Robust region based high resolution image reconstruction from low resolution video

Robust background normalization method for one-channel microarrays AKAL, TÜLAY; Purutçuoğlu Gazi, Vilda; Weber, Gerhard-Wilhelm (Walter de Gruyter GmbH, 2017-04-01) Background: Microarray technology, aims to measure the amount of changes in transcripted messages for each gene by RNA via quantifying the colour intensity on the arrays. But due to the different experimental conditions, these measurements can include both systematic and random erroneous signals. For this reason, we present a novel gene expression index, called multi-RGX (Multiple-probe Robust Gene Expression Index) for one-channel microarrays.
Robust Adaptive Kalman Filter for estimation of UAV dynamics in the presence of sensor/actuator faults Hacızade, Cengiz; Söken, Halil Ersin (2013-07-01) In this paper a Robust Adaptive Kalman Filter (RAKF) is introduced. The RAKF incorporates measurement and process noise covariance adaptation procedures (R and Q adaptation respectively) and utilizes adaptive factors in order to adapt itself against sensor/actuator faults. Thus the filter stands robust against the faults and even in case of sensor/actuator failure keeps providing accurate estimation results. In a single algorithm, the RAKF detects the fault, isolates it and applies the required adaptation p...
Robust Kalman filtering with single and multiple scale factors for small satellite attitude estimation Söken, Halil Ersin; Sakai, Shin-ichiro (Springer, 2015-11-01) In case of normal operational conditions for a satellite, a conventional Kalman Filter gives sufficiently good attitude estimation results. On the other hand, when there is a fault in the measurements then the Kalman filter fails about providing the required accuracy and may even collapse by time. In this paper, a Robust Kalman filtering method is proposed for the attitude estimation problem. By using the proposed method both the Extended Kalman Filter and Unscented Kalman Filter are modified ...
Robust adaptive unscented Kalman filter for attitude estimation of pico satellites Hacızade, Cengiz; Söken, Halil Ersin (Wiley, 2014-02-01) Unscented Kalman filter (UKF) is a filtering algorithm that gives sufficiently good estimation results for the estimation problems of nonlinear systems even when high nonlinearity is in question. However, in case of system uncertainty or measurement malfunctions, the UKF becomes inaccurate and diverges by time. This study introduces a fault-tolerant attitude estimation algorithm for pico satellites. The algorithm uses a robust adaptive UKF, which performs correction for the process noise covariance (Q-adapt...
Robust Kalman filtering for small satellite attitude estimation in the presence of measurement faults Söken, Halil Ersin; Sakai, Shin-ichiro (Elsevier BV, 2014-03-01) In normal working conditions it is possible to achieve sufficient attitude estimation accuracy for a satellite using regular Kalman filter algorithm. On the other hand, when there is a fault in the measurements, the Kalman filter fails in providing the required accuracy and may even collapse over time. In this paper, a Robust Kalman filtering method is proposed for the attitude estimation problem. By using the proposed method both the Extended Kalman Filter and Unscented Kalman Filter are modified and the n...

Citation Formats

P. E. Eren and A. M. TEKALP, “Robust region based high resolution image reconstruction from low resolution video,” 2015, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/69480.