Time series feature extraction for data mining using DWT and DFT

A planter for plants comprising a lamp of the oil-burning type and comprising a glass base adapted to contain water, a burner having a wick extending therethrough, and a transparent chimney, the lower end of which is sealed relative to the perimeter of the burner and soil is disposed in at least the lower portion of said chimney and said wick extending into said soil to convey moisture from the base into said soil by capillary action.

[1]  Eamonn J. Keogh,et al.  UCR Time Series Data Mining Archive , 1983 .

[2]  Hans-Peter Kriegel,et al.  The R*-tree: an efficient and robust access method for points and rectangles , 1990, SIGMOD '90.

[3]  Ingrid Daubechies,et al.  Ten Lectures on Wavelets , 1992 .

[4]  Christos Faloutsos,et al.  Efficient Similarity Search In Sequence Databases , 1993, FODO.

[5]  Clu-istos Foutsos,et al.  Fast subsequence matching in time-series databases , 1994, SIGMOD '94.

[6]  Alfred Ultsch.  The Integration of Neural Networks with Symbolic Knowledge Processing , 1994 .

[7]  Alberto Maria Segre,et al.  Programs for Machine Learning , 1994 .

[8]  Kyuseok Shim,et al.  Fast Similarity Search in the Presence of Noise, Scaling, and Translation in Time-Series Databases , 1995, VLDB.

[9]  Dina Q. Goldin,et al.  On Similarity Queries for Time-Series Data: Constraint Specification and Implementation , 1995, CP.

[10]  Alberto O. Mendelzon,et al.  Similarity-based queries for time series data , 1997, SIGMOD '97.

[11]  Alberto O. Mendelzon,et al.  Efficient Retrieval of Similar Time Sequences Using DFT , 1998, FODO.

[12]  S. Mallat.  A wavelet tour of signal processing , 1998 .

[13]  Jarke J. van Wijk,et al.  Cluster and Calendar Based Visualization of Time Series Data , 1999, INFOVIS.

[14]  Laura Firoiu,et al.  Clustering Time Series with Hidden Markov Models and Dynamic Time Warping , 1999 .

[15]  L. K. Hansen,et al.  On Clustering fMRI Time Series , 1999, NeuroImage.

[16]  Mohammed Waleed Kadous,et al.  Learning Comprehensible Descriptions of Multivariate Time Series , 1999, ICML.

[17]  Jonathan Goldstein,et al.  When Is ''Nearest Neighbor'' Meaningful? , 1999, ICDT.

[18]  Ada Wai-Chee Fu,et al.  Efficient time series matching by wavelets , 1999, Proceedings 15th International Conference on Data Engineering (Cat. No.99CB36337).

[19]  Divyakant Agrawal,et al.  A comparison of DFT and DWT based similarity search in time-series databases , 2000, CIKM '00.

[20]  Henrik Boström,et al.  Learning First Order Logic Time Series Classifiers , 2000, ILP Work-in-progress reports.

[21]  Pierre Geurts,et al.  Pattern Extraction for Time Series Classification , 2001, PKDD.

[22]  Charu C. Aggarwal,et al.  On the Surprising Behavior of Distance Metrics in High Dimensional Spaces , 2001, ICDT.

[23]  Yang-Sae Moon,et al.  Efficient time-series subsequence matching using duality in constructing windows , 2001, Inf. Syst..

[24]  Konstantinos Kalpakis,et al.  Distance measures for effective clustering of ARIMA time-series , 2001, Proceedings 2001 IEEE International Conference on Data Mining.

[25]  Renée J. Miller,et al.  Similarity search over time-series data using wavelets , 2002, Proceedings 18th International Conference on Data Engineering.

[26]  Eamonn J. Keogh,et al.  Clustering of streaming time series is meaningless , 2003, DMKD '03.

[27]  Clement T. Yu,et al.  Haar Wavelets for Efficient Similarity Search of Time-Series: With and Without Time Warping , 2003, IEEE Trans. Knowl. Data Eng..

[28]  A. Ultsch.  Maps for the Visualization of high-dimensional Data Spaces , 2003 .

[29]  Dimitrios Gunopulos,et al.  A Wavelet-Based Anytime Algorithm for K-Means Clustering of Time Series , 2003 .

[30]  Eamonn J. Keogh,et al.  On the Need for Time Series Data Mining Benchmarks: A Survey and Empirical Demonstration , 2002, Data Mining and Knowledge Discovery.