A comparison of DFT and DWT based similarity search in time-series databases

Similarity search in time-series databases has received significant attention lately. Popular techniques for efficient retrieval of time sequences in time-series databases has been to use Discrete Fourier Transform (DFT). Recently, the Discrete Wavelet Transform (DWT) has gained popular interest in database domain and several proposals have been made to replace DFT by DWT for similarity search over time-series databases. In this paper, we explore the feasibility of replacing DFT by DWT with a comprehensive analysis of the DFT and DWT as matching functions in time-series databases. Our results show that although the DWT based technique has several advantages, e.g., the DWT has complexity of O(N) whereas DFT is O(N log N ), DWT does not reduce relative matching error and does not increase query precision in similarity search as suggested by previous works 1. We conclude that, by exploring the conjugate property of DFT in real domain, the DFT-based and DWT-based techniques yiel...