Feature selection and statistical pattern recognition for the classification of ricker wavelets

Kou-Yuan Huang, Weng Yu Shyu, King Sun Fu

研究成果: Paper同行評審

1 引文 斯高帕斯(Scopus)

摘要

Feature selection and pattern recognition techniques are used for classification of Ricker wavelets. Envelope and instantaneous frequency are used as the features in the classification procedure. Three feature selection techniques are used. In the information-theoretic approach, divergence and Bhattacharyya distances are used as the criteria of feature selection. Feature space transformation of the discriminant method [maximum of tr(S2-1 S1)] is used to select the optima] feature. From the discriminant method, the optimal eigenvector is selected as the optimal feature. From the experiment, the result shows that instantaneous frequency is chosen as the feature to separate 20 and 30 Hz Ricker wavelets. Using instantaneous frequency as the feature, the Bayes classification result of 20 and 30 Hz Ricker wavelets is quite good.

原文English
頁面539-540
頁數2
DOIs
出版狀態Published - 1984
事件1984 Society of Exploration Geophysicists Annual Meeting, SEG 1984 - Atlanta, United States
持續時間: 2 12月 19846 12月 1984

Conference

Conference1984 Society of Exploration Geophysicists Annual Meeting, SEG 1984
國家/地區United States
城市Atlanta
期間2/12/846/12/84

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