CAJ | 학술논문

经验模式分解（EMD）能够有效获得非平稳非线性信号的时频特征，但传统的EMD分解算法存在严重的端点效应．在深入研究和分析EMD算法的基础上，提出了一种基于波形匹配的端点效应处理方案，通过计算波形匹配度，在平均包络线内部寻找与其端部变化趋势最为接近的子波，并用这段子波代替平均包络线的边缘部分，使处理后的平均包络线极大地接近真实包络线，并把这种端点效应处理方案的EMD分解算法应用到实际的股票市场价格趋势分解中．实验结果表明，与经典的EMD边界延拓算法相比，本文提出的算法能更有效地抑制EMD分解时的边界效应，分解得到的固有模式函数更能体现模拟信号真实的频率、幅值信息．应用实验表明：与现有方法相比，该方法更能提高预测精度．
경험모식분해（EMD）능구유효획득비평은비선성신호적시빈특정，단전통적EMD분해산법존재엄중적단점효응．재심입연구화분석EMD산법적기출상，제출료일충기우파형필배적단점효응처리방안，통과계산파형필배도，재평균포락선내부심조여기단부변화추세최위접근적자파，병용저단자파대체평균포락선적변연부분，사처리후적평균포락선겁대지접근진실포락선，병파저충단점효응처리방안적EMD분해산법응용도실제적고표시장개격추세분해중．실험결과표명，여경전적EMD변계연탁산법상비，본문제출적산법능경유효지억제EMD분해시적변계효응，분해득도적고유모식함수경능체현모의신호진실적빈솔、폭치신식．응용실험표명：여현유방법상비，해방법경능제고예측정도．
Empirical mode decomposition （EMD）, which can extract real time-frequency characteristics from non-stationary and nonlinear signals, however, has an involved end effect in the course of getting the envelops of the signal by the spline interpolation. In this paper, a new method based on wave matching to deal with the end effect is proposed, which replaces the ends of the mean envelop with the most suited sequence in the inner envelop making the post-dealing mean envelope have the most similarity of tendency with the real one. Compared with the classical boundary extension algorithm, the improved algorithm can increasingly suppress the end effect in EMD and reflect the true original signal frequency information as well as amplitude value, and it is well used to forecast the trend of stock market prices. The experiments show that the presented method can more effectively improve the prediction accuracy.