文档介绍：TEMPORAL PATTERN IDENTIFICATION OF TIME
SERIES DATA USING PATTERN WAVELETS AND
IC ALGORITHMS
RICHARD J. POVINELLI AND XIN FENG
Department of Electrical puter Engineering
Marquette University, . Box 1881, Milwaukee, WI 53201-1881, USA
E-mail: ******@
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ABSTRACT:
A new method for temporal pattern matching of a time series is
developed using pattern wavelets and ic algorithms. The
pattern wavelet is applied to the matching of an embedded time
series. A problem-specific fitness factor is introduced in the new
algorithm, which is useful to construct a fitness function of the
feature space. A two-step process discovers the pattern wavelet that
yields high fitness value. The best temporal pattern matches are
found through a thresholding process. These matches are kept and
the future time series data point is used in the ic algorithm's
fitness function. The algorithm has been essfully applied to the
identification of statistically significant temporal patterns in
financial time series data.
Keywords: Temporal Pattern Identification, ic Algorithms, Pattern
Recognition, Time Series Analysis, Wavelets
INTRODUCTION
Data mining is the exploration of data with the goal of discovering hidden structure.
In many real-world applications, it is important to study the change of