4 papers
Error Analysis for the Linear Feedback Particle Filter
Amirhossein Taghvaei, Prashant G. Mehta
This paper is concerned with the convergence and the error analysis for the feedback particle filter (FPF) algorithm. The FPF is a controlled interacting particle system where the…
How regularization affects the critical points in linear networks
Amirhossein Taghvaei, Jin W. Kim, Prashant G. Mehta
This paper is concerned with the problem of representing and learning a linear transformation using a linear neural network. In recent years, there has been a growing interest in t…
Attitude Estimation with Feedback Particle Filter
Chi Zhang, Amirhossein Taghvaei, Prashant G. Mehta
This paper presents theory, application, and comparisons of the feedback particle filter (FPF) algorithm for the problem of attitude estimation. The paper builds upon our recent wo…
Gain Function Approximation in the Feedback Particle Filter
Amirhossein Taghvaei, Prashant G. Mehta
This paper is concerned with numerical algorithms for gain function approximation in the feedback particle filter. The exact gain function is the solution of a Poisson equation inv…