136 citations · 190 across the 18 of their papers we have counts for
6 papers · 1 filter
Analysis of A Nonsmooth Optimization Approach to Robust Estimation
Laurent Bako, Henrik Ohlsson
In this paper, we consider the problem of identifying a linear map from measurements which are subject to intermittent and arbitarily large errors. This is a fundamental problem in…
Robust Subspace System Identification via Weighted Nuclear Norm Optimization
Dorsa Sadigh, Henrik Ohlsson, S. Shankar Sastry +1
Subspace identification is a classical and very well studied problem in system identification. The problem was recently posed as a convex optimization problem via the nuclear norm…
Blind Identification via Lifting
Henrik Ohlsson, Lillian J. Ratliff, Roy Dong +1
Blind system identification is known to be an ill-posed problem and without further assumptions, no unique solution is at hand. In this contribution, we are concerned with the task…
Nonlinear Compressive Particle Filtering
Henrik Ohlsson, Michel Verhaegen, S. Shankar Sastry
Many systems for which compressive sensing is used today are dynamical. The common approach is to neglect the dynamics and see the problem as a sequence of independent problems. Th…
Blind Identification of ARX Models with Piecewise Constant Inputs
Henrik Ohlsson, Lillian Ratliff, Roy Dong +1
Blind system identification is known to be a hard ill-posed problem and without further assumptions, no unique solution is at hand. In this contribution, we are concerned with the…
Compressive Shift Retrieval
Henrik Ohlsson, Yonina C. Eldar, Allen Y. Yang +1
The classical shift retrieval problem considers two signals in vector form that are related by a shift. The problem is of great importance in many applications and is typically sol…