信号处理中的随机微分几何入门
A Primer on Stochastic Differential Geometry for Signal Processing
摘要：
本书解释了如何在流形上定义和研究连续时间随机过程（准确地说，布朗运动和其他伊藤扩散）。没有知识是假定无论是微分几何或连续时间过程。可以说干的方法是避免首先引入微分几何，然后才引入随机过程;这两个领域的动机和共同发展。
英文摘要：
This primer explains how continuous-time stochastic processes (precisely, Brownian motion and other Ito diffusions) can be defined and studied on manifolds. No knowledge is assumed of either differential geometry or continuous-time processes. The arguably dry approach is avoided of first introducing differential geometry and only then introducing stochastic processes; both areas are motivated and developed jointly.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
