论文标题
部分可观测时空混沌系统的无模型预测
Enabling the autofocus approach for parameter optimization in planar measurement geometry clinical optoacoustic imaging
论文作者
论文摘要
储层计算是预测湍流的有力工具,其简单的架构具有处理大型系统的计算效率。然而,其实现通常需要完整的状态向量测量和系统非线性知识。我们使用非线性投影函数将系统测量扩展到高维空间,然后将其输入到储层中以获得预测。我们展示了这种储层计算网络在时空混沌系统上的应用,该系统模拟了湍流的若干特征。我们表明,使用径向基函数作为非线性投影器,即使只有部分观测并且不知道控制方程,也能稳健地捕捉复杂的系统非线性。最后,我们表明,当测量稀疏、不完整且带有噪声,甚至控制方程变得不准确时,我们的网络仍然可以产生相当准确的预测,从而为实际湍流系统的无模型预测铺平了道路。
In optoacoustic (photoacoustic) tomography, several parameters related to tissue and detector features are needed for image formation, but they may not be known a priori. An autofocus (AF) algorithm is generally used to estimate these parameters. However, the algorithm works iteratively, therefore, it is impractical for clinical imaging with systems featuring planar geometry due to long reconstruction times. We have developed a fast autofocus (FAF) algorithm for optoacoustic systems with planar geometry that is much simpler computationally than the conventional AF algorithm. We show that the FAF algorithm required about 5 sec. to provide accurate estimates of the speed of sound in simulated data and experimental data obtained using an imaging system that is poised to enter the clinic. The applicability of FAF for estimating other image formation parameters is discussed. We expect the FAF algorithm to contribute decisively to the clinical use of optoacoustic tomography systems with planar geometry.