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Title: On selecting the best features in a noisy environment (English)
Author: Flusser, Jan
Author: Suk, Tomáš
Language: English
Journal: Kybernetika
ISSN: 0023-5954
Volume: 34
Issue: 4
Year: 1998
Pages: [411]-416
Summary lang: English
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Category: math
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Summary: This paper introduces a novel method for selecting a feature subset yielding an optimal trade-off between class separability and feature space dimensionality. We assume the following feature properties: (a) the features are ordered into a sequence, (b) robustness of the features decreases with an increasing order and (c) higher-order features supply more detailed information about the objects. We present a general algorithm how to find under those assumptions the optimal feature subset. Its performance is demonstrated experimentally in the space of moment-based descriptors of 1-D signals, which are invariant to linear filtering. (English)
Keyword: Mahalanobis distance
Keyword: 1-D signals
MSC: 62H30
MSC: 62H99
MSC: 62M20
MSC: 65C60
MSC: 68T10
idZBL: Zbl 1274.62433
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Date available: 2009-09-24T19:18:09Z
Last updated: 2015-03-28
Stable URL: http://hdl.handle.net/10338.dmlcz/135224
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Reference: [4] Teh C. H., Chin R. T.: On image analysis by the methods of moments.IEEE Trans. Pattern Anal. Mach. Intell. 10 (1988), 496–512 Zbl 0709.94543, 10.1109/34.3913
Reference: [5] Pawlak M.: On the reconstruction aspects of moment descriptors.IEEE Trans. Inform. Theory 38 (1992), 1698–1708 Zbl 0761.68104, MR 1187813, 10.1109/18.165444
Reference: [6] Liao S. X., Pawlak M.: On image analysis by moments.IEEE Trans. Pattern Anal. Mach. Intell. 18 (1996), 254–266 10.1109/34.485554
Reference: [7] Flusser J., Suk T.: Invariants for recognition of degraded 1-D digital signals.In: Proc. 13th ICPR, Vienna 1996, vol. II, pp. 389–393
Reference: [8] Flusser J., Suk T.: Classification of degraded signals by the method of invariants.Signal Processing 60 (1997), 243–249 Zbl 1006.94512, 10.1016/S0165-1684(97)00075-3
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