經驗模態分解法於信號分解之研究

The Signal Resolving Using in the Empirical Mode Decomposition Method

江鴻鑫(Hong-Shin Jiang) ； 夏榮生(Jung-Sheng Hsia)

《地圖 ： 中華民國地圖學會會刊》 15期 (2005/07) Pp. 77-85

https://doi.org/10.30006/JC.200507.0007

摘要

經驗模態分解法(Empirical Mode Decomposition, EMD)對數值高程模型(Digital Elevation Model, DEM)此種非週期、非線性、非穩態的渾沌信號，有較佳的改進。但EMD分解過程中以標準中誤差作為終止條件未必嚴謹，該條件會影響篩選過程中「內建模態函數」(Intrinsic Mode Function, IMF)分解的次數，即決定了基底(Bias)的數目，進而改變趨勢面，造成資訊的誤判。本文以「標準化互相關」(Normalized Cross-Correlation, NCC)技術作為分解過程中的終止條件，成果顯示能有效抑制分解次數，確保內建模態函數趨於收斂，求得趨勢面，更可觀察地形瞬間變化，有助於三維數位地形之建立與判釋，以供後續之用。

關鍵字

經驗模態分解法 ； 數值高程模型 ； 內建模態函數 ； 標準化互相關

並列摘要

The Empirical Mode Decomposition method can improve the processing of non-cycle, nonlinear and non-stationary chaos signals, such as Digital Elevation Model data. By the method with the characteristics of intuitive, direct, a posteriori and adaptive, instantaneous frequencies can be shown. This paper using Normalized Cross-Correlation to be a stop condition, the results display that the condition can restrain the resolving numbers and make sure convergence of IMF, and get a trend assistant to tree dimension digital terrain building.

並列關鍵字

Empirical Mode Decomposition, EMD ； Digital Elevation Model, DEM ； Intrinsic Mode Function, IMF ； Normalized Cross-Correlation, NCC

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