Geometric Optimization Methods for Adaptive Filtering

Understand

The techniques and analysis presented in this thesis provide new methods to solve optimization problems posed on Riemannian manifolds.

• These methods are applied to the subspace tracking problem found in adaptive signal processing and adaptive control.
• A new point of view is offered for the constrained optimization problem.
• Some classical optimization techniques on Euclidean space are generalized to Riemannian manifolds.