摘要
针对傅里叶正则算法在复杂温度场重建过程中存在的不足 ,首先用正则化方法获得温度场重建这一不适定问题的稳定解 ,然后利用迭代技术对解进行一次迭代优化修正 ,充分考虑观测矩阵降质对温度场重建的影响·提出一种基于正则化方法与一次迭代技术相结合的复杂温度场重建算法·仿真结果表明该算法温度场重建精度优于傅里叶正则算法 。
The Forier regularizing algorithm in reconstructing complex temperature field was discussed. The stable solution of temperature-field reconstruction problem was obtained by using regularization method, and then the solution was modified by using one-time iterative technology for optimization. Considering the influence of observation matrix on the complex temperature-field reconstruction a new complex temperature field reconstruction algorithm was proposed based on combination of regularization method and one-time iterative technology. The proposed method is fast and more accurate than Forier regularizing algorithm.
出处
《东北大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2003年第4期307-310,共4页
Journal of Northeastern University(Natural Science)
基金
国家自然科学基金资助项目 (5 0 0 740 16)
关键词
正则化
声学图像重建
重建算法
复杂温度场
逆问题
迭代技术
regularization
acoustic image reconstruction
reconstruction algorithms
complex temperature field
inverse problem
iterative technology
