Abstract
Knowledge-based recognition (or classification) under uncertainty may be considered as a good example of the general problems and methods presented in the previous chapters. In this chapter recognition problems based on the relational and logical knowledge representation are described. Classical methods based on probabilistic description and new approaches (application of uncertain variables are the learning process consisting in the knowledge validation and updating) are presented and discussed in a uniform way, as specific analysis and decision problems with the descriptions of the uncertainty considered in Chapters 3, 5, 6, 7, 11.
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© 2004 Springer-Verlag London
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Bubnicki, Z. (2004). Pattern Recognition. In: Analysis and Decision Making in Uncertain Systems. Communications and Control Engineering. Springer, London. https://doi.org/10.1007/978-1-4471-3760-3_14
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DOI: https://doi.org/10.1007/978-1-4471-3760-3_14
Publisher Name: Springer, London
Print ISBN: 978-1-84996-909-3
Online ISBN: 978-1-4471-3760-3
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