Abstract
In this paper we discuss classifier architectures to categorize time series. Three different architectures for the fusion of local classifier decisions are presented and applied to classify recordings of cricket songs. Different features from local time windows are extracted automatically from the waveform of the sound patterns. These features are used to classify the whole time series. We present results for all three classifier architectures on a data set of 28 different categories.
This is a preview of subscription content, log in via an institution to check access.
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
C. Dietrich, F. Schwenker, K. Riede, and G. Palm. Automated classification of cricket songs utilizing pulse detection, time and frequency features and data fusion. submited to Journal of the Acoustical Society of America, 2001.
K. Fukunaga. Introduction to Statistical Pattern Recognition. Academic Press, New York, 1990.
S. Ingrisch. Taxonomy, stridulation and development of podoscirtinae from thailand. Senckenbergiana biologica, 77:47–75, 1997.
S. Ingrisch and G. Koehler. Die Heuschrecken Mitteleuropas. Westarp Wissenschaften, Magdeburg, 1998.
L. I. Kuncheva. Clustering and selection model for classifier combination. In 4th International Conference on Knowledge-Based Intelligent Engineering Systems, 2000.
L. I. Kuncheva and J. C. Bezdek. An integrated framework for generalized nearest prototype classifier design. Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 6(5):437–457, 1998.
F. Nischk. Die Grillengesellschaften zweier neotropischer Waldökosysteme in Ecuador. PhD thesis, University of Köln in Germany, 1999. Memorandum UCB/ERL-M89/29.
J. Pearl. Probabilistic Reasoning in Intelligent Systems. Morgan Kaufmann Publishers, San Francisco, 1988.
L. R. Rabiner and S. E. Sambur. An algorithm for determining the endpoints of isolated utterances. Bell Syst. Technical Journal, 54(2):297–315, 1997.
S. Singh. 2D spiral pattern recognition with possibilistic measures. Pattern Recognition Letters, 19(2):141–147, 1998.
D. B. Skalak. Prototype Selection for Composite Nearest Neighbour Classifiers. PhD thesis, University of Massachusetts, 1997.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2001 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Dietrich, C., Schwenker, F., Palm, G. (2001). Classification of Time Series Utilizing Temporal and Decision Fusion. In: Kittler, J., Roli, F. (eds) Multiple Classifier Systems. MCS 2001. Lecture Notes in Computer Science, vol 2096. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48219-9_38
Download citation
DOI: https://doi.org/10.1007/3-540-48219-9_38
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-42284-6
Online ISBN: 978-3-540-48219-2
eBook Packages: Springer Book Archive