. Neural Syst. 2 43-61
20. - 1994 Self-organisation of transformation-invariant detectors for constituents of perceptual patterns Network: Comput. Neural Syst. 5 471-96
21. - 1997 Generalisation and discrimination emerge from a self-organising componential network: a speech example Network: Comput. Neural Syst. 8 425-40
22. - 1998 Self-organisation of symmetry networks Neural Comput. submitted
23. Zemel R 1993 A minimum description-length framework for unsupervised learning PhD Thesis University of Toronto