Nonlinear Signal Processing Using Geometric Methods  048969





Lecture 
Exercise 
Laboratory 
Project or Seminar 
House Work 
Weekly Hours 
2 





Determination of the grade according to progress during the semester.
Prerequisites:
 
(
  Intro. to Digital Signal Processing 
044198
 
  
and
 Random Signals 
044202
 ) 
The Goal of This Course Is to Understand the Mathematical Foundation of Many Recent Methods for Interinsic Modeling and GeometryAssisted Signal Processing. Novel Methods That Extend the Classical Fourier Analysis and Enable Natural DataDriven Parameteriz
1. to Define Fundamental Terms, Including "Intrinsic Modeling"
2. to Analyze Special Cases of Signals and Systems Analytically, Build Intrinsic Metrics, and Prove Their Main Properties
3. to Implement (in Matlab) An Algorithm for Building Intrinsic Models of Synthetic and Real Signals.Heir Main Properties 3. to Implement (in Matlab) An Algorithm for Building Intrinsic Models of Synthetic and Real Signals.Hm for Building Intrinsic Models
Timetable to semester 01/2017
2017/2018 Winter Semester
Room  Building  Hour  day  Lecturer  Exercise Lecture  no.  Registering Group 

353  áð.îàééø  14:3016:30  Sunday  Assistant Professor Talmon Ronen  Lecture  10  10 
TextbooksPublished  Publisher  Authors  Book 

2003  neural computation  belkin, m. and niyogi, p.  laplacian eigenmaps for dimensionality reduction and data representation 
2008   singer, a. and coifman, r.r  non linear independent component analysis with diffusion maps 
1997   chung f.r  spctral graph theory 
Created in 25/09/2017 Time 05:29:38