吉林大学学报(地球科学版)
吉林大學學報(地毬科學版)
길림대학학보(지구과학판)
Journal of Jilin University (Earth Science Edition)
2015年
6期
1855-1861
,共7页
刘霞%陈晨%赵玉婷%汪鑫
劉霞%陳晨%趙玉婷%汪鑫
류하%진신%조옥정%왕흠
多子波%匹配追踪%粒子群
多子波%匹配追蹤%粒子群
다자파%필배추종%입자군
multi-wavelet%matching pursuit%particle swarm optimization
针对地震信号多子波分解与重构技术中匹配追踪算法能够根据地震信号自身特点进行自适应分解、但其计算量庞大的问题,笔者提出一种粒子群快速优化算法,用于快速搜索地震信号稀疏分解的最优匹配原子。即在迭代过程中,将搜索区域确定在高斯函数能量集中的部分,避免了搜索过程的“贪婪性”,能有效降低稀疏分解复杂度。同时,在粒子群算法中引入了一种多项式变异算子,可以有效避免搜索最优解的过度集中。实验结果证明,此算法将匹配追踪的分解精度提高了67倍,更使计算效率提高了153倍。
針對地震信號多子波分解與重構技術中匹配追蹤算法能夠根據地震信號自身特點進行自適應分解、但其計算量龐大的問題,筆者提齣一種粒子群快速優化算法,用于快速搜索地震信號稀疏分解的最優匹配原子。即在迭代過程中,將搜索區域確定在高斯函數能量集中的部分,避免瞭搜索過程的“貪婪性”,能有效降低稀疏分解複雜度。同時,在粒子群算法中引入瞭一種多項式變異算子,可以有效避免搜索最優解的過度集中。實驗結果證明,此算法將匹配追蹤的分解精度提高瞭67倍,更使計算效率提高瞭153倍。
침대지진신호다자파분해여중구기술중필배추종산법능구근거지진신호자신특점진행자괄응분해、단기계산량방대적문제,필자제출일충입자군쾌속우화산법,용우쾌속수색지진신호희소분해적최우필배원자。즉재질대과정중,장수색구역학정재고사함수능량집중적부분,피면료수색과정적“탐람성”,능유효강저희소분해복잡도。동시,재입자군산법중인입료일충다항식변이산자,가이유효피면수색최우해적과도집중。실험결과증명,차산법장필배추종적분해정도제고료67배,경사계산효솔제고료153배。
In a multi‐wavelet decomposition and reconstruction of seismic signal , the matching pursuit algorithm can be adaptive according to the characteristics of the seismic signal itself .In view of the large amount of calculation ,the author presents a particle swarm fast optimization algorithm ,which is used for fast search optimum matching atoms of seismic signal sparse decomposition .In concrete ,the searching area is determined by the energy concentrated part of Gaussian function in the process of iteration .This can avoid the greediness during the searching process ,and effectively reduce the sparse decomposition complexity . At the same time , a polynomial mutation operator is introduced in the particle swarm optimization algorithm ,which can effectively avoid the excessive concentration during searching the optimal solution .The experimental results show that the algorithm can reach a precision of matching pursuit decomposition 67 times higher than before ,and increase the calculation efficiency by 153 times .