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38 papers · 1 filter
Effective Data Augmentation with Multi-Domain Learning GANs
Shin'ya Yamaguchi, Sekitoshi Kanai, Takeharu Eda
For deep learning applications, the massive data development (e.g., collecting, labeling), which is an essential process in building practical applications, still incurs seriously…
An Adaptive Reaction Force Observer Design
Emre Sariyildiz, Kouhei Ohnishi
In this paper, a new adaptive design method is proposed for reaction force observer (RFOB) based robust force control systems. It is a well-known fact that an RFOB has several supe…
A Guide to Design Disturbance Observer
Emre Sariyildiz, Kouhei Ohnishi
The goal of this paper is to clarify the robustness and performance constraints in the design of control systems based on disturbance observer (DOB). Although the bandwidth constra…
Stability and Robustness of Disturbance Observer based Motion Control Systems
Emre Sariyildiz, Kouhei Ohnishi
This paper analyzes the robustness and stability of a disturbance observer (DOB) and a reaction torque observer (RTOB) based robust motion control systems. Conventionally, a DOB is…
Emergent discrete 3-form symmetry and domain walls
Yoshimasa Hidaka, Muneto Nitta, Ryo Yokokura
We show that axion models with the domain wall number in dimensions, i.e., periodic scalar field theories admitting axion domain walls, exhibit an emergent ${\mathb…
Exploring the QCD phase diagram at finite density by the complex Langevin method on a lattice
Shoichiro Tsutsui, Yuta Ito, Hideo Matsufuru +3
We explore the QCD phase diagram at finite density with four-flavor staggered fermions using the complex Langevin method, which is a promising approach to overcome the sign problem…