6 papers
Learning High-Quality Latent Representations for Anomaly Detection and Signal Integrity Enhancement in High-Speed Signals
Muhammad Usama, Hee-Deok Jang, Soham Shanbhag +3
This paper addresses the dual challenge of improving anomaly detection and signal integrity in high-speed dynamic random access memory signals. To achieve this, we propose a joint…
Transversally exponentially stable Euclidean space extension technique for discrete time systems
Soham Shanbhag, Dong Eui Chang
We propose a modification technique for discrete time systems for exponentially fast convergence to compact sets. The extension technique allows us to use tools defined on Euclidea…
Machine learning based state observer for discrete time systems evolving on Lie groups
Soham Shanbhag, Dong Eui Chang
In this paper, a machine learning based observer for systems evolving on manifolds is designed such that the state of the observer is restricted to the Lie group on which the syste…
Angular velocity and linear acceleration measurement bias estimators for the rigid body system with global exponential convergence
Soham Shanbhag, Dong Eui Chang
Rigid body systems usually consider measurements of the pose of the body using onboard cameras/LiDAR systems, that of linear acceleration using an accelerometer and of angular velo…
Globally exponentially convergent observer for systems evolving on matrix Lie groups
Soham Shanbhag, Dong Eui Chang
We propose a globally exponentially convergent observer for the dynamical system evolving on matrix Lie groups with bounded velocity with unknown bound. We design the observer in t…
Design of a Discrete Time Observer for the Continuous Time Rotation Kinematics on
Soham Shanbhag, Ravi Banavar
This report proposes a discrete time observer for the continuous time rigid body kinematics on the rotation group . The work draws on two research schools…