2007/08/13 by Bhashyam Balaji, Balaji, Bhashyam
Computer Science · Engineering · Physics and Astronomy · #Advanced Adaptive Filtering Techniques #FOS: Physical sciences #Gaussian Processes and Bayesian Inference #Neural Networks and Applications #Other Condensed Matter (cond-mat.other) #cond-mat.other
paper · pdf · doi:10.48550/arxiv.0708.1663
Interdisciplinary, 41 pages, 5 figures, JHEP3 class; added more discussion and references
openalex publication_date 2007/08/13 · arxiv created 2008/04/03 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In this paper, the Feynman path integral formulation of the continuous-continuous filtering problem, a fundamental problem of applied science, is investigated for the case when the noise in the signal and measurement model is additive. It is shown that it leads to an independent and self-contained analysis and solution of the problem. A consequence of this analysis is Feynman path integral formula for the conditional probability density that manifests the underlying physics of the problem. A corollary of the path integral formula is the Yau algorithm that has been shown to be superior to all other known algorithms. The Feynman path integral formulation is shown to lead to practical and implementable algorithms. In particular, the solution of the Yau PDE is reduced to one of function computation and integration.