Tel Aviv University, Applied Mathematics Seminar
Date:       Tuesday December 25, 2012, 15:10
Place:      Schreiber Bldg, Room 309
Speaker: Ronen Talmon, Yale University
Title: Nonlinear Signal Processing Based on Empirical
Intrinsic Geometry
In this talk, I will present a method for nonlinear signal processing
based on empirical intrinsic geometry (EIG). This method provides a
convenient framework for combining geometric and statistical analysis
and incorporates concepts from information geometry. Unlike classic
information geometry that assumes known probabilistic models, we
empirically infer an intrinsic model of distribution estimates, while
maintaining similar theoretical guarantees. The key observation is
that the probability distributions of signals, rather than specific
realizations, uncover relevant geometric information. The proposed
modeling exhibits two important properties which demonstrate its
advantage compared to common geometric algorithms. We show that our
model is noise resilient and invariant under different observation
and instrumental modalities. In addition, we show that it can be
extended efficiently to newly acquired measurements in a sequential
manner. These two properties make the proposed model especially
suitable for signal processing. We revisit the Bayesian approach and
incorporate statistical dynamics and empirical intrinsic geometric
models into a unified nonlinear filtering framework. We then apply
the proposed method to nonlinear and non-Gaussian filtering problems.
In addition, we show applications to biomedical signal analysis and
acoustic signal processing.
Webpage of the applied mathematics seminar:
Dr. Yoel Shkolnisky
Department of Applied Mathematics
School of Mathematical Sciences        phone:  972-3-640-8705
Tel Aviv University,                   fax  :  972-3-640-9357
Tel Aviv, 69978 Israel                 email:   <>
Technion Math Net-2 (TECHMATH2)
Editor: Michael Cwikel   <> 
Announcement from: Yoel Shkolnisky   <>