1) iterated optimal stack
优化迭代叠加
1.
These techniques include prestack S/N ratio enhancement, heightening of the dominant frequency of reflected signals and spreading of the frequency band of significant signals, frequency divided processing, iterated optimal stack, signal direction constrained noise elimination, as well as predicted trace interpolation in 3-D FXY domain.
针对高分辨采集的地震资料 ,采用了高分辨地震资料处理的各种技术 :地震资料叠前提高信噪比处理、提高反射信号主频和展宽有效信号频带、分频处理方法、优化迭代叠加方法、信号方向约束预测去噪方法、三维FXY域预测道内插方法等 ,并讨论了叠后提高横向分辨率问题 ,在实际资料处理中取得了较好的效果。
2) iterative optimization
迭代优化
1.
Lastly,the iterative optimization algorithm.
最后,给出了求解该模型的迭代优化算法,并进行了算例验证。
2.
In this paper, by applying of the boundary integral equation method and iterative optimization technique, a crack identification method based on the static displacement measurement is given, where the normal problem is solved by author′s high precision boundary integral equation method.
本文使用边界积分方程方法（ＢＥＭ）与迭代优化技术，建立了一种以静态边界位移测量为补充信息的裂纹识别方法，迭代中正问题的求解，采用了作者提出的高精度边界积分方程算法，结果表明在测量点充分、选位合理的前提下，该方法具有收敛快、识别精度好的特
3.
This paper focuses on the methods of localization with iterative optimization in wireless sensor networks.
研究了迭代优化方法在无线传感器网络节点定位中的应用,针对多维尺度分析定位技术和传统的梯度迭代优化方法,根据数值实验确定了迭代步长和网络连通度之间的函数关系,提出了一种基于连通度的分布式多维尺度分析节点定位算法(a connectivity-based distributed weighted multidimensional scaling algorithm,简称dwMDS(C))。
4) optimization stack
优化叠加
1.
This paper suggests that fine processing results can reached through a series of processing such as surface consistent amplitude processing, denoising in multiple domains, residual moveout correction, and dominant energy optimization stack.
针对深层地震信号能量弱、频率低、可描述性差及信噪比低的特点 ,对深层地震资料的处理方法开展了研究 ,提出了采用地表一致性振幅处理技术、多域去噪技术、剩余时差校正技术、主能量优化叠加技术等进行精细处理 ,并且 ,将地质模型作为一种约束条件引入深层资料处理的整个环节 ,提高了叠加成象的精度。
5) iterative shift and add method
迭代位移叠加法
1.
Because there are many kinds of noise, the noise bias terms are introduced in the iterative shift and add method for astronomical image reconstruction when working in real data.
当工作于实际数据时 ,由于存在着多种噪声 ,导致了天文像复原迭代位移叠加法中的噪声偏差项。
6) iterative median stack
迭代中值叠加
补充资料：层层迭迭
1.见"层层迭迭"。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条