摘要： 针对时序数据相似性搜索面临的高维性问题，提出一种利用按沃尔什序数排列的离散沃尔什变换((DWHT)W)对时序数据进行维归约的方法。(DWHT)W是正交变换，变换矩阵简单，可以应用快速算法，对时序数据有更好的特征提取能力，用其索引时间序列数据在理论上具备非漏报性质。与基于离散傅里叶变换和基于离散沃尔什变换的对比实验表明，该方法可以获得更高的查询效率。
关键词:
时间序列,
离散沃尔什变换,
按沃尔什序数排列,
范围查询,
近邻查询
Abstract: In order to solve the high-dimensional problem in similarity search over time series data, a new method of indexing and similarity searching in time series databases based on (DWHT)W is proposed in this paper. (DWHT)W is orthogonal and can use fast algorithm, and its transformation matrix is very simple. (DWHT)W has excellent performance in feature extraction and is used as an efficient dimensionality reduction technique to permit similarity search over large time series databases without false dismissals. Experimental results demonstrate that performance of the proposed method is more efficient than that of DFT(Discrete Fourier Transform) and DWT(Discrete Wavelet Transform).
Key words:
time series,
Discrete Walsh Transform(DWT),
arranged according to Walsh sequence,
range query,
nearest neighbor query
中图分类号:
崔保良, 滕少华, 崔振. 基于Walsh变换的时序数据相似性搜索[J]. 计算机工程, 2011, 37(8): 55-57.
CUI Bao-Liang, TENG Shao-Hua, CUI Zhen. Similarity Search over Time Series Data Based on Walsh Transform[J]. Computer Engineering, 2011, 37(8): 55-57.