Abstract
In this chapter we wish to show how our general approach allows us to deal with central problems in pattern recognition. In Sect. 12.1 we will rederive relations allowing feature selection that will be explained below. In Sect. 12.2 we present the basic scheme for the construction of a parallel computer for pattern recognition. The subsequent sections, 12.3 and 12.4, show how such a system can learn patterns to be recognized. Finally, Sect. 12.5 extends these results to the learning of processes. Section 12.1 is a bit formal so that readers who are only interested in the most important topics of this chapter need to read this section only as far as equation (12.1) and may then proceed to the subsequent sections.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
H. Haken (ed.): Pattern Formation by Dynamic Systems and Pattern Recognition, Springer Ser. Syn., Vol. 5 (Springer, Berlin, Heidelberg 1979)
J.S. Denker (ed.): Neural Networks for Computing, AIP Conf. Proc. 151, New York 1986
M. Candill, S. Butler: IEEE First Int. Conf. on Neural Networks, Vols. I-IV, SOS Printing, San Diego 1987
Section 12.1
P.A. Devijver, J. Kittler: Pattern Recognition, A Statistical Approach (Prentice Hall, Englewood Cliffs, N.J. 1982)
Section 12.2
H. Haken: In Computational Systems, Natural and Artificial, ed. by H. Haken, Springer Ser. Syn., Vol. 38 (Springer, Berlin, Heidelberg 1987)
Section 12.3
H. Haken: unpublished
Section 12.4
H. Haken: unpublished
For the special case of spin glasses see D.H. Ackley, G.E. Hinton, T.J. Sejnowski: Cognitive Science 9, 147 (1985)
Section 12.5
H. Haken: unpublished
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 1988 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Haken, H. (1988). Pattern Recognition. In: Information and Self-Organization. Springer Series in Synergetics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-07893-8_12
Download citation
DOI: https://doi.org/10.1007/978-3-662-07893-8_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-07895-2
Online ISBN: 978-3-662-07893-8
eBook Packages: Springer Book Archive