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Mesh-free adjoint methods for nonlinear filters

机译:非线性滤波器无网的伴随方法

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We apply a new industrial strength numerical approximation, called the "mesh-free adjoint method", to solve the nonlinear filtering problem. This algorithm exploits the smoothness of the problem, unlike particle filters, and hence we expect that mesh-free adjoints are superior to particle filters for many practical applications. The nonlinear filter problem is equivalent to solving the Fokker-Planck equation in real time. The key idea is to use a good adaptive non-uniform quantization of state space to approximate the solution of the Fokker-Planck equation. In particular, the adjoint method computes the location of the nodes in state space to minimize errors in the final answer. This use of an adjoint is analogous to optimal control algorithms, but it is more interesting. The adjoint method is also analogous to importance sampling in particle filters, but it is better for four reasons: (1) it exploits the smoothness of the problem; (2) it explicitly minimizes the errors in the relevant functional; (3) it explicitly models the dynamics in state space; and (4) it can be used to compute a corrected value for the desired functional using the residuals. We will attempt to make this paper accessible to normal engineers who do not have PDEs for breakfast.
机译:我们应用新的工业强度数值近似,称为“无网址方法”,解决非线性滤波问题。这种算法利用问题的平滑度,与粒子过滤器不同,因此我们预计近距离伴随着许多实际应用的粒子过滤器。非线性滤波器问题相当于实时解决Fokker-Planck方程。关键的想法是使用良好的自适应非均匀量化状态空间来近似Fokker-Planck方程的解决方案。特别地,伴随方法计算状态空间中节点的位置以最小化最终答案中的错误。这种伴随的使用类似于最佳控制算法,但它更有趣。伴随方法也类似于粒子过滤器中的重要性采样,但是由于四个原因更好:(1)它利用问题的平滑度; (2)它明确地最小化了相关功能中的错误; (3)它明确地模拟了国家空间中的动态; (4)可用于计算使用残差来计算所需功能的校正值。我们将尝试通过早餐没有PDE的普通工程师来制作本文。

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