Optimal design of simultaneous source encoding
Optimal design of simultaneous source encoding
复制标题
同步源编码的优化设计
DOI：
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发表时间：
2015
期刊：
影响因子：
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通讯作者：
L. Horesh
中科院分区：
文献类型：
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作者：
E. Haber;K. van den Doel;L. Horesh
广泛的参数估计问题涉及收集过多数量的观测数据N。通常，每个这样的观测数据都涉及通过在一些预定义位置注入能量来激励区域以及在另一组位置记录域的响应。已经观察到，通过考虑K个小得多的多个线性叠加的实验，通常可以得到类似的结果。这允许及时构造反问题的解，而不是。考虑到这些考虑，不需要执行所有的N个实验，而只需要进行数量少得多的K个实验，这些K个实验的同时震源是具有一定权重的叠加。设计这样的程序将导致获取时间的急剧减少。我们试图在这项工作中严格研究的问题是：什么是最优权重？我们将问题描述为最优实验设计问题，并表明通过利用该领域的技术，答案是容易获得的。设计最优实验需要一些统计框架，因此，一个人选择使用的统计框架在权重的选择中起着重要作用。
A broad range of parameter estimation problems involve the collection of an excessively large number of observations N. Typically, each such observation involves excitation of the domain through injection of energy at some predefined sites and recording of the response of the domain at another set of locations. It has been observed that similar results can often be obtained by considering a far smaller number K of multiple linear superpositions of experiments with . This allows the construction of the solution to the inverse problem in time instead of . Given these considerations it should not be necessary to perform all the N experiments but only a much smaller number of K experiments with simultaneous sources in superpositions with certain weights. Devising such procedure would results in a drastic reduction in acquisition time. The question we attempt to rigorously investigate in this work is: what are the optimal weights? We formulate the problem as an optimal experimental design problem and show that by leveraging techniques from this field an answer is readily available. Designing optimal experiments requires some statistical framework and therefore the statistical framework that one chooses to work with plays a major role in the selection of the weights.