Error entropy is a well-known learning criterion in information theoretic learning (ITL), and it
has already been applied to a wide range of fields. However, the shape of error entropy …

Detecting and tracking moving vehicles is one of the most fundamental functions of
autonomous vehicles driving in complex scenarios, as it forms the foundation of decision …

In this paper, an interactive Kalman filter (IKF) is proposed to demonstrate the interaction
between targets as to how the behavior of a desired target is affected by the behavior of its …

For vehicle state estimation, conventional Kalman filters work well under Gaussian
assumptions. Still, they are likely to degrade dramatically in the practical non-Gaussian …

Vehicle tracking is an attractive problem in the field of public transportation with several
research projects conducted using Kalman filter (KF) to tackle this. While a driver may act on …

Noninvasive medical procedures are usually preferable to their invasive counterparts in the
medical community. Anemia examining through the palpebral conjunctiva is a convenient …

Multi-object tracking is a well known problem in the context of vehicle tracking. Kalman filter
is a common tool to solve the problem in real world. In a driving enviroment, there are other …

Vehicular accidents caused by driver drowsiness involve about 7,000 people/year in Brazil,
only on federal highways, and cause psychic damage and traumatic stresses for both the …

In this paper, the observability property for a class of Nonlinear systems is analyzed under
the theoretical framework of Takagi-Sugeno (TS) fuzzy systems. The main contribution of this …

For vehicle state estimation, the conventional Kalman filter performs well under the
Gaussian assumption, but in the real non-Gaussian situation (especially when the noise is …