3 accepted papers
This paper studies fixed step-size stochastic approximation (SA) schemes, including stochastic gradient schemes, in a Riemannian framework. It is motivated by several applications, where geodesics can be computed explicitly, and their use accelerates crude Euclidean methods. A fixed step-size scheme…
Many signal and image processing applications, including SAR polarimetry and texture analysis, require the classification of complex covariance matrices. The present paper introduces a geometric learning approach on the space of complex covariance matrices based on a new distribution called Riemanni…
This paper describes the application of particle filtering to the solution of the problem of filtering with observations in a manifold. Mathematically, this is based on an original use of so-called connector maps. It is shown that well-chosen connector maps can be used to transform successive sample…