Fundamentals of speech recognition
Fundamentals of speech recognition
An Online Algorithm for Segmenting Time Series
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Scaling up Dynamic Time Warping to Massive Dataset
PKDD '99 Proceedings of the Third European Conference on Principles of Data Mining and Knowledge Discovery
Time Series Segmentation for Context Recognition in Mobile Devices
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Estimating the number of segments in time series data using permutation tests
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
On the Need for Time Series Data Mining Benchmarks: A Survey and Empirical Demonstration
Data Mining and Knowledge Discovery
A PCA-based similarity measure for multivariate time series
Proceedings of the 2nd ACM international workshop on Multimedia databases
Temporal classification: extending the classification paradigm to multivariate time series
Temporal classification: extending the classification paradigm to multivariate time series
Identity authentication using improved online signature verification method
Pattern Recognition Letters
An efficient k nearest neighbor search for multivariate time series
Information and Computation
Review: Expert systems and evolutionary computing for financial investing: A review
Expert Systems with Applications: An International Journal
Artificial Intelligence in Medicine
Modified Gath--Geva clustering for fuzzy segmentation of multivariate time-series
Fuzzy Sets and Systems
Data Mining and Knowledge Discovery
Asynchronism-based principal component analysis for time series data mining
Expert Systems with Applications: An International Journal
On-line signature verification using vertical signature partitioning
Expert Systems with Applications: An International Journal
| Hi-index | 12.05 |
In recent years, dynamic time warping (DTW) has begun to become the most widely used technique for comparison of time series data where extensive a priori knowledge is not available. However, it is often expected a multivariate comparison method to consider the correlation between the variables as this correlation carries the real information in many cases. Thus, principal component analysis (PCA) based similarity measures, such as PCA similarity factor (SPCA), are used in many industrial applications. In this paper, we present a novel algorithm called correlation based dynamic time warping (CBDTW) which combines DTW and PCA based similarity measures. To preserve correlation, multivariate time series are segmented and the local dissimilarity function of DTW originated from SPCA. The segments are obtained by bottom-up segmentation using special, PCA related costs. Our novel technique qualified on two databases, the database of signature verification competition 2004 and the commonly used AUSLAN dataset. We show that CBDTW outperforms the standard SPCA and the most commonly used, Euclidean distance based multivariate DTW in case of datasets with complex correlation structure.