Forgetting is an important tool for reducing ontologies by eliminating some redundant concepts and roles while preserving sound and complete reasoning. Attempts have previously been made to address the problem of forgetting in relatively simple description logics (DLs) such as DL-Lite and extended EL. However, the issue of forgetting for ontologies in more expressive description logics, such as...

Recent work suggests a link between sleep and memory consolidation, indicating that sleep in comparison to wakefulness stabilizes memories. However, relatively little is known about how sleep affects forgetting. Here we examined whether sleep influences directed forgetting, the finding that people can intentionally forget obsolete memories when cued to do so. We applied the list-method directed...

Adaptive algorithm based on multi-channel linear prediction is an effective dereverberation method balancing well between the attenuation of the long-term reverberation and the dereverberated speech quality. However, the abrupt change of the speech source position, usually caused by the shift of the speakers, forms an obstacle to the adaptive algorithm and makes it difficult to guarantee both t...

Exponentially Weighted Recursive Least Squares (EWRLS) is adopted to estimate adaptive prediction filters for f-x seismic interpolation. Adaptive prediction filters are able to model signals where the dominant wavenumbers are varying in space. This concept leads to a f-x interpolation method that does not require windowing strategies for optimal results. In other words, adaptive prediction filt...

In this paper, a new fuzzy forgetting factor (FFF) is developed in order to aid a modified input estimation (MIE) technique and enhance its performance in tracking high maneuvering targets. The MIE has been introduced recently and succeeds in presenting reasonably accurate target trajectory, velocity and acceleration estimation in low and mild maneuvering situations. However, after some iterati...

Frequency-domain equalization (FDE) based on the minimum mean square error (MMSE) criterion can increase the downlink bit error rate (BER) performance of DS-CDMA beyond that possible with conventional rake combining in a frequency-selective fading channel. FDE requires accurate channel estimation. Recently, we proposed a pilot-assisted channel estimation (CE) based on the MMSE criterion. Using ...

In some estimation or identification techniques, a forgetting factor has been used to improve the tracking performance for time-varying systems. However, the value of has been typically determined empirically, without any evidence of optimality. In our previous work, this open problem is solved using the framework of H optimization. The resultant H filter enables the forgetting factor to be opt...

This paper proposes an efficient online learning algorithm to track the smoothing functions of Additive Models. The key idea is to combine the linear representation of Additive Models with a Recursive Least Squares (RLS) filter. In order to quickly track changes in the model and put more weight on recent data, the RLS filter uses a forgetting factor which exponentially weights down observations...

Recent studies have identified molecular pathways driving forgetting and supported the notion that forgetting is a biologically active process. The circuit mechanisms of forgetting, however, remain largely unknown. Here we report two sets of Drosophila neurons that account for the rapid forgetting of early olfactory aversive memory. We show that inactivating these neurons inhibits memory decay ...

We extend results of the recursive-least-squares-with-forgetting-factor identifier for single-input-single-output systems to multiple-output case by, under assumption persistence excitation, deriving corresponding minimized objective function and by showing exponential convergence estimation error.