基于动态逻辑方法的瞬态混合过程参数优化估计

R. Kozma, L. Perlovsky, R. Deming
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引用次数: 5

摘要

本文推广了具有时变能量函数的瞬态过程的动态逻辑方法。早期的研究已经为深度学习在高噪声和杂波环境下的模式识别奠定了坚实的基础。我们推导了具有时变能量函数的DL方程,并将其应用于二维图像的瞬态过程检测。该方法已在仿真数据上进行了验证。结果表明,在爆炸过程和内爆过程中,空间传播梯度和能量增加/减少速率等瞬态参数的估计精度较高
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal Estimation of Parameters of Transient Mixture Processes Using Dynamic Logic Approach
In this work we generalize dynamic logic approach for the case of time transient processes with time-dependent energy function. Earlier studies have laid down the firm foundations of DL to pattern recognition in the presence of very high noise and clutter. We derive DL equations with time-dependent energy function and apply it to the detection of transient processes in 2-dimensional images. The developed method has been tested on simulated data. The results show good accuracy of the estimation of transient parameters, including the gradient of spatial propagation, and rate of the energy increase/decrease in the case of processes with explosive/implosive processes, respectively
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